Transportation Conformity Guidance
for Quantitative Hot-spot Analyses in
PM2.5 and PM10 Nonattainment and
Maintenance Areas
&EPA
United States
Environmental Protection
Agency
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Transportation Conformity Guidance
for Quantitative Hot-spot Analyses in
PM2.5 and PM10 Nonattainment and
Maintenance Areas
Transportation and Regional Programs Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
&EPA
United States
Environmental Protection
Agency
EPA-420-B-10-040
December 2010
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Table of Contents
LIST OF EXHIBITS V
LIST OF APPENDICES V
SECTION 1: INTRODUCTION 1
1.1 PURPOSE OF THIS GUIDANCE 1
1.2 TIMING OF QUANTITATIVE PM HOT-SPOT ANALYSES 1
1.3 DEFINITION OF A HOT-SPOT ANALYSIS 2
1.4 PROJECTS REQUIRING A PM HOT-SPOT ANALYSIS 2
1.5 OTHER PURPOSES FOR THIS GUIDANCE 3
1.6 ORGANIZATION OF THIS GUIDANCE 3
1.7 ADDITIONAL INFORMATION 4
1.8 GUIDANCE AND EXISTING REQUIREMENTS 5
SECTION 2: TRANSPORTATION CONFORMITY REQUIREMENTS 6
2.1 INTRODUCTION 6
2.2 OVERVIEW OF STATUTORY AND REGULATORY REQUIREMENTS 6
2.3 INTERAGENCY CONSULTATION AND PUBLIC PARTICIPATION REQUIREMENTS 8
2.4 HOT-SPOT ANALYSES ARE BUILD/NO-BUILD ANALYSES 9
2.4.1 General 9
2.4.2 Suggested approach for PM hot-spot analyses 9
2.4.3 Guidance focuses on refined PM hot-spot analyses 11
2.5 EMISSIONS CONSIDERED IN PM HOT-SPOT ANALYSES 13
2.5.1 General requirements 13
2.5.2 PM emissions from motor vehicle exhaust, brake wear, and tire wear 13
2.5.3 PM2.s emissions from re-entrained road dust. 13
2.5.4 PM 10 emissions from re-entrained road dust 13
2.5.5 PM emissions from construction-related activities 14
2.6 NAAQS CONSIDERED IN PM HOT-SPOT ANALYSES 14
2.7 BACKGROUND CONCENTRATIONS 14
2.8 APPROPRIATE TIME FRAME AND ANALYSIS YEARS 15
2.9 AGENCY ROLES AND RESPONSIBILITIES 16
2.9.1 Project sponsor 16
2.9.2 DOT 16
2.9.3 EPA 16
2.9.4 State and local transportation and air agencies 16
SECTION 3: OVERVIEW OF A QUANTITATIVE PM HOT-SPOT ANALYSIS 18
3.1 INTRODUCTION 18
3.2 DETERMINE NEED FOR A PM HOT-SPOT ANALYSIS (STEP i) 18
3.3 DETERMINE APPROACH, MODELS, AND DATA (STEP 2) 18
3.3.1 General 18
3.3.2 Determining the geographic area and emission sources to be covered by the analysis 20
3.3.3 Deciding the general analysis approach and analysis year(s) 20
3.3.4 Determining the PM NAAQS to be evaluated 21
3.3.5 Deciding on the type of PM emissions to be modeled. 22
3.3.6 Determining the models and methods to be used. 22
3.3.7 Obtaining project-specific data 22
3.4 ESTIMATE ON-ROAD MOTOR VEHICLE EMISSIONS (STEP 3) 23
3.5 ESTIMATE EMISSIONS FROM ROAD DUST, CONSTRUCTION, AND ADDITIONAL SOURCES
(STEP 4) 23
3.6 SELECT AN AIR QUALITY MODEL, DATA INPUTS AND RECEPTORS (STEP 5) 23
3.7 DETERMINE BACKGROUND CONCENTRATIONS FROM NEARBY AND OTHER SOURCES
(STEP 6) 24
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3.8 CALCULATE DESIGN VALUES AND DETERMINE CONFORMITY (STEP 7) 24
3.9 CONSIDER MITIGATION OR CONTROL MEASURES (STEP 8) 25
3.10 DOCUMENT THE PM HOT-SPOT ANALYSIS (STEP 9) 25
SECTION 4: ESTIMATING PROJECT-LEVEL PM EMISSIONS USING MOVES 27
4.1 INTRODUCTION 27
4.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS 29
4.2.1 Highway and intersection projects 30
4.2.2 Transit and other terminal projects 32
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 Projects with additional travel activity data 35
4.4 DEVELOPING BASIC RUN SPECIFICATION INPUTS 35
4.4.1 Description 36
4.4.2 Scale 36
4.4.3 Time Spans 37
4.4.4 Geographic Bounds 37
4.4.5 Vehicles/Equipment 37
4.4.6 Road Type 38
4.4.7 Pollutants and Processes 39
4.4.8 Manage Input Data Sets 40
4.4.9 Strategies 40
4.4.10 Output 41
4.4.11 Advanced Performance Features 41
4.5 ENTERING PROJECT DETAILS USING THE PROJECT DATA MANAGER 42
4.5.1 Meteorology 43
4.5.2 Age Distribution 44
4.5.3 Fuel Supply and Fuel Formulation 45
4.5.4 Inspection and Maintenance (I/M) 45
4.5.5 Link Source Type 45
4.5.6 Links 46
4.5.7 Describing Vehicle Activity 46
4.5.8 Deciding on an approach for activity 48
4.5.9 Off-Network 48
4.6 GENERATING EMISSION FACTORS FOR USE IN AIR QUALITY MODELING 50
4.6.1 Highway and intersection links. 50
4.6.2 Transit and other terminal links 51
SECTION 5: ESTIMATING PROJECT-LEVEL PM EMISSIONS USING EMFAC (IN
CALIFORNIA) 52
5.1 INTRODUCTION 52
5.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS 54
5.2.1 Highway and intersection projects 54
5.2.2 Transit and other terminal projects 55
5.3 DETERMINING THE NUMBER OF EMFAC RUNS 56
5.4 DEVELOPING BASIC SCENARIO INPUTS 58
5.4.1 Geographic area and calculation method 58
5.4.2 Calendar year 59
5.4.3 Season or month 59
5.4.4 Scenario title 59
5.4.5 Model years 59
5.4.6 Vehicle classes 60
5.4.7 I/M program schedule and other state control measures 60
5.5 CONFIGURING EMISSION FACTOR OUTPUTS 61
5.5.1 Temperature and relative humidity. 61
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5.5.2 Speed. 62
5.5.3 Output rate file 63
5.5.4 Output p articulate 63
5.6 EDITING PROGRAM CONSTANTS 64
5.6.1 Overview 64
5.6.2 Default data in the Emfac mode 64
5.6.3 Comparing project data and EMFA C defaults to determine adjustments 65
5.6.4 Adjustment of default activity distributions to reflect project data 65
5.7 GENERATING EMISSION FACTORS FOR USE IN AIR QUALITY MODELING 68
5.7.7 Highway and intersection links. 68
5.7.2 Transit and other terminal links 70
SECTION 6: ESTIMATING EMISSIONS FROM ROAD DUST, CONSTRUCTION, AND
ADDITIONAL SOURCES 73
6.1 INTRODUCTION 73
6.2 OVERVIEW OF DUST METHODS AND REQUIREMENTS 73
6.3 ESTIMATING RE-ENTRAINED ROAD DUST 74
6.3.1 PM2.s nonattainment and maintenance areas 74
6.3.2 PM10 nonattainment and maintenance areas 74
6.3.3 Using AP-42 for road dust on paved roads 74
6.3.4 Using AP-42 for road dust on unpaved roads 74
6.3.5 Using alternative local approaches for road dust 75
6.4 ESTIMATING TRANSPORTATION-RELATED CONSTRUCTION DUST 75
6.4.1 Determining whether construction dust must be considered 75
6.4.2 Using AP-42 for construction dust 75
6.4.3 Using alternative approaches for construction dust 75
6.5 ADDING DUST EMISSIONS TO MOVES/EMFAC MODELING RESULTS 76
6.6 ESTIMATING ADDITIONAL SOURCES OF EMISSIONS IN THE PROJECT AREA 76
6.6.1 Construction-related vehicles and equipment 76
6.6.2 Locomotives 76
6.6.3 Additional emission sources 76
SECTION 7: SELECTING AN AIR QUALITY MODEL, DATA INPUTS, AND RECEPTORS 77
7.1 INTRODUCTION 77
7.2 GENERAL OVERVIEW OF AIR QUALITY MODELING 77
7.3 SELECTING AN APPROPRIATE AIR QUALITY MODEL 79
7.3.1 Recommended air quality models 79
7.3.2 How emissions are represented in CAL3QHCR and AERMOD 82
7.3.3 Alternate models 82
7.4 CHARACTERIZING EMISSION SOURCES 83
7.4.1 Physical characteristics and location 83
7.4.2 Emission rates/emission factors 84
7.4.3 Timing of emissions 84
7.5 INCORPORATING METEOROLOGICAL DATA 84
7.5.7 Finding representative meteorological data 84
7.5.2 Surface and upper air data 86
7.5.3 Time duration of meteorological data record. 87
7.5.4 Considering surface characteristics 88
7.5.5 Specifying urban or rural sources 89
7.6 PLACING RECEPTORS 90
7.6.1 Overview 90
7.6.2 General guidance for receptors for all PM NAAQS 91
7.6.3 Additional guidance for receptors for the PM2.s NAAQS 93
7.7 RUNNING THE MODEL AND OBTAINING RESULTS 94
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SECTION 8: DETERMINING BACKGROUND CONCENTRATIONS FROM NEARBY AND
OTHER EMISSION SOURCES 95
8.1 INTRODUCTION 95
8.2 NEARBY SOURCES THAT REQUIRE MODELING 96
8.3 OPTIONS FOR BACKGROUND CONCENTRATIONS 97
8.3.1 Using ambient monitoring data to estimate background concentrations 98
8.3.2 Adjusting air quality monitoring data to account for future changes in air quality:
using chemical transport models 101
8.3.3 Adjusting air quality monitoring data to account for future changes in air quality:
using an on-road mobile source adjustment factor 104
SECTION 9: CALCULATING PM DESIGN VALUES AND DETERMINING CONFORMITY... 105
9.1 INTRODUCTION 105
9.2 USING DESIGN VALUES IN BUILD/NO-BUILD ANALYSES 106
9.3 CALCULATING DESIGN VALUES AND DETERMINING CONFORMITY FOR PM HOT-SPOT
ANALYSES 109
9.3.1 General 109
9.3.2 Annual PM2.5NAAQS. 109
9.3.3 24-hour PM2.5NAAQS 113
9.3.4 24-hour PM10NAAQS. 120
9.4 DETERMINING APPROPRIATE RECEPTORS FOR COMPARISON TO THE ANNUAL PM2.5NAAQS... 124
9.4.1 General 124
9.4.2 Factors for determining appropriate receptors for comparison to the annual
PM2.5 NAAQS 124
9.4.3 Overview of PM2S monitoring regulations 125
9.4.4 Conformity guidance for all projects in annual PM25 NAAQS areas 727
9.4.5 Additional conformity guidance for the annual PM21 NAAQS and highway and
intersection projects 129
9.5 DOCUMENTING CONFORMITY DETERMINATION RESULTS 131
SECTION 10: MITIGATION AND CONTROL MEASURES 132
10.1 INTRODUCTION 132
10.2 MITIGATION AND CONTROL MEASURES BY CATEGORY 132
10.2.1 Retrofitting, replacing vehicles/engines, and using cleaner fuels 132
10.2.2 Reduced idling programs 133
10.2.3 Transportation project design revisions 134
10.2.4 Fugitive dust control programs 134
10.2.5 Addressing other source emissions 135
IV
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List of Exhibits
EXHIBIT 3-1. OVERVIEW OF A PM QUANTITATIVE HOT-SPOT ANALYSIS 19
EXHIBIT 4-1. STEPS FOR USING MOVES IN A QUANTITATIVE PM HOT-SPOT ANALYSIS 28
EXHIBIT 4-2. TYPICAL NUMBER OF MOVES RUNS FOR AN ANALYSIS YEAR 33
EXHIBIT 5-1. STEPS FOR USING EMFAC IN A QUANTITATIVE PM HOT-SPOT ANALYSIS 53
EXHIBIT 5 -2. SUMMARY OF EMFAC INPUTS NEEDED TO EVALUATE A PROJECT SCENARIO 58
EXHIBIT 5-3. CHANGING EMFAC DEFAULT SETTINGS FOR TEMPERATURE AND RELATIVE HUMIDITY 62
EXHIBIT 5-4. SELECTING POLLUTANT TYPES IN EMFAC FOR PMIO AND PM2.5 63
EXHIBIT 5-5. EMFAC PROGRAM CONSTANTS AND MODIFICATION NEEDS FOR PM HOT-SPOT ANALYSES 64
EXHIBIT 5-6. MAPPING EMFAC VEHICLE CLASSES TO PROJECT-SPECIFIC ACTIVITY INFORMATION 65
EXHIBITS-?. EXAMPLE DEFAULT EMFAC VMT BY VEHICLE CLASS DISTRIBUTION 66
EXHIBIT 5-8. EXAMPLE ADJUSTED EMFAC VMT BY VEHICLE CLASS DISTRIBUTION 67
EXHIBIT 5-9. EXAMPLE EMFAC RUNNING EXHAUST, TIRE WEAR, AND BRAKE WEAR EMISSION FACTORS IN THE
SUMMARY RATES (RTS) OUTPUT FILE 69
EXHIBIT 5-10. EXAMPLE SOAK TIMES FOR SEVERAL PROJECT SCENARIOS 70
EXHIBIT 7-1. OVERVIEW AND DATA FLOW FOR AIR QUALITY MODELING 78
EXHIBIT 7-2. SUMMARY OF RECOMMENDED AIR QUALITY MODELS 79
EXHIBIT 7-3. AIR QUALITY MODEL CAPABILITIES FOR METEOROLOGICAL DATA FOR EACH SCENARIO 88
EXHIBIT 7-4. GUIDANCE FOR RECEPTORS IN PM HOT-SPOT ANALYSES 91
EXHIBIT 9-1. GENERAL PROCESS FOR CALCULATING DESIGN VALUES FOR PM HOT-SPOT ANALYSES 105
EXHIBIT 9-2. GENERAL PROCESS FOR USING DESIGN VALUES IN BUILD/NO-BUILD ANALYSES 107
EXHIBIT 9-3. DETERMINING CONFORMITY TO THE ANNUAL PM2.5NAAQS Ill
EXHIBIT 9-4. DETERMINING CONFORMITY TO THE 24-HOUR PM2.5 NAAQS USING FIRST TIER ANALYSIS 115
EXHIBIT 9-5. RANKING OF 98™ PERCENTILE BACKGROUND CONCENTRATION VALUES 116
EXHIBIT 9-6. DETERMINING CONFORMITY TO THE 24-HOUR PM2.5 NAAQS USING SECOND TIER ANALYSIS 118
EXHIBIT 9-7. RANKING OF 98™ PERCENTILE BACKGROUND CONCENTRATION VALUES 119
EXHIBIT 9-8. DETERMINING CONFORMITY TO THE 24-HOUR PMIONAAQS 122
EXHIBIT 9-9. DETERMINING SCALE OF RECEPTOR LOCATIONS FOR THE ANNUAL PM25 NAAQS 130
List of Appendices
APPENDIX A: CLEARINGHOUSE OF WEBSITES, GUIDANCE, AND OTHER TECHNICAL RESOURCES FOR PM
HOT-SPOT ANALYSES
APPENDIX B : EXAMPLES OF PROJECTS OF LOCAL AIR QUALITY CONCERN
APPENDIX c: HOT-SPOT REQUIREMENTS FOR PMi» AREAS WITH PRE-2006 APPROVED CONFORMITY SIPS
APPENDIX D: CHARACTERIZING INTERSECTION PROJECTS FOR MOVES
APPENDIX E : EXAMPLE QUANTITATIVE PM HOT-SPOT ANALYSIS OF A HIGHWAY PROJECT USING MOVES
AND CAL3QHCR
APPENDIX F: EXAMPLE QUANTITATIVE PM HOT-SPOT ANALYSIS OF A TRANSIT PROJECT USING MOVES AND
AERMOD
APPENDIX G: EXAMPLE OF USING EMFAC FOR A HIGHWAY PROJECT
APPENDIX H: EXAMPLE OF USING EMFAC TO DEVELOP EMISSION FACTORS FOR A TRANSIT PROJECT
APPENDIX i: ESTIMATING LOCOMOTIVE EMISSIONS
APPENDIX J: ADDITIONAL REFERENCE INFORMATION ON AIR QUALITY MODELS AND DATA INPUTS
APPENDIX K: EXAMPLES OF DESIGN VALUE CALCULATIONS FOR PM HOT-SPOT ANALYSES
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Section 1: Introduction
1.1 PURPOSE OF THIS GUIDANCE
This guidance describes how to complete quantitative hot-spot analyses for certain
highway and transit projects in PIVb.s and PMio (PM) nonattainment and maintenance
areas. This guidance describes transportation conformity requirements for hot-spot
analyses, and provides technical guidance on estimating project emissions with the
Environmental Protection Agency's (EPA's) MOVES model, California's EMFAC
model, and other methods. It also outlines how to apply air quality models for PM hot-
spot analyses and includes additional references and examples. However, the guidance
does not change the specific transportation conformity rule requirements for quantitative
PM hot-spot analyses, such as what projects require these analyses. EPA has coordinated
with the Department of Transportation (DOT) during the development of this guidance.
Transportation conformity is required under Clean Air Act (CAA) section 176(c) (42
U.S.C. 7506(c)) to ensure that federally supported highway and transit project activities
are consistent with (conform to) the purpose of a state air quality implementation plan
(SIP). Conformity to the purpose of the SIP means that transportation activities will not
cause or contribute to new air quality violations, worsen existing violations, or delay
timely attainment of the relevant national ambient air quality standards (NAAQS) or
required interim milestones. EPA's transportation conformity rule (40 CFR 51.390 and
Part 93) establishes the criteria and procedures for determining whether transportation
activities conform to the SIP. Conformity applies to transportation activities in
nonattainment and maintenance areas for transportation-related pollutants, including
PM2.5 and PMio. This guidance is consistent with existing regulations and guidance for
the PM NAAQS, SIP development, and other regulatory programs as applicable. This
guidance does not address carbon monoxide (CO) hot-spot requirements or modeling
procedures.1
1.2 TIMING OF QUANTITATIVE PM HOT-SPOT ANALYSES
On March 10, 2006, EPA published a final rule establishing transportation conformity
requirements for analyzing the local PM air quality impacts of transportation projects (71
FR 12468). The conformity rule requires a qualitative PM hot-spot analysis to be
performed until EPA releases guidance on how to conduct quantitative PM hot-spot
analyses and announces in the Federal Register that such requirements are in effect (40
CFR 93.123(b)).2 EPA also stated in the March 2006 final rule that quantitative PM hot-
1 EPA has issued a separate guidance document on how to use MOVES for CO project-level analyses
(including CO hot-spot analyses for conformity purposes). This guidance is available online at:
www.epa.gov/otaq/stateresources/transconf/policv.htm.
2 For more information on qualitative PM hot-spot analyses, see "Transportation Conformity Guidance for
Qualitative Hot-spot Analyses in PM2 5 and PM10 Nonattainment and Maintenance Areas," EPA420-B-06-
902 (March 2006); available online at: www.epa.gov/otaq/stateresources/transconf/policv.htm. The
qualitative PM hot-spot requirements under 40 CFR 93.123(b)(2) will no longer apply in any PM25 and
1
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spot analyses would not be required until EPA released an appropriate motor vehicle
emissions model for these project-level analyses.3
Quantitative PM hot-spot analyses will be required after the end of the conformity grace
period for applying motor vehicle emissions models for such analyses. See the Federal
Register notice of availability for more information on EPA's approval of MOVES (and
EMFAC in California) for PM hot-spot analyses. The effective date of the Federal
Register notice constitutes the start of the two-year conformity grace period.4 EPA has
issued policy guidance on when these models will be required for PM hot-spot analyses
and other purposes.5
1.3 DEFINITION OF A HOT-SPOT ANALYSIS
A hot-spot analysis is defined in 40 CFR 93.101 as an estimation of likely future
localized pollutant concentrations and a comparison of those concentrations to the
relevant NAAQS. A hot-spot analysis assesses the air quality impacts on a scale smaller
than an entire nonattainment or maintenance area, including, for example, congested
highways or transit terminals. Such an analysis of the area substantially affected by the
project demonstrates that CAA conformity requirements are met for the relevant NAAQS
in the "project area." When a hot-spot analysis is required, it is included within a project-
level conformity determination.
1.4 PROJECTS REQUIRING A PM HOT-SPOT ANALYSIS
PM hot-spot analyses are required for projects of local air quality concern, which include
certain highway and transit projects that involve significant levels of diesel vehicle traffic
and any other project identified in the PM SIP as a localized air quality concern. See
Section 2.2 of the guidance for further information on the specific types of projects where
a PM hot-spot analysis is required. A PM hot-spot analysis is not required for projects
that are not of local air quality concern. This guidance does not alter the types of projects
that require a PM hot-spot analysis.
Note that additional projects may need hot-spot analyses in PMio nonattainment and
maintenance areas with approved conformity SIPs that are based on the federal PMio hot-
spot requirements that existed before the March 2006 final rule.6 EPA strongly
PM10 nonattainment and maintenance areas once the grace period is over and quantitative requirements are
in effect. At that time, the 2006 EPA/FHWA qualitative PM hot-spot guidance will be superseded by
EPA's quantitative PM hot-spot guidance.
3 See EPA's March 2006 final rule (71 FR 12498-12502).
4 EPA posts all Federal Register notices for approving new emissions models on its website:
www.epa.gov/otaq/sMeresources/transconf/policv.htnrfmodels.
5 "Policy Guidance on the Use of MOVES2010 for State Implementation Plan Development,
Transportation Conformity, and Other Purposes," EPA-420-B-09-046 (December 2009); available online
at: www.epa.gov/otaq/stateresources/transconf/policv.htm#models.
6 A "conformity SIP" includes a state's specific criteria and procedures for certain aspects of the
transportation conformity process (40 CFR 51.390).
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encourages states to revise these types of approved conformity SIPs to take advantage of
the streamlining flexibilities provided by the current CAA.7 See Appendix C for further
details on how these types of approved conformity SIPs can affect what projects are
required to have PM hot-spot analyses.
1.5 OTHER PURPOSES FOR THIS GUIDANCE
This guidance addresses how to complete a quantitative PM hot-spot analysis for
transportation conformity purposes. However, certain sections of this technical guidance
may also be applicable when completing analyses of transportation projects for general
conformity determinations and for other purposes. For example, Sections 4 or 5 can be
used to estimate transportation project emissions using MOVES or EMFAC, and Sections
7 and 8 can be used to conduct PM air quality analyses of transportation projects.
1.6 ORGANIZATION OF THIS GUIDANCE
The remainder of this guidance is organized as follows:
• Section 2 provides an overview of transportation conformity requirements for PM
hot-spot analyses.
• Section 3 describes the general process for conducting PM hot-spot analyses.
• Sections 4 and 5 describe how to estimate vehicle emissions from a project using
the latest approved emissions model, either MOVES (for all states other than
California) or EMFAC (for California).
• Section 6 discusses how to estimate emissions from road dust, construction dust,
and additional sources, if necessary.
• Section 7 describes how to determine the appropriate air quality dispersion model
and select model inputs.
• Section 8 covers how to determine background concentrations, including nearby
source emissions in the project area.
• Section 9 describes how to calculate the appropriate design values and determine
whether or not the project conforms.
• Section 10 describes mitigation and control measures that could be considered, if
necessary.
The following appendices for this guidance may also help state and local agencies
conduct PM hot-spot analyses:
• Appendix A is a clearinghouse of information and resources external to this
guidance that may be useful when completing PM hot-spot analyses.
• Appendix B gives examples of projects of local air quality concern.
7 For more information about conformity SIPs, see EPA's "Guidance for Developing Transportation
Conformity State Implementation Plans (SIPs)," EPA-420-B-09-001 (January 2009); available online at:
www.epa. gov/otaq/stateresources/transconf/policv/420b09001 .pdf.
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• Appendix C discusses what projects need a PMio hot-spot analysis if a state's
approved conformity SIP is based on pre-2006 requirements.
• Appendix D demonstrates how to characterize links in an intersection when
running MOVES.
• Appendices E and F are abbreviated PM hot-spot analysis examples using
MOVES and air quality models for a highway and transit project, respectively.
• Appendices G and H are examples on how to configure and run EMFAC for a
highway and transit project, respectively.
• Appendix I describes how to estimate locomotive emissions in the project area.
• Appendix J includes details on how to input data and run air quality models for
PM hot-spot analyses, as well as prepare outputs for design value calculations.
• Appendix K has examples of how to calculate design values and determine
transportation conformity.
Except where indicated, this guidance applies equally for the annual PM2.s NAAQS, the
24-hour PM2.s NAAQS, and the 24-hour PMio NAAQS. This guidance is written for
current and future PM2.5 and PMio NAAQS. EPA will re-evaluate the applicability of
this guidance, as needed, if different PM NAAQS are promulgated in the future.
1.7 ADDITIONAL INFORMATION
For specific questions concerning a particular nonattainment or maintenance area, please
contact the transportation conformity staff person responsible for your state at the
appropriate EPA Regional Office. Contact information for EPA Regional Offices can be
found at: www.epa.gov/otaq/stateresources/transconf/contacts.htm.
General questions about this guidance can be directed to Meg Patulski at EPA's Office of
Transportation and Air Quality, patulski.meg@epa.gov, (734) 214-4842.
Technical questions about conformity hot-spot analyses can be directed to conformity-
hotspot@epa.gov.
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1.8 GUIDANCE AND EXISTING REQUIREMENTS
This guidance does not create any new requirements. The CAA and the regulations
described in this document contain legally binding requirements. This guidance is not a
substitute for those provisions or regulations, nor is it a regulation in itself. Thus, it does
not impose legally binding requirements on EPA, DOT, states, or the regulated
community, and may not apply to a particular situation based upon the circumstances.
EPA retains the discretion to adopt approaches on a case-by-case basis that may differ
from this guidance but still comply with the statute and applicable regulations. This
guidance may be revised periodically without public notice. As noted above, EPA's
Federal Register notice describes the two-year conformity grace period for MOVES and
EMFAC for PM hot-spot analyses, and when the requirements for quantitative PM hot-
spot analyses in 40 CFR 93.123(b) will take effect.
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Section 2: Transportation Conformity Requirements
2.1 INTRODUCTION
This section outlines the transportation conformity requirements for quantitative PM hot-
spot analyses, including the general statutory and regulatory requirements, specific
analytical requirements, and the different types of agencies involved in developing hot-
spot analyses.
2.2 OVERVIEW OF STATUTORY AND REGULATORY REQUIREMENTS
CAA section 176(c)(l) is the statutory requirement that must be met by all projects in
nonattainment and maintenance areas that are subject to transportation conformity.
Section 176(c)(l)(B) states that federally-supported transportation projects must not
"cause or contribute to any new violation of any standard [NAAQS] in any area; increase
the frequency or severity of any existing violation of any standard in any area; or delay
timely attainment of any standard or any required interim emission reductions or other
milestones in any area."8
Section 93.109(b) of the conformity rule outlines the requirements for project-level
conformity determinations. For example, PM hot-spot analyses must be based on the
latest planning assumptions available at the time the analysis begins (40 CFR 93.110).
Also, the design concept and scope of the project must be consistent with that included in
the conforming transportation plan and transportation improvement program (TIP) or
regional emissions analysis (40 CFR 93.114).
Section 93.123(b)(l) of the conformity rule defines the projects that require a PM2.5 or
hot-spot analysis as:
"(i) New highway projects that have a significant number of diesel vehicles, and
expanded highway projects that have a significant increase in the number of diesel
vehicles;
(ii) Projects affecting intersections that are at Level-of-Service D, E, or F with a
significant number of diesel vehicles, or those that will change to Level-of-
Service D, E, or F because of increased traffic volumes from a significant number
of diesel vehicles related to the project;
8 See EPA's March 2006 final rule (71 FR 12469-12490) and March 24, 2010 final rule (75 FR 14274-
14285). Both of these final rules address the statutory conformity requirements and explain how the hot-
spot analyses required by EPA's regulations satisfy those requirements. Issues relating to the statutory
conformity requirements are therefore not addressed in this guidance document. See also Environmental
Defense v. EPA 467 F.3d 1329 (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 PMio applicable implementation plan or implementation
plan submission, as appropriate, as sites of violation or possible violation."
A PM hot-spot analysis is not required for projects that are not of local air quality
concern. For these projects, state and local project sponsors should document in their
project-level conformity determinations that the requirements of the CAA and 40 CFR
93.116 are met without a hot-spot analysis, since such projects have been found not to be
of local air quality concern under 40 CFR 93.123(b)(l). Note that all other project-level
conformity requirements must continue to be met. See Appendix B for examples of
projects that are most likely to be of local air quality concern, as well as examples of
projects that are not.9
Section 93.123(c) of the conformity rule includes the general requirements for all PM
hot-spot analyses. A PM hot-spot analysis must:
• Estimate the total emissions burden of direct PM emissions that may result from
the implementation of the project(s), summed together with future background
concentrations;
• Include the entire transportation project, after identifying the major design
features that will significantly impact local concentrations;
• Use assumptions that are consistent with those used in regional emissions
analyses for inputs that are needed for both analyses (e.g., temperature, humidity);
• Assume the implementation of mitigation or control measures only where written
commitments for such measures have been obtained; and
• Consider emissions increases from construction-related activities only if they
occur during the construction phase and last more than five years at any
individual site.
Finally, the interagency consultation process must be used to develop project-level
conformity determinations to meet all applicable conformity requirements for a given
project. In general, when a hot-spot analysis is required, it is done when a project-level
conformity determination is completed. Conformity determinations are typically
developed during the National Environmental Policy Act (NEPA) process, although
conformity requirements are separate from NEPA-related requirements. There can also
9 See the preamble of the March 2006 final rule for further information regarding how and why EPA
defined projects of local air quality concern (71 FR 12491-12493). EPA also clarified Section
93.123(b)(l)(i) in the January 24, 2008 final rule (73 FR 4435-4436).
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be limited cases when conformity requirements apply after the initial NEPA process has
been completed.10
2.3 INTERAGENCY CONSULTATION AND PUBLIC PARTICIPATION
REQUIREMENTS
The interagency consultation process is an important tool for completing project-level
conformity determinations and hot-spot analyses. Interagency consultation must be used
to develop a process to evaluate and choose models and associated methods and
assumptions to be used in PM hot-spot analyses (40 CFR 93.105(c)(l)(i)). For example,
each area's interagency consultation procedures must be used to determine the models
and associated methods and assumptions for:
• The geographic area covered by the analysis (see Section 3.3);
• The emissions models used in the analysis (see Section 4 for MOVES and
Section 5 for EMFAC);
• Whether and how to estimate road and construction dust emissions (see
Section 6);
• The nearby sources considered, background data used, and air quality model
chosen, including the background monitors/concentrations selected and any
interpolation methods used (see Sections 7 and 8); and
• The appropriateness of receptors to be compared to the annual PM2.5 NAAQS
(see Section 9.4).
State and local agencies have flexibility to decide whether the process outlined in the
interagency consultation procedures should be used for aspects of PM hot-spot analyses
where consultation is not required. The roles and responsibilities of various agencies for
meeting the transportation conformity requirements are addressed in 40 CFR 93.105 or in
a state's approved conformity SIP. See Section 2.9 for further information on the
agencies involved in interagency consultation.
This guidance describes when consultation on specific decisions is necessary, but for
many aspects of PM hot-spot analyses, the general requirement for interagency
consultation can be satisfied without consulting separately on each and every specific
decision that arises. In general, as long as the consultation requirements are met,
agencies have discretion as to how they consult on hot-spot analyses. For example, the
interagency consultation process could be used to make decisions on a case-by-case basis
for individual transportation projects for which a PM hot-spot analysis is required. Or,
agencies involved in the consultation process could develop procedures that will apply
for any PM hot-spot analysis and agree that any departures from procedures would be
discussed by involved agencies. For example, interagency consultation is required on the
emissions model used for the analysis, but agencies could agree up front that the latest
EPA-approved version of MOVES will be used for any hot-spot analysis necessary in an
10 Such an example may occur when NEPA is completed prior to an area being designated nonattainment,
but additional federal project approvals are required after conformity requirements apply.
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area that is not located in California. As a second example, agencies could agree ahead
of time that, if appropriate, instead of modeling all four quarters of the year for a 24-hour
PM NAAQS, only the quarters that were modeled for the latest SIP demonstration for
that NAAQS need to be modeled in a hot-spot analysis.
The conformity rule also requires agencies completing project-level conformity
determinations to establish a proactive public involvement process that provides
opportunity for public review and comment (40 CFR 93.105(e)). The NEPA public
involvement process is typically used to satisfy this public participation requirement.n If
a project-level conformity determination that includes a PM hot-spot analysis is
performed after NEPA is completed, a public comment period must still be provided to
support that determination. In these cases, agencies have flexibility to decide what
specific public participation procedures are appropriate, as long as the procedures provide
a meaningful opportunity for public review and comment.
2.4 HOT-SPOT ANALYSES ARE BUILD/NO-BUILD ANALYSES
2.4.1 General
As noted above, the conformity rule requires that the emissions from the proposed
project, when considered with background concentrations, will not cause or contribute to
any new violation, worsen existing violations, or delay timely attainment of the relevant
NAAQS or required interim milestones. As described in Section 1.3, the hot-spot
analysis examines the area substantially affected by the project (i.e., the "project area").
In general, a hot-spot analysis compares the air quality concentrations with the proposed
project (the build scenario) to the air quality concentrations without the project (the no-
build scenario).12 These air quality concentrations are determined by calculating a
"design value," a statistic that describes a future air quality concentration in the project
area that can be compared to a particular NAAQS. It is always necessary to complete
emissions and air quality modeling on the build scenario and compare the resulting
design values to the relevant PM NAAQS. However, it will not always be necessary to
conduct emissions and air quality modeling for the no-build scenario, as described further
below.
2.4.2 Suggested approach for PM hot-spot analyses
To avoid unnecessary work, EPA suggests the following approach when completing a
PM hot-spot analysis:
11 Section 93.105(e) of the conformity rule requires agencies to "provide opportunity for public
involvement in conformity determinations for projects where otherwise required by law."
12 See 40 CFR 93.116(a). See also November 24, 1993 conformity rule (58 FR 62212-62213). Please note
that a build/no-build analysis for project-level conformity determinations is different than the build/no-
build interim emissions test for regional emissions analyses in 40 CFR 93.119.
