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Rule2024-27636

Guideline on Air Quality Models; Enhancements to the AERMOD Dispersion Modeling System

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Published

November 29, 2024

Effective

January 28, 2025

Issuing agencies

Environmental Protection Agency

Abstract

In this action, the Environmental Protection Agency (EPA) promulgates revisions to the Guideline on Air Quality Models ("Guideline"). The Guideline has been incorporated into the EPA's regulations, satisfying a requirement under the Clean Air Act (CAA), for the EPA to specify, with reasonable particularity, models to be used in the Prevention of Significant Deterioration (PSD) program. The Guideline provides EPA-preferred models and other recommended techniques, as well as guidance for their use in predicting ambient concentrations of air pollutants. The EPA is revising the Guideline, including enhancements to the formulation and application of the EPA's near-field dispersion modeling