-------
• First, model the build scenario and account for background concentrations in
accordance with this guidance. If the design values for the build scenario are less
than or equal to the relevant NAAQS, the project meets the conformity rule's hot-
spot requirements and no further modeling is needed (i.e., there is no need to
model the no-build scenario). If this is not the case, the project sponsor could
choose mitigation or control measures, perform additional modeling that includes
these measures, and then determine if the build scenario is less than or equal to
the relevant NAAQS.
• If the build scenario results in design values greater than the NAAQS, then the
no-build scenario will also need to be modeled. The no-build scenario will model
the air quality impacts of sources without the proposed project. The modeling
results of the build and no-build scenarios should be combined with background
concentrations as appropriate. If the design values for the build scenario are less
than or equal to the design values for the no-build scenario, then the project meets
the conformity rule's hot-spot requirements. If not, then the project does not meet
conformity requirements without further mitigation or control measures. If such
measures are considered, additional modeling will need to be completed and new
design values calculated to ensure that the build scenario is less than or equal to
the no-build scenario.
The project sponsor can decide to use the suggested approach above or a different
approach (e.g., conduct the no-build analysis first, calculate design values at all build and
no-build scenario receptors). The project sponsor can choose to apply mitigation or
control measures at any point in the process.13 This guidance applies to any of the above
approaches for a given PM hot-spot analysis.
In general, assumptions should be consistent between the build and no-build scenarios for
a given analysis year, except for traffic volumes and other project activity changes or
changes in nearby sources that are expected to occur due to the project (e.g., increased
activity at a nearby marine port or intermodal terminal due to a new freight corridor
highway). Project sponsors should document the build/no-build analysis in the project-
level conformity determination, including the assumptions, methods, and models used for
each analysis year(s).
The conformity rule defines how to determine if new NAAQS violations or increases in
the frequency or severity of existing violations are predicted to occur based on the hot-
spot analysis. Section 93.101 states:
"Cause or contribute to a new violation for a project means:
(1) To cause or contribute to a new violation of a standard in the area
substantially affected by the project or over a region which would
13 If mitigation or control measures are used to demonstrate conformity during the hot-spot analysis, the
conformity determination for the project must include written commitments to implement such measures
(40CFR93.125).
10
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otherwise not be in violation of the standard during the future period in
question, if the project were not implemented; or
(2) To contribute to a new violation in a manner that would increase the
frequency or severity of a new violation of a standard in such area."
"Increase the frequency or severity means to cause a location or region to exceed
a standard more often or to cause a violation at a greater concentration than
previously existed and/or would otherwise exist during the future period in
question, if the project were not implemented."
A build/no-build analysis is typically based on design value comparisons done on a
receptor-by-receptor basis. However, there may be certain cases where a "new" violation
at one receptor (in the build scenario) is relocated from a different receptor (in the no-
build scenario). As discussed in the preamble to the November 24, 1993 transportation
conformity rule, EPA believes that "a seemingly new violation may be considered to be a
relocation and reduction of an existing violation only if it were in the area substantially
affected by the project and if the predicted [future] design value for the "new" site would
be less than the design value at the "old" site without the project - that is, if there would
be a net air quality benefit" (58 FR 62213). Since 1993, EPA has made this interpretation
only in limited cases with CO hot-spot analyses where there is a clear relationship
between a proposed project and a possible relocated violation (e.g., a reduced CO
NAAQS violation is relocated from one corner of an intersection to another due to traffic-
related changes from an expanded intersection). Any potential relocated violations in PM
hot-spot analyses should be determined through an area's interagency consultation
procedures.
2.4.3 Guidance focuses on refined PM hot-spot analyses
Finally, the build/no-build analysis described in this guidance represents a refined PM
hot-spot analysis, rather than a screening analysis. Refined analyses rely on detailed
local information and simulate detailed atmospheric processes to provide more
specialized and accurate estimates, and can be done for both the build and no-build
scenarios. In contrast, screening analyses estimate the maximum likely air quality
impacts from a given source under worst case conditions for the build scenario only.14
EPA believes that, because of the complex nature of PM emissions, the statistical form of
each NAAQS, the need to consider temperature effects throughout the time period
covered by the analysis, and the variability of background concentrations over the course
of a year, quantitative PM hot-spot analyses need to be completed using the refined
analysis procedures described in this guidance.
However, there may be cases where using a screening analysis or components of a
screening analysis could be supported in PM hot-spot analyses, such as:
14 Screening analyses for the 1-hour and 8-hour CO NAAQS have been completed based on peak emissions
and worst case meteorology. The shorter time period covered by these NAAQS, the types of projects
modeled, and other factors make screening analyses appropriate for the CO NAAQS.
11
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• Where a project can be characterized as a single source (e.g., a transit terminal
that could be characterized as a single area source). Such a case may be a
candidate for a screening analysis using worst case travel activity and
meteorological data and an appropriate screening model.15
• Where emissions modeling for a project is completed using worst case travel
activity and a recommended air quality model (see Section 7.3).
Both of these options would be appropriate only for the build scenario and may be most
feasible in areas where monitored PM air quality concentrations are significantly below
the applicable NAAQS. In addition, other flexibilities that can simplify the hot-spot
analysis process are included in later parts of this guidance (e.g., calculating design
values in the build scenario first for the receptor with highest modeled concentrations
only).
EPA notes, however, that this guidance assumes that emissions modeling, air quality
modeling, and representative background concentrations are all necessary as part of a
quantitative PM hot-spot analysis in order to demonstrate conformity requirements. For
example, an approach that would involve comparing only emissions between the build
and no-build scenarios, without completing air quality modeling or considering
representative background concentrations, would not be technically supported.16
Furthermore, EPA believes that the value of using a screening option decreases for a PM
hot-spot analysis if a refined analysis will ultimately be necessary to meet conformity
requirements.
Evaluating and choosing models and associated methods and assumptions used in
screening options must be completed through the process established by each area's
interagency consultation procedures (40 CFR 93.105(c)(l)(i)). Please consult with your
EPA Regional Office, which will coordinate with EPA's Office of Transportation and Air
Quality (OTAQ) and Office of Air Quality Planning and Standards (OAQPS), if a
screening analysis option is being considered for a PM hot-spot analysis.
15 Such as AERSCREEN or AERMOD using meteorological conditions suitable for screening analyses.
16 Since Section 93.123(b)(l) of the conformity rule requires PM hot-spot analyses for projects with
significant new levels of PM emissions, it is unlikely that every portion of the project area in the build
scenario would involve the same or fewer emissions than that same portion in the no-build scenario. Such
an approach would not consider the variation of emissions and potential NAAQS impacts at different
locations throughout the project area, which is necessary to meet conformity requirements.
12
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2.5 EMISSIONS CONSIDERED IN PM HOT-SPOT ANALYSES
2. 5. 1 General requirements
PM hot-spot analyses include only directly emitted PM2.5 or PMio emissions. PM2.5 and
PMio precursors are not considered in PM hot-spot analyses, since precursors take time at
the regional level to form into secondary PM. 1?
2.5.2 PM emissions from motor vehicle exhaust, brake wear, and tire wear
Exhaust, brake wear, and tire wear emissions from on-road vehicles are always be
included in a project's PM2.5 or PMio hot-spot analysis. See Sections 4 and 5 for how to
quantify these emissions using MOVES (outside California) or EMFAC (within
California).
2. 5. 3 PM2.5 emissions from re-entrained road dust
Re-entrained road dust must be considered in PM2.5 hot-spot analyses only if EPA or the
state air agency has made a finding that such emissions are a significant contributor to the
PM2.5 air quality problem in a given nonattainment or maintenance area (40 CFR
93.102(b)(3) and 93.119(f)(8)).18
• If a PM^area has no adequate or approved SIP budgets for the PM^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 PM^ area has adequate or approved SIP budgets, re-entrained road dust
would have to be included in a hot-spot analysis only if such budgets include re-
entrained road dust.
See Section 6 for further information regarding how to estimate re-entrained road dust for
PM2.s hot-spot analyses, if necessary.
2. 5. 4 PMio emissions from re-entrained road dust
Re-entrained road dust must be included in all PMio hot-spot analyses. Because road
dust is a significant component of PMio inventories, EPA has historically required road
dust emissions to be included in all conformity analyses of direct PMio emissions -
17 See 40 CFR93.102(b)forthe general requirements for applicable pollutants and precursors in
conformity determinations. Section 93.123(c) provides additional information regarding certain PM
emissions for hot-spot analyses. See also EPA's March 2006 final rule preamble (71 FR 12496-8).
18 See the July 1, 2004 final conformity rule (69 FR 40004).
13
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including hot-spot analyses.19 See Section 6 for further information regarding how to
estimate re-entrained road dust for PMio hot-spot analyses.
2.5.5 PMemissions from construction-related activities
Emissions from construction-related activities are not required to be included in PM hot-
spot analyses if such emissions are considered temporary as defined in 40 CFR
93.123(c)(5) (i.e., emissions which occur only during the construction phase and last five
years or less at any individual site). Construction emissions would include any direct PM
emissions from construction-related dust and exhaust emissions from construction
vehicles and equipment.
For most projects, construction emissions would not be included in PM2.5 or PMio hot-
spot analyses (because, in most cases, the construction phase is less than five years at any
90
one site). However, there may be limited cases where a large project is constructed
over a longer time period, and non-temporary construction emissions must be included
when an analysis year is chosen during project construction. See Section 6 for further
information regarding how to estimate transportation-related construction emissions for
PM hot-spot analyses, if necessary.
2.6 NAAQS CONSIDERED IN PM HOT-SPOT ANALYSES
The CAA and transportation conformity regulations require that conformity be met for all
transportation-related NAAQS for which an area has been designated nonattainment or
maintenance. Therefore, a project-level conformity determination must address all
applicable NAAQS for a given pollutant.21
Accordingly, results from a quantitative hot-spot analysis will need to be compared to all
relevant PM2.5 and PMio NAAQS in effect for the area undertaking the analysis. For
example, in an area designated nonattainment or maintenance for only the annual PM2.5
NAAQS or only the 24-hour PM2.5 NAAQS, the hot-spot analysis would have to address
only that respective PM2.s NAAQS. If an area is designated nonattainment or
maintenance for the annual and 24-hour PM2.5 NAAQS, the hot-spot analysis would have
to address both NAAQS for conformity purposes.
2.7 BACKGROUND CONCENTRATIONS
As required by 40 CFR 93.123(c)(l) and discussed in Section 2.2, a PM hot-spot analysis
"must be based on the total emissions burden which may result from the implementation
of the project, summed together with future background concentrations...." By
19 See the March 2006 final rule (71 FR 12496-98).
20 EPA's rationale for limiting the consideration of construction emissions to five years can be found in its
January 11, 1993 proposed rule (58 FR 3780).
21 See EPA's March 2006 final rule (71 FR 12468-12511).
14
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definition, background concentrations do not include emissions from the project itself.
Background concentrations include the emission impacts of all sources that affect
concentrations in the project area other than the project. Section 8 provides further
information on how background concentrations can be determined.
2.8 APPROPRIATE TIME FRAME AND ANALYSIS YEARS
Section 93.116(a) of the conformity rule requires that PM hot-spot analyses consider
either the full time frame of an area's transportation plan or, in an isolated rural
nonattainment or maintenance area, the 20-year regional emissions analysis.22
Conformity requirements are met if the analysis demonstrates that no new or worsened
violations occur in the year(s) of highest expected emissions - which includes the
project's emissions in addition to background concentrations.23 Areas should analyze the
year(s) within the transportation plan or regional emissions analysis, as appropriate,
during which:
• Peak emissions from the project are expected; and
• A new NAAQS violation or worsening of an existing violation would most likely
occur due to the cumulative impacts of the project and background concentrations
in the proj ect area.
If such a demonstration occurs, then no adverse impacts would be expected to occur in
any other years within the time frame of the transportation plan or regional emissions
analysis.24
The following factors (among others) should be considered when selecting the year(s) of
peak emissions:
• Changes in vehicle fleets;
• Changes in traffic volumes, speeds, and vehicle miles traveled (VMT); and
• Expected trends in background concentrations, including any nearby sources that
are affected by the project.
In some cases, selecting only one analysis year, such as the last year of the transportation
plan or the year of project completion, may not be sufficient to satisfy conformity
requirements. For example, if a project is being developed in two stages and the entire
two-stage project is being approved, two analysis years should be modeled: one to
examine the impacts of the first stage of the project and another to examine the impacts
22 Although CAA section 176(c)(7) and 40 CFR 93.106(d) allow the election of changes to the time
horizons for transportation plan and TIP conformity determinations, these changes to do not affect the time
frame and analysis requirements for hot-spot analyses.
23 If such a demonstration can be made, then EPA believes it is reasonable to assume that no adverse
impacts would occur in any other years within the time frame of the transportation plan or regional
emissions analysis.
24 See EPA's July 1, 2004 final conformity rule (69 FR 40056-40058).
15
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l-\£
of the completed project. Selecting appropriate analysis year(s) should be considered
through the process established by each area's interagency consultation procedures (40
CFR93.105(c)(l)(i)).
2.9 AGENCY ROLES AND RESPONSIBILITIES
The typical roles and responsibilities of agencies implementing the PM hot-spot analysis
requirements are described below. Further details are provided throughout later sections
of this guidance.
2.9.1 Project sponsor
The project sponsor is typically the agency responsible for implementing the project (e.g.,
a state department of transportation, regional or local transit operator, or local
government). The project sponsor is the lead agency for developing the PM hot-spot
analysis, meeting interagency consultation and public participation requirements, and
documenting the final hot-spot analysis in the project-level conformity determination.
2.9.2 DOT
DOT is responsible for making project-level conformity determinations. PM hot-spot
analyses and conformity determinations would generally be included in documents
prepared to meet NEPA requirements. It is possible for DOT to make a project-level
conformity determination outside of the NEPA process (for example, if conformity
requirements apply after NEPA has been completed, but additional federal action on the
project is required). DOT is also an active member of the interagency consultation
process for conformity determinations.
2.9.3 EPA
EPA is responsible for promulgating transportation conformity regulations and provides
policy and technical assistance to federal, state, and local conformity implementers. EPA
is an active member of the interagency consultation process for conformity
determinations. In addition, EPA reviews submitted SIPs, and provides policy and
technical support for emissions modeling, air quality modeling, monitoring, and other
issues.
2.9.4 State and local transportation and air agencies
State and local transportation and air quality agencies are part of the interagency
consultation process and assist in modeling of transportation activities, emissions, and air
quality. These agencies are likely to provide data required to perform a PM hot-spot
analysis, although the conformity rule does not specifically define the involvement of
25 See EPA's July 1, 2004 final rule (69 FR 40057).
16
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these agencies in project-level conformity determinations. For example, the state or local
air quality agency operates the air quality monitoring network, processes meteorological
data, and uses air quality models for air quality planning purposes (such as SIP
development and modeling applications for other purposes). MPOs often conduct
emissions modeling, maintain regional population forecasts, and estimate future traffic
conditions relevant for project planning. The interagency consultation process can be
used to discuss the role of the state or local air agency, the MPO, and other agencies in
project-level conformity determinations, if such roles are not already defined in an area's
conformity SIP.
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Section 3: Overview of a Quantitative PM Hot-Spot Analysis
3.1 INTRODUCTION
This section provides a general overview of the process for conducting a quantitative PM
hot-spot analysis. All individual elements or steps presented here are covered in more
depth and with more technical information throughout the remainder of the guidance.
The general steps required to complete a quantitative PM hot-spot analysis are depicted
in Exhibit 3-1 (following page) and summarized in this section.
As previously noted in Section 2.3, the interagency consultation process is an essential
part of developing PM hot-spot analyses. As a number of fundamental aspects of the
analysis need to be determined through consultation, it is recommended that these
discussions take place as early and as often as necessary for the analysis to be completed
on schedule. In addition, early consultation allows potential data sources for the analysis
to be more easily identified.
3.2 DETERMINE NEED FOR A PM HOT-SPOT ANALYSIS (STEP i)
The conformity rule requires a PM hot-spot analysis only for projects of local air quality
concern. See Section 2.2 regarding how to determine if a project is of local air quality
concern according to the conformity rule.
3.3 DETERMINE APPROACH, MODELS, AND DATA (STEP 2)
3.3.1 General
There are several decisions that need to be made before beginning a PM hot-spot
analysis, including determining the:
• Geographic area to be covered by the analysis (the "project area") and emission
sources to be modeled;
• General approach and analysis year(s) for emissions and air quality modeling;
• Applicable PM NAAQS to be evaluated;
• Type of PM emissions to be modeled for different sources;
• Emissions and air quality models and methods to be used;
• Proj ect-specific data to be used; and
• Schedule for conducting the analysis and points of consultation.
Further details on these decisions are provided below. Evaluating and choosing models
and associated methods and assumptions must be completed through the process
established by each area's interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
18
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Exhibit 3-1. Overview of a PM Quantitative Hot-spot Analysis
Stepl: Determine Need
for Analysis
Is this a project of
local air quality
concern?
•<(
No
r
PM hot-spot analysis
not required
Step 3; Estimate On-Road Motor
Vehicle Emissions
KIs project located
in California?
T
No
r
Estimate using
MOVES
\ Yes
i
Estimate using
EMFAC
Step 4: Estimate Emissions from Road Dust,
Construction, and Additional Sources
Step 5; Select Air
Quality Model, Data
Inputs, and Receptors
Obtain and input
required site data (e.g..
meteorological)
I
Input MOVES/
EMFAC, dust, and
nearby source outputs
Run air quality model
and obtain results
Step 6:
Determine Background
Concentrations
Step 7: Calculate Design
Values and Determine
Conformity
Add Step 5 results to
background concentrations
to obtain design values for
build/no-build scenarios
Do the design
values allow the
project to
conform?
Yes
Step 8:
Consider Mitigation or
Control Measures
Consider measures to
reduce emissions and redo
analysis
Do the design
values allow the
project to
conform?
Step 9:
Document Analysis
No
19
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3.3.2 Determining the geographic area and emission sources to be covered by the
analysis
The geographic area to be covered by a PM hot-spot analysis (the "project area") is to be
determined on a case-by-case basis.26 PM hot-spot analyses must examine the air quality
impacts for the relevant PM NAAQS in the area substantially affected by the project (40
CFR 93.123(c)(l)). To meet this and other conformity requirements, it is necessary to
define the project, determine where it is to be located, and ascertain what other emission
sources are located in the project area.27 In addition to emissions from the proposed
9R
highway or transit project, there may be nearby sources of emissions that need to be
estimated and included in air quality modeling (e.g., a freight rail terminal that is affected
by the project). There also may be other sources in the project area that are determined to
be insignificant to project emissions (e.g., a service drive or small employee parking lot).
See Sections 4 through 6 for how to estimate emissions from the proposed project, and
Sections 6 through 8 for when and how to include nearby source emissions and other
background concentrations.
Hot-spot analyses must include the entire project (40 CFR 93.123(c)(2)). However, it
may be appropriate in some cases to focus the PM hot-spot analysis only on the locations
of highest air quality concentrations. For large projects, it may be necessary to analyze
multiple locations that are expected to have the highest air quality concentrations and,
consequently, the most likely new or worsened PM NAAQS violations. If conformity is
demonstrated at such locations, then it can be assumed that conformity is met in the entire
project area. For example, if a highway project involves several lane miles with similar
travel activity (and no nearby sources that need to be modeled), the scope of the PM hot-
spot analysis could involve only the point(s) of highest expected PM concentrations. If
conformity requirements are met at such locations, then it can be assumed that
conformity is met throughout the project area. Such an approach would be preferable to
modeling the entire length of the highway project, which would involve additional time
and resources.
Questions regarding the scope of a given PM hot-spot analysis can be determined through
the interagency consultation process.
3.3.3 Deciding the general analysis approach and analysis year(s)
As stated in Section 2.4, there are several approaches for completing a build/no-build
analysis for a given project. For example, a project sponsor may want to start by
completing the build scenario first to see if a new or worsened PM NAAQS violation is
26 Given the variety of potential projects that may require a PM hot-spot analysis, it is not possible to
provide one definition or set of parameters that can be used in all cases to determine the area covered by the
PM hot-spot analysis.
27 See more in the March 24, 2010 final conformity rule entitled "Transportation Conformity Rule PM2s
and PM10 amendments," 75 FR 14281; found online at: www.epa.gov/otaq/stateresources/transconf/conf-
regs.htm.
28 40 CFR 93.101 defines "highway project" and "transit project" for transportation conformity purposes.
20
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predicted (if not, then modeling the no-build scenario would be unnecessary). In
contrast, a project sponsor could start with the no-build scenario first if a future PM
NAAQS violation is anticipated in both the build and no-build scenarios (even after
mitigation or control measures are considered).
It is also necessary to select one or more analysis years within the time frame of the
transportation plan or regional emissions analysis when emissions from the project, any
nearby sources, and background are expected to be highest. See Section 2.8 for more
information on selecting analysis year(s).
3.3.4 Determining the PM NAAQS to be evaluated
As stated in Section 2.6, PM hot-spot analyses need to be evaluated only for the NAAQS
for which an area has been designated nonattainment or maintenance. In addition, there
are aspects of modeling that can be affected by whether a NAAQS is an annual or a 24-
hour PM NAAQS. It is also important to conduct modeling for those parts of an analysis
year where PM concentrations are expected to be highest. For example, a hot-spot
analysis for the annual PM2.5 NAAQS would involve data and modeling throughout a
9Q
given analysis year (i.e., all four quarters of the analysis year).
A hot-spot analysis for the 24-hour PM2.5 or PMio NAAQS would also involve data and
modeling throughout an analysis year, except when future NAAQS violations and peak
emissions in the project area are expected to occur in only one quarter of the future
analysis year(s). In such cases, a project sponsor could choose to complete emissions and
air quality modeling for only that quarter, as determined through the interagency
consultation process. For example, if an area's SIP demonstration is based on only one
quarter for a 24-hour PM NAAQS, it may be appropriate to make the same assumption
for hot-spot analyses for that NAAQS. This could be the case in a PMio nonattainment or
maintenance area that has PMio NAAQS violations only during the first quarter of the
year (January-March), when PM emissions from other sources, such as wood smoke, are
highest. In such an area, if the highest emissions from the project area are also expected
to occur in this same quarter, then the project sponsor could complete the PM hot-spot
analysis for only that quarter. EPA notes, however, that it may be difficult to determine
whether 24-hour PM2.5 NAAQS violations will occur in only one quarter. State and local
air quality agencies should be consulted regarding when it may be appropriate for a PM
hot-spot analysis for a 24-hour PM NAAQS to cover only one quarter in an analysis year.
These agencies are responsible for monitoring air quality violations and for developing
SIP attainment demonstrations.
29 Calendar quarters in this guidance are defined in the following manner: Ql (January-March), Q2 (April-
June), Q3 (July-September), and Q4 (October-December). These quarters are also used by EPA and state
and local agencies to calculate design values for air quality monitoring purposes and for SIP development.
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3.3.5 Deciding on the type of PM emissions to be modeled
See Section 2.5 for further information on what types of directly emitted PM must be
included in hot-spot analyses and Sections 4 through 6 and Section 8 on when and how to
quantify PM emissions.
3.3.6 Determining the models and methods to be used
The emissions and air quality models and methods used in PM hot-spot analyses must be
evaluated and chosen through the process established by each area's interagency
consultation procedures (40 CFR 93.105(c)(l)(i)). The latest approved emissions
models must be used in PM hot-spot analyses (40 CFR 93.111). See Sections 3.4 through
3.6 and the subsequent sections of the guidance they refer to for specific information
about models and methods that apply.
Note: It is important to select an air quality model to be used in the PM hot-spot analysis
early in the process, since this information is necessary to prepare emissions model
outputs for air quality modeling purposes. See Section 7 for further information on when
AERMOD and CAL3QHCR are recommended air quality models for PM hot-spot
analyses.
3.3.7 Obtaining project-specific data
The conformity rule requires that the latest planning assumptions available at the time
that the analysis begins be used in conformity determinations (40 CFR 93.110). In
addition, the regulation states that hot-spot analysis assumptions must be consistent with
those assumptions used in the regional emissions analysis for any inputs that are required
for both analyses (40 CFR 93.123(c)(3)).
The project sponsor should use project-specific data for both emissions and air quality
modeling whenever possible, though default inputs may be appropriate in some cases.
The use of project-specific versus default data is discussed further in this guidance.
The following are examples of data needed to run MOVES or EMFAC, as described in
Sections 4 and 5:
• Traffic data sufficient to characterize each link in the project area;
• Starts per hour and number of vehicles idling during each hour for off-network
links/sources;
• Vehicle types and age distribution expected in the project area; and
• Temperature and humidity data for each month and hour included in the analysis.
Depending on the air quality model to be used, the following are examples of data that
will likely be needed, as described in Sections 7 through 9:
• Surface meteorological data from monitors that measure the atmosphere near the
ground;
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• Upper air data describing the vertical temperature profile of the atmosphere;
• Land use data describing surface characteristics near the surface meteorological
monitors;
• Nearby population data; and
• Information necessary for determining locations of air quality modeling receptors.
To complete the PM hot-spot analysis, areas will also need data on background
concentrations in the project area from nearby or other emission sources, as described in
Section 8.
3.4 ESTIMATE ON-ROAD MOTOR VEHICLE EMISSIONS (STEP 3)
There are two approved motor vehicle emissions models available for estimating the
project's exhaust, brake wear, and tire wear emissions. See Section 4 for more on
estimating these PM emissions with EPA's MOVES model. Section 5 describes how to
apply EMFAC for estimating these emissions for projects in California.
3.5 ESTIMATE EMISSIONS FROM ROAD DUST, CONSTRUCTION, AND
ADDITIONAL SOURCES (STEP 4)
Section 2.5 provides more information about when re-entrained road dust and/or
construction emissions are included in PM hot-spot analyses. Section 6 describes
methods for estimating these emissions.
There may be other sources of emissions that also need to be estimated, and included in
air quality modeling. Section 8 provides further information regarding how to account
for these emissions in a PM hot-spot analysis and Appendix I describes how to estimate
locomotive emissions.
3.6 SELECT AN AIR QUALITY MODEL, DATA INPUTS AND RECEPTORS
(STEP 5)
An air quality model estimates PM concentrations at specific points in the project area
known as "receptors." Emissions that result from the project (including those from
vehicles, dust, and construction from Steps 3 and 4) as well as any other nearby emission
sources that are affected by the project (e.g., expanded locomotive emissions at a freight
terminal) are included in the selected air quality model, which predicts how emissions are
dispersed based on meteorological and other input data.
There are two air quality models—AERMOD and CAL3QHCR— recommended for use
in PM hot-spot analyses, depending on the project involved. Basic information about
23
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these models, including how to select an appropriate model for a particular project and
the data needed to run them, is found in Section 7 and Appendix J.
3.7 DETERMINE BACKGROUND CONCENTRATIONS FROM NEARBY AND
OTHER SOURCES (STEP 6)
The PM hot-spot analysis must also account for background PM concentrations in the
project area. Section 8 provides further information on selecting representative
background concentrations, including when to incorporate nearby sources into air quality
modeling.
3.8 CALCULATE DESIGN VALUES AND DETERMINE CONFORMITY (STEP 7)
In general, the PM concentrations estimated from air quality modeling (from Step 5) are
then combined with background concentrations (from Step 6) at the receptor locations for
both the build and no-build scenarios. The resulting statistic is referred to as a design
value; how it is calculated depends on the form of the NAAQS. If the design value in the
build scenario is less than or equal to the relevant PM NAAQS at appropriate receptors,
then the project meets conformity requirements. In the case where the design value is
greater than the NAAQS in the build scenario, a project could still meet conformity
requirements if the design values in the build scenario were less than or equal to the
design values in the no-build scenario at appropriate receptors. See Sections 2.4 and 9
for further details on build/no-build approaches and implementation.
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3.9 CONSIDER MITIGATION OR CONTROL MEASURES (STEP 8)
Where a project does not meet conformity requirements, a project sponsor may consider
mitigation or control measures to reduce emissions in the project area. If such measures
are considered, additional modeling will need to be completed and new design values
calculated to ensure that conformity requirements are met. A project sponsor could
decide to add mitigation or control measures at any time in the process; such measures
must include written commitments for implementation (40 CFR 93.125). See Section 10
for more information on possible measures for consideration.
3.10 DOCUMENT THE PM HOT-SPOT ANALYSIS (STEP 9)
The PM hot-spot analysis should include sufficient documentation to support the
conclusion that a proposed project meets conformity rule requirements per 40 CFR
93.116 and 93.123. This documentation should include, at a minimum:
• A description of the proposed project, including where the project is located, the
project's scope (e.g., adding an interchange, widening a highway, expanding a
major bus terminal), when the project is expected to be open to traffic, travel
activity proj ected for the analysis year(s), and what part of 40 CFR 93.123(b)(l)
applies; °
• A description of the analysis year(s) examined and the factors considered in
determining the year(s) of peak emissions;
• Emissions modeling, including the emissions model used (e.g., MOVES),
modeling inputs and results, and how the project was characterized in terms of
links;
• Modeling inputs and results for estimating re-entrained road dust, construction
emissions, and any nearby source emissions (if applicable to a particular PM hot-
spot analysis);
• Air quality modeling data, including the air quality model used, modeling inputs
and results, and description of the receptors employed in the analysis;
• A description of the assumptions used to determine background concentrations;
• A discussion of any mitigation or control measures that will be implemented, the
methods and assumptions used to quantify their expected effects, and associated
written commitments;
• A description of how the interagency consultation and public participation
requirements in 40 CFR 93.105 were met; and
• A conclusion for how the proposed project meets 40 CFR 93.116 and 93.123
conformity requirements for the PM2.5 and/or PMio NAAQS.
Documentation should describe the sources of data used in preparing emissions and air
quality modeling inputs. This documentation should also describe any critical
30 This information could reference the appropriate sections of any NEP A document prepared for the
project.
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assumptions that have the potential to affect predicted concentrations. Documentation of
PM hot-spot analyses would be included in the project-level conformity determination.
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Section 4: Estimating Project-Level PM Emissions Using
MOVES
4.1 INTRODUCTION
This section of the guidance describes how to use MOVES to estimate PM exhaust, brake
wear, and tire wear emissions for PM hot-spot analyses outside of California.31 This
section focuses on determining the appropriate project-level inputs and how MOVES
should be run to provide the necessary information to complete air quality modeling.32
MOVES is a computer model designed by EPA to estimate emissions from cars, trucks,
buses and motorcycles. MOVES replaces MOBILE6.2, EPA's previous emissions
model.33 MOVES is based on an extensive review of in-use vehicle data collected and
analyzed since the release of MOBILE6.2. MOVES estimates PM emissions to account
for speed and temperature variations and models emissions at a high resolution. As a
result, MOVES allows users to incorporate a much wider array of vehicle activity data
for each roadway link, as well as start and extended idle activity in transit or other
terminal projects.
Exhibit 4-1 (following page) shows the necessary steps for applying the MOVES model
for project-level PM hot-spot analyses.
This section presumes users already have a basic understanding of how to run the
MOVES model.34 MOVES includes a default database of meteorology, fleet, activity,
fuel, and control program data for the entire United States. The data included in this
database come from a variety of sources which are not necessarily the most accurate or
up-to-date information available at the local level for a particular project. This section
describes when the use of that default database is appropriate for PM hot-spot analysis, as
well as when available local data must be used (40 CFR93.110 and 93.123(c)).
31 This guidance is applicable to current and future versions of the MOVES model, unless EPA notes
otherwise when approving the model for conformity purposes.
32 Technical guidance on using MOVES for regional emissions inventories can be found in "Technical
Guidance on the Use of MOVES2010 for Emission Inventory Preparation in State Implementation Plans
and Transportation Conformity," EPA-420-B-10-023 (April 2010); available online at:
www.epa.gov/otaq/stateresources/transconf/policv.htm.
33 EPA stated in the preamble to the March 2006 final rule that finalizing the MOVES emissions model was
critical before quantitative PM hot-spot analyses are required, due to the limitations of applying
MOBILE6.2 for PM at the project level. See EPA's March 2006 final rule for further information (71 FR
12498-12502).
34 The MOVES model, user guide, and supporting documentation are available online at:
www.epa.gov/otaq/models/moves/index.htm.
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Exhibit 4-1. Steps for Using MOVES in a Quantitative PM Hot-spot Analysis
Divide the project into
links
(Section 4.2)
,
,
Determine the number of
MOVES runs
(Section 4,3)
i
Generate Run Specification ("RunSpec")
r
Enter time period
(Section 4.4.3)
i
^ Select road type
* (Section 4.4.6)
i
r
Specify county
(Section 4. 4. 4)
^
r
ject have \
network'' \ Yes Include "off-
nt engine / type
r idling? /
/
I No
Select Select PM
fuel/vehicle pollutants & .
combination processes
(Section 4.4.5) (Section 4.4.7)
1
I
L
Enter Data into P
Enter meteorology
data
(Section 4. 5.1)
4.
Build age
distribution table
(Section 4. 5.2)
Define
•^ fuels/fuel mix
(Section 4. 5. 3)
1
Populate link
•^ source type
(Section 4. 5. 5)
reject Data Manager
Populate off-
network table 4 ~ ~
(Section 4. 5. 9)
Describe link Run MOVES &
r_ ^ activity ^ generate emission
(Sections 4.5.6 - factors
4.5.8) (Section 4.6)
Note: The steps in this exhibit and in the accompanying text describe how to use MOVES at the
project-level for a PM hot-spot analysis.
28
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As discussed in Section 2.4, it is suggested that project sponsors conduct emissions and
air quality modeling for the project build scenario first. If the resulting design value does
not exceed the NAAQS, then the project meets the hot-spot analysis requirements of
project-level conformity, and it is not necessary to model the no-build scenario.
Following this approach will allow users to avoid unnecessary emissions and air quality
modeling.
Finally, Section 4 describes how to use MOVES to estimate emissions from a highway or
transit project that requires a PM hot-spot analysis ("the project"); this section could also
be used to estimate emissions for any other highway and transit facilities in the project
area, when necessary.
4.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS
Prior to entering data into MOVES, the first step is to identify the project type and the
associated emission processes (running, start, brake wear, tire wear, extended idle, and
crankcase) to be modeled. This guidance distinguishes between two types of
transportation projects: (1) highway and intersection projects, and (2) transit or other
terminal projects:
• For highway and intersection projects, running exhaust, crankcase, brake wear,
and tire wear emissions are the main focus.
• For transit and other terminal projects, start, crankcase, and extended idle
emissions are typically needed; in some cases, these projects will also need to
address cruise, approach and departure running exhaust emissions on affected
links.
The goal of defining a project's links is to accurately capture emissions where they occur.
Within MOVES, a link represents a segment of road or an "off-network" location where
a certain type of vehicle activity occurs.35 Generally, the links specified for a project
should include segments with similar traffic/activity conditions and characteristics (e.g.,
decelerating vehicles approaching an intersection should be treated as one link). From
the link-specific activity and other inputs, MOVES calculates emissions from every link
of a project for a given time period (or run). In MOVES, running emissions, including
periods of idling at traffic signals, are defined in the Links Importer (see Section 4.5.6),
while starts and extended periods of idling (e.g., truck idling at a freight terminal) are
defined in the Off-Network Importer (see Section 4.5.9). There are no limits to the
number of links that can be defined in MOVES.
35 "Off-network" in the context of MOVES refers to an area of activity not occurring on a roadway.
Examples of off-network links include parking lots and freight or bus terminals.
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4.2.1 Highway and intersection projects
General
A PM hot-spot analysis fundamentally depends on the availability of accurate data on
roadway link speed and traffic volumes for build and no-build scenarios.36 Thus, local
traffic data should be used to characterize each link sufficiently. It is recommended that
the user divide a project into separate links to allow sufficient resolution at different
vehicle traffic and activity patterns; characterizing this variability in emissions within the
project area will assist in air quality modeling (see Section 7).
In MOVES, activity on free-flow highway links can be defined by an average speed, link
drive schedule, or operating mode ("Op-Mode") distribution (discussed in Section 4.5.7).
For analyses with MOVES, average speed and traffic volume, at a minimum, is needed
for each link. If no other information is available, MOVES uses default assumptions of
vehicle activity patterns (called drive cycles) for average speed and type of roadway to
estimate emissions. Default drive cycles use different combinations of vehicle activity
(acceleration, deceleration, cruise, and/or idle) depending on the speed and road type.
For example, if the link average speed is 30 mph and it is an urban arterial (urban
unrestricted road type), MOVES uses a default drive cycle that includes a high proportion
of acceleration, deceleration, and idle activity as would be expected on an urban arterial
with frequent stops. If the average speed is 60 mph and it is a rural freeway (rural
restricted road type), MOVES uses a default drive cycle that assumes a higher proportion
of cruise activity, smaller proportions of acceleration and deceleration activity, and little
or no idle activity.
Project sponsors should determine average congested speeds by using appropriate
methods based on best practices used for highway analysis.37 Some resources are
available through FHWA's Travel Model Improvement Program (TMIP).38
Methodologies for computing intersection control delay are provided in the Highway
Capacity Manual 2000.39
As described further in Section 4.5.7, users should take advantage of the full capabilities
of MOVES for estimating emissions on different highway and intersection project links.
36 Project sponsors should document available traffic data sets, their sources, key assumptions, and the
methods used to develop build and no-build scenario inputs for MOVES. Documentation should include
differences between how build and no-build traffic projections are obtained. For projects of local air
quality concern, differences in traffic volumes and other activity changes between the build and no-build
scenarios must be accounted for in the data that is used in the PM hot-spot analysis.
37 As discussed in Section 7, the use of the CAL3QHCR queuing algorithm for intersection idle queues is
not recommended. Rather, idling vehicles should be represented in combination with decelerating,
accelerating, and free-flow traffic on an approach segment of an intersection.
38 See FHWA's TMIP website: http://tmip.fhwa.dot.gov/.
39 Users should consult the most recent version of the Highway Capacity Manual. As of the release of this
guidance, the latest version is the Highway Capacity Manual 2000, which can be obtained from the
Transportation Research Board (see http://144.171.ll.107/Main/Public/Blurbs/152169.aspx for details).
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Although average speeds and travel volumes are typically available for most
transportation projects and may need to be relied upon during the transition to using
MOVES, users can develop and use more precise data through the MOVES Operating
Mode Distribution Importer or Link Drive Schedule Importer, as described further below.
When more detailed data are available to describe the pattern of changes in vehicle
activity (proportion of time in acceleration, deceleration, cruise, or idle activity) over a
length of road, MOVES is capable of calculating these specific emission impacts. EPA
encourages users to consider these options for highway and intersection projects,
especially as MOVES is implemented further into the future, or for more advanced
MOVES applications.
Free-flow Highway Links
The links defined in MOVES should capture the expected physical layout of a project and
representative variations in vehicle activity. A simple example would be a single, one
directional, four-lane highway that could be characterized as just one link. More
sophisticated analyses may break up traffic flow on that single link into multiple links of
varying operating modes or drive cycles that may have different emission factors
depending on the relative acceleration, cruise, or deceleration activity on each segment of
that link. In general, the definition of a link will depend on how much the type of vehicle
activity (acceleration, deceleration, cruise or idle) changes over a length of roadway, the
level of detail of available data, and the modeling approach used with MOVES. For a
highway lane where vehicle behavior is fairly constant, the length of the link could be
longer and the use of detailed activity data will have a smaller impact on results.
Intersection Links
If the project analysis involves intersections, the intersections need to be treated
separately from the free-flow links that connect to those intersections. Although road
segments between intersections may experience free-flow traffic operations, the
approaches and departures from the intersections will likely involve acceleration,
deceleration, and idling activity not present on the free-flow link. For intersection
modeling, the definition of link length will depend on the geometry of the intersection,
how that geometry affects vehicle activity, and the level of detail of available activity
information. Guidance for defining intersection links is given in Appendix D, but the
definition of links used for a particular project will depend of the specific details of that
project and the amount of available activity information.40
Note: For both free-flow highway and intersection links, users may directly enter output
from traffic simulation models in the form of second-by-second individual vehicle
trajectories. These vehicle trajectories for each road segment can be input into MOVES
using the Link Drive Schedule Importer and defined as unique LinklDs. There are no
limits in MOVES as to how many links can be defined; however, model run times
40 As discussed in Section 7, the use of the CAL3QHCR queuing algorithm for intersection idle queues is
not recommended. Rather, idling vehicles should be represented in combination with decelerating,
accelerating, and free-flow traffic on an approach segment of an intersection.
31
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increase as the user defines more links. More information on using vehicle trajectories
from traffic micro-simulation models is found in Appendix D.
4.2.2 Transit and other terminal projects
For off-network sources such as a bus terminal or intermodal freight terminal, the user
should have information on starts per hour and number of vehicles idling during each
hour. This activity will likely vary from hour to hour. Additionally, if there are vehicles
starting, it is necessary to provide an estimate of the duration that vehicles are parked
before starting (soak-time distribution). It is recommended that the user divide such a
project into separate links to appropriately characterize variability in emission density
within the project area (as discussed in Section 7). In this case, each "link" describes an
area with a certain number of vehicle starts per hour, or a certain number of vehicles
idling during each hour.
Some transit and other terminal projects may have significant running emissions similar
to free-flow highway projects (such as buses and trucks coming to and from an
intermodal terminal). These emissions can be calculated by defining one or more unique
running links as described in Section 4.2.1 and Appendix D (that is, in addition to any
other roadway links associated with the project). These running link emissions can then
be aggregated with the emissions from starts and idling from non-running activity on the
transit or other terminal link outside of the MOVES model to generate the necessary air
quality model inputs.
Long duration idling (classified in MOVES as OpModelD 200) can only be modeled in
MOVES for long-haul combination trucks. Idling for other vehicles and shorter periods
of idling for long-haul combination trucks should be modeled as a project link with an
operating mode distribution that consists only of idle operation (OpMode 1). This can be
specified in the Links table by inputting the vehicle population and specifying an average
speed of "0" mph.
Note: The user may choose to exclude sources such as a separate service drive, separate
small employee parking lot, or other minor sources that are determined to be
insignificant to project emissions.
4.3 DETERMINING THE NUMBER OF MOVES RUNS
4.3.1 General
When MOVES is run at the project scale, it estimates emissions for only the hour
specified by the user. Before running MOVES to calculate emission factors, users should
first determine the number of unique scenarios that can sufficiently describe activity
variation in a project. In most projects, traffic volume, average speed, idling, fleet mix,
and the corresponding emission factors will likely vary from hour to hour, day to day,
and month to month. However, it is unlikely that data are readily available that capture
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such finite changes. Project sponsors may have activity data collected at a range of
possible temporal resolutions. The conformity rule requires the use of the latest planning
assumptions or data available at the time the conformity analysis begins (40 CFR
93. 1 10).41 Depending on the sophistication of the activity data analysis for a given
project, these data may range from a daily average-hour and peak-hour value to hourly
estimates for all days of the year. EPA encourages the development of sufficient travel
activity data to capture the expected ranges of traffic conditions for the build and no-build
scenarios.
The number of MOVES runs should be based on the best available activity data and the
PM NAAQS involved. One of the advantages to using MOVES is that, for the first time,
PM emission estimates are sensitive to temperature changes through a day and across a
year. Therefore, EPA is recommending the minimum number of MOVES runs that is
necessary for PM hot-spot analysis to capture changes in emission rates due to changes in
ambient conditions.42 Exhibit 4-2 includes EPA's recommendations for PM hot-spot
analyses:
Exhibit 4-2. Typical Number of MOVES Runs for an Analysis Year
Applicable NAAQS
Annual PM2.5 NAAQS only
24-hour PM2.5 NAAQS only
24-hour PMio NAAQS only
Annual and 24-hour PM
NAAQS44
Build Scenario
16
16 (4 in certain cases)
16 (4 in certain cases)
16
No-build Scenario
16
16 (4 in certain cases)
16 (4 in certain cases)
16
Hot-spot analyses for the annual PM2 5 NAAQS should include 16 unique MOVES runs
(i.e., four runs for different time periods for each of four calendar quarters). For a typical
build/no-build analysis, a total of 32 runs would be needed (16 for the build scenario and
16 for the no-build scenario). Hot-spot analyses for only the 24-hour PM2 5 or PMio
NAAQS should also be completed with 16 MOVES runs for each scenario, except in
cases where potential PM NAAQS violations are expected to occur in only one quarter of
the calendar year. In such cases, the user may choose to model only that quarter with
41 See "EPA and DOT Joint Guidance for the Use of Latest Planning Assumptions in Transportation
Conformity Determinations," EPA-420-B-08-901 (December 2008) for a more detailed discussion of the
latest planning assumptions requirements:
www.epa. gov/otaq/stateresources/transconf/policv/420b08901 .pdf.
42 Information on PM emission rate sensitivity to temperature inputs is available in "Draft MOVES2009
Highway Vehicle Temperature, Humidity, Air Conditioning, and Inspection and Maintenance
Adjustments" at: www.epa.gov/otaq/models/moves/techdocs/420p09003.pdf.
43 There are some cases where the no-build scenario and associated emissions and air quality modeling is
not necessary. See Section 2.4 for further information.
44 Such a situation would include cases where a project is located in a nonattainment/maintenance area for
both the annual PM25 NAAQS and either a 24-hour PM25 NAAQS or the 24-hour PM10 NAAQS.
33
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four MOVES runs for each scenario. See Section 3.3 for more information on when
using fewer MOVES runs is appropriate for the 24-hour PM NAAQS.
The product of the MOVES analysis is a year's (or quarter's) worth of hour-specific
emission factors for each project link that will be applied to the appropriate air quality
model (discussed in Section 7) and compared to the relevant PM NAAQS (discussed in
Section 9). The following subsections provide further information for determining
MOVES runs for all PM NAAQS, based on the level of available travel activity data.
4.3.2 Projects with typical travel activity data
Traffic forecasts for highway and intersection projects are often completed for annual
average daily traffic volumes, with an allocation factor for a daily peak-hour volume.
This data can be used to conduct an analysis with MOVES that is representative for all
hours of the year. To complete 16 MOVES runs as outlined above, the user should run
MOVES for four months: January, April, July, and October; and four weekday time
periods: morning peak (AM), midday (MD), evening peak (PM), and overnight (ON).45
The AM and PM peak periods should be run with peak-hour traffic activity; MD and ON
periods should be run with average-hour activity. The most reasonable methods in
accordance with good practice should be used to obtain the peak hour allocation factors
and diurnal distribution of traffic; these methods must be determined in accordance with
interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
The results for each of the four hours can then be extrapolated to cover the entire day.
For example, the peak-hour volume can be used to represent activity conditions over a
three-hour morning (AM) and three-hour evening (PM) period. The remaining 18 hours
of the day can be represented by the average-hour volume. These 18 hours would be
divided into a midday (MD) and overnight (ON) scenario.
The following is one suggested approach for an analysis employing the average-
hour/peak-hour traffic scenario:
• Morning peak (AM) emissions based on traffic data and meteorology occurring
between 6 a.m. and 9 a.m.;
• Midday (MD) emissions based on data from 9 a.m. to 4 p.m.;
• Evening peak (PM) emissions based on data from 4 p.m. to 7 p.m.; and
• Overnight (ON) emissions based on data from 7 p.m. to 6 a.m.
If there are local or project-specific data to suggest that the AM or PM peak traffic
periods will occur in different hours than the default values suggested here, or over a
longer or shorter period of time, that information should be documented and the hours
representing each time period adjusted accordingly. Additionally, users should determine
peak periods for the build and no-build scenarios independently and not assume that each
scenario is identical.
45 If only four MOVES runs are required for a PM hot-spot analysis for a 24-hour PM NAAQS, four runs
would be done for the same weekday time periods, except only for one quarter (i.e., January, April, July, or
October) for each build or no-build scenario.
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The emission factors for each month's runs should be used for the other months within
the quarter. The months suggested for the minimum number of MOVES runs correspond
to the first month of each quarter. For instance, January emissions should be assumed to
represent February and March emissions, April should be used to represent May and June
emissions, and so forth.46
4.3.3 Projects with additional travel activity data
Some project sponsors may have developed traffic or other activity data to show
variations in volume and speed across hours, days, or months. Additionally, if users are
modeling a transit or other terminal project, traffic volumes, starts, and idling estimates
are likely to be readily available for each hour of the day. Under either of these
circumstances, users have the option of applying the methodology described above (using
average-hour and peak-hour as representative for all hours of the year) if it is determined
through the interagency consultation process that using the additional data would not
significantly impact the emissions modeling results. Alternatively, additional MOVES
runs could be generated to produce unique emission factors using these additional activity
data and emission factors for each period of time for which specific activity data are
available.
4.4 DEVELOPING BASIC RUN SPECIFICATION INPUTS
Once the user has defined the project conceptually in terms of links and determined the
number of MOVES runs, the next step in using MOVES for project-level analyses is to
develop a run specification ("RunSpec"). The RunSpec is a computer file in XML
format that can be edited and executed directly or with the MOVES Graphical User
Interface (GUI). MOVES needs the user to set up a RunSpec to define the place and time
of the analysis as well as the vehicle types, road types, fuel types, and the emission-
producing processes and pollutants that will be included in the analysis.
The headings in this subsection describe each set of input options needed to create the
RunSpec as defined in the Navigation panel of the MOVES GUI. In order to create a
project-level RunSpec, the user would go down the Navigation panel filling in the
appropriate data for each of the items listed. A new panel will open for each item:
• Description
• Scale
• Time Spans
• Geographic Bounds
• Vehicles/Equipment
• Road Type
• Pollutants and Processes
• Manage Input Data Sets
46 Rather than use the middle month of the first quarter (February), January is used because it is typically
the coldest month of the year and therefore has the highest PM emission rates.
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• Strategies
• Output
• Advanced Performance Features
Additional information on each panel can be found in the MOVES User Guide available
on EPA's website (www.epa.gov/otaq/models/moves/index.htm). The appropriate
sections of the user guide are referenced when describing the RunSpec creation process
below.
4.4.1 Description
(MOVES User Guide Section 2.2.1)
The Description panel allows the user to enter a description of the RunSpec using up to
5,000 characters of text. Entering a complete description of the RunSpec is important for
users to keep track of their MOVES runs as well as to provide supporting documentation
for the regulatory submission. Users may want to identify the project, the time period
being analyzed, and the purpose of the analysis in this field.
4.4.2 Scale
(MOVES User Guide Section 2.2.2)
The Scale panel in MOVES allows the user to select different scales or domains for the
MOVES analysis. All MOVES runs for project-level analysis must be done using the
"Project" domain in the Scale panel. Selecting the "Project" domain is necessary to
allow MOVES to accept detailed activity input at the link level.47
Users can select either "Inventory" or "Emission Rates" as output, depending on the air
quality model being used:
• When using AERMOD, a grams/hour emission factor is needed. Users should
select "Inventory," which produces results for total emissions on each link; this is
equivalent to a grams/hour/link emission factor.
• When using CAL3QHCR, the "Emission Rates" option should be selected to
produce link specific grams/vehicle-mile emission factors.
This guidance explains the steps of post-processing both "Inventory" and "Emission
Rates" results to produce the desired emission factors in Section 4.6.
47 Running MOVES using the "County" or "National" domains would not allow for detailed link-level
input or output that is needed for PM hot-spot analyses.
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4.4.3 Time Spans
(MOVES User Guide Section 2.2.3)
The Time Spans panel is used to define the specific time period covered in the MOVES
run. The Time Spans panel allows the user to select the time aggregation level and the
year, month, day, and hour included in the run.
For the project domain, the MOVES model processes one hour, of one day, of one
month, of one year for each run; that is, each MOVES run represents one specific hour.
The user should enter the desired time period in the MOVES Time Span panel for
estimating PM2.5 and/or PMio emissions for the relevant NAAQS in a given
nonattainment or maintenance area. Time aggregation should be set to "hour," which
indicates no pre-aggregation. The "day" selection should be set to "weekday" or
"weekend," but not both. Most users will be defining activity for a typical weekday. The
year, month, and hour should be set to specifically describe each MOVES run. For
instance, one run might be: 2015, January, 8:00 to 8:59 a.m. (the start and end hours both
set to 8:00 to 8:59 a.m.). The user may choose to build a batch file to automate the
4R
process of running multiple scenarios.
4.4.4 Geographic Bounds
(MOVES User Guide Section 2.2.4)
The Geographic Bounds panel allows the user to define the specific county that will be
modeled. The MOVES database includes county codes and descriptive information for
all 3,222 counties in the United States. Specifying a county in MOVES determines
certain default information for the analysis. Users should select the specific county
where the project is located. Only a single county (or single custom domain) can be
included in a MOVES run at the project level. If a project spans multiple counties, users
have three options:
1. If the fuel supply and age distribution of vehicles in the fleet are the same for all
of the counties, select the county in which the majority of the project area is
located;
2. If not, separate the project into multiple parts (each of which is in a separate
county) and do a separate MOVES run for each part; or
3. Use the custom domain option to model one unique area that represents all the
project counties.
4.4.5 Vehicles/Equipment
(MOVES User Guide Section 2.2.5)
The Vehicles/Equipment panel is used to specify the vehicle types that are included in the
MOVES run. MOVES allows the user to select from among 13 "source use types" (the
terminology that MOVES uses to describe vehicle types) and several different fuels.
48 For more information about using batch commands, see Appendix C of the MOVES User Guide,
available online at: www.epa.gov/oms/models/moves/index.htm.
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Some fuel/source type combinations do not exist (e.g., diesel motorcycles) and therefore
are not included in the MOVES database. PM hot-spot analyses must include all vehicle
types that are expected to operate in the project area. Users should select the appropriate
fuel and vehicle type combinations in the On Road Vehicle Equipment panel to reflect
the full range of vehicles that will operate in the project area. The fuel type "Placeholder
Fuel Type" should not be selected as it can cause errors.
4.4.6 Road Type
(MOVES User Guide Section 2.2.6)
The Road Type panel is used to define the types of roads that are included in the project.
MOVES defines five different road types:
• Rural Restricted Access - a rural highway that can be accessed only by an on-
ramp;
• Rural Unrestricted Access - all other rural roads (arterials, connectors, and local
streets);
• Urban Restricted Access - an urban highway that can be accessed only by an on-
ramp;
• Urban Unrestricted Access - all other urban roads (arterials, connectors, and local
streets); and
• Off-Network - any location where the predominant activity is vehicle starts and
idling (parking lots, truck stops, rest areas, freight or bus terminals).
MOVES uses these road types to determine the default drive cycle on a particular link.
For example, MOVES uses drive cycles for unrestricted access road types that assume
stop-and-go driving, including multiple accelerations, decelerations, and short periods of
idling. For restricted access road types, MOVES uses drive cycles that include a higher
fraction of cruise activity with much less time spent accelerating or idling.
For project-level analyses, the extent upon which MOVES uses these default drive cycles
will depend on how much additional information the user can supply for the link. The
process of choosing default or local drive cycles is described in Sections 4.2 and 4.5.7.
However, even if the user will be supplying detailed, link-specific drive cycle
information or an Op-Mode distribution, road type is a necessary input in the RunSpec
and users should select one or more of the five road types that correspond to the road
types of the links that will be included in the project area. The determination of rural or
urban road types should be based on the Highway Performance Monitoring System
(HPMS) functional classification of the road type.
Additionally, any project that includes a significant number of engine starts or significant
amounts of extended idling for heavy-duty vehicles needs to include the "Off-Network"
road type to account for emissions from those activities properly. More details on
describing inputs for engine start and idling activity are given in Section 4.5.9.
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4.4.7 Pollutants and Processes
(MOVES User Guide Section 2.2.7)
The Pollutant and Processes panel is used to select both the types of pollutants and the
emission processes that produce them. For PM2.5 or PMio emissions, MOVES calculates
emissions for several pollutant species:
• Organic Carbon (OC)
• Elemental Carbon (EC)
• Sulfate Particulate
• Brake Wear Particulate
• Tire Wear Particulate
In addition, MOVES divides emissions by pollutant process. For a PM hot-spot analysis,
the categories are:
• Running Exhaust
• Start Exhaust
• Extended Idle Exhaust
• Crankcase Running Exhaust
• Crankcase Start Exhaust
• Crankcase Extended Idle Exhaust
• Brake Wear
• Tire Wear
For a PM2.5 hot-spot analysis, the user should select "Primary Exhaust PM2.5 - Total" (or
"Primary Exhaust PMio - Total" if it is a PMio hot-spot analysis), which is an aggregate
of each of the pollutant species (OC, EC, and sulfate) for each process. For MOVES to
run, the user would select each individual PM species (i.e., "Primary PM2.5 - Organic
Carbon," "Primary PM2.5 - Elemental Carbon," "Primary PM2.5 - Sulfate Particulate," or
the PMio equivalents). In addition, if the analysis has road links with running emissions,
users would also select "Primary PM2.s - Brake Wear Particulate" and "Primary PM2.s -
Tire Wear Particulate" (or their PMio equivalents) as brake wear and tire wear are not
included in the exhaust totals.
MOVES does not automatically sum the appropriate processes to create an aggregate
emission factor, although EPA is considering creating one or more MOVES scripts that
would automate the summing of aggregate emissions when completing project-level
analyses.49 Therefore, the user should calculate total PM from the MOVES output table
results for each link using the formulas described below:
For highway links (roads, intersections, ramps, etc.) where output was specified as a
grams/vehicle-mile emission factor ("Emission Rates" output), the aggregate total PM
49 These scripts would be made available for download on the MOVES website
(www.epa.gov/otaq/models/moves/tools.htmX when available.
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emission factor (i.e., the sum of all PM emission factors for a link) needs to be calculated
using the formula:
PMaggregate total = (PMtotal running) + (PMtotal crankcase running) + (brake Wear) + (tire Wear)
For transit and other terminal project activity (starts and extended idle) where output was
selected as grams/hour ("Inventory" output), the aggregate total PM emission factor (i.e.,
the sum of all PM emission factors for a link) needs to be calculated using the formula:
= (PMtotal starts) + (PMtotal crankcase starts) + (PMtotal ext. idle) +
total crankcase ext. idle)
For transit and other terminal project links that contain starts and extended idling as well
as running emissions, and output was selected as "Inventory" output (grams/hour/link),
the aggregate total PM emission factor for each link needs to be calculated using the
formula:
PMaggregate total = (PMtotal running) + (PMtotal crankcase running) + (PMtotal starts) +
(PMtotal crankcase starts) + (PMtotal ext. idle) + (PMtotal crankcase ext. idle) +
(brake wear) + (tire wear)
4. 4. 8 Manage Input Data Se ts
(MOVES User Guide Section 2.2.8)
Most analyses will not use the Manage Input Data Sets panel. One possible application is
to specify user-supplied databases to be read by the model during execution of a run.
However, for project-level analysis in MOVES, the Project Data Manager (described
below) serves this same function while providing for the creation of data table templates
and for the review of default data. EPA specifically developed the Project Data Manager
for project analyses and recommends using it, instead of the Manage Input Databases
panel, to create and specify user supplied database tables.
4.4.9 Strategies
(MOVES User Guide Section 2.2.9)
In MOVES, the Strategies panel can be used to model alternative control strategies that
affect the composition of the vehicle fleet. The MOVES model has two alternative
control strategies built into the Strategies panel:
• The Alternative Vehicle Fuels and Technologies (AVFT) strategy allows users to
modify the fraction of alternative fuel vehicles in each model year.
• The On-Road Retrofit strategy allows the user to enter information about diesel
trucks and buses that have been retrofitted with emission control equipment.
A common use of the AVFT panel would be to change the diesel fractions of the fleet.
Users can modify the default assumptions about diesel, gasoline, and CNG use for each
source type and model year. If local information is available on these fractions, the
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AVFT should be used to modify the defaults. For instance, users modeling a transit
facility may use the AVFT to specify that the entire fleet of buses uses CNG, or entirely
diesel, rather than a default mix of both fuel types.
Another application of the Strategies panel would be to apply a retrofit program to the
fleet. For example, a bus terminal project might include plans to mitigate emissions by
retrofitting the bus fleet that will operate at that terminal with control equipment that
reduces PM emissions. In that case, the user would specify the details of the retrofit
project using the On-Road Retrofit Strategy panel. The latest guidance on retrofit
programs can be located at the EPA's conformity website:
www.epa.gov/otaq/stateresources/transconf/policy.htm. Strategies that affect vehicle
activity, such as implementing a truck idle reduction plan, should be handled in the Off-
Network Importer and Links Importer.
See Section 10 for further information regarding the inclusion of mitigation and/or
control measures in PM hot-spot analyses.
4.4.10 Output
(MOVES User Guide Section 2.2.10)
Selecting Output in the Navigation panel provides access to two additional panels:
General Output and Output Emissions Detail. Each of these allows the user to specify
aspects of the output data.
Under General Output, users should make sure to choose "grams" and "miles" for the
output units in order to provide results for air quality modeling. Also, "Distance
Traveled" and "Population" should be selected under the "Activity" heading to obtain
vehicle volume information for each link in the output.
Output Emissions Detail is used to specify the level of detail desired in the output data.
Emissions by hour and link are the default selections and cannot be changed. Road type
will also be checked if output by Emission Rates was selected. EPA recommends that
users check the box labeled "Emission Process." No other boxes should be selected in
order to produce fleet aggregate emission factors for each link.50 Emission rates for each
process can be appropriately summed to calculate aggregate PM emission factors for each
link (as described in Section 4.4.7).
4.4.11 Advanced Performance Features
(MOVES User Guide Section 2.2.11)
Most analyses will not use the Advanced Performance Features panel. This menu item is
used to invoke features of MOVES that improve run time for complex model runs by
50 Users may choose to select output by Source Type if using AERMOD to model a volume source. It may
be appropriate to characterize a volume source with an initial vertical dimension and source release height
that is the emission-weighted average of light-duty and heavy-duty vehicles. See Section J.3.3 of the
Appendix for more information on characterizing volume sources.
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saving and reusing intermediate results. For specific applications, the user may want to
"save data" for deriving the intermediate MOVES calculation of an Op-Mode
Distribution from an average speed or link drive schedule. This is discussed further in
the MOVES User Guide, as well as demonstrated in the quantitative PM hot-spot analysis
example of a transit project in Appendix F.
4.5 ENTERING PROJECT DETAILS USING THE PROJECT DATA MANAGER
After completion of all the necessary panels to create the RunSpec, the user would then
create the appropriate input database tables that describe the project in detail. As
described in Section 4.3, a typical PM hot-spot analysis will involve 32 MOVES runs (16
runs for each build and no-build scenario), each run needing individual sets of input
database tables to be created. This is done using the Project Data Manager, which can be
accessed from the Pre-Processing menu item at the top of the MOVES GUI or by
selecting Enter/Edit Data in the Domain Input Database section of the Geographic
Bounds panel.
Since modeling a project involves many MOVES runs, good data management practices
are essential to prevent confusion and errors. For example, the name of the project input
database for each run should reflect the purpose of that run (e.g.,
"NoBuildSpringAMPeak_in"). A similar naming protocol should be used for the
RunSpec for each run. Also, each tab of the Project Data Manager includes a box for
entering a "Description of Imported Data." Modelers should make liberal use of these
descriptions to (1) indicate whether default or local data were used, and (2) indicate the
source and date of any local data, along with the filename of imported spreadsheets.
These descriptions are preserved with the input database so reviewers (or future users of
the same runs) will have the documentation of inputs readily at hand.
The Project Data Manager includes multiple tabs to open importers used to enter project-
specific data. These importers are:
• Meteorology
• Age Distribution
• Fuel Supply
• Fuel Formulation
• Inspection and Maintenance
• Link Source Type
• Links
• Link Drive Schedule
• Operating Mode Distribution
• Off-Network
Each of the importers allows the user to create a template file with the necessary data
field names and some key fields populated. The user then edits this template to add
project-specific local data with a spreadsheet application or other tool and imports the
data files into MOVES. In some importers, there is also the option to export default data
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from the MOVES database in order to review and then use it. Once the user determines
that the default data are accurate and applicable to the particular project, or determines
that the default data need to be changed and makes those changes, the user can then
import that data into MOVES. Details of the mechanics of using the data importers are
provided in the MOVES User Guide. Guidance for the use of these importers in PM hot-
spot analyses is described below.
4.5.1 Meteorology
(MOVES User Guide Section 2.3.3.4.1)
The Meteorology Data Importer is used to import temperature and humidity data for the
month and hour that are defined in the MOVES run specification. Although temperature
and humidity data can be entered for all hours, only the one hour selected in the run
specification will be used for PM hot-spot analyses. Meteorology inputs for MOVES
should be the same for build and no-build scenarios.
Users should enter data specific to the project's location and time period modeled, as PM
emissions are found to vary significantly depending on temperature. The accuracy of
emission estimates at the project level improves when meteorological data specific to the
modeled location is included. Default temperature and humidity values are available in
MOVES, but are not recommended for use in a PM hot-spot analysis.
Temperatures must be consistent with those used for the project's county in the regional
emissions analysis (40 CFR 93.123(c)(3)) as well as the air quality modeling inputs used
in the hot-spot analysis. Meteorological data may be obtained either from the National
Weather Service (NWS) or as part of a site-specific measurement program. Local
universities, the Federal Aviation Administration (FAA), military stations, and state and
local air agencies may also be sources of such data. The National Oceanic and
Atmospheric Administration's National Climatic Data Center (NCDC; online at
www.ncdc.noaa.gov/oa/ncdc.html) is the world's largest active archive of weather data
through which years of archived data can be obtained. A data source should be selected
that is representative of local meteorological conditions. Meteorological site selection is
discussed further in Section 7.5.
As discussed in Section 4.3, MOVES will typically be run for multiple time periods and
specific meteorology data that accurately represents these runs is needed to produce
emission estimates for comparison with both the 24-hour and annual PM NAAQS. The
user should employ a minimum of four hours (corresponding to AM peak traffic/PM
peak traffic/MD traffic/ON traffic), for one day (weekday), for January, April, July, and
October. Within each period of day in each quarter, temperatures should be used that
represent the average temperature within that time period. For example, for January AM
peak periods corresponding to 6 a.m. to 9 a.m., the average January temperature based on
the meteorological record for those hours should be used in estimating the average
January AM peak period temperature for MOVES runs. The user may choose to run
additional hours and temperatures beyond the number of traffic periods for which data
exist. For example, within an 11-hour overnight (ON) modeling period, temperature data
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could be used to differentiate hours with significantly different temperatures, despite
having assumed identical traffic estimates. Humidity estimates should be based on the
same hours and data source as the temperature estimates. See Section 4.3 for further
information on the number of MOVES runs recommended for different project analyses.
¥.5.2 Age Distribution
(MOVES User Guide Section 2.3.3.4.3)
The Age Distribution Importer is used to enter data that provides the distribution of
vehicle fractions by age for each calendar year (yearlD) and vehicle type
(sourceTypelD). These data are needed for running MOVES at the project level. The
distribution of agelD (the variable for age) fractions must sum to one for each vehicle
type. These inputs should generally be the same for build and no-build scenarios, unless
something about the project would change them (e.g., a bus terminal project that includes
the purchase of new buses in the build scenario).
To build a MOVES-compatible age distribution table, there are three possible options.
1. If available, users should use the latest state or local age distribution assumptions
from their SIP or transportation conformity regional emissions analysis. For the
initial transition from MOBILE6.2 to MOVES, EPA has provided a registration
distribution converter.51 The tool allows users to input a MOBILE6.2 registration
distribution table (10, 10, 5 format) and obtain a MOVES age distribution table.
Over time, users should develop age distribution data consistent with MOVES.
Some users may have local registration distribution tables for all vehicle classes.
However, there may be cases where the user has registration distributions only for
one or more vehicle classes (e.g., LDVs) and therefore relies on MOBILE6.2
defaults for the remaining vehicle classes. In these cases, the user may use
MOVES default distributions available on the EPA's website.
2. If the project is designed to serve a fleet that operates only locally, such as a
drayage yard or bus terminal, the user should provide project-specific fleet age
distribution data. For most captive fleets, an exact age distribution should be
readily available or obtainable. The data should be in a format compatible with
MOVES. This format includes age fractions in 30-year bins rather than the 25
used in MOBILE6.2. Additionally, vehicle categories need to be in terms of the
13 MOVES source types.
3. If no state or local age distribution is available, the MOVES default age
distribution should be used. This can be obtained from the tables available on the
EPA website: www.epa.gov/otaq/models/moves/tools.htm. The user can select
the analysis year(s) and find the corresponding age distribution. These fractions
are national defaults and could be significantly different than the local project age
distribution. Age distribution can have a considerable impact on emission
51 This converter can be found online at: www.epa.gov/otaq/models/moves/tools.htm.
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estimates, so the default data should be used only if an alternative state or local
dataset cannot be obtained.
4.5.3 Fuel Supply and Fuel Formulation
(MOVES User Guide Section 2.3.3.4.8 and 2.3.3.4.9)
The user needs to define in MOVES what fuel(s) and fuel mix will be used in the project
area. The Fuel Supply Importer and Fuel Formulation Importer are used to enter the
necessary information describing fuel mix and fuel type for each MOVES run. These
inputs should generally be the same for build and no-build scenarios, unless something
about the project would change them (e.g., a project that includes alternate fuel vehicles
and infrastructure in the build scenario).
Users should review the default fuel formulation and fuel supply data in MOVES and
make changes only if local volumetric fuel property information is available. Otherwise,
EPA recommends that the MOVES default fuel supply and formulation information be
used. The lone exception to this is in the case of Reid Vapor Pressure (RVP), where a
user should change the value to reflect the differences between ethanol and non-ethanol
blended gasoline.
For additional guidance on defining fuel supply and formulation information, consult the
EPA document "Technical Guidance on the Use of MOVES2010 for Emission Inventory
Preparation in State Implementation Plans and Transportation Conformity" available
online at: www.epa.gov/otaq/stateresources/transconf/policy.htm.
4.5.4 Inspection and Maintenance (I/M)
(MOVES User Guide Section 2.3.3.4.10)
MOVES does not provide a PM emission benefit from an I/M program. If the user
includes an I/M program in the run specification, the selection will have no impact on PM
emissions.
4.5.5 Link Source Type
(MOVES User Guide Section 2.3.3.4.13)
The Link Source Type Importer allows the user to enter the fraction of the link traffic
volume that is represented by each vehicle type (source type). It is not needed if the
project contains only a transit or other terminal (off-network) link. For each LinkID, the
"SourceTypeHourFractions" must sum to one across all source types.
Additionally, the user needs to ensure that the source types selected in the MOVES
Vehicles/Equipment panel match the source types defined through the Link Source Type
Importer.
There are no defaults that can be exported from the Link Source Type Importer. For any
analysis at the project level, the user needs to provide source type fractions for all
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vehicles being modeled and for each MOVES run (as vehicle mixes may change from
hour to hour and month to month). There are two options available to populate the Link
Source Type input:
1. For projects that will have an entirely different source type distribution than that
of the regional fleet, the preferred option is for the user to collect project-specific
data. For projects such as bus or freight terminals or maintenance facilities that
contain links that are primarily used by a specific subset of the regional fleet,
users need to develop the fractions of link traffic volume by vehicle type data
specific to the project. This could be based on analysis of similar existing
projects through the interagency consultation process.
2. If the project traffic data suggests that the source type distribution for the project
can be represented by the distribution of the regional fleet for a given road type,
the user can provide a source type distribution consistent with the road type used
in the latest regional emissions analysis. For example, highways tend to have a
higher fraction of truck traffic than arterial roads. Therefore, the highway source
type distribution used in the regional emissions analysis may be appropriate to use
for a highway project.
4.5.6 Links
(MOVES User Guide Section 2.3.3.4.12)
The Links Importer is used to define the individual roadway links. All links being
modeled should have unique IDs. The Links Importer requires information on each
link's length (in miles), traffic volume (units of vehicles per hour), average speed (miles
per hour), and road grade (percent). Users should follow guidance given above in
Section 4.2 when determining the number of links and the length of specific links.
Consult Section 7 for information on how these links should be formatted for use in air
quality modeling.
4.5.7 Describing Vehicle Activity
(MOVES User Guide Section 2.3.3.4.14 through Section 2.3.3.4.16)
MOVES determines vehicle emissions based on operating modes, which represent
different types of vehicle activity such as acceleration (at different rates), deceleration,
idle, and cruise that have distinct emission rates. MOVES handles these data in the form
of a distribution of the time vehicles spend in different operating modes. This capability
is central to the use of MOVES for PM hot-spot analyses because it allows for the
analysis of fine distinctions between vehicle behavior and emissions before and after
construction of the project. For example, the full emission benefits of a project designed
to smooth traffic flow can best be realized by taking into account the changes in
acceleration, deceleration, and idle activity that result from the project. There are several
methods that users may employ to calculate an Op-Mode distribution based on the project
design and available traffic information. MOVES currently offers three options that the
user can employ to add link activity data, depending on data availability. These are:
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1. Provide average speed and road type through the Links input:
Using this approach, MOVES will calculate emissions based on a default drive
cycle for a given speed, grade, and road type. Input of link drive schedules or
operating mode distributions is not needed. For users modeling a free-flow link
with only basic information on average speed and volume on a link, this option
may be appropriate. This approach accounts for some differences in emissions
due to changes in operating modes associated with different average speeds on a
specific road type. However, this approach provides the least resolution when
analyzing the emission impact of a project because the default drive cycles used
by the model may not accurately reflect the specific project. For instance, due to
the range of operating modes associated with intersection projects, a single
average speed would not spatially capture localized idling and acceleration
emissions.
2. Provide a link drive schedule using the Link Drive Schedule Importer:
The Link Drive Schedule Importer allows the user to define the precise speed and
grade as a function of time (seconds) on a particular roadway link. The time
domain is entered in units of seconds, the speed variable is miles-per-hour and the
grade variable in percent grade (vertical distance/lateral distance, 100% grade
equals a 45-degree slope). MOVES builds an Operating Mode Distribution from
the Link Drive Schedule and uses it to calculate link running emissions.
Individual Link Drive Schedules cannot be entered for separate source types. The
Link Drive Schedule therefore represents the "tracer" path of an average vehicle
on each link. Link drive schedules could be based on observations using methods
such as chase (floating) cars on similar types of links, or on expected vehicle
activity based on an analysis of link geometry. Link drive schedules will only
represent average vehicle activity, not the full range of activity that will occur on
the link. As described in Section 4.2 and Appendix D, users can overcome this
limitation by defining multiple links for the same portion of the project (links that
"overlap") with separate source distributions and drive schedules to model
individual vehicle types.
3. Provide a detailed operating mode distribution for the link:
The Operating Mode Distribution Importer allows the user to directly import
operating mode fraction data for source types, hour/day combinations, roadway
links, and pollutant/process combinations that are included in the run
specification. Operating mode distributions may be obtained from:
• Op-Mode distribution data from other locations with similar geometric
and operational (traffic) characteristics;52 or
• Output from traffic microsimulation models.53
52 For example, chase (or floating) cars, traffic cameras, and radar guns have been used previously to
collect some traffic data for use in intelligent transportation systems and other applications. EPA
encourages the development of validated methods for collecting verifiable vehicle operating mode
distribution data at specific locations representative of different projects covered by this guidance.
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4.5.8 Deciding on an approach for activity
Users should consider the discussion in Section 4.2 when deciding on the appropriate
activity input. The MOVES model is capable of using complex activity datasets with
high levels of resolution to calculate link-level emissions. EPA encourages the
development of validated methods for collecting verifiable vehicle Op-Mode distribution
data at locations and in traffic conditions representative of different projects covered by
this guidance. However, the user should determine the most robust activity dataset that
can be reasonably collected while still achieving the goal of determining an accurate
assessment of the PM air quality impacts from a given project. The decision to populate
the Links table, Link Drive Schedule, or Op-Mode Distribution should be based on the
data available to the user and should reflect the vehicle activity and behavior on each
link.
Note: If either the average speed or link-drive schedule approach is used, it is not
necessary to input an Op-Mode distribution for on-road link activity.
4.5.9 Off-Network
(MOVES User Guide Section 2.3.3.4.16)
The Off-Network Importer is where the user can provide information about vehicles not
driving on the project links, but still contributing to the project's emissions. Currently,
only one off-network link may be described per run. If more than one off-network link is
associated with the project, another set of 16 MOVES runs would be needed to
characterize each additional off-network location for each build or no-build scenario.
The Off-Network Importer should be used if the project includes an area where highway
vehicles are parked, starting their engines, or in extended idling mode (such as at a truck
stop, parking lot, or passenger or freight intermodal terminal). All such areas within the
project area should be modeled, regardless of whether they are part of the project.
There are no default values available for any of the off-network inputs, so users will need
to populate the Off-Network table with information describing vehicle activity in the off-
network area being modeled. The necessary fields are vehicle population, start fraction,
and extended idle fraction:
• The vehicle population reflects the total number of vehicles parked, starting, or
idling on the off-network area over the course of the hour covered by the MOVES
run.
• The start fraction is the fraction of the total vehicle population that starts during
the hour.
53 A traffic microsimulation model can be used to construct link drive schedules or operating mode
distributions if prior validation of the model's predictions of speed and acceleration patterns for roadway
links similar to those in the project was conducted. If a user has a microsimulation model that has been
previously demonstrated to adequately predict speed/acceleration patterns for relevant vehicle classes (e.g.,
heavy-duty), and has a procedure for importing data into MOVES, it may be appropriate to use the
microsimulation model, subject to interagency consultation.
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• The extended idle fraction specifies the fraction of time that the vehicle
population spends in extended idle operation in the hour.54
Extended idle operation applies only to long-haul combination trucks and is defined as
the operation of the truck's propulsion engine when not engaged in gear for a period
greater than 15 consecutive minutes, except when associated with routine stoppages due
to traffic movement or congestion.55 As discussed in Section 4.2.2, shorter periods of
idling for long-haul combination trucks and all idling for other vehicles should be
modeled as a project link with an Op-Mode distribution that consists only of idle
operation (Op-Mode 1). This can be specified in the Links table by inputting the vehicle
population and specifying an average speed of "0" mph.
For vehicle population inputs, the user should be able to rely on existing project
documentation. The user will also need to estimate the number of starts and idle
operation of the facility for other inputs, which will depend on the project involved. For
example, in a bus terminal project, the user could estimate the number of starts and idling
based on expected passenger ridership and proposed operating schedules for the buses
using the terminal. Most buses would be expected to first start early in the morning, prior
to the morning peak period. The buses might operate all day, with little or no start
activity during the midday hours. Idle operation is likely a function of the volume of
buses accessing the terminal each hour and the duration that those buses idle prior to
leaving the terminal. Conversely, an employee parking lot would have little or no idle
activity and may have the opposite trend in start activity. Typically, employees arrive
during the morning peak period and leave during the evening peak period. In this case,
most starts would occur during the evening peak period.
Information on start and idle activity should be specific to the project being modeled.
However, data from similar projects could be adapted for use in a quantitative PM hot-
spot analysis, when appropriate. For instance, the ratio of starts to vehicles and the
distribution of starts throughout the day for a project being analyzed could be determined
by studying a similar parking lot.
If an off-network link is defined, users need to also define an Op-Mode distribution that
describes the soak-time distribution of vehicles on the link; this will affect the start
emissions. Additionally, any extended idle operation on an off-network link needs to be
described by the Op-Mode distribution with a fraction of 1.0 for Op-Mode 200 (Extended
Idle Mode). Since there is only one possible extended idle mode in MOVES, this
fraction should always be 1.0.
The soak time is the time a vehicle is stationary with the engine turned off, following the
last time it was operated. There are no default soak-time distributions available. Soak
times and soak-time distributions should be specific to the type of project being modeled.
54 Parked fraction is not required as an input and can be left blank.
55 See "Guidance for Quantifying and Using Long Duration Truck Idling Emission Reductions in State
Implementation Plans and Transportation Conformity"; available online at
www.epa. gov/smartwav/documents/420b04001 .pdf.
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This information could either be directly collected or obtained from information collected
for a similar project. For instance, a park-and-ride lot may have vehicles parked for eight
or nine hours prior to starting, while an intermodal freight terminal may have vehicles
parked for only one hour before starting. This information should be defined through the
appropriate distribution of soak-time Op-Modes (OpModes 101-108) in the Op-Mode
Distribution table.
The methods and assumptions used to derive off-network inputs (including starts, idle
activity, and soak-time distributions) should be documented as part of the analysis,
including any adjustments based on data from similar projects.
4.6 GENERATING EMISSION FACTORS FOR USE IN AIR QUALITY
MODELING
The MOVES model provides results as either an emission total (if "Inventory" output is
selected) or an emission factor (if "Emission Rates" output is selected). The emission
results are produced for each pollutant and process and are calculated in terms of grams
per link or grams/vehicle-mile per link. Using the equations in Section 4.4.7, the user
will need to sum the appropriate pollutants and processes to derive a link total
grams/vehicle-mile or grams/hour emission factor. These totals will be needed as inputs
into the appropriate air quality model. Instructions on running AERMOD and
CAL3QHCR for quantitative PM hot-spot analyses are in Section 7 and Appendix J.
Note: If MOVES is being run in batch-mode, or if multiple runs are being saved to the
same output database, the user should make sure to separate link emissions in the result
database by "MOVESRunlD" or "monthlD, daylD, hourlD." Aggregating separate
runs will result in incorrect emission rates.
4.6.1 Highway and intersection links
For links characterized as "highway" or "running" segments of a project, a
grams/vehicle-mile emission rate is needed for CAL3QHCR; if AERMOD is being used,
a grams/hour emission factor for each roadway link is needed:
• CAL3QHCR uses grams/vehicle-mile emission factors and calculates air quality
estimates based on the volume of traffic and length of a given link. All of the
information necessary to generate the necessary inputs is available in the MOVES
MySQL output database. After running MOVES for a particular hour/day/month
scenario, emission results can be located in the user defined MOVES output
database in the table "rateperdistance." All links defined in the Project Level
Importer will have results in the column "rateperdistance." The units should have
been defined as grams and miles in the MOVES RunSpec (see Section 4.4.10).
As shown in the equations in Section 4.4.7, all relevant pollutants and processes
should be summed together to get a single "rateperdistance" value. This value
can then be paired with link volume and link length for use in CAL3QHCR for
each link.
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• AERMOD uses a grams/hour emission factor for each hour of the day (which
should be mapped based on the time periods analyzed with MOVES, as described
in Section 4.3). If "Inventory" is selected in the Scale panel, MOVES will
produce output in terms of grams/hour/link. The user should then calculate
aggregate PM grams/hour emission factors by summing the appropriate pollutants
and processes as described in Section 4.4.7. Since AERMOD processes emission
factors in terms of grams/hour (or second), no further calculation is necessary.
Section 7 and Appendix J discuss input formats for different AERMOD source
configurations.
4.6.2 Transit and other terminal links
For transit and other terminal projects, or a combination of highway and transit or other
terminal components, AERMOD is recommended (see Section 7). AERMOD uses a
grams/hour emission factor for each hour of the day (which should be mapped based on
the time periods analyzed with MOVES as described in Section 4.3). If "Inventory" is
selected in the Scale panel, MOVES will produce output in terms of grams/hour/link.
The user should then calculate aggregate PM grams/hour emission factors by summing
the appropriate pollutants and processes as described in Section 4.4.7. Since AERMOD
processes emission factors in terms of grams/hour (or second), no further calculation is
necessary. Section 7 and Appendix J discuss input formats for different AERMOD
source configurations.
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Section 5: Estimating Project-Level PM Emissions Using
EMFAC (in California)
5.1 INTRODUCTION
This section of the guidance addresses the necessary steps to run EMFAC to estimate a
project's exhaust, brake wear, and tire wear emissions for PM hot-spot analyses in
California.56 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.5 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 PMio emission rates for three exhaust emission processes (running,
starting, and idle), tire wear, and brake wear.
To complete an EMFAC-based PM hot-spot analysis, users need to determine the scope
and resolution of traffic activity data, specify basic scenario data inputs, choose the
desired outputs of the EMFAC model, and gather project-specific traffic data and fleet
data. Next, users would run EMFAC through the "EMFAC Area Fleet Average
Emissions Output Mode" (Emfac mode) to produce a look-up table of average emission
factors for the planning area and/or county where the project is located. At that point, the
relevant emission factors from the model can be combined with project-specific activity
data to calculate total link-level emission factors. The emission factors can then be used
in air quality modeling as discussed in Section 7 of the guidance. The steps to using
EMFAC are illustrated in Exhibit 5-1 (following page).
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 this scenario does not exceed
the NAAQS, then it is unnecessary to model the no-build scenario. If the resulting design
value does not exceed the NAAQS, then the project meets the hot-spot analysis
requirements of project-level conformity and it is not necessary to model the no-build
scenario. Following this approach will allow users to avoid additional emissions and air
quality modeling.
Finally, this section describes how to use EMFAC to estimate emissions from a highway
and transit project that requires a PM hot-spot analysis ("the project"); this section could
also be used to estimate emissions for any other highway and transit facilities in the
project area, when necessary.
56 This guidance is applicable to current and future versions of the EMFAC model, unless EPA notes
otherwise when approving the model for conformity purposes.
57 The current version of the EMFAC model, future model versions, and supporting documentation can be
downloaded from the CARB website at: www.arb.ca.gov/msei/onroad/latest version.htm.
52
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Exhibit 5-1. Steps for Using EMFAC in a Quantitative PM Hot-spot Analysis
Divide the project into
links
(Section 5.2)
I
Determine the number of
EMFAC runs
(Section 5.3)
Spe<
Select
geographic area
(Section 5.4.1)
Select calendar
(Section 5.4.2)
Configure Emission Factor O
(Section 5.5)
Select "Emfac" Select
:ify Basic Scenario Inputs (Section 5.4
/ Does fleet \
> / activity vary
\ season/month? /
Yes
Build EMFAC
scenario for each
month/season
(Section 5.4.3)
Modify vehicle
classes
(Sections 5.4.5-6)
, ,
No
k.
No
)
Use a
avei
(Sectio
i
Enter s
tit
(Sectio
^
nnual
-age
n 5.4.3)
r
cenario
le
n 5.4.4)
r
/ Does project \
/ include all \
^ \ vehicle /
\ classes? /
utputs Edit Program
Constants (Section 5.6)
Change distributions of
Output VMT, trips, and/or
Yes
Generate Emission
Factors (Section 5.7)
Save scenario
Type
(Section 5.5.4)
vehicle population to
reflect project fleet mix
mode
Configure temp.,
relative humidity,
& speed
(Section 5.5.1-2)
Select Output
Summary Rate
File (RTS File)
(Section 5.5.3)
Output emission
factor look-up
table
Note: The steps in this exhibit and in the accompanying text describe how to use EMFAC to
complete a scenario run using the model's "Emfac " mode for a PM hot-spot analysis.
53
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This section presumes users already have a basic understanding of how to run EMFAC.
Please note that there are some aspects of Section 5 that differ from the MOVES
guidance discussed in Section 4, due to the inherent differences between MOVES and
EMFAC. For example, unlike MOVES, EMFAC emission rates do not vary by
temperature. EMFAC users will not account for variations in temperature over the course
of the day or year, and therefore will complete fewer model runs. Additionally,
EMFAC generates an emission factor look-up table for a range of average speeds.
MOVES calculates emission factors based on a distribution of operating modes, which
allows the option of more advanced methods of defining link-level activity.
5.2 CHARACTERIZING A PROJECT IN TERMS OF LINKS
Prior to using EMFAC, users need to first 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 extended idle emissions are
typically needed, and in some cases these projects will also need to address cruise,
approach and departure running exhaust emissions on affected links.
The goal of defining a project's links is to accurately capture emissions where they occur.
A link represents a segment of a highway or transit project characterized by a certain type
of vehicle activity. Generally, the links specified for a highway project should include
road segments with similar traffic conditions and characteristics. Links representing
transit or other terminal projects should similarly reflect variation in idle and start
activity, as well as other relevant cruise, approach and departure running exhaust
emissions.
5.2.1 Highway and intersection projects
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.59 Thus, local
traffic data should be used to characterize each link sufficiently. It is recommended that
58 If future versions of EMFAC include PM emission rates that differ by temperature, EPA would work
with CARB to develop additional EMFAC guidance as needed so that users could adequately capture
hourly and seasonal temperature variability in PM hot-spot analyses.
59 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.
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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.60
A simple example would be a single, one directional, four-lane highway that could be
characterized as one link with one average speed. If the project analysis involves
intersections, the intersections need to be treated separately from the free-flow links that
connect to those intersections. Although road segments between intersections may
experience free-flow traffic operations, the approaches and departures from the
intersections will involve acceleration, deceleration, and idling activity not present on the
free-flow link. For intersection modeling, the definition of link length will depend on the
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.61 Some resources are
available through FHWA's Travel Model Improvement Program (TMIP).62
Methodologies for computing intersection control delay are provided in the Highway
Capacity Manual.63
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
60 Unlike MOVES, the current version of 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.
61 As discussed in Section 7, the use of the CAL3QHCR queuing algorithm for intersection idle queues is
not recommended. Rather, idling vehicles should be represented in combination with decelerating,
accelerating, and free-flow traffic on an approach segment of an intersection.
62 See FHWA's TMIP website: http://tmip.fhwa.dot.gov/.
63 Users should consult the most recent version of the Highway Capacity Manual. As of the release of this
guidance, the latest version is the Highway Capacity Manual 2000, which can be obtained from the
Transportation Research Board (see http://144.171.ll.107/Main/Public/Blurbs/152169.aspx for details).
55
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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, but only for heavy-duty vehicles. Users
need to have data on the number of vehicle starts per hour and number of heavy-duty
diesel 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 and Appendix G (that is, in
addition to any other roadway links associated with the project). These running link
emissions can then be aggregated with the 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 running 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).64 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.
64 See "EPA and DOT Joint Guidance for the Use of Latest Planning Assumptions in Transportation
Conformity Determinations," EPA-420-B-08-901 (December 2008); available online at:
www.epa. gov/otaq/stateresources/transconf/policv/420b08901 .pdf.
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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
(40CFR93.105(c)(l)(i)).
One option is to use average-hour and peak-hour traffic volumes 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-hour volume. These 18 hours would
be divided into a midday (MD) and overnight (ON) scenario.
The following is one suggested approach for an analysis employing the average-
hour/peak-hour traffic scenario:
• Morning peak (AM) emissions based on traffic data occurring between 6 a.m. and
9 a.m.;
• Midday (MD) emissions based on data from 9 a.m. to 4 p.m.;
• Evening peak (PM) emissions based on data from 4 p.m. to 7 p.m.; and
• Overnight (ON) emissions based on data from 7 p.m. to 6 a.m.
If there are local or project-specific data to suggest that the AM or PM peak traffic
periods will occur in different hours than the default values suggested here, or over a
longer or shorter period of time, that information should be documented and the hours
representing each time period adjusted accordingly. Additionally, users should determine
peak periods for the build and no-build scenarios independently and not assume that each
scenario is identical.
If the fleet mix does not vary between the peak-hour and average-hour, then only one
EMFAC run is necessary. If there is a difference in fleet mix, two separate runs are
necessary.
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
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scenarios could be generated to produce a unique emission factor for each activity
scenario (i.e., each period of time for which specific activity data are available).
5.4 DEVELOPING BASIC SCENARIO INPUTS
To generate emission factors in EMFAC for PM hot-spot analyses, users need to first
enter a series of basic inputs to the user interface of the EMFAC model. Exhibit 5-2
presents a summary of all basic inputs needed to complete an EMFAC scenario run
("scenario"). The EMFAC defaults can be used directly for most basic input categories;
however, some inputs need to be modified to reflect project-specific information.
Exhibit 5-2. Summary of EMFAC Inputs Needed to Evaluate a Project Scenario
Step
1
2
3
4
5
6
7
EMFAC Basic Input Category
Geographic Area
Calculation Method
Calendar Year
Season or Month
Scenario Title
Model Years
Vehicle Classes
I/M Program Schedule and
Other State Control Measures
EMFAC Basic Input Data
State
Air Basin
District
County
By Sub -Area
Use Average
Calendar Year
Month
Season
Annual
Default
Modify
All
Modify
All
Modify
Default
Modify
Modification Needed?
Yes
Yes
Yes
Yes
Optional
No
Optional*
No (for I/M); Varies for
Other Measures
* If a project uses a subset of the default fleet, users should delete unwanted vehicle classes through
the "Vehicle Classes" user interface.
5.4.1 Geographic area and calculation method
Users should enter into EMFAC the geographic area where the project is located.
EMFAC offers four geographic scales and each corresponds to specific defaults for fleet
characteristics. The "Area Type" category includes State, Air Basin, District, and
County. For PM hot-spot analyses, users will typically select the County area type.
When "County" is selected, a list of all the counties in California will be available. Users
should select the county where the project is located.
If the selected county is part of only one air basin, users can continue to the next step to
specify calendar years. However, if the selected county is within multiple air basins,
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EMFAC will show two options, "By Sub-Area" and "Use Average," as calculation
methods. Users should select "By Sub-Area" to generate EMFAC emission factors in
look-up tables for all sub-areas within the selected county.
For instance, Los Angeles County is located in both the Mojave Desert Air Basin and the
South Coast Air Basin. If the project is located near the Port of Los Angeles and "Los
Angeles County" with "By Sub-Area" selected in EMFAC runs, EMFAC will provide
emission data for both the Mojave Desert Air Basin and the South Coast Air Basin. Only
the look-up tables for the South Coast Air Basin would be used because this is where the
port is located; the Mojave Desert Air Basin data would be ignored.
5.4.2 Calendar year
EMFAC is able to analyze calendar years from 1970 to 2040 and allows emission
calculations for multiple calendar years in a single run. Users should select one or more
calendar years in EMFAC based on the project scenarios to be analyzed. If an analysis
year beyond 2040 is needed, select 2040 to represent that year.
5.4.3 Season or month
EMFAC can estimate emission factors for each month, two seasons (winter and summer),
or an annual average. Although VMT and speed are handled external to the model, the
vehicle mix may vary by hour and season and these scenarios should be modeled
explicitly. As discussed in Section 5.3, users should run EMFAC for the appropriate
number of scenarios based on the availability of travel activity data. Users with typical
travel activity data may run one or two scenarios (depending whether vehicle mix varies
between the peak-hour and average-hour) and will select "annual average" in the "Season
or Month" selection panel. Users with additional data that shows variation in fleet mix
across seasons or months should select the appropriate month or season for each run.
5.4.4 Scenario title
EMFAC generates a default scenario title that includes the name of the county,
calculation method, season or month, and calendar year. A replacement scenario title can
be specified, if desired.
5.4.5 Model years
EMFAC includes vehicle model years from 1965 to 2040 and default assumptions about
mileage accumulation that vary by model year. EMFAC will generate emission factors
for 45 model years (ages 1 through 45) for the build and no-build scenarios for each
analysis year. Users can change the range of model years to be included in an EMFAC
run through the model interface. If a project involves a specialized and simple fleet (e.g.,
buses operating in a bus terminal) for which the range of model years is well known or
reliably estimated, users may consider including only those model years and exclude
unrelated vehicle types in an EMFAC run.
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However, under most circumstances, projects that involve multiple vehicle types and
model years will need EMFAC defaults to be used for PM hot-spot analyses. The two
reasons for this recommendation are: (1) most projects will not affect the age distribution
of the vehicles operating at the project site, and (2) changing EMFAC defaults to reflect
specific fleet age distributions is complicated for projects that involve multiple vehicle
types and model years. These changes involve a level of familiarity with EMFAC that
many users may not have or need for most hot-spot analyses. Therefore, if users
anticipate that it will be necessary to adjust the age distribution of their vehicle fleet, they
should consult with CARB for further guidance.
5.4.6 Vehicle classes
All 13 default vehicle classes should be selected for most projects. The exception would
be a project or link that involves a specialized fleet of limited vehicle types (e.g., a bus
terminal). The EMFAC model assumes vehicle population and travel activity
distributions by vehicle class, depending on the geographic area and analysis year
selected. Editing the default distribution of vehicle classes will be discussed in Section
5.5. If only one vehicle type is selected (e.g., heavy-heavy duty trucks (HHDTs)), all
emission information in the EMFAC output will be calculated for that one vehicle type.
5.4.7 I/Mprogram schedule and other state control measures
When a particular county from the Geographic Area panel is selected in EMFAC, the
model assumes a default I/M program. Although EMFAC allows edits for each I/M
program, users should not alter the default settings and parameters associated with I/M
programs and their coverage. If I/M program modifications are considered, users should
consult with the local air district or CARB for specific guidance. Currently, no PM
emission benefit from I/M programs exists in EMFAC2007.
The PM emission reductions from any additional state PM emission control measure
should be applied outside of the EMFAC model and be consistent with current
implementation of measures and how reductions are calculated for SIP and other air
quality planning purposes. For instance, EMFAC2007 currently does not have the
capability of modeling diesel engine retrofits. It is recommended that manufacturer
specification data be used for calculating emission factors from engines equipped with
such devices, consistent with EPA's and CARB's retrofit guidance and methods used to
calculate reductions for the SIP. Any issues regarding the models and associated
methods and assumptions for the inclusion of state control measures in PM hot-spot
analyses must be considered through the process established by each area's interagency
consultation procedures (40 CFR 93.105(c)(l)(i)).65
65 For information about quantifying the benefits of retrofitting diesel vehicles and engines to conformity
determinations, see EPA's website for the most recent guidance on this topic:
www.epa.gov/otaq/stateresources/transconf/policv.htm. Also, see CARB's website at:
www.arb.ca.gov/msprog/onrdiesel/calculators.htm.
60
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5.5 CONFIGURING EMISSION FACTOR OUTPUTS
Users need to configure how the model will produce emission factor output based on the
inputs provided in the previous steps. The following discussion covers these
configuration steps in the same order in which users will encounter these options when
running EMFAC.
EMFAC includes three scenario types or modeling modes: Burden, Emfac, and
Calimfac. For PM hot-spot analyses, users should select the "Emfac" mode, which
generates area-specific fleet average emission factors for running exhaust, brake wear,
tire wear, starting, and idling emissions.
5.5.1 Temperature and relative humidity
The default settings in the Emfac mode include 15 temperature bins (-20F to 120F) and
11 relative humidity bins (0% to 100% RH) to generate average emission factors.
However, because EMFAC PM emission rates are insensitive to changes in temperature
and humidity, generating emission factors for all default temperature/relative humidity
combinations throughout an analysis year is not necessary. As shown in Exhibit 5-3
(following page), users need to remove the default temperature/relative humidity settings
and input only one value (e.g., 60F, 70% RH) for temperature and relative humidity,
respectively, to perform an Emfac mode run. Selecting one combination of
temperature/relative humidity will reduce computer run time and produce PM emission
factor look-up tables that can be easily used. Temperatures must be consistent with those
used for the project county's regional emissions analysis (40 CFR 93.123(c)(3)) as well
as the air quality modeling inputs used in the hot-spot analysis. See Section 7.5 for more
information on selecting representative meteorology data.
61
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Exhibit 5-3. Changing EMFAC Default Settings for Temperature and Relative
Humidity
Select/Edit temperature for Emfac calculations
Enter data for temperature.
f* Delete temperature 1
C" Delete temperature 2
<" Delete temperature 3
f Delete temperature 4
f Delete temperature 5
r Delete temperature 6
f Delete temperature 7
<" Delete temperature 8
''" Delete temperature 9
f" Delete temperature 10
f Delete temperature 11
f Delete temperature 12
]7 Sort the array (done aft
Click button
-10
0
10
20
30
40
50
60
70
80
90
3r exit]
to enable new value.
f~ Delete temperature 1 ;
C Delete temperature 1 4
(~ Delete temperature 15
f~ Enter temperature 1 6
r
C Enter temperature 18
(~ Enter temperature 19
(~ Enter temperature 20
f* Enter temperature 21
(~ Enter temperature 22
f Enter temperature 23
C Enter temperature 24
| OK ] C
100
110
120
ncel |
Select/Edit rel hum for Emfac calculations
Enter data for rel hum. Clic
(? Delete rel hum 1
''" Delete re! hum 2
r Delete rel hum 3
'•" Delete rel hum 4
f" Delete rel hum 5
f Delete rel hum 6
f~ Delete rel hum 7
<" Delete rel hum 8
f~ Delete rel hum 9
''~ Delete rel hum 10
^' Delete rel hum 11
<~ Enter rel hum 12
& Sort the array (done aft
* button to enable new value.
10
20
30
40
50
60
70
80
90
100
r exit)
\ Enter e! hum 13
C Enter el hum 14
C Enter el hum 1 5
f~ Enter el hum 16
C Enter el hum 17
f Enter el hum 18
r Enter el hum 13
C Enter el hum 20
f~ Enter el hum 21
C Enter el hum 22
(* Enter e! hum 23
f* Enter el hum 24
ncel
Select/Edit temperature for Emfac calculations
Enter data for temperature.
(* Delete temperature 1
f Enter temperature 2
f* Enter temperature 3
C Enter temperature 4
f* Enter temperature 5
f Enter temperature 6
f" E filer temperature 7
f"* Enter temperatures
C Enter temperature 3
C" Enter temperature 10
f* Enter temperature 11
r Enter temperature 12
fV Sort the array (done aft
Click button to enable new value.
[3? ("" Enter temperature 13
<"* Enter temperature 14
f*1 Enter temperature 15
f* Enter temperature 16
^ Enter temperature 1 7
r1 Enter lempr.
<" Enter temperatijie 13
C* Enter temperature 20
C Enter tempetatuie £\
f Enter temperature 22
f Enter temperature 23
C Enter ternpei-aturfr 24
;f exit) | OK ] C
incel |
Select/Edit rel hum for Emfac calculations
Enter data for rel hum. Clic
<• Delete rel hum 1
(* Enter rel hum 2
C Enter rei hi
f Enter rel hum 4
C~ Enter rel hum 5
f" Enter rel hum 6
C" Enter rel hum 7
C Enter rel hum 8
r Enter rel hum 9
C Enter rel hum 10
C Enter rel hum 11
C Enrerielhum12
fv Sort the array (done aft
< button to enable new value.
g| ( Enter rel hum 1 3
f* Enter rei hum 14
r Enter rel hum I 5
r° Enter (el hum 16
f Enter rei hum 1 /
r Enter ret hum 18
r Enter rei hum 19
C Enter ret hum 20
C Eniei rel hum J1
C Enter ret hum 22
C Entei ret hum 23
C Entei iel hum J4
-f eKit) | OK ] C
ncel I
5.5.2 Speed
The Emfac mode allows users to input up to 24 speed values to populate average
emission factors. The default setting specifies speed bins for 0 mph through 65 mph in 5
mph increments. Emission factors associated with the 0 mph speed bin can be applied for
idle emissions (essentially for heavy-duty trucks only; EMFAC idle emission factors are
unavailable for most other vehicle classes).66 Emission factors for intermediate speeds
can also be generated if specific speed values are input into the EMFAC model.
Users have several options to calculate appropriate speed-dependent emission factors for
a project. For instance, if a highway link in a build scenario is known to have an average
speed of 32 mph, it can be directly input into the speed list of EMFAC to produce the
associated PM emission factors. Alternatively, if the EMFAC default settings are used to
generate a look-up table for different speed bins, users can either select the emission
66 Among the 13 vehicle classes in EMFAC, idle emission factors are available only for LHDT1 and
LHDT2 (included in the MDT vehicle group in the output .rts file) and MHDT, HHDT, School Buses, and
Other Buses (included in the HDT vehicle group in the output .rts file); see Exhibit 5-6 for further
information.
62
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factors associated with the closest speed bin (e.g., 30 mph bin, representing speeds of
27.5 mph to 32.5 mph), or interpolate between the emission factors for speed bins of
30 mph and 35 mph.
Users should include 0 mph in an EMFAC run unless the project to be evaluated does not
involve idle emissions. For specific cases for which the average link speed is less than
5 mph, users can either select the emission factors from the 5 mph speed bin, or
extrapolate down to the desired speed by using the emission factors from the speed bins
for 5 mph and 10 mph to create a trend line to lower speeds.
5.5.3 Output rate file
The Emfac mode can provide emission information in four output formats with different
levels of detail. Users should select "Summary Rates (RTS)." The Summary Rates
format generates average emission factors by speed for six vehicle groups (aggregated
from the 13 vehicle classes modeled in EMFAC) and an overall average emission factor
for the entire vehicle fleet. The overall average emission factors are appropriate for use
in air quality dispersion modeling.
5.5.4 Output particulate
As shown in Exhibit 5-4, users have to select either PMio or PM2.5 in an Emfac mode run
to obtain particulate emission factors. EMFAC must be run twice to obtain both
and PM2.5 data for those projects that are located in both PMio and PM2.5
nonattainment/maintenance areas.
Exhibit 5-4. Selecting Pollutant Types in EMFAC for PMio and PM2.5
^wn^*^4*A*i^^gi^±Mf^x^
Input! j Input 2 Mode and Output
Burden - Area planning inventory
—
TecMM | CYr Basis] .
Emfac - Atea fleet average emissions
Scenario Type: EMFAC --Area-specific
peeds
Configure EMFMu Outputs
"[ I'-Tnpi; [,=r!i ,• --
Relative Humidities |
Speed...
Cancel
r
leet average emissions (g/hr) for s
Binary Impacts (BIN)
ASCII Impacts (ERP)
| Summary Rates (RTS)
Detailed Impact Rates (RTL)
1
Calim ac- Detailed vehicle data j
elected
f= Edit Program 1=
< Back Constants
emperatures, relative humidites, <
<~ Total PM
<=• PM10 r PM25
Output Hydrocarbons As...
«• TOG P THC
f~ ROE r CH4
Finish
63
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5.6 EDITING PROGRAM CONSTANTS
5.6.1 Overview
Typically, users will start the analysis process with only a broad understanding of the
project-specific vehicle fleet - specifically, the percentage of vehicles that are considered
"trucks" versus those that are "non-trucks." In all cases, projects that require a
quantitative PM hot-spot analysis will have a different fleet distribution than the EMFAC
regional default mix. Users will therefore need to adjust the project fleet and fleet
activity (VMT, trips) to reflect the expected project fleet mix for each EMFAC scenario.
Depending on the project, users should modify some combination of VMT (which affects
running exhaust emission factors), vehicle trips (which affects starting emission factors),
and/or vehicle population (which affects idling emission factors). In the following
discussion, overall guidance is provided on how to make these adjustments. Appendices
G and H provide more specific illustrations of the step-by-step procedures involved.
5.6.2 Default data in the Emfac mode
The Emfac mode is associated with a range of pre-populated program constants linked to
specific time periods and California geographic areas. Exhibit 5-5 lists the default data
available in the Emfac mode that can be accessed through the "Edit Program Constants"
in the user interface. For a PM hot-spot analysis, many of the defaults do not need to be
modified. However, users do need to determine which adjustments are needed for the
default distributions of VMT, trips, and vehicle population by vehicle class. The
EMFAC interface has "Copy with Headers" and "Paste Data Only" tabs that are helpful
for users to easily export the default data and import the adjusted data.
Exhibit 5-5. EMFAC Program Constants and Modification Needs for PM Hot-spot
Analyses
EMFAC Program
Constants
Exh Tech Fractions
Evap Tech Fractions
Interim I/M
Population
Accrual
Trips
VMT
Speed Fractions
Idle Time
Description
Exhaust control technology fractions
Evaporative control technology factions
Enhanced interim I/M program
Vehicle population by class, fuel type, and age
Odometer accrual rate by class, fuel type, and age
Vehicle trips/starts per day by class, fuel type, and age
Vehicle miles traveled per day by class, fuel type, and age
VMT by speed bin distribution for each vehicle class
Idle times by vehicle class, fuel, and hour of day
Modification
Needed for PM
Analyses?
No
No
No
Yes*
No
Yes*
Yes*
No
No
* Different distributions in VMT, trips, or vehicle population than those reflected by the EMFAC
defaults should be updated through the user interface to incorporate project-specific vehicle activity
information.
64
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5.6.3 Comparing project data andEMFAC defaults to determine adjustments
Individual projects will have a mix of vehicle types that varies from the regional average
fleet mix. Because PM hot-spot analyses can be especially sensitive to diesel-powered
truck activity, it is important to characterize the relative fraction of the fleet that is
comprised of trucks compared to light-duty vehicles properly. Users should determine
the base (default) case and forecasted vehicle mix (trucks versus non-trucks) applicable to
their project's build and no-build scenarios and use that information to adjust EMFAC
defaults.
Users should first collapse VMT, vehicle trip and vehicle population data for EMFAC's
13 vehicle classes to two general data categories: "truck" and "non-truck." The common
practice in California is to define, for emission purposes, "truck" activity as being
comprised of all activity associated with what EMFAC identifies as medium-duty and
heavier vehicles. In addition, travel activity data typically identify "trucks" in a general
sense, without regard to their fuel type. Exhibit 5-6, therefore, shows the suggested
vehicle class mapping given the likely data available at the project level.
Exhibit 5-6. Mapping EMFAC Vehicle Classes to Project-specific Activity
Information
Typical Projects
(2 categories)
Non-truck
Truck
EMFAC
Default
(13 classes)
LDA
LDT1
LDT2
MCY
MDV
LHDT1
LHDT2
MHDT
HHDT
MH
OBUS
SBUS
UBUS
Description
Passenger cars
Light-duty trucks 1
Light-duty trucks 2
Motorcycles
Medium-duty trucks
Light-heavy-duty trucks 1
Light-heavy-duty trucks 2
Medium-heavy-duty trucks
Heavy-heavy-duty trucks
Motor homes
Other buses
School buses
Urban buses
EMFAC Output
Summary Rates (RTS)
File
(6 groups)
LDA
LOT
MCY
MDT
HOT
UBUS
5.6.4 Adjustment of default activity distributions to reflect project data
After the vehicle mapping is complete, users will need to compare the project-specific
distributions to the default data included in EMFAC for trucks and non-trucks. For
example, assume 2009 is used as the analysis year for a hypothetical highway project in
Sacramento County with 25% of total annual average daily VMT apportioned to trucks.
After entering all the basic inputs in the EMFAC modeling software, pre-populated
(default) county VMT for the truck portion of the fleet is equal to 6,269,545 (when all
65
-------
appropriate vehicle classes are summed up), and the model default activity shows that
truck VMT represents 19% of total VMT in Sacramento County (see Exhibit 5-7).
The VMT should then be re-allocated to the correct percentage. EMFAC allows users to
adjust the calculated fleet-average emission factors by varying the relative weightings of
the 13 vehicle classes. This adjustment is done by replacing the default numbers for each
vehicle class in the EMFAC user interface, using the "VMT" option for a highway
project, or the "Trips" or "Population" option if analyzing a transit or other terminal
project, under the "Edit Program Constants" function available via the Emfac mode
screen.
Note: EMFAC also allows users to modify the fuel characteristics (gas/diesel/electric) for
each of the 13 vehicle classes. For most PMhot-spot analyses for highway projects with
non-captive fleets, users will not need to modify the fuel assumed for the fleet vehicles.
For projects involving captive fleets with known fuel use distributions, the default
fractions should be modified.
Exhibit 5-7. Example Default EMFAC VMT by Vehicle Class Distribution
f diling VMT data for scenario 1: Sacramento Counly Subarea Annual CYr ?OQ9 Default.
Total VMT kxsea
Sacwnento County j
Paste Data Orty
EdttngMorfe Edfr0\MT{veKcfeR*MtttMfedpervM*(lv)
Trtal VMT By Vebde daw I By Vehcfe and Fuel | By VerKle/FueUHou |
01 - Lijhl-Ouly Altos (PC)
02 -Light-DJy Trucks (Tlj
03 -Usfit-OutyT rucks (T2)
04 - MwiuifrOulj. Trucks (T3]
05 -UgHHD Trucks (T4)
06 -ligKHD Trucks (T5)
07 • Mmhjn HD Trucks (T6)
08 'Heavy HD Trucks (T7J
03 • Qtrw Bute:
10- Urban Bu»*$
1 1 • Motorcydes
12 • School Bus*i
13-MotorHOBM
|t 5271757.
J340432.
7266306,
3535454,^
81627B.
302809.
638543.
704156.
W59Q.
.:n-.
256367.
31176.-]
3t341.J
Total "tmcK'
VMT = 6,269 5
-------
in Exhibit 5-8, when the VMT values for the truck classes are adjusted, their sum is equal
to 8,101,117 (25% of total county VMT). Adjusted non-truck VMT is now 24,303,350
(75% of total VMT). The details of this example are presented in Appendix G. When
updating the EMFAC default VMT by vehicle class, the total VMT (for all 13 vehicle
classes) must remain unchanged.
Exhibit 5-8. Example Adjusted EMFAC VMT by Vehicle Class Distribution
fdiling VMF data to; scenario 1: Sacrdmenlo E.ounly Sulidrea Annual CYr 7009 Default Title
TotdVMT Uxae-i
Copy wdl-i Heacirigj Patte Data 0 rjy
EtfengMod* Edtog VMT |v«hde rntei b*v«Mper wMfcdv)
ToW VMT 6y VehcfeCbn I fyVehcle and Fuel | By Vdbde/Fuel/Hou |
01
03
05 UgNHDTnjct,s(74|
06 UsNHDTmtMITSi
Of-HMMfHOTwd«(n]
09 OOwBuwt
10 • Urban Buiei
11
12-
13-MolOfHcnw:
14201491
31C639&
6757073
4568294
1054743
B1271
902614
909867
S4077
51941
238400
40284
118025.
>•
Total "tmck"
VMT =8,101,117
25% of total Vm
[: co-
Note that, in special cases, if one or more of the default vehicle classes are not present in
the project area, users should set VMT (to address running exhaust emissions), number of
trips (to address starting emissions) and population (to address idling emissions) for that
class to "1" in the EMFAC interface. In other words, users should functionally zero-out
the appropriate vehicle class by inputting a value of "1" because EMFAC does not allow
an input of zero in the interface for VMT, trip, and vehicle population distributions. A
complete example illustrating how to change EMFAC default distributions to exclude
some vehicle classes for a transit project is presented in Appendix H. An alternate way is
to delete unwanted vehicle classes in the basic scenario data input to the model.
Appendices G and H provide more detailed examples of these steps; these modifications
will typically only be necessary for projects involving unique conditions such as truck-
only activity.
61
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Note: The average emission factors provided by EMFAC in the "Emfac mode " are VMT-
weighted (for running emissions), vehicle trip-weighted (for start emissions), or vehicle
population-weighted (for idle emissions) across different vehicle classes. If a user runs
the model for a county, the weighting reflects county-level VMT, trips (starts), or vehicle
fleet and their absolute values are not relevant at the project level.
For most transit and other terminal projects, users may have very detailed information on
not only vehicle mix, but also fuel mix (diesel/gas/electric) and age distribution (model
year distribution). Users should adjust the fuel mix (changed through the "By Vehicle
and Fuel" tabs of the VMT, Population, and Trips panels) to reflect the known or
expected fuel use (if, for instance, a bus fleet is expected to use entirely diesel fuel).
Similarly, if the age distribution (model year distribution) is known for a particular fleet,
this should be entered in place of the EMFAC default values (found in the "By
Vehicle/Fuel/Age" tab of the Edit Population panel). Note that EMFAC's ability to
model alternate fuel options is not uniform among vehicle classes. If users determine that
modification of the fleet in terms of fuel or age distribution is needed, they should contact
CARB for further guidance. However, for most highway and intersection projects with a
non-captive fleet, the EMFAC default fuel mix and age distribution should be used.
5.7 GENERATING EMISSION FACTORS FOR USE IN AIR QUALITY
MODELING
For each EMFAC run, emission factors will be generated in the "Summary Rates (RTS)"
file (.its file) in the form of look-up tables. These tables are organized and numbered by
different emission processes and pollutant types. PM emission factors for running
exhaust, idle exhaust, tire wear, and brake wear are included in Table 1 of the .its file;
PM start emission factors are included in Table 2 of the .its file. Exhibit 5-9 (following
page) includes example screenshots of EMFAC .its file output.
5.7.1 Highway and intersection links
For each speed value (greater than 0 mph), EMFAC outputs running exhaust, tire wear,
and brake wear emission factors in grams/vehicle-mile, for six vehicle groups plus an
aggregate emission factor named as "All" (see Exhibit 5-6). Note that the .its output file
includes only six vehicle groups - an aggregation of the 13 vehicle classes manipulated
during the input process. In general, assuming users have run the model with VMT-
weighted distributions appropriate for the project's fleet activity (see Section 5.6), only
the emission factors from the "All" column will be needed. The "All" column includes a
grams/vehicle-mile value that is a VMT-weighted average based on the user-provided
vehicle activity mix. The sum of running exhaust, tire wear, and brake wear grams/mile
PM emission factors for a given speed is the total fleet-average grams/vehicle-mile
emission factor appropriate for modeling highway project links:
Total Link Emission Factor = (EFnmning) + (EF^S wear) + (EFbraks wear)
68
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The total link emission factor (grams/vehicle-mile) can be used in combination with the
link volume and link length as input into CAL3QHCR. If using AERMOD, an emission
rate (in grams/hour) should be calculated for each link. This can be done by multiplying
the total link emission factor (calculated above) by the link hourly volume and link
length.
Exhibit 5-9. Example EMFAC Running Exhaust, Tire Wear, and Brake Wear
Emission Factors in the Summary Rates (rts) Output File
1 default, rts- WordPad J Q[E][X|
File Edit View Insert
D H? Q S Et
Pollutant
Speed
HPH
0
5
10
15
20
25
30
35
10
15
SO
55
60
65
Pollutant
Speed
HPH
0
5
10
15
20
25
30
35
10
15
50
55
60
65
Pollutant
Speed
HPH
0
5
10
15
20
25
30
<_
For Help, press Fl
Format
Help
m ^m •" %
Name :
LDA
0.000
o.oso
0.033
0.022
0.016
0.013
0.010
0.009
0.008
0.007
0.007
0.007
0.008
0.009
Name :
LDA
0.000
0.003
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.008
0.003
Name :
LDA
0.000
0.013
0.013
0.013
0.013
0.013
0.013
PH10
0
a
0
0
0
0
0
0
0
0
0
0
0
0
PH10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
PH10
0
0
0
0
0
0
0
Temperature :
LDT
.000
.095
.062
.013
.032
.021
.020
.017
.015
.011
.011
.011
.015
.018
HDT
0.057
0.098
0.065
0.016
0.031
0.026
0.021
0.018
0.016
0.015
0.011
0.015
0.016
0.018
1
1
1
0
c
0
0
0
0
0
L
c
0
0
HDT
.380
.630
.129
.763
.519
.160
.395
.350
.327
.321
.310
.376
.131
.SOS
- Tire ITear
LDT
.000
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
HDT
0.000
0.009
0.009
0.009
0 . 009
0.009
0.009
0.009
0.009
0.009
0 . 009
0.009
0.009
0.009
0
0
c
L
c
0
0
0
0
L
0
0
0
0
HDT
.000
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
.026
- Brake Wear
LDT
.000
.013
.013
.013
.013
.013
.013
HDT
0.000
0.013
0.013
0.013
0.013
0.013
0.013
c
c
0
c
0
0
0
HDT
.000
.022
.022
.022
.022
.022
.022
0
0
0
0
0
0
0
0
0
0
0
0
0
0
UBUS
.000
.888
.613
.183
.376
.303
.252
.218
.195
.181
.173
.172
.177
.189
Temperature :
0
0
0
0
0
0
0
0
0
0
0
0
0
0
UBUS
.000
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
.008
Temperature :
0
0
0
c
0
0
0
UBUS
.000
.013
.013
.013
.013
.013
.013
60F
HCY
0.000
0.051
0.010
0.033
0.029
0.026
0.025
0.021
0.025
0.027
0.031
0.037
0.016
0.060
60F
HCY
0.000
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
60F
HCY
0.000
0.006
0.006
0.006
0.006
0.006
0.006
Relative Humidity: 70%
ALL
0.081
0.163
0.111
0.076
O.OSS
0.015
0.037
0.033
0.030
0.029
0.030
0.032
0.036
0.012
Relative Humidity: 70%
ALL
0.000
0.009
0.009
0.009
0 . 009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
Relative Humidity : 70%
ALL
0.000
0.013
0.013
0.013
0.013
0.013
0.013
.1 _>l
MUM
69
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5.7.2 Transit and other terminal links
For transit and other terminal projects, such as bus terminals or intermodal freight terminals,
grams/trip (or grams/start) emission factors can be combined with project-specific estimates of
vehicle trips (or starts) per hour to calculate grams/hour emissions. Starting emission factors
depend on the vehicle soak time (the soak time is the time a vehicle is stationary with the engine
turned off, following the last time it was operated). The longer a vehicle is turned off, or soaks,
the higher the start emissions embedded in EMFAC. The output look-up table for start emissions
includes 18 time bins (5 minutes to 720 minutes); users need to choose an appropriate time bin
that is representative for the project activity. Selected examples of some potential associated
soak times are shown in Exhibit 5-10 for several possible scenarios.
Exhibit 5-10. Example Soak Times for Several Project Scenarios
Project Type
Bus Transit Facility
Truck Refueling Station
Intermodal Distribution Center
Truck Stop Parking Lot
Example Soak Time
(min)*
10
60
180
480
PMio Start Emission
Factors (g/trip)
0.002
0.008
0.013
0.016
* Example soak times and emission factors are for illustration purposes and are not to be used
as literal values. Users should select soak times and estimate emission factors appropriate to
the specific project and implementation dates to be evaluated. Emission factors will vary by
analysis year.
Idling emission factors are in grams/idle-hour and are available in Table 1 of the .its file
associated with a speed value of 0 mph (available only for MDT and HDT groups due to
EMFAC's data limitations). Note that, for transit and other terminal projects, idling and
starting emission factors from EMFAC should not be combined directly because they are
generated in different units. The project idling and starting emissions (in grams) need to
be calculated separately for a particular time period, based on project-specific idle hour
and trips/hour data. The total transit or other terminal project emissions for the time
period are the sum of the two values:
Total Project Emissions =
*
idle hours) + (EFstarting * trips)
The result of this calculation is a grams/hour emission rate that can be used for air quality
modeling.
In some cases, users may need to model running exhaust emissions from cruise,
approach, and departure link activity, as well as start and idle emissions at the project
site. For instance, to assess impacts from a proposed bus terminal, users may need to
evaluate both the start and idle emissions from buses at the terminal as well as the bus
running exhaust emissions along the links approaching and departing from the terminal.
Given that the link activity will involve a unique vehicle fleet (one with a
disproportionate amount of bus activity), users should modify the default travel activity
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in EMFAC to reflect the bus activity (see the discussion above). EMFAC allows users to
generate emission factors for both the approaching/departing links and the bus terminal
itself in a single run. To obtain project-specific running exhaust emission factors, users
can modify the VMT associated with the buses at the approaching link by adjusting the
values for each of the 13 vehicle classes in the user interface with the method described
in Section 5.6. In the same EMFAC run, users can enter project-specific vehicle
population and trip distributions to produce project-specific start and idle emission
factors.
Another special case may involve modeling idling emissions for a specific fleet of heavy
heavy-duty diesel trucks (HHDT). Because EMFAC provides only an overall average
idle emission factor for heavy-duty trucks regardless of fuel type, ambient conditions,
accessory usage, and engine speed, CARB has created supplemental guidance that, off-
model, provides season-specific HHDT emission factors for activity that CARB has
termed "high idle" and "low idle."67 Low idle (sometimes also called "curb idle")
involves short-term idling with engine speeds of 800 rpm or less and no accessory
loading. High idle is idling over an extended period of time with engine speeds over
800 rpm, usually involving the use of heaters, air conditioners, or other vehicle
accessories. If the project under evaluation involves HHDT and the user has detailed
information about the fleet (vehicle model years and the amount of time spent in low and
high idle, in particular), the information from this supplemental guidance may be used to
obtain more specific idle emission factors for HHDT than would otherwise be available
by simply using EMFAC.
Other special projects may need additional data manipulation. Project sponsors should
contact CARB or the local air quality management district for further guidance.
Note: The product of any transit or other terminal project should be a grams/hour
emission factor for each defined project area. If approach/departure running emissions
are calculated, a grams/hour emission factor should be calculated from the grams/mile
EMFAC output as described in Section 5.7.1.
Alternative Method to Estimate Idle and Start Emission Factors for a Specific Vehicle
Class
A relatively simple method is available to obtain idle and start emission factors for those
cases in which users are interested in only one vehicle class (such as for heavy-duty
trucks). Note that this method is not recommended for situations involving multiple
vehicle classes (e.g., medium- and heavy-duty trucks). Because this is a methodology to
support development of idle and start emission factors, it is applicable only to those
vehicle classes for which EMFAC includes idle emissions (LHDT1, LHDT2, MHDT,
HHDT, School Buses, and Other Buses).
67 See EMFAC Modeling Change Technical Memo, "Revision of Heavy Duty Diesel Track Emissions
Factors and Speed Correction Factors" (original and amendment), October 20, 2006; available through
ARE online at: www.arb.ca.gov/msei/supportdocs.htnrfonroad.
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For example, suppose a project or link involves just HHDT. In this case, users could
modify EMFAC's basic input of Vehicle Classes in Section 3.6 in the user interface and
select "Heavy Heavy Duty Trucks." Editing EMFAC default population and trip
distributions is not needed because the output .its file will reflect emission factors that are
associated with the selected single vehicle class only.
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Section 6: Estimating Emissions from Road Dust,
Construction, and Additional Sources
6.1 INTRODUCTION
This section provides guidance on how to estimate re-entrained road dust and
transportation-related construction dust emissions. MOVES and EMFAC do not estimate
emissions of road or construction dust, so this section must be consulted if dust is
required to be included in the PM hot-spot analysis. See Section 2.5 for further
information regarding when dust emissions are required to be included in a PM hot-spot
analysis. This section also includes information on quantifying emissions from
construction vehicles and equipment and additional sources in the project area, when
applicable. The models and associated methods and assumptions used in estimating these
emissions must be evaluated and chosen through the process established by each area's
interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
6.2 OVERVIEW OF DUST METHODS AND REQUIREMENTS
In summary, road or construction dust can be quantified using EPA's AP-42 method or
alternative local methods. AP-42 is EPA's compilation of data and methods for
estimating average emission rates from a variety of activities and sources from various
sectors. Refer to EPA's website (www.epa.gov/ttn/chief/ap42/index.html) to access the
latest version of AP-42 sections and for more information about AP-42 in general. The
sections of AP-42 that address emissions of re-entrained road dust from paved and
unpaved roads and emissions of construction dust are found in AP-42, Chapter 13,
"Miscellaneous Sources." The key portions of the chapter include:
• Section 13.2: "Introduction to Fugitive Dust Sources,"
• Section 13.2.1: "Paved Roads"
• Section 13.2.2: "Unpaved Roads"
• Section 13.2.3: "Heavy Construction Operations" (includes road construction)
Users should consult EPA's website to ensure they are using the latest approved version
/-Q
of AP-42, as the methodology and procedures may change over time.
In addition to the latest version of AP-42, alternative local methods can be used for
estimating road or construction dust; in some areas, these methods may already exist and
can be considered for use in quantitative PM hot-spot analyses.
This section presumes users already have a basic understanding of how to use AP-42 or
other dust methods.
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.s
nonattainment problem. See Section 2.5 for further information.
6.3.2 PMj o nonattainment and maintenance areas
Re-entrained road dust must be included in all PMio hot-spot analyses. EPA has
historically required road dust emissions to be included in all conformity analyses of
direct PMio emissions - including hot-spot analyses. See Section 2.5 for further
information.
6.3.3 Using AP-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. This section can
be downloaded from EPA's website at: www.epa.gov/ttn/chief/ap42/ch 13/index.html.
When estimating emissions of re-entrained road dust from paved roads, site-specific silt
loading data must be consistent with the data used for the project's county in the regional
emissions analysis (40 CFR 93.123(c)(3)). In addition, if the project is located in an area
where anti-skid abrasives for snow-ice removal are applied, information about their use
should be included (e.g., the number of times such anti-skid abrasives are applied).
6.3.4 Using AP-42 for road dust on unpaved roads
Section 13.2.2 of AP-42 provides a method for estimating emissions of re-entrained road
dust from unpaved roads. Different equations are provided for vehicles traveling
unpaved surfaces at industrial sites and vehicles traveling on publicly accessible roads.
Most PM hot-spot analyses will involve only vehicles traveling on publicly accessible
roads. When applying an equation that accounts for surface material moisture content,
the percentage of surface material moisture must be consistent with the data used for the
project's county in the regional emissions analysis (40 CFR 93.123(c)(3)).
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6.3.5 Using alternative local approaches for road dust
Some PM areas have historically used locally-developed methods for estimating re-
entrained road dust emissions that may be more appropriate than the AP-42 methods
given specific local conditions. Other areas may develop alternatives in the future.
Also, an alternative method could be used if the equations in AP-42 do not apply
to a particular project, as they were developed using a particular range of source
conditions. Section 13.2.1 of AP-42 currently states that users should use caution
when applying the 13.2.1 equation outside of the range of variables and operating
conditions specified. In these cases, users are encouraged to consider alternative
methods that can better reflect local conditions.
6.4 ESTIMATING TRANSPORTATION-RELATED CONSTRUCTION DUST
6.4.1 Determining whether construction dust must be considered
Construction-related PM2.5 or PMio emissions associated with a particular project are
required to be included in hot-spot analyses only if such emissions are not considered
temporary as defined in 40 CFR 93.123(c)(5) (see Section 2.5.5). The following
discussion includes guidance only for construction-related dust emissions; any other
construction emissions (e.g., exhaust emissions from construction equipment) would need
to be calculated separately, as discussed in Section 6.6.
6.4.2 Using AP-42 for construction dust
Section 13.2.3 of AP-42 describes how to estimate emissions of dust from construction of
transportation projects. This section can be downloaded from EPA's website at:
www.epa.gov/ttn/chief/ap42/ch 13/index.html. Section 13.2.3 of AP-42 indicates that a
substantial source of construction-related emissions could be from material that is tracked
out from the site and deposited on adjacent paved streets. Therefore, AP-42 states that
persons developing construction site emission estimates need to consider the potential for
increased adjacent emissions from off-site paved roadways; users should refer to the
discussion regarding paved roads in Section 6.3.3.
6.4.3 Using alternative approaches for construction dust
Some PM nonattainment or maintenance areas have historically used alternative methods
for estimating construction dust that may be more appropriate than AP-42, given specific
local conditions. Other areas may develop alternatives in the future.
Also, an alternative method may be more appropriate if the project's conditions - such as
surface material silt and moisture content percentages, mean vehicle weight and speed -
are not within the ranges of source conditions that were tested in developing the
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equations. In such cases, users may consider alternative methods that are more
appropriate for local conditions.
6.5 ADDING DUST EMISSIONS TO MOVES/EMFAC MODELING RESULTS
Emission factors for road and construction dust should be added to the emission factors
generated for each link by MOVES or EMFAC (in California). Once this data is
available, the user can move on to Section 7 to develop input files for the appropriate air
quality model.
6.6 ESTIMATING ADDITIONAL SOURCES OF EMISSIONS IN THE PROJECT
AREA
6.6.1 Construction-related vehicles and equipment
In certain cases, emissions resulting from construction vehicles and equipment, including
exhaust emissions as well as dust, must be included in an analysis; refer to Section 2.5.5
for more information on when to include such emissions. State and local air agencies
may have quantified these types of emissions for the development of SIP non-road
mobile source inventories, and related methods should be considered for PM hot-spot
analyses. Evaluating and choosing models and associated methods and assumptions for
quantifying construction-related emissions must be determined through an area's
interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
6.6.2 Locomotives
EPA has developed guidance to quantify locomotive emissions when they are a
component of a transit or freight terminal or otherwise a source in the project area being
modeled. See Appendix I for further general guidance, resources, and examples.
6.6.3 Additional emission sources
When applicable, additional sources need to be estimated and included in air quality
modeling, as described in Section 8.
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Section 7: Selecting an Air Quality Model, Data Inputs, and
Receptors
7.1 INTRODUCTION
This section describes the recommended air quality models, data inputs, and receptor
considerations for PM hot-spot analyses. This guidance is consistent with the conformity
rule and recommendations for air quality modeling in EPA's "Guideline on Air Quality
Models" (Appendix W to 40 CFR Part 51).
Regardless of the model used, the quality of a model's predictions depends on
appropriate input data, proper formatting, model setup, quality assurance, and other
assumptions. As noted in Section 2, air quality modeling for PM hot-spot analyses must
meet the conformity rule's general requirements for such analyses (40 CFR 93.123(c))
and rely on the latest planning assumptions available when the conformity analysis
begins (40 CFR 93.110).
This section presumes that users already have a basic understanding of air quality models
and their operation. EPA has also included additional details on air quality modeling in
Appendix J of this guidance. The models in this section, user guides, and supporting
documentation are available through EPA's Support Center for Regulatory Air Models
(SCRAM) website at: www.epa.gov/scram001. Project sponsors conducting PM hot-spot
analyses will need to refer to the latest user guides and available guidance for complete
instructions.
7.2 GENERAL OVERVIEW OF AIR QUALITY MODELING
Air quality models, methods, and assumptions need to be determined for each PM hot-
spot analysis through the interagency consultation process (40 CFR 93.105(c)(l)(i)).
Exhibit 7-1 (following page) outlines the basic process for conducting air quality
modeling for a given project. This exhibit depicts the flow of information developed for
air quality modeling (as described in this section), the development of background
concentration estimates (see Section 8), and the calculation of design values and
comparison to the NAAQS (see Section 9).
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Exhibit 7-1. Overview and Data Flow for Air Quality Modeling
Reference Documents
Appendix W to
40CFRPart 51
(throughout)
AERMOD
Implementation
Guide
MPRM User
Guide (for
CAL3QHCR)
AERMET User-
Guide (for
AERMOD)
Running the Air Quality Model
(Section?)
Select appropriate air
quality model
(Section 7.3)
Characterize sources
(location, timing, etc.)
(Section 7.4)
Obtain representative
meteorological data
(Section 7.5)
Run appropriate met pre-
processor
(Section 7.5)
Specify urban or rural
sources
(Section 7.5)
Place receptors
(Section 7.6)
Run air quality model
and obtain results
(Section 7.7)
Calculate design
values and determine
conformity
(Section 9)
Ambient
monitor. CTM-
based data, or
other
Determine
background
concentrations from
nearby & other
sources
(Section 8)
Modeling sequence 1 1 Actlon
_ _ ^ 1 ] Document
Model inputs
CD
a
Results previously
calculated
External data
* If applicable
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7.3 SELECTING AN APPROPRIATE AIR QUALITY MODEL
7.3.1 Recommended air quality models
PM hot-spot analyses should be developed consistent with EPA's current recommended
models under Appendix W to 40 CFR Part 51. The purpose of recommending a
particular model is to ensure that the best-performing methods are used in assessing PM
impacts from a particular project and are employed in a consistent fashion.69 Exhibit 7-2
summarizes the recommended air quality models for PM hot-spot analyses for required
projects under 40 CFR 93.123(b)(l).
Exhibit 7-2. Summary of Recommended Air Quality Models
Type of Project
Highway and intersection projects
Transit, freight, and other terminal projects
Projects that involve both highway/intersections
and terminals, and/or nearby sources*
Recommended Model
AERMOD, CAL3QHCR
AERMOD
AERMOD
* Note that "nearby sources" refers to those sources that (1) are not part of the project but are affected by
the project or (2) are sources in the project area whose emissions are not adequately captured by the
selected background concentrations. See Section 8.2 for more information.
The American Meteorological Society/EPA Regulatory Model (AERMOD) is EPA's
recommended near-field dispersion model for many regulatory applications. EPA
recommended AERMOD in a November 9, 2005 final rule that amended EPA's
"Guideline on Air Quality Models" after more than ten years of development and peer
review that resulted in substantial improvements and enhancements.70 AERMOD
includes options for modeling emissions from volume, area, and point sources and can
therefore model the impacts of many different source types, including highway and
transit projects. In addition, EPA conducted a study to evaluate AERMOD and other air
quality models in preparation for developing this guidance and the study supported
69 The best performing model is one that best predicts regulatory design values for a particular pollutant.
EPA's "Protocol for Determining the Best Performing Model" (EPA-454/R-92-025) defines operational
and statistical criteria for this evaluation. According to the document: "For a pollutant.. .for which short-
term ambient standards exist, the statistic of interest involves the network-wide highest concentration.. .the
precise time, location, and meteorological condition is of minor concern compared to the magnitude of the
highest concentration actually occurring."
70 The final rule can be found at: www.epa.gov/scram001/guidance/guide/appw 05.pdf. Extensive
documentation is available on EPA's SCRAM website describing the various components of AERMOD,
including user guides, model formulation, and evaluation papers. See:
www.epa.gov/scram001/dispersion_prefrec.htm#aermod.
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AERMOD's use.71 To date, AERMOD has already been used to model air quality near
roadways, other transportation sources, and other ground-level sources for regulatory
applications by EPA and other federal and state agencies.72
CAL3QHCR is an extension of the CAL3QHC model, which is the model recommended
for use in analyzing CO impacts from intersections.73 In addition, CAL3QHCR
incorporates enhancements to process up to a year of meteorological data and emissions
data that vary by day of week and hour of day. It is appropriate to use CAL3QHCR for
PM hot-spot modeling for specified projects; however, its queuing algorithm should not
be used.
Both the AERMOD and CAL3QHCR models (and related documentation) can be
obtained through EPA's SCRAM website. OAQPS maintains the SCRAM website and
maintains, codes, and supports AERMOD on an ongoing basis. Modelers should
regularly check this website to ensure use of the latest regulatory version. CAL3QHCR
is not maintained by EPA and is no longer updated; therefore, technical support for the
model code is not available through OAQPS. However, EPA will provide technical
support for implementing AERMOD and the current version of CAL3QHCR for PM hot-
spot analyses completed with this guidance.
Appendix J includes important additional information about configuring AERMOD and
CAL3QHCR when using these models to complete PM hot-spot analyses. In the future,
it is possible that other recommended models will become available.
Highway and Intersection Projects
Some projects may consist exclusively of highways and intersections, with little or no
emissions coming from extended idling, non-road engine operations, or modeled nearby
sources (see more below). Both AERMOD and CAL3QHCR are recommended air
quality models for these types of projects.74 When using CAL3QHCR for such highway
and intersection projects, its queuing algorithm should not be used. As discussed in
Sections 4 and 5, as well as in Appendix D, idling vehicle emissions should instead be
71 Hartley, W.S.; Can, E.L.; Bailey, C.R. (2006). Modeling hotspot transportation-related air quality
impacts using ISC, AERMOD, and HYROAD. Proceedings of Air & Waste Management Association
Specialty Conference on Air Quality Models.
72 For example, EPA used AERMOD to model concentrations of nitrogen dioxide (NO2) as part of the 2008
Risk and Exposure Assessment for revision of the primary NO2 NAAQS. Also, other agencies have used
AERMOD to model PM and other concentrations from roadways (represented as a series of area sources)
for purposes of NEPA and CAA analyses.
73 CAL3QHC is a CALINES -based screening model with a traffic model to calculate delays and queues at
signalized intersections; CAL3QHCR is a refined model based on CAL3QHC that requires local
meteorological data. The CALSQHCR's User Guide ("User's Guide to CAL3QHC Version 2.0: A
Modeling Methodology for Predicting Pollutant Concentrations Near Roadway Intersections") can be
found at: www.epa. gov/scramOO 1.
74 Appendix W to 40 CFR Part 51 describes both AERMOD and CAL3QHCR as being appropriate for
modeling line sources. For further background, see Sections 3.0, 4.0, 5.0, and 8.0 of Appendix W, as well
as Appendix A to Appendix W of 40 CFR Part 51.
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accounted for by properly specifying links for emission analysis and reflecting idling
activity in the activity patterns used for MOVES or EMFAC modeling.
Note: Users should be aware that, to handle quarterly emissions and multiple years of
meteorological data, AERMOD and CAL3QHCR need different numbers of input files
and runs. AERMOD can handle quarterly variations in emissions and multiple years of
meteorological data using a single input file and run. In contrast, CAL3QHCR can
handle only one quarter's emissions and one year of meteorological data at a time. See
further information in Section 7.5.3.
Transit and Other Terminal Projects
Other projects may include only transit or freight terminals and transfer points where a
large share of total emissions arise from engine start and idling emissions or from non-
road engine activity. AERMOD is the recommended air quality model for these types of
projects.
Projects that Involve Both Highway/Intersection and Terminal Projects, and/or Nearby
Sources
There may be some projects that are a combination of the "highway and intersection" and
"transit and freight terminal" project types. AERMOD is the recommended model for
these projects. As a general recommendation, if AERMOD is used for modeling any
source associated with the project, it should be the only air quality model used for the PM
hot-spot analysis.75 There may be other cases where the project area also includes a
nearby source that is affected by the project, and as a result, needs to be modeled to
account for background concentrations around the project (e.g., locomotives at a nearby
freight terminal or marine port). In these cases, AERMOD should be used for the project
and any such nearby sources. In general, it should be unnecessary to include nearby
sources in air quality modeling if they are not affected by the project (assuming the
impacts of such sources are adequately accounted for in the selected representative
background concentrations). See Section 8.2 for further information on nearby sources.
75 There are several reasons for this recommendation. First, AERMOD is flexible in how different sources
are represented, while CAL3QHCR represents all sources as "line sources" (see Section 7.3.2). Second,
AERMOD allows a much wider number of receptors and sources to be modeled simultaneously, which is
useful for large projects with different source configurations. Third, AERMOD's treatment of dispersion in
the lower atmosphere is based on more current atmospheric science than CAL3QHCR. Furthermore, the
use of a single model, rather than multiple models, is recommended to avoid the need to run the same
meteorological data through different preprocessors (AERMET, MPRM), avoid different receptor networks
for different sources, reduce the number of atmospheric modeling runs required to analyze a project, avoid
the use of different modeling algorithms that perform the same task, and reduce double-counting or other
errors.
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7.3.2 How emissions are represented in CAL3QHCR andAERMOD
Both CAL3QHCR and AERMOD simulate how pollutants disperse in the atmosphere.
To do so, the models classify emission sources within a project as line, volume, area, and
point sources:
• Line sources are generally linear emission sources, which can include highways,
intersections, and rail lines. They are directly-specified in the CAL3QHCR input
file using road link coordinates. AERMOD can simulate a highway "line source"
using a series of adjacent volume or area sources (see the AERMOD User Guide
and the AERMOD Implementation Guide for suggestions).76
• Volume sources (used in AERMOD only) are three-dimensional spaces from
which emissions originate. Examples of sources that could be modeled as volume
sources include areas designated for truck or bus queuing or idling (e.g., off-
network links in MOVES), driveways and pass-throughs in bus terminals, and
locomotive activity at commuter rail or freight rail terminals.77
• Area sources (used in AERMOD only) are flat, two-dimensional surfaces from
which emissions arise (e.g., parking lots).
• Point source emissions (used in AERMOD only) emanate from a discrete location
in space, such as a bus garage or transit terminal exhaust stack.
Each of these source types may be appropriate for representing different sources in a PM
hot-spot analysis. For example, highways may be modeled as line sources in
CAL3QHCR, but they may also be modeled as a series of adjoining volume or area
sources in AERMOD, as described below. Using another example, an exhaust vent from
a bus garage might be best represented as a point source, area source, or volume source,
depending on its physical characteristics. Project sponsors should consult with the most
recent user guides for air quality models to determine the most appropriate way to
represent a particular source within a model. Appendix J includes additional specific
information for modeling highway and transit projects.
7.3.3 A Iternate models
In limited cases, an alternate model for use in a PM hot-spot analysis may be considered.
As stated in Section 3.2 of Appendix W, "Selection of the best techniques for each
individual air quality analysis is always encouraged, but the selection should be done in a
consistent manner." This section of Appendix W sets out objective criteria by which
alternate models may be considered.
Analyses of individual projects are not expected to involve the development of new air
quality models. However, should a project sponsor seek to employ a new or alternate
model for a particular transit or highway project, that model must address the criteria set
forth in Section 3.2 of Appendix W. Determining model acceptability in a particular
76 The AERMOD Implementation Guide is updated on a periodic basis. The latest version is posted on the
SCRAM web site at: www.epa.gov/ttn/scram/dispersion_prefrec.htm#aermod.
77 See Appendix I for information on estimating locomotive emissions.
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application is an EPA Regional Office responsibility involving consultation with EPA
Headquarters, when appropriate.
7.4 CHARACTERIZING EMISSION SOURCES
Characterizing sources is the way in which the transportation project's features and
emissions are represented within an air quality model. In order to determine the
concentrations downwind of a particular emission source, an air quality model needs to
have a description of the sources, including:
• Physical characteristics and location;
• Emission rates/emission factors; and
• Timing of emissions.
There may be several different emission sources within the project area. Sections 4 and 5
describe how a project can be characterized into different links, which will each have
separate emission rates to be used in air quality modeling. Sections 6 and 8.2 outline how
nearby source emissions, when present, can be characterized to account for emissions
throughout the project area. Properly characterizing all of these distinct sources within
the PM hot-spot analysis will help ensure that the locations with the greatest impacts on
PM air quality concentrations are identified.
This section describes the major elements needed to characterize a source properly for
use in an air quality model.
7.4.1 Physical characteristics and location
When modeling an emission source, its physical characteristics and location need to be
described using the relevant model's input format, as described in the appropriate user
guide. Sources with the same emission rate but with different physical characteristics
may have different impacts on predicted concentrations.
Refer to Appendix J of this guidance and to the user guides for CAL3QHCR and
AERMOD for specific information about how physical characteristics and location of
sources are included in these models.
In addition, for emissions on or near rooftops, such as those from exhaust stacks on
transit or other terminal projects, building downwash can result in higher concentrations
•yo
on the downwind side of nearby buildings than would otherwise be present. Consult
Appendix J for guidance on when to include building downwash for these projects when
using AERMOD.
Building downwash occurs when air moving over a building mixes to the ground on the downwind side
of the building.
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7.4.2 Emission rates/emission factors
The magnitude of emissions within a given time period or location is a necessary
component of dispersion modeling. For motor vehicles, MOVES-based emission rates
are required in all areas other than the state of California, where 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.
CAL3QHCR and AERMOD accept emission rates in different formats. For highways
and intersections, CAL3QHCR needs emissions to be specified in grams/vehicle-mile
traveled (grams/mile).79 AERMOD needs emission rates in grams/hour (or
grams/second). When employing area sources with AERMOD (e.g., parking lots),
emission rates must be specified in grams/second per unit area.
7.4.3 Timing of emissions
The proper description of emissions across time of year, day of week, and hour of day is
or\
critical to the utility of air quality modeling. 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. As described in Section 3.3.4, air quality modeling for the
annual PM2.5 NAAQS would involve data and modeling for all four quarters of the
analysis year; air quality modeling for the 24-hour PM NAAQS may involve all four
quarters, or one quarter in certain circumstances.
Sections 4 and 5 and Appendix J describe how results from MOVES and EMF AC should
be prepared for use as inputs in both AERMOD and CAL3QHCR.
7.5 INCORPORATING METEOROLOGICAL DATA
7.5.1 Finding representative meteorological data
One of the key factors in producing credible results in a PM hot-spot analysis is the use
of meteorological data that is as representative as possible of the project area.
Meteorological data are necessary for running either AERMOD or CAL3QHCR because
meteorology affects how pollutants will be dispersed in the lower atmosphere. The
following paragraphs provide an overview of the meteorological data needed and sources
of this data. More detailed information can be found in Appendix J and in model user
79 CAL3QHCR uses the hourly volume of vehicles on each road link and the emission factor (in
grams/mile) for the vehicles on each link to calculate time-specific emission rates for use in air quality
modeling. As described in Sections 4 and 5, the idle emission factor inputs in CAL3QHCR should not be
used in a PM hot-spot analysis.
80 The timing of emissions in AERMOD is described in Section 3.3.5 of the AERMOD User Guide.
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and implementation guides. EPA's SCRAM web site also contains additional
information, including additional guidance, archived meteorological data (which may be
suitable for some analyses), and links to data sources.
Meteorological data is used by air quality dispersion models to characterize the extent of
wind-driven (mechanical) and temperature-driven (convective) mixing in the lower
atmosphere throughout the day.81 For emissions near the ground, as is common in
transportation projects, dispersion is driven more by mechanical mixing, but temperature-
driven mixing can still have a significant impact on air quality. As a source's plume
moves further downwind, temperature-driven mixing becomes increasingly important in
determining concentrations.
Depending on the air quality model to be used, the following types of information are
needed to characterize mechanical and convective mixing:
• Surface meteorological data, from surface meteorological monitors that measure
the atmosphere near the ground (typically at a height of 10 meters—see Section
7.5.2);
• Upper air data on the vertical temperature profile of the atmosphere (see Section
7.5.2);
• Data describing surface characteristics, including the surface roughness, albedo,
and Bowen ratio (see Section 7.5.4); and
• Population data to account for the "urban heat island effect" (see Section 7.5.5).
Project sponsors may want to first consult with their respective state and local air quality
agencies for any representative meteorological data for the project area. In addition,
some state and local air agencies may maintain preprocessed meteorological data suitable
for use in PM hot-spot analyses. Interagency consultation can be used to determine
whether preprocessed meteorological data are available, which could reduce time and
resources forPM hot-spot analyses.
To format meteorological data appropriately and prepare them for use in air quality
models, EPA maintains meteorological processing software on the SCRAM website.82
These programs produce input data files that the air quality models read to produce
calculations of atmospheric dispersion. AERMOD and CAL3QHCR employ different
meteorological preprocessing programs. AERMET is the meteorological preprocessor
for AERMOD. The Meteorological Processor for Regulatory Models (MPRM) program
is the meteorological preprocessor for CAL3QHCR. User guides for both AERMET and
MPRM should be consulted for specific instructions.
The meteorological data used as an input to an air quality model should be selected on the
basis of geographic and climatologic representativeness and how well measurements at
81 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).
82
These programs and their user guides may be downloaded from the SCRAM website at:
www.epa.gov/scram001/metobsdata_procaccprogs.htm
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one site represent the likely transport and dispersion conditions in the area around the
project. The representativeness of the data depends on factors such as:
• The proximity of the project area to the meteorological monitoring site;
• The similarity of the project area to the meteorological monitoring site in surface
characteristics (particularly surface measurements);
• The time period of data collection;
• Topographic characteristics within and around the project area; and
• Year-to-year variations in weather conditions (hence, a sufficient length of
meteorological data should be employed, as discussed in Section 7.5.3 and
Appendix J).
The AERMOD Implementation Guide provides up-to-date information and
recommendations on how to judge the representativeness of meteorological data.83
Modelers should consult the most recent version of the AERMOD Implementation Guide
for assistance in obtaining and handling meteorological information. Although intended
for users of AERMOD, its recommendations for how to assess the representativeness of
meteorological data apply to analyses employing CAL3QHCR as well.
7.5.2 Surface and upper air data
Surface Data
Air quality models need representative meteorological data from a near-ground surface
weather monitoring station ("surface data"). Models have minimum needs for surface
observations. For example, when using National Weather Service (NWS) data to
produce meteorological input files for AERMOD, the following surface data
measurements are needed:
• Wind vector (speed and direction);
• Ambient temperature; and
• Opaque sky cover (or, in the absence of opaque sky cover, total sky cover).
Station barometric pressure is recommended, but not needed (AERMET includes a
default value in the absence of such data).
When processing data using MPRM for use in CAL3QHCR, information on stability
category is also needed. MPRM estimates stability internally. Alternatively, when using
NWS data, the calculation needs:
• Wind speed and direction;
• Ceiling height; and
• Cloud cover (opaque or total).
For details, refer to the AERMET or MPRM user guides on the SCRAM website.
84
See www.epa.gov/scram001/dispersionjrefrec.htnrfaermod.
See www.epa.gov/scram001/metobsdata_procaccprogs.htm.
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Upper Air Data
Upper air soundings measure gradients of vertical temperature in the atmosphere. The
vertical temperature gradients of the lower atmosphere are used by air quality models to
calculate convective mixing heights. Models need upper air sounding data from a
representative measurement site. For AERMOD, consult the AERMOD Implementation
Guide for specific recommendations. For CAL3QHCR, consult the MPRM user guide.
Obtaining Surface and Upper Air Meteorological Data
Meteorological data that is most representative of the project area should always be
sought. Meteorological data that can be used for air quality modeling are routinely
collected by the NWS. Other organizations, such as the FAA, local universities, military
bases, industrial facilities, and state and local air agencies may also collect such data.
Project sponsors may also choose to collect site-specific data for use in PM hot-spot
analyses, but it is not necessary to do so. If site-specific data are used, it should be
o c
obtained in a manner consistent with EPA guidance on the topic.
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.86 Meteorological data files that have been
preprocessed by the relevant state or local air agency may be used, when appropriate. If
meteorological data are collected on the project area prior to analysis, at least one year of
site-specific data is needed. Consult Section 8.3.1 of Appendix W for additional
explanation.
AERMOD and CAL3QHCR have different capabilities for modeling meteorological
data, as illustrated in Exhibit 7-3 (following page). The numbers in the exhibit pertain to
each analysis year and build or no-build scenario analyzed.
85 See Section 8.3.3 in Appendix W to 40 CFR Part 51 ("Site Specific Data") and the "Monitoring
Guidance for Regulatory Modeling Applications" (www.epa.gov/scram001/metguidance.htm'). Other
meteorological guidance documents are also available through SCRAM, including procedures for
addressing missing data and for quality assuring meteorological measurements.
86 As noted above, meteorological data are available through the NCDC website. Meteorological data are
continuously collected by NWS from sources such as airports. Five years of meteorological data are also
routinely used in other dispersion modeling applications.
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Exhibit 7-3. Air Quality Model Capabilities for Meteorological Data for Each
Scenario
Type of Air
Quality Model
AERMOD
CAL3QHCR
Number of Runs with 5
Years of Off-Site
Meteorological Data
1-5
20
Number of Runs with 1 Year
of Site-Specific
Meteorological Data
1
4
AERMOD can model either five years of representative off-site meteorological data (e.g.,
from NWS) or one year of site-specific data in a single run, since the model handles
different emissions within a year and multiple years of meteorological data with a single
input file. This requires a user to externally join meteorological data files before
preprocessing them with AERMET. Alternatively, AERMOD can be run five times, with
one year of meteorological data processed per run.
CAL3QHCR needs different input files for each quarter that is modeled using MOVES or
EMFAC, since CAL3QHCR does not distinguish between emission changes due to
seasonal differences. If site-specific data are collected, CAL3QHCR needs to be run only
four times, once for each quarter. If off-site data are used (e.g., from NWS), modeling
five years of consecutive meteorological data involves five runs of CAL3QHCR for each
quarter, which results in 20 runs for all four quarters.
7.5.4 Considering surface characteristics
In addition to surface and upper air meteorological data, three surface characteristics for
the site of meteorological monitoring are needed for air quality modeling, depending on
the model used:
• The surface roughness length (z0\ which indicates how much the surface features
at a given site (e.g., buildings, trees, grass) interrupt a smooth-flowing wind;
• Albedo (r), which is the amount of solar radiation reflected by the surface; and
• Bowen ratio (B0), which indicates how much heat the ground imparts to the air,
instead of evaporating moisture at the surface.
AERMOD and AERMET make use of these parameters directly. CAL3QHCR and
MPRM do not need data on surrounding surfaces' albedo or Bowen ratio for modeling
ambient PM concentrations, but surface roughness is an input to CAL3QHCR.87 As
described above, surface characteristics are also used to assess a meteorological
monitor's representativeness.
The AERMOD Implementation Guide should be consulted for the latest information on
processing land surface data, when using either AERMOD or CAL3QHCR. Although its
recommendations are intended for AERMOD, they also apply to CAL3QHCR with
As described in Section 4.2 of its user guide, MPRM makes use of surface roughness in calculating
stability categories.
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meteorological data processed by MPRM. 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.89 As of the writing of this guidance,
versions of the NLCD have been released representing calendar years 1992 and 2001,
with five areas/states (New England, Mississippi, South Dakota, Washington, and
Southern California) being updated to reflect 2006. Consult the AERMOD
Implementation Guide for recommendations for using NLCD data when processing
meteorological data.90
In most situations, the project area should be modeled as having flat terrain. However, in
some situations a project area may include complex terrain, such that sources and
receptors included in the model are found at different heights. See Appendix J for
information on handling complex terrain in air quality modeling.
7.5.5 Specifying urban or rural sources
In addition to surface characteristics, night-time dispersion in urban areas can be greater
than in surrounding rural areas with similar surface characteristics as a result of the
"urban heat island effect."91 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
88 The CAL3QHCR User Guide does not address preprocessing meteorological data, which is necessary for
PM hot-spot analyses. In the absence of such information, project sponsors should rely on the AERMOD
Implementation Guide when using either dispersion model.
89 This database can be accessed at: www.mrlc.gov.
90 The AERSURFACE model, a non-regulatory component of AERMOD, may also be used to generate
information on surface roughness, albedo, and Bowen ratio. As of this writing, AERSURFACE is based on
the 1992 NLCD. The latest version of AERSURFACE may be accessed via SCRAM
(www.epa.gov/scram001/).
91 The MPRM User Guide refers to the "urban heat island effect" as "anthropogenic heat flux."
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areas. The magnitude of the urban heat island effect is driven by the urban-rural
temperature difference that develops at night.
The implications for highway and transit projects are that the same emissions in a rural
area will undergo less dispersion than the same source in an urban area, all other factors
(e.g., surface characteristics, meteorology) being equal. For the purposes of a hot-spot
analysis, then:
• In urban areas, sources should generally be treated as urban.
• In isolated rural nonattainment and maintenance areas (as defined by 40 CFR
93.101), sources should be modeled as rural.
• Near the edge of urban areas, additional considerations apply that should be
addressed through the interagency consultation process.92
Modeling sources as urban or rural can have a large impact on predicted concentrations.
Both AERMOD and CAL3QHCR can account for the urban/rural differences in
dispersion. When sources are modeled as urban in AERMOD, the urban area's
population is a necessary input.
For projects near or beyond the edge of an urbanized area, there may be situations where
the build and no-build scenarios result in different degrees of urbanization. In these
situations, sources in the build scenario might be treated as urban, while in the no-build
they are treated as rural. Local data on such cases may not be universally available,
although some planning agencies have adopted models that may allow the impacts of
projects on population growth to be described. Given the potentially large impact of
modeling sources as either urban or rural, all available information on population growth
in the greater area around the project should be used when modeling projects near or
beyond the edge of an urbanized area.
When using AERMOD, consult the latest version of the AERMOD Implementation
Guide for additional information, including instructions on what type of population data
should be used in making urban/rural determinations. When using CAL3QHCR, consult
Section 7.2.3 of Appendix W for guidance on determining urban sources. Refer to
Appendix J for additional information on how to handle this data for each model.
7.6 PLACING RECEPTORS
7.6.1 Overview
Receptors for conformity purposes are locations in the project area where an air quality
model estimates future PM concentrations. Section 93.123(c)(l) of the conformity rule
requires PM hot-spot analyses to estimate air quality concentrations at "appropriate
receptor locations in the area substantially affected by the project." An "appropriate
92 Since the urban heat island is not a localized effect, but regional in character, Section 7.2.3 of Appendix
W recommends that all sources within an "urban complex" be modeled as urban.
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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.93
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 modeling and monitors for the PM NAAQS that may be relevant for PM hot-spot
analyses.
Exhibit 7-4 indicates the applicable parts of this guidance that can be used for receptors
in PM hot-spot analyses.
Exhibit 7-4. Guidance for Receptors in PM Hot-spot Analyses
NAAQS
24-hour PMio NAAQS
24-hour PM2.5 NAAQS
Annual PM2.5 NAAQS
Applicable Receptor Guidance
Section 7.6.294
Sections 7.6.2, 7.6.3
Sections 7.6.2, 7.6.3, and 9.4
The paragraphs below include general guidance for placing receptors for all PM NAAQS,
as well as additional guidance for consideration in PM2.5 hot-spot analyses.
7.6.2 General guidance for receptors for all PM NAAQS
Section 7.2.2 of Appendix W to 40 CFR Part 51 provides guidance on the selection of
critical receptor sites for refined analyses, and recommends that receptor sites be placed
in sufficient detail to estimate the highest concentrations and possible violations of a
NAAQS. The selection of receptor sites for all PM NAAQS should be determined on a
case-by-case basis taking into account project-specific factors that may influence areas of
expected high concentrations, such as prevailing wind directions, monitor locations,
topography, and other factors. In designing a receptor network (e.g., the entire coverage
of receptors for the project area), the emphasis should be placed on resolution and
location, not the total number of receptors. Design of the receptor network should also
93 CAA section 176(c)(l)(B) requires that transportation activities do not cause or contribute to new
NAAQS violations, worsen existing NAAQS violations, or delay timely attainment of the NAAQS or
interim milestones in the project area. EPA interprets "NAAQS" in this provision to mean the specific
NAAQS that has been established through rulemaking and monitored for designation purposes.
94 The current 24-hour PM10 NAAQS was established to account for ambient air quality concentrations at
receptor locations that can be accessed by one or more members of the public around homes, hospitals,
schools, sidewalks, etc. This conformity guidance is consistent with how air quality planning and
monitoring are done for this NAAQS.
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consider whether any locations within the project area should be excluded from the
modeling based on a location being restricted from public access or where a member of
the public would normally be present only for a very short period of time. Examples
include locations within a fenced property of a business, a median strip of a highway, a
right-of-way on a limited access highway, or an approach to a tunnel.
As described in Appendix W, air quality dispersion models are more reliable for
estimating the magnitude of highest concentrations somewhere within a specified area
and span of time than in predicting concentrations at a specific place and time.
Therefore, receptors should be sited at all locations at which high concentrations may
occur, rather than simply focusing on the expected worst case location.
Receptor spacing in the vicinity of the source should be of sufficient resolution to capture
the concentration gradients around the locations of maximum modeled concentrations.
The majority of emissions from a highway or transit project will occur within several
meters of the ground, and concentrations are likely to be greatest in proximity of near-
ground sources. As such, receptors should be placed with finer spacing (e.g., 10-25
meters) closer to a near-ground source, and with wider spacing (e.g., 50-100 meters)
farther from such a source. While prevailing wind directions may influence where
maximum impacts are likely to occur, receptors should also be placed in all directions
surrounding a project.
It should not be assumed that the location of maximum concentration will always be
located closest to the project itself. For example, if a highway project consists of a new
bypass that branches off an existing highway with significant emissions, maximum
concentrations may be expected at receptors farther from the project, but closer to the
existing highway.
Receptors should be sited as near as five meters from a source (e.g., the edge of a traffic
lane or a source in a terminal), except possibly with projects involving urban street
canyons where receptors may be appropriate within 2-10 meters of a project.95 In
addition, if AERMOD is used to create a standardized receptor network (e.g., using
AERMOD's Cartesian or polar grid functions), receptors may inadvertently be placed
within five meters of a project, and subsequently modeled. Such receptors should not be
used when calculating design values in most cases.
Receptors should be placed to capture the impacts of the project and any nearby source
that needs to be modeled. Receptor placement should be extended out to a sufficient
distance from sources to account for emissions that affect concentrations throughout the
project area, depending on the spatial extent of the project and the impacts of other
modeled sources.
EPA recommends that receptors should be sited to represent concentrations near-ground
level, generally at a height of 1.8 meters above grade or less. Receptors should also be
95 See 40 CFR Part 58, Appendix D, Section 4.7.1(c)(l) and Appendix E, Section 6.3(b). The interagency
consultation process should be used to determine when these provisions are relevant for a given analysis.
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placed at higher elevations if needed to represent concentrations at several heights along
multi-story buildings, such as apartment or office buildings.
When completing air quality modeling for build and no-build scenarios, receptors should
be placed in the same geographic locations in both scenarios so that direct comparisons
can be made between the design values calculated at each receptor. Receptors are first
determined based on the build scenario, and then placed in the same locations in the no-
build scenario (when this scenario is modeled). See Section 9 for further information
regarding calculating design values in a build/no-build analysis and appropriate receptors.
7.6.3 Additional guidance for receptors for the PM2.5 NAA QS
There are additional considerations when placing receptors for the PM2.5 NAAQS, due to
how this NAAQS was established. In the March 2006 final rule, EPA stated:
"Quantitative hot-spot analyses for conformity purposes would consider how
projects of air quality concern are predicted to impact air quality at existing and
potential PM2.5 monitor locations which are appropriate to allow the comparison
of predicted PM2.5 concentrations to the current PM2.5 standards, based on PM2.5
monitor siting requirements (40 CFR Part 58)." (71 FR 12471)
EPA included this language in the preamble to the March 2006 final rule so that PM2.5
hot-spot analyses would be consistent with how the PM2.5 NAAQS were developed,
monitored, and implemented. Receptors cannot be used for PM2.s hot-spot analyses if
they are at locations that would be inappropriate for ambient air quality monitoring for
purposes of comparison to the NAAQS.
In general, there are two factors in the PM2.s monitoring regulations that need to be
considered in determining the appropriateness of receptors for use in PM2.5 hot-spot
analyses. First, a receptor must be "population-oriented" in order to be appropriate for
comparison to either the 24-hour or annual PM2.5 NAAQS. Section 58.1 of the PM2.5
monitoring regulations defines population-oriented sites as:
"...residential areas, commercial areas, recreational areas, industrial areas where
workers from more than one company are located, and other areas where a
substantial number of people may spend a significant fraction of their day."
Population-orientated receptors can be determined when receptors are placed for air
quality modeling. In general, most locations, especially in urban areas, are population-
oriented. Receptors placed near transportation projects, therefore, will most likely be
population-oriented. Also, consideration should be given to the presence of people at
locations around each receptor in determining whether the receptor is population-
oriented, because the concentration predicted for the receptor can represent
concentrations surrounding the receptor. Changes in the project area in the future
analysis year should also be considered when placing receptors. For example, if a
receptor is at a location that is currently not population-oriented, but a housing
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development is planned for that location under the build and/or the no-build scenario, that
receptor may be appropriate for comparison to the PM2.s NAAQS.
The second factor from the PM2.5 monitoring regulations is only relevant for the annual
PM2.5 NAAQS. The PM2.5 monitoring regulations require that receptors for the annual
PM2.5 NAAQS also represent "community-wide air quality." Although receptors can be
placed for the annual PIVb.s NAAQS prior to air quality modeling, further consideration is
needed after air quality modeling to determine whether any of the modeled receptors are
not appropriate for comparison to the annual PM2.5 NAAQS. See Section 9.4 of this
guidance for how to determine appropriate receptor locations for the annual PM2.5
NAAQS.
7.7 RUNNING THE MODEL AND OBTAINING RESULTS
After preparing all model inputs, the air quality model should be run to predict
concentrations. Next, background concentrations need to be determined, as described in
Section 8. Finally, the resulting concentrations at receptors should be combined with
background concentrations from other sources to calculate design values, as described in
Section 9.
Note that, before the results of either AERMOD or CAL3QHCR are ready for use in
calculating design values and determining conformity, the data will have to undergo
some post-processing, depending on how the data was run in the models and the NAAQS
being evaluated. See Appendix J for more details.
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Section 8: Determining Background Concentrations from
Nearby and Other Emission Sources
8.1 INTRODUCTION
This section describes how to determine background concentrations for PM hot-spot
analyses. Section 93.123(c)(l) of the conformity rule states that "estimated pollutant
concentrations must be based on the total emissions burden which may result from the
implementation of the project, summed together with future background
concentrations...." Background concentrations do not include the emissions from the
project itself96 Instead, background concentrations for PM hot-spot analyses involve:
• Nearby sources: These are individual sources other than the highway or transit
project that contribute to ambient concentrations in the project area. Some nearby
sources may be included in the air quality modeling for PM hot-spot analyses,
while other nearby sources can be reflected in representative background
concentrations. In general, nearby sources would be included in air quality
modeling only when those sources would be affected by the project; and
• Other sources: This term is intended to capture the background concentrations in
the project area that are not from the project or any nearby sources that are
modeled.
Further information is provided in Section 8.2 on when to include nearby sources in air
quality modeling and in Section 8.3 on how to include the impact of other sources of
emissions in a future analysis year. It is important to note that nearby sources may only
be present for some PM hot-spot analyses.
This section is consistent with EPA's "Guideline on Air Quality Models" (Appendix W
to 40 CFR Part 51), which provides the appropriate framework for defining the elements
of background concentrations. Section 8.2.1 of Appendix W states that "background
concentrations are an essential part of the total air quality concentration to be considered
in determining source impacts."97 Concentrations are expected to vary throughout a PM
nonattainment or maintenance area, resulting from differences in emission sources,
meteorology, terrain, and other factors. EPA believes that meeting Section 93.123(c)(l)
requirements for PM hot-spot analyses will be different from what has occurred
historically for CO hot-spot analyses, due to the fundamental differences between the
contributors to PM and CO pollution and the projects that are required to have
quantitative PM and CO hot-spot analyses. Additional information is provided in Section
8.3 of this guidance.
97
1 See Sections 4 through 6 for more information on how to estimate project emissions.
Section 8.2.3 recommends for "multi-source areas" that "two components of background should be
determined: contributions from nearby sources and contributions from other sources."
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Evaluating and choosing the models and associated methods and assumptions for nearby
sources and representative background concentrations must be completed through the
process established by each area's interagency consultation procedures (40 CFR
State and local air quality agencies will have the primary expertise on what emission
sources are expected to affect background concentrations, including any nearby sources.
The state or local air agency is likely to have an understanding of the project area and
knowledge about information needed to characterize background concentrations
appropriately, due to experience in developing air quality demonstrations, emission
inventories, and siting air quality monitors for a given NAAQS. The EPA Regional
Office is also a key resource for discussions regarding the air quality monitoring network,
SIP modeling, and other issues.
8.2 NEARBY SOURCES THAT REQUIRE MODELING
Nearby sources are individual sources that contribute PM concentrations to the project
area.9 In general, nearby sources need to be included in air quality modeling only when
those sources would be affected by the project. An example of a project that could affect
nearby sources would be a highway project whose primary purpose is to accommodate
future growth in freight and goods movement; such a project could affect emissions from
related activity at nearby marine ports, rail yards, or intermodal facilities. These types of
nearby sources (that is, those affected by the project) need to be included in air quality
modeling for the PM hot-spot analysis, as described in Section 7, because their emissions
will change between build and no-build scenarios.
EPA anticipates that most PM hot-spot analyses will not involve modeling of nearby
sources that are not affected by the project, such as a stationary source, since these types
of nearby sources would typically be captured in the representative background
concentrations described in Section 8.3.
The following questions can be used by project sponsors, the relevant state or local air
agency, the EPA Regional Office, and other members of the interagency consultation
process to identify any nearby sources that are affected by the project:
• Are there any nearby sources in the project area? If no, then the remainder of
Section 8.2 can be skipped.
• If yes, then:
o Do these sources emit significant levels of emissions that could affect PM
concentrations in the project area?
o Are emissions from any nearby sources expected to differ between the
build and no-build scenarios as a result of the project?
98 Section 8.2.3 of Appendix W describes "nearby sources" more generally as: "All sources expected to
cause a significant concentration gradient in the vicinity of the source or sources under consideration for
emission limit(s) should be explicitly modeled."
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EPA notes that there may be limited cases where nearby sources not affected by the
project would also need to be included in the modeling for a PM hot-spot analysis.
However, such cases would only occur when these sources are not captured in
background concentrations for the project area. See Section 8.3 for further information
on the factors used to determine representative background concentrations for these
cases.
For example, if a stationary source is located upwind of the project area, representative
background concentrations should include concentrations from such a source whenever
possible. As stated above, state and local air quality agencies and the EPA Regional
Office are key resources in understanding how to characterize nearby sources in PM hot-
spot analyses, including those nearby sources not affected by the project.
As discussed in Section 7.3, EPA recommends that AERMOD be used for any PM hot-
spot analyses that involve nearby sources that need to be modeled. The air quality
modeling for nearby sources that would be affected by the project must include any
reasonably expected changes in operation of the nearby source between the build and no-
build scenarios when both scenarios are necessary to demonstrate conformity. Refer to
Section 7 for more information about using AERMOD, placing receptors, and other
information for air quality modeling.
Specific information on emissions from nearby sources should be obtained. The state and
local air agency should be consulted on characterizing nearby sources. In addition,
emission rates and other parameters of nearby sources should be consistent with any
permits approved by the state or local air agency, when applicable. For unpermitted
sources, emission information should be consistent with information used by air agencies
for developing emission inventories for regulatory purposes. Sections 8.1 and 8.2 of
Appendix W describe the information needed to characterize the emissions of nearby
sources for air quality models. For the 24-hour PM2.5 and PMio NAAQS, it is also
important to consider Section 8.2.3 of Appendix W, which states that it is appropriate to
"model nearby sources only during those times when they, by their nature, operate at the
same time as the primary source(s) being modeled." Finally, estimation of nearby source
impacts may take into account the effectiveness of anticipated control measures in the
SIP if they are already enforceable in the SIP.
8.3 OPTIONS FOR BACKGROUND CONCENTRATIONS
PM hot-spot analyses should also include background concentrations from "other
sources" as well as any nearby sources that are not included in modeling." There are
several options provided below that meet the requirements of Section 93.123(c)(l) of the
conformity rule that involve using representative air quality monitoring data. Whatever
option is selected, the same background concentrations would be used at every receptor
99 Section 8.2.3 of Appendix W defines "contributions from other sources" as "that portion of the
background attributable to all other sources (e.g., natural sources, minor sources and distant major
sources)
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used in the build and no-build scenarios for a PM hot-spot analysis. Additional options
for background concentrations can be considered by the EPA Regional Office, OTAQ,
and OAQPS. See Section 1.7 for contact information.
8.3.1 Using ambient monitoring data to estimate background concentrations
Ambient monitoring data for PMio and 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 PMio concentrations that may be appropriate for
estimating background concentrations.100 Project sponsors, relevant state or local air
agencies, and the EPA Regional Office should identify the appropriate PMio and PM2.5
monitoring data, along with information on each monitor's site location, purpose,
geographic scale, nearby land uses, and sampling frequency. EPA offers Air Explorer
(based on Google Earth™ mapping software) as a user-friendly way to identify and
visualize where monitoring sites are in operation and to obtain concentration data and
descriptions of the site (such as the reported scale of spatial representation).101
The evaluation and selection of monitoring data for use in a particular analysis must
follow the process defined in each area's interagency consultation procedures. These
discussions, as well as any maps or statistical techniques used to analyze background
data, should be well-documented and included in the project-level conformity
determination.
Project sponsors should not use monitoring data for which EPA has granted data
exclusion under the Exceptional Events rule (see 40 CFR 50.14).
Using a Single Monitor
Background concentration data should be as representative as possible for the project area
examined by the PM hot-spot analysis.102 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:
100 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.
101 Available online at: www.epa.gov/airexplorer/monitor kml.htm.
102 In particular, there should be interagency consultation prior to using any ambient monitoring data set for
PM2 5 that does not meet EPA requirements in Appendix N to 40 CFR Part 50 regarding data completeness,
and any data set that reflects a sampling schedule that has been erratic or has resulted in more frequent
samples in some seasons of a year than others. The guidance in Section 9 of this document assumes that
the normal data completeness requirement (75% of scheduled samples in each calendar quarter of each
year) has been met and that the monitoring data is evenly distributed across the year. Deviation from these
conditions may make the steps given in Section 9 inappropriate.
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• Similar characteristics between the monitor location and project area: Monitors at
locations that are similar to the project area should be preferred for this factor,
whenever possible. If several monitors are available, preference should be given to
the monitor with the most similar characteristics as the project area. Some questions
to be considered include:
o Is the density and mix of emission sources around the monitor location
similar to those around the project site?
o How well does the monitor capture the influence of nearby sources that
are not affected by the project?
o Are there differences in land use or terrain between the two locations that
could influence air quality in different ways?
o Is the monitor probe located at a similar height as the project (e.g., is the
project at grade, but the monitor is on top of a high building)?
o What is the purpose of the monitor and what geographic scale of
representation does the monitor have?
• Distance of monitor from the project area: Monitors closer to the project may have
concentrations most similar to the project area. If more than one such monitor is
available, preference may be given to the closest representative monitor for this
factor. There are some cases, however, where consideration of distance alone may
mask the influence of other factors that need to also be considered (e.g., a monitor
upwind of the project location may be preferred to an even closer monitor located
downwind of the project).
• Wind patterns between the monitor and the project area: Monitors that are located in
directions that are frequently upwind of a project are more likely to represent a
project area's background concentrations than monitors that are frequently
downwind.103 Preference should be given to upwind monitors for this factor,
whenever appropriate.
The factors considered when selecting a particular monitor to represent background
concentrations should be documented as part of the PM hot-spot analysis.
Interpolating Between Several Monitors
If, during interagency consultation, agencies conclude that no single ambient monitor is
sufficiently representative of the project area, interpolating the data of several monitors
surrounding the project area is also an option. The advantage of interpolation is that no
single monitor is used exclusively in representing air quality for a project area. There
may be projects sited in locations between large emission sources and areas several miles
away with relatively low emissions, suggesting a gradient in concentrations across the
nonattainment or maintenance area. If there are no monitors within or near the project
Constructing a "wind rose" (a graph that depicts the frequency of wind blowing from different
directions) can be a useful tool in examining the frequency of wind blowing from different directions.
EPA's SCRAM website contains two programs for calculating wind statistics and wind roses, WINDROSE
and WRPLOT.
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area, then background concentrations from other sources may be difficult to estimate.
Interpolation is an approach that allows estimates of background concentrations for a
project to take advantage of monitoring data from multiple monitoring sites. Any
planned interpolation methods must be addressed through the interagency consultation
process.
There are several approaches to interpolation that can be used. One simple method is
weighted averaging, which places greater weight on nearby monitors and uses the inverse
distance between the project site and the monitor to weight each monitor. For example,
suppose monitors A, B, and C surround an unmonitored location, at distances 5, 10, and
15 miles from the site, respectively, the weighting of data from monitor A:
Weight(A) = -/[- + — + — 1=0.55
S 5/ (5 10 15 J
The weighting for monitor B:
Weight(B) = — /(- + — + —}= 0.27
10/ ^5 10 15 J
The weighting for monitor C:
Weight(Q = — /( - + — + —| = 0.18
15/ ^5 10 15 J
If concentrations at A, B, and C are 10.0, 20.0, and 30.0 |lg/m3, respectively, then the
predicted concentration at the unmonitored site is 16.3 |lg/m3. In most situations, the
inverse-distance weighted average will provide a reasonable approximation of
background concentrations due to other sources. Another interpolation approach is the
inverse-squared distance weighting that weights monitors based on how close they are to
the project (1/distance squared).
Other, more advanced statistical methods to interpolate monitoring data may also be
used, but these require significant geostatistical expertise.104
104 EPA's MATS (www. epa. gov/ttn/scram/modelingapps mats .hrm) and BenMAP
(www.epa. gov/air/benmap') models incorporate another interpolation-based approach (Voronoi Neighbor
Averaging). Consult those models' documentation for further information.
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8.3.2 Adjusting air quality monitoring data to account for future changes in air quality:
using chemical transport models
Options Using Chemical Transport Models (CTMs)
To account for future emission changes, it may be appropriate in some cases to use future
background concentrations that have been calculated based on modeled outputs from a
CTM. CTMs are photochemistry models that are routinely used in regulatory analyses,
including attainment demonstrations for PM SIPs and EPA regulatory analyses to support
national or regional final rules. 105 In these types of analyses, CTM modeling is
completed for a base and future year, and then these resulting PM concentrations are used
to develop relative response factors (RRFs). These factors are then used to adjust the air
quality monitoring data from the base year of the SIP or EPA final rule modeling. The
end result will be predicted PM concentrations for monitoring locations for a future year
(e.g., the attainment year addressed in the SIP).
Although project sponsors are not expected to operate CTMs, there may be available
information from CTM modeling to support PM hot-spot analyses. There are two CTM-
based options that may be available for PM hot-spot analyses:
1. Use existing pre-calculated future year PM concentrations from EPA or state or
local air quality agency modeling. If available, the future year concentrations at a
monitor used in the SIP or EPA rulemaking can be used for a PM hot-spot
analysis, if the monitor is representative of the project area. Typically, projected
annual average and/or 24-hour average PM design values for a future year will be
available for monitoring site locations that are part of such modeling
demonstrations.
2. In some cases, site-specific, post-processed concentrations may not be readily
available from states or EPA. Depending on the nature of the modeling, it may be
possible to obtain CTM outputs that can be used to derive background
concentrations.106 This may be an option if the standard post-processed data
includes only a subset of monitoring sites in the domain or a subset of averaging
times (e.g., annual average results are available, but not 24-hour average results).
Details on the recommended procedures for projecting PM2.5 concentrations using CTMs
are contained in EPA's "Guidance on the Use of Models and Other Analyses for
Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional
105 Examples of commonly employed CTMs are shown on the SCRAM website at:
www.epa.gov/scram001/photochemicalindex.htm.
106 Many CTM applications are post-processed with EPA's MATS program available at:
www.epa.gov/ttn/scram/modelingapps mats.htm. MATS produces future year annual and quarterly PM2 5
outputs for both the annual and 24-hour PM2 5 NAAQS. The quarterly concentration information may not
be routinely documented.
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Haze."107 The location where CTM modeling is completed, the location of the project,
and determining representative monitors are important considerations in using CTM-
based options for PM hot-spot analyses. Evaluating and choosing the models and
associated methods and assumptions for using CTM-based options must be determined
through interagency consultation (40 CFR 93.105(c)(l)(i)). The EPA Regional Office
should consult with OTAQ and OAQPS in applying the above options or considering
other options.
Additional Information and Considerations about CTMs
EPA's photochemical modeling guidance recommends using CTM outputs in a relative
sense. Therefore the absolute predictions of a CTM in a future analysis year are not used
to predict future background concentrations directly. Instead, appropriate future year
design values or concentrations are derived from monitoring data that have been adjusted
using the modeled relative change in PM concentrations. RRFs are calculated from the
outputs of current (base) year and future year CTM results. These RRFs reflect the
1 OR
relative changes in concentrations between current and future years. An RRF is
generally calculated as:
Concentrations in future year, predicted by CTM
KKr =
Concentrations in base year, predicted by CTM
Future year concentrations are then calculated by multiplying base year monitoring data
by modeled RRFs, as follows:
Base year measured concentration * RRF = Future year concentration
Additionally, when using the CTM-based options, several criteria should be met:
• The CTM has demonstrated acceptable performance for the project area using
standard indicators of model performance.109
• 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).
107 See guidance for further information at: www.epa. gov/scramOO l/guidance/guide/final-03 -pm-rh-
guidance.pdf.
108 Future year concentrations of PM25 are calculated based on PM25 species concentrations that have been
projected using RRFs for individual PM2 5 species.
109 Details on model performance evaluation and examples of model evaluation statistics may be found in
Chapter 18 and Appendix A of the document "Guidance on the Use of Models and Other Analyses for
Demonstrating Attainment of Air Quality Goals for Ozone, PM2 5, and Regional Haze," referenced above.
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• EPA or state modeling which includes future emissions reductions from a
proposed rule or hypothetical emissions reductions that are not associated with
enforceable SIP commitments or state or Federal rules should not be used.
• Any future emission reductions for sources within the CTM modeling
demonstration should take effect prior to the year(s) for which the PM hot-spot
analysis is conducted.
The PM hot-spot analysis year(s) will often be after a year for which CTM modeling is
performed. In this case, the future background concentration for the analysis year should
be the same year for which CTM modeling was performed. It is not technically justified
to extrapolate background concentrations beyond the year in which data are available for
the CTM modeling. For example, if future background concentrations were estimated
based on CTM modeling for the year 2014, and the PM hot-spot analysis year was 2016,
then the 2014 background estimate could be used for 2016. A project sponsor could not
make a further adjustment based on an extrapolation to the year 2016; such an
extrapolation would not be based on credible modeling or mathematical practices.
Similarly, emissions-based "roll-back" and "roll-forward" techniques for adjusting
current air quality monitoring data for future background concentrations are also not
technically supported and would not allow projects sponsors to meet Section 93.123(c)(l)
requirements.
Note that in some cases, CTM adjusted background predictions for a future year may
already incorporate emissions from the project's no-build scenario (e.g., if the monitor
used in the SIP modeling demonstration included emissions from the current project
area). Adding modeled concentrations for the build scenario to this value would be
essentially adding build emissions to the no-build emissions already accounted for in the
background. In these cases, an adjustment may be appropriate only when comparing the
build scenario to the NAAQS. In such cases, to evaluate predicted concentrations in the
build scenario, the difference between modeled concentrations at each receptor in the
build and no-build scenarios should be calculated as:
Differencereceptori = Concentrationreceptoribmldscenano - Concentrationreceptorinobmldscenano
The result - the difference between the build and no-build scenarios at each receptor -
should be added to background concentrations when calculating design values for the
build scenario. Comparing a build scenario to the no-build scenario to demonstrate
conformity will not involve any similar adjustments, since the same background
concentrations are used in the build and no-build scenarios. Using this approach, only the
changes in receptor concentrations affected by emission changes from the project or
modeled nearby sources used in calculating design values. Evaluating and choosing the
models and associated methods and assumptions for using these adjustments must be
determined through interagency consultation (40 CFR 93.105(c)(l)(i)).
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8.3.3 Adjusting air quality monitoring data to account for future changes in air quality:
using an on-road mobile source adjustment factor
There may be limited cases in PMio nonattainment or maintenance areas where it would
be appropriate to adjust representative air quality monitoring data by the factor described
in Section 93.123(c)(2) of the conformity rule. This provision states that".. .the future
background concentration should be estimated by multiplying current background by the
ratio of future to current traffic and the ratio of future to current emission factors." This
method has been a credible option for CO hot-spot analyses. Since CO air quality
problems are primarily due to on-road CO emissions, such a ratio is appropriate for CO
hot-spot analyses.
EPA has determined that this method may also be a credible option when on-road mobile
sources overwhelm overall PMio SIP inventories. Such a case could occur in a limited
number of PMio areas where on-road mobile emissions for directly emitted PMio
represent most of the overall directly emitted PMio emission inventory (e.g., are 75% or
more of the overall inventory).no Such cases include smaller PMio areas where paved
and unpaved road dust are the main source of direct PMio emissions. EPA notes that this
option would increase background concentrations (as compared to options discussed in
Section 8.3.1), in cases where road dust and VMT are expected to increase in the future.
The EPA Regional Office should be consulted on a case-by-case basis if Section
93.123(c)(2) is considered for a PMio hot-spot analysis.
However, EPA has determined that the method described in Section 93.123(c)(2) is not
required by the conformity rule and is not a technically viable option for estimating
background concentrations in all PM2.5 hot-spot analyses and most PMio hot-spot
analyses. PM2.s and PMio nonattainment problems are typically more complex and result
from many different types of emission sources, including emissions from on-road, non-
road, stationary, and area sources. It would not be appropriate to adjust PM air quality
monitoring data from all source types based on an on-road mobile source adjustment
factor only, as has been done in CO hot-spot analyses. While the conformity rule
requires CO hot-spot analyses for only the largest and most congested intersections in a
given area (40 CFR 93.123(a)(2)), PM hot-spot analyses are required for more complex
highway and transit projects that can also involve nearby sources (40 CFR 93.123(b)(l)).
For all of the above reasons, using the same ratios in most PM hot-spot analyses would
not allow project sponsors to meet Section 93.123(c)(l) requirements.
110 Precursor emissions inventories should not be considered in such a determination, since precursor
emissions are not considered in hot-spot analyses.
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Section 9: Calculating PM Design Values and Determining
Conformity
9.1 INTRODUCTION
This section describes how to combine all previous steps of a PM hot-spot analysis into a
design value so that a project sponsor can determine if conformity requirements are met.
For conformity purposes, a design value is a statistic that describes a future air quality
concentration in the project area that can be compared to a particular NAAQS.m In
general, design values are calculated by combining two pieces of data:
• Modeled PM concentrations from the project and nearby sources (Sections 7 and
8); and
• Monitored background PM concentrations from other sources (Section 8).
Exhibit 9-1 illustrates the conceptual flow of information described in this section, which
is similar for all PM NAAQS.
Exhibit 9-1. General Process for Calculating Design Values for PM Hot-spot
Analyses
Data Inputs
(from Sections 7 and 8)
/^ Project and f
nearby source /
\ from air quality \
\ model \^
/ Background /
\ concentrations \
E
)etermining Conformity
(Section 9)
Combine to determine
total concentrations
1
Calculate design value(s)
i
Determine conformity
111 Design values based on monitoring data are used to determine the air quality status of a given
nonattainment or maintenance area (40 CFR Part 50). Design values are also used for SIP modeling and
other air quality planning purposes.
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This section describes how to calculate the specific statistical form of design values for
each PM NAAQS and how to apply design values in build/no-build analyses for
conformity purposes. This section also discusses how to determine which receptors for a
particular project may or may not be appropriate for comparison to the annual PM2.5
NAAQS.
This guidance is consistent with how design values are calculated for designations and
other air quality planning purposes for each PM NAAQS. EPA is considering whether
spreadsheet tools can be developed to assist state and local agencies in calculating design
values for PM hot-spot analyses. This guidance is written for current and future PM2.s
and PMio NAAQS. EPA will re-evaluate the applicability of this guidance as needed, if
different PM NAAQS are promulgated in the future.
The interagency consultation process must be used to determine the models, methods,
and assumptions used for PM hot-spot analyses, including those used in calculating
design values and completing build/no-build analyses (40 CFR 93.105(c)(l)(i)). State
and local air quality agencies and EPA have significant expertise in air quality planning
that may be useful resources for the topics covered by this section. Project sponsors
should document the data and other details used for calculating design values for the
build and no-build scenarios for a project-level conformity determination, as well as how
appropriate receptors were determined.
9.2 USING DESIGN VALUES IN BUILD/NO-BUILD ANALYSES
Design values are a fundamental component of PM hot-spot analyses, as they are the
values compared to the NAAQS and between build and no-build scenarios. In general, a
hot-spot analysis compares air quality concentrations with the proposed project (the build
scenario) to air quality concentrations without the project (the no-build scenario). The
conformity rule requires that the build scenario not cause or contribute to any new
violations of the NAAQS, increase the frequency or severity of existing violations, or
delay timely attainment as compared to the no-build scenario (40 CFR 93.116(a) and
93.123(c)(l)).
Exhibit 9-2 (following page) illustrates the build/no-build analysis approach suggested in
Section 2.4.
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Exhibit 9-2. General Process for Using Design Values in Build/No-build Analyses
Identify the receptor
with the highest
concentration and
calculate its design
value
Is design value
less than or
equal to
NAAQS?
Yes
Calculate build
scenario design values
at all receptors
Calculate no-build
design values at all
receptors that exceeded
NAAQS in build
Are build design
values less than or
equal to no-build
design values?
\N.
/ Are the receptors
/ where the build
exceeds the no-
build appropriate
\ for comparison to
\ the NAAQS?*
* Annual PM:, NAAQS only
** Mitigation and control measures can be
considered at any point in the process
In general, project sponsors could begin by determining the design value for only one
receptor in the build scenario: the receptor with the highest modeled air quality
concentration, as described in Section 9.3. If the design value for this receptor is less
than or equal to the relevant NAAQS, it can be assumed that conformity requirements are
met at all receptors in the project area, without further analysis. If this is not the case, the
project sponsor could choose to add mitigation or control measures and then determine if
the new build scenario concentrations at the receptor with the highest modeled
concentrations is less than or equal to the relevant NAAQS. If this is not the case, the
project sponsor would calculate the design values at all receptors in the build scenario
and also model the no-build scenario. Design values should then be calculated for the no-
build scenario at all receptors with design values that exceeded the NAAQS in the build
scenario. Conformity requirements are met if the design value for every appropriate
receptor in the build scenario is less than or equal to the same receptor in the no-build
scenario.112 If not, then the project does not meet conformity requirements without
This would be the receptor at the same geographic location in the build and no-build scenarios.
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further mitigation or control measures to address air quality concentrations at such
receptors, except in certain cases described below.113
A build/no-build analysis is typically based on design value comparisons done on a
receptor-by-receptor basis. However, there may also be cases where a possible "new"
violation at one receptor (in the build scenario) is relocated from a different receptor (in
the no-build scenario). It would be necessary to calculate the design values for all
receptors in the build and no-build scenarios to determine whether a "new" violation is
actually a relocated violation. EPA addressed this issue in the preamble to the
November 24, 1993 transportation conformity rule (58 FR 62213), where a "new"
violation within the same intersection could be considered a relocated violation. Since
1993, EPA has made this interpretation only in limited cases with CO hot-spot analyses
where there is a clear relationship between such changes (e.g., a reduced CO NAAQS
violation is relocated from one corner of an intersection to another due to traffic-related
changes from an expanded intersection). Any potential relocated violations in PM hot-
spot analyses should be determined through the process established by each area's
interagency consultation procedures.
When completing air quality modeling for build and no-build scenarios, receptors should
be placed in identical locations so that direct comparisons can be made between design
values calculated at receptors under each scenario. Also, design values are compared to
the relevant NAAQS and between build and no-build scenarios after rounding has been
done, which occurs in the final steps of design value calculations.114 Further details on
rounding conventions for different PM NAAQS are included in Section 9.3 below.
Determining whether receptors are appropriate for the annual PM2.5 NAAQS would be
done after air quality modeling is completed and design values are calculated, as
described further in Section 9.4.
113 Additional mitigation or control measures can be considered at any point in the hot-spot analysis
process. When such measures are considered, additional emissions and air quality modeling would need to
be completed and new design values calculated to ensure that conformity requirements are met.
114 For example, conformity requirements would be met at a receptor if the final build design value is no
greater than the final no-build design value, even if the pre-rounding build design value is greater than the
pre-rounding no-build design value.
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9.3 CALCULATING DESIGN VALUES AND DETERMINING CONFORMITY FOR
PM HOT-SPOT ANALYSES
9.3.1 General
As noted above, this conformity guidance is generally consistent with how design values
are calculated for air quality monitoring and other EPA regulatory programs.115
Further details are included below about how design values should be calculated at
receptors for build/no-build analyses, and examples of each design value calculation can
be found in Appendix K of this guidance. These details and examples are primarily
narrative in nature. EPA has also provided mathematical formulas of design values in
Appendix K, which may be helpful for certain users.
9.3.2 Annual PM2.5NAAQS
Design Value
The annual PM2.5 design value is currently defined as the average of three consecutive
years' annual averages, each estimated using equally-weighted quarterly averages.116
This NAAQS is met when the three-year average concentration is less than or equal to
the annual PM2.5NAAQS (currently 15.0 |lg/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
[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 |lg/m3. For example,
15.049 rounds to 15.0, and 15.050 rounds to 15.1.117 These rounding conventions should
be followed when calculating design values for this NAAQS.
115 EPA notes that design value calculations forPM 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.
116 The design value for the annual PM2 5 NAAQS is defined for air quality monitoring purposes in 40 CFR
Part 50.13.
117 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.
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Necessary Data
This design value calculation assumes the project sponsor already has the following data
in hand:
• Air quality modeling results: Average annual concentrations from the project and
any nearby sources should be calculated from the air quality model output files.118
The methodology for post-processing the air quality model output files will vary
depending on what air quality model is used. Refer to Appendix J for details on
preparing air quality model outputs for use in design value calculations.
• Air quality monitoring data: 12 quarters of background concentration
measurements (four quarters for each of three consecutive years). See Section 8
for more details on determining representative monitored background
concentrations that meet all applicable monitoring requirements (such as data
completeness).119
Calculating Design Values and Determining Conformity
Exhibit 9-3 (following page) illustrates how a design value is to be calculated and
conformity determined for the annual PM2.5 NAAQS. This exhibit assumes that the
project sponsor would first compare the receptor with the highest average annual
concentration in the build scenario to the NAAQS to determine conformity. If
conformity is not met at this receptor, design values would be calculated at all receptors
in the build scenario. For any receptors with design values above the NAAQS in the
build scenario, the project sponsor would then model the no-build scenario and calculate
design values to determine if conformity requirements are met.
An example of how to calculate design values for the annual PM2.5 NAAQS using this
procedure is included in Appendix K. The steps below can also be described
mathematically using the formulas found in Equation Set 1 in Appendix K.
The steps shown in Exhibit 9-3 are described below. The initial step is to compare the
build scenario to the NAAQS to see if the project conforms:
• Step 1. For each receptor, calculate the average annual concentrations with the air
quality modeling results for each quarter and year of meteorological data used. If
using AERMOD, the model does this step for you and provides the average
annual concentrations as output; proceed to Step 2. If using CAL3QHCR, for
each year of meteorological data, first determine the average concentration in
each quarter. Then, within each year of meteorological data, add the average
concentrations of all four quarters and divide by four to calculate the average
annual modeled concentration for each year of meteorological data. Sum the
modeled average annual concentrations from each year of meteorological data,
and divide by the number of years of meteorological data used.
118 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.
119 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
110
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• Step 2. Identify the receptor with the highest modeled average annual
concentration.
• Step 3. For each year of background data, first determine the average monitored
concentration in each quarter. Then, within each year of background data, add the
average concentrations of all four quarters and divide by four to calculate the
average annual background concentration for each year of monitoring data. Next,
add the average annual concentrations from each of the consecutive years of
monitoring data and divide by three. This value is the average annual background
concentration based on monitoring data. 12°
Exhibit 9-3. Determining Conformity to the Annual PM2.5 NAAQS
Build Scenario <= NAAQS
1. Calculate average
annual modeled
concentration at all
receptors (if using
AERMOD: skip to
Step 2)
2. Identify receptor
with the highest
average annual
concentration
3. Calculate average
annual background
concentration
4. Add values from
Steps 2 and 3
5. Round to nearest 0.1
iig/m3
Is design value
less than or
equal to
NAAQS?
Build Scenario <= No-build Scenario
6. Repeat Step 1 for all
receptors
7 . Add values from
Steps 6 and 3
8. Round to nearest 0.1
ug'm- and identify all
receptors that exceed
NAAQS
9 . Calculate annual
averages for the no-
build scenario
10. Add values from
Steps 9 and 3
i
1 1 . Round to nearest
0.1 ug/m3
* May need to also determine appropriateness of receptors
** Mitigation and control measures can be considered at
any point in the process
120 Each year, EPA calculates quarterly average and annual average concentrations for all PM2 5 monitoring
sites reporting data to EPA's Air Quality System. The results are posted at:
www.epa.gov/airtrends/values.html. Results are in Excel spreadsheet form, in a worksheet with "site
listing" in the worksheet name.
Ill
-------
• Step 4. Add the average annual background concentration (from Step 3) to the
average annual modeled concentration at the highest receptor (from Step 2) to
determine the total average annual background concentration at this receptor.
• Step 5. Round to the nearest 0.1 |lg/m3. This result is the annual PM2.5 design
value at the highest receptor in the build scenario.
The project sponsor should then compare the design value from Step 5 to the annual
PM2.5 NAAQS (currently 15.0 |lg/m3). If the value is less than or equal to the NAAQS,
the project conforms. If the design value is greater than the NAAQS, the project sponsor
should then continue to Step 6:
• Step 6. Repeat the calculations described in Step 1 to determine average annual
concentrations for all receptors in the build scenario.
• Step 7. Add the average annual modeled concentrations (from Step 6) to the
average annual background concentrations (from Step 3).121 The result will be
the total average annual concentration at each receptor in the build scenario.
• Step 8. Round to the nearest 0.1 |ig/m3. At each receptor, this value is the annual
PM2.5 design value for the build scenario. Identify all receptors that exceed the
annual PM2.5 NAAQS.
• Step 9. From the no-build air quality modeling results, calculate the average
annual concentrations at each receptor identified in Step 8.
• Step 10. For the no-build scenario, add the average annual modeled
concentrations for the no-build scenario (from Step 9) to the average annual
background concentrations (from Step 3). The result will be the total average
annual concentration for each receptor identified in Step 8 under the no-build
scenario.
• Step 11. Round to the nearest 0.1 |lg/m3. This result is the annual PM2.5 design
value for each receptor identified in Step 8 under the no-build scenario.
For each receptor with a design value that exceeded the NAAQS in the build scenario,
compare the build design value (Step 8) to the no-build design value (Step 11). For the
project to conform, the build design value must be less than or equal to the no-build
design value at each receptor in the build scenario that exceeded the NAAQS (Step 8). If
this is not the case, it may be necessary to determine if any receptors are not appropriate
for conformity purposes (see Section 9.4).122
If a build scenario design value is greater than the no-build design value at any
appropriate receptor, the sponsor should then consider additional mitigation and control
measures, and revise the PM hot-spot analysis accordingly. Mitigation and control
121 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.
122 Project sponsors could decide to determine appropriate receptors for this NAAQS at Step 8, for any
receptors where a NAAQS violation is predicted to occur. Also, in certain cases, project sponsors can also
decide to calculate the design values for all receptors in the build and no-build scenarios and use the
interagency consultation process to determine whether a "new" violation has been relocated (see Section
9.2).
112
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measures could also be considered at any other point in the analysis before the project-
level conformity determination is made. Refer to Section 10 for a discussion of potential
measures.
9.3.3 24-hour PM2.5NAAQS
Design Value
The 24-hour PM2.5 design value is currently defined as the average of three consecutive
years' 98* percentile concentrations of 24-hour values for each of those years.123 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 |lg/m3 for nonattainment areas for the 2006 PM2.5 NAAQS and 65 |lg/m3 for
nonattainment areas for the 1997 PM2.5 NAAQS).m
The design value for comparison to any 24-hour PM2.5 NAAQS is rounded to the nearest
1 |ig/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
O I r\c
rounds to 35 |lg/m , while 35.500 rounds to 36. 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 value.126 Project sponsors can start with either the first or second
tier analysis, since either tier is a viable approach for meeting conformity requirements.
There may be cases where a project sponsor may decide to start with a first tier analysis,
which is a conservative but less intensive approach.127 In other cases, project sponsors
may decide to go directly to a second tier analysis. For example, depending on how the
air quality model was run and its data post-processed, the actions needed to identify the
highest modeled 24-hour concentration by quarter for a second tier analysis may not
involve much additional time or effort, in which case the second tier approach may be
123 The design value for the 24-hour PM2 5 NAAQS is defined for air quality monitoring purposes in 40
CFR Part 50.13.
124 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.
125 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.
126 This approach is consistent with EPA's approach for calculating design values for other EPA regulatory
programs. See the EPA March 23, 2010 memorandum from Stephen D. Page at
www.epa.gov/scram001/Official%20Signed%20Modeling%20Proc%20for%20Demo%20Compli%20w%2
OPM2.5.pdf.
127 While less data intensive and therefore possibly quicker to execute, the first tier approach is considered
more conservative as compared to the second tier analysis. The first tier approach assumes that the
estimated highest predicted concentration attributable to the project and nearby sources will occur in the
future on each of the days from which the three-year average 98th percentile background concentration is
derived (which may not occur).
113
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preferred from that start. Under either tier, the contributions from the project, any nearby
sources, and background concentrations from other sources are combined for a given
analysis year, as described further below.
Examples of how to calculate design values for the 24-hour PM2.5 NAAQS using each
tier are included in Appendix K.
Necessary Data
This design value calculation assumes the project sponsor already has the following data
in hand:
• Air quality modeling results: The highest 24-hour average concentration from the
project and any nearby sources should be calculated based on the air quality
model output files, depending on what tier of analysis is used:
o In a first tier analysis, the highest 24-hour values from each year of
meteorological data should be averaged together.
o In a second tier analysis, the highest 24-hour values from each quarter and
year of meteorological data should be averaged together per quarter.
Post-processing the air quality model output files will vary depending on what air
quality model is used in the hot-spot analysis. Refer to Appendix J for a
discussion of air quality model output file formats.
• Air quality monitoring data: 12 quarters of background concentration
measurements (four quarters for each of three consecutive years). See Section 8
for more details on determining representative monitored background
concentrations that meet all applicable monitoring requirements (such as data
completeness).128
Calculating Design Values and Determining Conformity Using a First Tier Analysis
The first tier consists of directly adding the highest average modeled 24-hour
concentrations to the average 98* percentile 24-hour background concentrations.
Exhibit 9-4 (following page) illustrates how a design value would be calculated under a
first tier analysis for a given receptor. The steps shown in Exhibit 9-4 are described in
detail below, and are also described mathematically using the formulas found in Equation
Set 2 in Appendix K.
128 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
114
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Exhibit 9-4. Determining Conformity to the 24-hour
Analysis
.s NAAQS Using First Tier
1. From build scenario
modeling results,
identify the receptor
with the highest
average 24-hour
concentration
Project conforms
2. Determine the 3-
year average of the
98th percentile 24-hour
background
concentrations
3. Add results of Steps
1 and 2 to obtain
design value
Yes
Is design value
less than or equal
to NAAQS?
Conduct no-build
analysis and/or
second tier
analysis
The initial step in a first tier analysis is to compare the build scenario to the NAAQS to
see if the project conforms:
• Step 1. From the air quality modeling results from the build scenario, identify the
receptor with the highest average 24-hour concentration. This is done by first
separating the air quality model output into each year of meteorological data.
Second, for each receptor and year of meteorological data, identify the 24-hour
period (midnight-to-midnight) with the highest average concentration throughout
the entire year. Finally, at each receptor, average the highest 24-hour
concentrations from each year of meteorological data across all years. The
receptor with the highest value is used to calculate the 24-hour PM2.5 design
value.
• Step 2. Calculate the average 98* percentile 24-hour background concentration
using the 98th percentile 24-hour concentrations of the three most recent years of
air quality monitoring data. To calculate the 98th percentile background
concentrations for each year of monitoring data, first count the number of 24-hour
background measurements in each year. Next, order the highest eight monitoring
values in each year from highest to lowest and rank each value from 1 (highest) to
8 (eighth highest). Consult Exhibit 9-5 (following page) to determine which of
these eight values is the 98* percentile value. Using the results from the three
115
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years of monitoring data, calculate the three-year average of the 98* percentile
129
concentrations.
Step 3. Add the highest average 24-hour modeled concentration (Step 1) to the
average 98* percentile 24-hour background concentration (Step 2) and round to
the nearest 1 |ig/m3. The result is the 24-hour PM2.5 design value at the highest
receptor in the build scenario.
Exhibit 9-5. Ranking of 98 Percentile Background Concentration Values
130
Number of
Background
Concentration
Values
1-50
51-100
101-150
151-200
201-250
251-300
301-350
351-366
Rank of Value
Corresponding to
98th Percentile
Concentration
1
2
3
4
5
6
7
8
If the design value calculated in Step 3 is less than or equal to the relevant 24-hour PM2.5
NAAQS, then the project conforms. If it is greater than the 24-hour PM2.5 NAAQS,
conformity is not met, and the project sponsor has two options:
• Repeat the first tier analysis for the no-build scenario at all receptors that
exceeded the NAAQS in the build scenario. If the calculated design value for the
build scenario is less than or equal to the design value for the no-build scenario at
all of these receptors, then the project conforms;131 or
• Conduct a second tier analysis as described below.
129 Assuming a regular monitoring schedule and a resulting data set that meets the completeness
requirements of 40 CFR Part 50 Appendix N, the result of Step 2 will be the design value for the
monitoring site used to estimate the background concentrations. Each year, EPA calculates the 98th
percentile concentration for each of the most recent three years and the average of the three current annual
values for every PM2 5 monitor, based on the data reported to EPA's Air Quality System. Project sponsors
may use the EPA-calculated design values directly instead of executing Step 2, or may compare their result
from Step 2 to the EPA-calculated design value. These design values appear in the worksheet "Site
Listing" of the latest PM25 design value spreadsheet posted at: www.epa.gov/airtrends/values.html.
130 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.
131 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).
116
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Calculating Design Values and Determining Conformity Using a Second Tier Analysis
The second tier involves a greater degree of analysis, in that the highest modeled
concentrations and the 98 percentile background concentrations are not added together
for each receptor directly, as in a first tier analysis. Unlike a first tier analysis, which
uses the average of the highest modeled 24-hour concentration from each year of
meteorological data, a second tier analysis uses the average of the highest modeled 24-
hour concentration within each quarter of each year of meteorological data. In other
words, impacts from the project, nearby sources, and other background concentrations are
calculated on a quarterly basis before determining the 98th percentile concentration
resulting from these inputs.
Exhibit 9-6 (following page) and the following steps provide details for calculating a
design value for the 24-hour PM2.5 NAAQS under a second tier analysis. These steps can
also be described mathematically using the formulas found in Equation Set 3 in Appendix
K.
A project sponsor would initially complete these steps for the build scenario; then, if
necessary, repeat the steps for the no-build scenario. Steps 1 and 2 of a second tier
analysis are completed only once for all receptors, since the same background
concentrations would be used for every receptor in either the build or no-build scenario.
• Step 1. Count the number of measurements for each year of monitoring data used
for background concentrations for other sources.
• Step 2. For each year of monitoring data used, determine the eight highest 24-
hour background concentrations for each quarter modeled. For most hot-spot
analyses for the 24-hour PlV^.s NAAQS, modeling would be completed for all
four quarters of each analysis year. This would therefore result in 32 values
(eight concentrations for four quarters) for each year of monitoring data. 132' 133
The remaining steps are completed for calculating the 24-hour PIVb.s design value at each
receptor:
• Step 3. At each receptor, identify the highest modeled 24-hour concentration in
each quarter, averaged across each year of meteorological data used for air quality
modeling.
• Step 4. At each receptor, add the highest modeled concentration in each quarter
(from Step 3) to each of the eight highest 24-hour background concentrations for
the same quarter for each year of monitoring data (from Step 2). At each
receptor, this step will result in eight 24-hour concentrations in each of four
quarters for a total of 32 values for each year of monitoring data.
132 Section 3.3.4 describes how the number of quarters modeled should be determined. In most PM hot-
spot analyses for the 24-hour PM25 NAAQS, all four quarters of the analysis year will be modeled. There
are limited cases where modeling only one quarter would be appropriate.
133
24-hour PM25 concentrations for any monitoring site reported to EPA's Air Quality System can be
obtained by using the data download tools available at: www.epa.gov/airexplorer/monitor kml.htm.
117
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Exhibit 9-6. Determining Conformity to the 24-hour
Tier Analysis
NAAQS Using Second
Build Scenario <= NAAQS
1. Count the number of
measurements for each
year of background
data
2. Determine the 8
highest 24-hour
background values for
each quarter
3. For each receptor in
each quarter, identify
the highest
concentration
4. At each receptor.
add values from Steps
2 and 3 for each
quarter
5. Rank values in Step
4 from highest to
lowest for each year of
monitoring data
6. Determine the value
in Step 5
corresponding to the
98*percentile
I
7.Repeat Step 6 for
each year of
background data
. Average the three
QS^percentile
concentrations
9. Round to nearest
1 ng/m3
Are all design
values less than
or equal to
NAAQS?
\No
Yes
Project
conforms
Build Scenario <= No-build
Scenario
10. Repeat Steps 3
through 9 using no-
build modeling results
Yes
Are build design
values less than
or equal to no-
build design
values'?
No
Project does not
conform
Consider
measures to
reduce emissions
and redo
analysis*
* Mitigation and control measures can be
considered at any point in the process
118
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Step 5. For each receptor and year of monitoring data, order the 32 values from
Step 4 from highest to lowest and rank each value from 1 (highest concentration)
to 32 (lowest concentration).
Step 6. Based on the number of background concentration values you have (from
Step 1), use Exhibit 9-7 to determine which value in the column (from Step 5)
represents the 98th percentile concentration for each receptor. For example, if you
have 180 background concentration values in a year, Exhibit 9-7 shows that the
4* highest value would represent the 98* percentile. Take the value at each
receptor that has this rank.
Exhibit 9-7. Ranking of 98 Percentile Background Concentration Values
134
Number of
Background
Concentration
Values
1-50
51-100
101-150
151-200
201-250
251-300
301-350
351-366
Rank of Value
Corresponding to
98th Percentile
Concentration
1
2
O
4
5
6
7
8
• Step 7. Repeat Step 6 for each of the three years of background monitoring data.
The result will be three 24-hour 98* percentile concentrations at each receptor,
one for each year of monitoring data.
• Step 8. At each receptor, calculate the average of the three 24-hour 98th percentile
concentrations determined in Step 7.
• Step 9. Round the average concentrations from Step 8 to the nearest 1 |ig/m3. At
each receptor, this value is the 24-hour PM2.5 design value for the build scenario.
Compare the design values to the relevant 24-hour PM2.5 NAAQS. If the design values at
all receptors are less than or equal to the NAAQS, then the project conforms. If this is
not the case, proceed to Step 10:
• Step 10. Using modeling results for the no-build scenario, repeat Steps 3 through
9 for all receptors with a design value that exceeded the PM2.5 NAAQS in the
build scenario. The result will be a 24-hour PM2.5 design value at such receptors
for the no-build scenario.
134 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 number of air quality monitoring measurements.
119
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Compare the build design values (from Step 9) to the no-build design values (from Step
10), identifying which value is higher at each receptor. For the project to conform, the
build design values must be less than or equal to the no-build design value for all of the
receptors that exceeded the NAAQS in the build scenario.135
If the build scenario design value is greater than the no-build design value at any
appropriate receptor, the project sponsor should then consider additional mitigation and
control measures, and revise the PM hot-spot analysis accordingly. Mitigation and
control measures could also be considered at any other point in the analysis before the
project-level conformity determination is made. Refer to Section 10 for a discussion of
potential measures.
9.3.4 24-hour PM10 NAAQS
Design Value
Compliance with the 24-hour PMio NAAQS is based on the expected number of 24-hour
exceedances of a particular level (currently 150 |ig/m3), averaged over three consecutive
years.136 Currently, the NAAQS is met when the expected number of exceedances is less
than or equal to 1.0.13?
The 24-hour PMio NAAQS design value is rounded to the nearest 10 |lg/m3. For
example, 155.511 rounds to 160, and 154.999 rounds to 150.138 These rounding
conventions should be followed when calculating design values for this NAAQS.
The contributions from the project, any nearby sources, and background concentrations
from other sources are combined for a given analysis year, as described further below.
Examples of how to calculate design values for the 24-hour PMio NAAQS are included in
Appendix K.
135 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).
136 The 24-hour PM10 NAAQS and supporting technical documentation can be found in 40 CFR Part 50.6.
137 The term "expected" means that the actual number of observed exceedances is adjusted upwards when
observations are missing for some days, to reflect the air quality statistically expected for those days. The
design value for the 24-hour PM10 NAAQS is the next highest observed (monitored or modeled)
concentration after the concentrations that could be above 150 ug/m3 without causing the expected number
of exceedances to be greater than 1.0.
138 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.
120
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Necessary Data
This design value calculation assumes the project sponsor already has the following data
in hand:
• Air quality modeling results: In most PM hot-spot analyses, five years of
meteorological data will be used to complete air quality modeling for the project
and any nearby sources.139 In this case, the sixth-highest 24-hour modeled
concentration should be calculated for each receptor. 14° Note that AERMOD can
be configured to give you these values directly. CAL3QHCR output needs to be
post-processed to obtain the sixth-highest value from five years of meteorological
data. See more details below and refer to Appendix J for a discussion of air
quality model output file formats.
• Air quality monitoring data: 12 quarters of background concentration
measurements (four quarters for each of three consecutive years). See Section 8
for more details on determining representative monitored background
concentrations that meet all applicable monitoring requirements (such as data
completeness).141
Calculating Design Values and Determining Conformity
The 24-hour PMio design value is calculated at each receptor by directly adding the sixth-
highest modeled 24-hour concentrations (if using five years of meteorological data) to the
highest 24-hour background concentration (from three years of monitoring data).
Exhibit 9-8 (following page) illustrates how a design value would be calculated. The
steps shown in Exhibit 9-8 are described in detail below and are also described
mathematically using the formulas found in Equation Set 4 in Appendix K.
The initial step is to compare the build scenario to the NAAQS to see if the project
conforms:
• Step 1. From the air quality modeling results for the build scenario, identify the
sixth-highest 24-hour concentration for each receptor (across five years of
meteorological data, in most cases). When using AERMOD, the model can be
configured to produce these values.142 When using CAL3QHCR, output needs to
be post-processed to obtain the sixth-highest values from five years of
meteorological data.
• Step 2. Identify the receptor with the highest sixth-highest 24-hour concentration.
That is, compare the sixth-highest modeled concentrations (i.e., the concentrations
139 Section 7.5.3 of this guidance provides further information on the number of years of meteorological
data used in air quality modeling.
140 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 PM\ 0 concentration. If using less than one year of meteorological
data (such as one quarter), users should select the highest 24-hour concentration.
141 The interagency consultation process should be used when situations require incorporation of any CTM
results into design value calculations.
142
For example, users could employ the RECTABLE keyword in the AERMOD output pathway. See
Appendix J to this guidance for further information.
121
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at Rank 6) across receptors and identify the receptor with the highest value at
Rank 6.
Step 3. Identify the highest 24-hour background concentration from the three
most recent years of air quality monitoring data.143
Step 4. For the receptor identified in Step 2, add the sixth-highest 24-hour
modeled concentration to the highest 24-hour background concentration (from
Step 3).
Step 5. Round to the nearest 10 |lg/m3. The result is the highest 24-hour
design value in the build scenario.
Exhibit 9-8. 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 highest
24 -hour background
concentration
4. Add values from
Steps 2 and 3
5. Round to nearest 10
Hg/m3
Is design value
less than or
equal to
NAAQS?
No
Build Scenario <= No-build Scenario
6. Add values from
Step 1 and Step 3 at
each receptor
7. Round to nearest 10
Lig<'m3 and identify all
receptors that exceed
NAAQS
8. From no-build
modeling results.
identify sixth-highest
concentration for each
receptor identified in
Step?
9. Add values from
Steps 8 and 3
10. Round to nearest
10 Lig/m3
* Mitigation and control measures can be
considered at any point in the process
24-hour PM10 concentrations for any monitoring site reported to EPA's Air Quality System can be
obtained by using the data download tools available at: www.epa.gov/airexplorer/monitor kml.htm.
122
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The project sponsor should then compare the design value from Step 5 to the 24-hour
PMioNAAQS (currently 150 |lg/m3). If the design value calculated in Step 5 is less than
or equal to the NAAQS, the project conforms. If the design value is greater than the
NAAQS, the project sponsor should then continue to Step 6:
• Step 6. For each receptor in the build scenario, add the sixth-highest 24-hour
modeled concentration (from Step 1) to the highest 24-hour background
concentration from the three most recent years of air quality monitoring data
(from Step 3).
• Step 7. Round to the nearest 10 |ig/m3. At each receptor, this value is the 24-
hour PMio design value for the build scenario. Identify all receptors that exceed
the 24-hour PMio NAAQS.
• Step 8. From the no-build air quality modeling results, identify the sixth-highest
24-hour concentration for each receptor identified in Step 7.
• Step 9. Add the sixth-highest 24-hour modeled concentration in the no-build
scenario (from Step 8) to the highest 24-hour background concentration from the
three most recent years of air quality monitoring data (from Step 3).
• Step 10. Round to the nearest 10 |lg/m3. The result is the 24-hour PMio design
value under the no-build scenario for each receptor identified in Step 7.
For each receptor with a design value that exceeded the NAAQS in the build scenario,
compare the build design value (from Step 7) to the no-build design value (from Step 10).
For the project to conform, the build design value must be less than or equal to the no-
build design value at each receptor in the build scenario that exceeded the NAAQS (Step
?)144
If the build scenario design value is greater than the no-build design value at any
appropriate receptor, the project sponsor should then consider additional mitigation and
control measures, and revise the PM hot-spot analysis accordingly. Mitigation and
control measures could also be considered at any other point in the analysis before the
project-level conformity determination is made. Refer to Section 10 for a discussion of
potential measures.
More advanced methods of calculating a PMio design value, such as combining modeled
and monitored concentrations on a quarterly basis, may be considered on a case-by-case
basis by the EPA Regional Office, OTAQ, and OAQPS. Any alternative methods for
calculating PMio design values must be evaluated and chosen through the process
established by each area's interagency consultation procedures (40 CFR 93.105(c)(l)(i)).
144 In certain cases, project sponsors can also decide to calculate the design values for all receptors in the
build and no-build scenarios and use the interagency consultation process to determine whether a "new"
violation has been relocated (see Section 9.2).
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9.4 DETERMINING APPROPRIATE RECEPTORS FOR COMPARISON TO THE
ANNUAL PM2.5 NAAQS
9.4.1 General
When hot-spot analyses are done for the annual PM2.s NAAQS, there is an additional step
that may be necessary to determine whether a receptor is appropriate to compare to this
NAAQS. In the March 2006 final rule, EPA stated:
"Quantitative hot-spot analyses for conformity purposes would consider how
projects of air quality concern are predicted to impact air quality at existing and
potential PM2.5 monitor locations which are appropriate to allow the comparison
of predicted PM2.5 concentrations to the current PM2.5 standards, based on PM2.5
monitor siting requirements (40 CFR Part 58)." (71 FR 12471)
EPA included this language in the preamble to the March 2006 final rule so that PM2.5
hot-spot analyses would be consistent with how the PM2.5 NAAQS are developed,
monitored, and implemented. Receptors cannot be used for PM2.s hot-spot analyses if
they are at locations that would not be appropriate for air quality monitoring purposes for
the NAAQS. 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.
An "appropriate receptor location" under Section 93.123(c)(l) of the conformity rule is a
location that is suitable for comparison to the relevant NAAQS, consistent with how the
PM NAAQS are established and monitored for air quality planning purposes.145
9.4.2 Factors for determining appropriate receptors for comparison to the annual
PM2.5 NAAQS
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.s NAAQS (and the 24-hour PMio NAAQS) can be determined prior to air quality
modeling. However, for the annual PM2.5 NAAQS, appropriate receptors should be
determined after air quality modeling is completed, in order to be consistent with the
PM2.5 monitoring regulations.146 The paragraphs below provide additional guidance
145 See CAA Section 176(c)(l)(B). EPA interprets "NAAQS" in this provision to mean the specific
NAAQS that has been established through rulemaking and monitored for designations purposes.
146 As stated above, PM hot-spot analysis must be based on receptors that are appropriate for comparison to
the annual PM2 5 NAAQS and consistent with the monitoring regulations for this NAAQS. EPA's
monitoring regulations allow for micro and middle scale sites to be compared to the annual PM2 5 NAAQS
"where certain population-oriented micro scale or middle scale PM2 5 monitoring sites are determined by
the Regional Administrator to collectively identify a larger region of localized high ambient PM2 5
concentrations" (40 CFR 58.30(a)). 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 and whether a significant number of similar receptors with high
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when calculating design values and determining conformity for the annual PM2.5
NAAQS, through the steps described in Section 9.3.2.
There are generally two factors in the PM2.5 monitoring regulations that need to be
considered in determining the appropriateness of receptors for use in PM2.5 hot-spot
analyses:
• Population-orientation: A receptor must be "population-oriented" in order to be
appropriate for comparison to either the 24-hour or annual PM2.5 NAAQS.14?
This factor can be addressed when placing receptors prior to air quality modeling
(see Section 7.6).
• Community-wide air quality: A receptor for the annual PM2.5 NAAQS must also
represent "community-wide air quality"; this factor does not have to be satisfied
for the 24-hour PM2.5 NAAQS.
Section 9.3.2 includes an approach for conducting build/no-build analyses for the annual
PM2.5 NAAQS, in which the appropriateness of receptors is determined only in cases
where a design value in the build scenario is higher than the NAAQS and the design
value in the no-build scenario. As noted above, if conformity requirements are met at all
receptors, it is unnecessary to determine whether receptors are not appropriate for
comparison to the annual PM2.5 NAAQS; in such a case, project sponsors can conclude
that conformity requirements are met at all appropriate receptors.
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 that may be useful resources in
determining appropriate receptor locations for the annual PM2.5 NAAQS. For example,
under the PM2.5 monitoring regulations, the EPA Regional Offices determine whether
micro or middle scale PIVb.s air quality monitors are eligible for comparison to the annual
PM2.5 NAAQS, as discussed further below.
9.4.3 Overview ofPM2.5 monitoring regulations
The annual PM2.5 NAAQS was established to capture air quality concentrations over
larger areas that represent "community-wide air quality."148 Therefore, an appropriate
receptor for hot-spot analyses for this NAAQS must also represent community-wide air
quality. There are several parts of the PM2.5 monitoring regulations that describe how an
existing or potential monitor location can represent community-wide air quality, and EPA
will rely on this same information for determining appropriate receptor locations for
concentrations represent a large portion of the project area. Such an assessment cannot be done
qualitatively prior to air quality modeling.
147 See 40 CFR 58.1.
148 The 1997 annual PM2 5 NAAQS was primarily based on health studies using neighborhood and larger
scale air quality monitoring data (62 FR 38651-38760).
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conformity purposes. Like ambient PM2.5 monitoring sites, not every receptor may be
appropriate for comparing a predicted design value with the annual PM2.5 NAAQS.
Air quality monitors that represent community-wide air quality and are compared to the
annual PM2.5 NAAQS typically are of neighborhood and larger scales, as defined by the
PM2.5 monitoring regulations. Section 4.7. l(b) of Appendix D to 40 CFR Part 58 states:
"The required monitoring stations or sites must be sited to represent community-
wide air quality... .These monitoring stations will typically be at neighborhood or
urban scale."
Therefore, conformity requirements must be met at any receptor that is at a location that
would also be appropriate for an existing or potential neighborhood or larger scale air
quality monitor for the annual PM2.5 NAAQS. In general, population-oriented receptors
that are farther away from the project would be similar to potential neighborhood or
larger scale monitoring sites and would be representative of community-wide air quality
in all PM hot-spot analyses.
The PM2.5 monitoring regulations also address when smaller scale locations are
considered to represent community-wide air quality and can be compared to the annual
PM2.5 NAAQS. Section 58.30(a) of the regulations states:
"(1) PM2.5 data that are representative, not of areawide but rather, of relatively
unique population-oriented microscale, or localized hot-spot, or unique
population-oriented middle-scale impact sites are only eligible for comparison to
the 24-hour PM2.5 NAAQS; and
(2) There are cases where certain population-oriented microscale or middle scale
PM2.5 monitoring sites are determined by the Regional Administrator to
collectively identify a larger region of localized high ambient PM2.5
concentrations. In those cases, data from these population-oriented sites would be
eligible for comparison to the annual PM2.5 NAAQS."149
Other parts of the PM2.5 monitoring regulations also address middle and microscale
locations. Section 4.7. l(b) of Appendix D to 40 CFR Part 58 states:
"... in certain instances where population-oriented micro or middle scale PM2.5
monitoring are determined by the Regional Administrator to represent many such
locations throughout a metropolitan area, these smaller scales can be considered
to represent community-wide air quality."
149 Thus, unless the Regional Administrator has made this finding after a case-by-case evaluation, a
population-oriented microscale or middle scale monitoring site (including one located near malls,
neighborhoods, schools, etc.) cannot be presumed to represent community-wide air quality.
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Section 4.7.1(c)(l) and (2) note that sites very close to individual sources, such as traffic
corridors in urban areas, may be appropriate sites for locating PM2.5 monitors that
represent community-wide air quality:
"In some circumstances, the microscale is appropriate for particulate sites;
community-oriented... sites measured at the microscale level should, however, be
limited to urban sites that are representative of long-term human exposure and of
many such microenvironments in the area.
In many situations, monitoring sites that are representative of microscale or
middle-scale impacts are not unique and are representative of many similar
situations. This can occur along traffic corridors or other locations in a residential
district. In this case, one location is representative of a number of small scale sites
and is appropriate for evaluation of long-term or chronic effects."
In general, receptors that are closer to a project would be similar to potential micro and
middle scale air quality monitoring sites and would be appropriate for comparison to the
annual PM2.5 NAAQS if they represent community-wide air quality.150
9.4.4 Conformity guidance for all projects in annual PM2.5 NAA QS areas
Receptors at Neighborhood or Larger Scale Locations
As described above, all population-oriented receptors at locations where a neighborhood
or larger scale monitor could be located are appropriate for comparison to the annual
PM2.5 NAAQS in a PM2.5 hot-spot analysis. In general, receptors farther away from any
transportation project (e.g., 100 meters or more away from a larger highway project)
would represent neighborhood scale locations under the PM2.5 monitoring regulations.151
The PM2.5 monitoring regulations do not provide further specific information for
determining neighborhood or larger scale locations for PM hot-spot analyses. However,
Figure E-l in Appendix E of 40 CFR Part 58 specifies distances from a roadside where
monitors of different scales may be located relative to a highway or intersection. See
Section 9.4.5 for further information on when a receptor represents neighborhood and
larger scale locations for these types of projects.
Receptors at Micro or Middle Scale Locations
As described above, population-oriented receptors that are at locations where a micro or
middle scale monitor could be located are appropriate for comparison to the annual PM2.5
NAAQS, if they represent community-wide air quality. In general, a receptor or
150 PM2 5 data from population-oriented microscale or middle scale monitoring sites (including those located
near malls, neighborhoods, schools, etc.) cannot be presumed to represent community-wide air quality and
be eligible for comparison to the annual PM2 5 NAAQS. However, on a case-by-case basis, certain
microscale or middle scale locations may represent or collectively identify a larger area of community-wide
air quality. PM2 5 data from such locations would be eligible for comparison to the annual PM2 5 NAAQS
(40 CFR 58.30).
151 See Exhibit 9-9 in Section 9.4.5 of this guidance for further information.
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collection of receptors closer to any project (e.g., 100 meters or less from a larger
highway project) would represent community-wide air quality and be appropriate for the
annual PM2.5 NAAQS if such receptor(s) collectively identify a larger region of localized
high PM2.5 concentrations and are not within a unique location(s).
The PM2.5 monitoring regulations do not provide further information for determining
when micro or middle scale locations are appropriate for PM hot-spot analyses.
However, 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 addition, a unique location may involve a portion of a project area
that involves concentrations, land uses, development, or a transportation project not like
other locations in the nonattainment or maintenance area. In addition, Figure E-l in
Appendix E of 40 CFR Part 58 specifies distances from a roadside where monitors of
different scales may be located relative to a highway or intersection. See Section 9.4.5
for further information on when a receptor represents a micro or middle scale location for
these types of projects.
The following are examples of micro and middle scale locations where receptors may
represent community-wide air quality and be compared to the annual PM2.5NAAQS:
• Locations with characteristics (e.g., land use and development patterns, emission
sources, and/or populations) that are similar to locations where existing air quality
monitors are sited that are eligible for use in annual PM2.5 designations;
• Locations where similar high annual PM2.5 concentrations are modeled in the PM
hot-spot analysis at adjacent receptors that cover a sufficiently large populated
area; and
• Locations along urban highway corridors in residential areas that are not
considered unique; that involve areas with large neighborhoods, schools, etc.; and
where similar high annual PM2.s concentrations are modeled at adjacent receptors.
The following are examples of micro and middle scale locations where receptors may not
be appropriate to compare to the annual PM2.5 NAAQS:
• Locations with characteristics (e.g., land use and development patterns, emission
sources, and/or populations) that are similar to locations where existing air quality
monitors are sited that are not eligible for use in annual PM2.5 designations;
• Locations where uniquely high annual PM2.s concentrations at one or a few
adjacent receptors are modeled in the PM hot-spot analysis in small isolated
portions of the greater project area; and
• Locations closer to the project than neighborhood or larger scale that would be
considered unique under the PM2.5 monitoring regulations, such as locations
within 100 meters of a new or expanded transit terminal where no other such
terminals exist in the nonattainment or maintenance area.
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
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93.105(c)(l)(i)). The above examples are illustrative in nature and may not reflect a
specific PM hot-spot analysis. A case-by-case review of each situation is necessary to
ensure that PM hot-spot analyses for the annual PM2.5 NAAQS meet applicable
requirements.
Additional Considerations and Techniques
Decisions about whether receptors are appropriate for the annual PM2.5 NAAQS for
conformity purposes cannot be determined based on existing conditions in the project
area (see Section 9.4.5). Receptors will be at the same locations in the build and no-build
scenarios, but the decision on whether a receptor represents community-wide air quality
should be based on information for the build scenario. Any differences between the build
and no-build scenarios should be documented. For example, anticipated changes in the
number of populated areas within the project area, such as zoned or platted housing or
commercial developments, should be described.
To assist project sponsors, it is recommended that the locations of populations,
businesses, other institutions, any air quality monitors, and predicted receptor
concentrations and other relevant concentration data be displayed on a map along with
the project area, whenever possible. Such a map may help visualize locations where
receptors are population-oriented and determine whether particular receptor
concentrations represent small, unique areas (and therefore are not appropriate for the
annual PM2.5 NAAQS) or represent "a larger region of localized high PM2.5
concentrations" (and therefore are appropriate for the annual PM2.5 NAAQS).
There are several common visualization techniques in the air quality modeling and
geography professions that are likely to be useful ways of displaying receptor
concentrations, such as contour plots, surface plots, and maps generated using geographic
information systems (GIS). Many computer programs can generate these types of
graphics.
9.4.5 Additional conformity guidance for the annual PM2.5 NAA QS and highway and
intersection projects
As noted above in Sections 9.4.3 and 9.4.4., Appendix E of the PM2.5 monitoring
regulation provides further information to determine whether a receptor represents a
micro, middle, neighborhood, or larger scale location for highway and intersection
projects. Exhibit 9-9 (following page) is a helpful guide in determining what receptor
locations could be considered neighborhood scale, and thus always appropriate for
comparison to the annual PM2.5 NAAQS in PM hot-spot analyses.152 This exhibit could
also help implementers identify what receptor locations could be considered micro and
middle scale.
152 Exhibit 9-9 is adapted from Figure E-l in Appendix E of 40 CFR Part 58.
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Exhibit 9-9 categorizes population-oriented receptors into Portion A, Portion B, and
Portion C, expressed as annual average daily traffic (AADT) and the distance of receptors
from a proposed highway or intersection location.
Exhibit 9-9. Determining Scale of Receptor Locations for the Annual
NAAQS
200000
180000 -
20000
PORTION B: Population-oriented receptors with this
spacing from the nearest traffic lane are "middle scale"
or "micro scale" in representation and initially
presumed to be comparable with the annual NAAQS,
but may not be.
Receptors in this region should be analyzed to
determine receptor eligibility
PORTION A: Population-oriented
receptors with this spacing from the
nearest traffic lane are "neighborhood
scale" or "urban scale" in representation
and comparable with the animal
NAAQS
20 30 40 50 60 70 80 90
Distance of receptor from project's nearest traffic lane (meters)
100
110
Note: Exhibit 9-9 does not apply to receptors near projects that consist of terminals,
garages, or other non-road emission sources, such as transit terminals, bus garages, and
intermodal freight terminals. In addition, Exhibit 9-9 does not apply when evaluating
receptors that capture the impacts of nearby sources that do not involve highways and
intersections, since such projects do not involve AADT data.
Portion A
Receptors at these locations are considered appropriate for comparison to the annual
PM2.5 NAAQS because they represent locations that would be considered neighborhood
scale locations under the PM2.5 monitoring regulations. In addition, any receptor farther
than 100 meters from the nearest lane of traffic is comparable to the annual Plvb.s
NAAQS, regardless of AADT. Neighborhood or urban scale monitoring sites are always
compared to the annual Plvb.s NAAQS.
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Receptors in Portion A are at least 15 meters away from the project's nearest lane of
traffic for every 10,000 AADT. For example, if a highway has 80,000 AADT, any
receptor presumed to be comparable to the annual PIVb.s NAAQS at neighborhood and
larger scales must be located at least 80 meters from the project's nearest lane of traffic.
Again, any receptor farther than 100 meters from the nearest lane of traffic is comparable
to the annual NAAQS, regardless of AADT.
Portion B
Receptors at these locations need further evaluation to determine if they are not
appropriate for comparison to the annual PM2.5 NAAQS because they represent micro
and middle scale locations under the PM2.5 monitoring regulations. Micro and middle
scale monitoring sites are compared to the annual PM2.5 NAAQS if they represent
community-wide air quality, as described above.
Receptors in Portion B of Exhibit 9-9 would initially be modeled with respect to the
annual PM2.5 NAAQS; subsequent analysis could then be used to determine whether
certain receptors or groups of receptors are appropriate for comparison to the annual
PM2.5 NAAQS (i.e., to determine whether such locations do or do not represent
community-wide air quality).
Portion C
In most cases, receptors within five meters of a highway or transit project are not
considered appropriate for comparison to any NAAQS, including the annual PM2.5
NAAQS. However, in cases involving urban canyons, receptors may be appropriate for
comparison to both PM2.5 NAAQS within 2-10 meters of a project.153
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.
153 See 40 CFR Part 58, Appendix D, Section 4.7. l(c)(l) and Appendix E, Section 6.3(b).
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Section 10: Mitigation and Control Measures
10.1 INTRODUCTION
This section describes mitigation and control measures that could be considered by
project sponsors to reduce emissions and any predicted new or worsened PM NAAQS
violations. These measures can be applied to the transportation project itself or other PM
sources in the project area. Written commitments for mitigation or control measures
must be obtained from the project sponsor and/or operator, or other emission source's
owner and/or operator, as appropriate, prior to making a project-level conformity
determination (40 CFR 93.123(c)(4) and 93.125(a)). If measures are selected, additional
emissions and air quality modeling will need to be completed and new design values
calculated to ensure that conformity requirements are met.
The following information provides more details on potential measures for PM hot-spot
analyses; others may be possible. Evaluating and choosing any models and associated
methods and assumptions for any measures that are relied upon in the PM hot-spot
analysis must be completed through the process established by each area's interagency
consultation procedures (40 CFR 93.105(c)(l)(i)). The models, methods, and
assumptions used to quantify reductions should be documented in the final project-level
conformity determination.
General categories of mitigation and control measures that could be considered include:
• Retrofitting, replacing vehicles/engines, and using cleaner fuels;
• Reducing idling;
• Redesigning the transportation project itself;
• Controlling fugitive dust; and
• Controlling other sources of emissions.
More information is provided for each of these categories below.
10.2 MITIGATION AND CONTROL MEASURES BY CATEGORY
10.2.1 Retrofitting, replacing vehicles/engines, and using cleaner fuels
• The installation of retrofit devices on older, higher emitting vehicles is one way to
reduce emissions. Retrofit devices such as Diesel Paniculate 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.154
154 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.155 In some areas, local
regulations to ban older trucks at specific port facilities have encouraged early
replacement of vehicles. Such an option would need to be discussed with the
local government with implementing authority.
o For additional information about quantifying the benefits of retrofitting
and replacing diesel vehicles and engines for conformity determinations,
see EPA's website for the most recent guidance on this topic:
www.epa.gov/otaq/stateresources/transconf/policy.htm.
o Also see EPA's National Clean Diesel Campaign website, which includes
information about retrofitting vehicles, including lists of EPA-verified
retrofit technologies and certified technologies; clean fuels; grants; case
studies; toolkits; and partnership programs: www.epa.gov/otaq/diesel/.
10.2.2 Reduced idling programs
• Anti-idling programs for diesel trucks or buses may be relevant for proj ects where
significant numbers of diesel vehicles are congregating for extended periods of
time (e.g., restrictions on long duration truck idling, truck stop electrification, or
time limits on bus idling at a terminal).
o For additional information about quantifying the benefits of anti-idling
programs for conformity determinations, see EPA's website for the most
recent guidance on this topic:
www.epa.gov/otaq/stateresources/transconf/policy.htm.
o A list of EPA-verified anti-idle technologies for trucks can be found at:
www. epa. gov/otaq/smartwav/transport/what-smartwav/verified-
technologies.htm.
155 The Federal Transit Administration (FTA) has minimum service life requirements for transit vehicles
purchased with FTA funds. If a transit agency disposes of a vehicle earlier than its full useful service life,
it will incur a payback penalty. Please refer to Chapter IV of FTA Circular 5010. ID for the establishment
and calculation of a vehicle's useful service life. In addition, Appendix D of the circular address the useful
life calculation and disposition of vehicles acquired with FTA funds:
www.fta.dotgov/documents/C 5010 ID Finalpub.pdf.
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10.2.3 Transportation project design revisions
• For transit and other terminals, project sponsors could consider redesigning the
project to reduce the number of diesel vehicles congregating at any one location.
Terminal operators can also take steps to improve gate operations to reduce
vehicle idling inside and outside the facility. Fewer diesel vehicles congregating
could reduce localized PM2.5 or PMio emissions for transit and other terminal
projects.
o A list of strategies to reduce emissions from trucks operating at marine
and rail terminals are available at:
www. epa. gov/otaq/smartway/transport/partner-resources/resources-
publications.htm.
• It may be possible in some cases to route existing or projected traffic away from
populated areas to an industrial setting (e.g., truck only lanes). Project sponsors
should take into account any changes in travel activity, including additional VMT,
that would result from rerouting this traffic. Note that this option may also
change the air quality modeling receptors that are examined in the PM hot-spot
analysis.
• Finally, project sponsors could consider additional modes for travel and goods
movement. An example would be transporting freight by cleaner rail instead of
by highway (e.g., putting port freight on electric trains instead of transporting it
by truck).
10.2.4 Fugitive dust control programs
Fugitive dust control programs will primarily be applicable in PMio hot-spot analyses,
since all PMio nonattainment and maintenance areas must include these emissions in such
analyses. However, there may be PM2.5 nonattainment and maintenance areas that also
could take advantage of these measures if re-entrained road dust or construction dust is
required for a PM2.5 hot-spot analysis. See Section 2.5 for further background.
• A project sponsor could commit to cover any open trucks used in construction of
the project if construction emissions are included in an analysis year. Some states
have laws requiring that open truck containers be covered to reduce dispersion of
material. Laws may differ in terms of requirements, e.g., some require covering
at all times, some require covering in limited circumstances, and some restrict
spillage.
• A project sponsor could employ or obtain a commitment from another local
agency to implement a street cleaning program. There is a variety of equipment
available for this purpose and such programs could include vacuuming or flushing
techniques. There have been circumstances where municipalities have
implemented street sweeping programs for air quality purposes.
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• Another option to reduce dust could be a site-watering program, which may be
relevant during the construction phase of a project, if construction emissions are
included in the PM hot-spot analysis.
• Project sponsors may consider street and shoulder paving and runoff and erosion
control in the project area, which can reduce significant quantities of dust.
• It may also be possible to reduce the use of sand in snow and ice control
programs, to apply additional chemical treatments, or to use harder material (that
is less likely to grind into finer particles).
10.2.5 Addressing other source emissions
Note: Controlling emissions from other sources may sufficiently reduce background
concentrations in the PM hot-spot analysis.
• Reducing emissions from school buses may be relevant where such emissions are
part of background concentrations. Information about retrofitting, replacing, and
reducing idling of school buses can be found on EPA's website at:
www.epa.gov/otaq/schoolbus/index.htm.
• Reducing emissions from ships, cargo handling equipment and other vehicles at
ports may change the result of the PM hot-spot analysis. Options such as
retrofitting, repowering, or replacing engines or vehicles, use of cleaner fuels, or
"cold ironing" (that allows ships to plug in to shore-side power units) could be
relevant where these sources significantly influence background concentrations in
the project area. More information about reducing emissions at ports can be
found on EPA's website at: www.epa.gov/otaq/diesel/ports/index.htm and
www. epa. gov/otaq/smartwav/transport/partner-resources/resources-
publications.htm.
• Adopting locomotive anti-idling policies or other measures. For additional
information, see the following EPA resources:
o "Guidance for Quantifying and Using Long Duration Switch Yard
Locomotive Idling Emission Reductions in State Implementation Plans,"
EPA420-B-04-09-037 (October 2009) available at:
www.epa.gov/otaq/diesel/documents/420b09037.pdf.
o EPA-verified anti-idle technologies for locomotives can be found at:
www. epa. gov/otaq/smartway/transport/what-smartway/verified-
technologies.htm.
• Remanufacturing existing locomotives to meet more stringent standards at a rate
faster than the historical average, or using only Tier 3 and/or Tier 4 locomotives
at a proposed terminal (once such locomotives become available).
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• Reducing emissions from a stationary source might also change the result of the
PM hot-spot analysis. Reductions could come from adding a control technology
to a stationary source or adopting policies to reduce peak emissions at such a
source. EPA and the state and/or local air quality agency could provide input on
the feasibility and implementation of such a measure, as well as any necessary
commitments to such measures from operators.
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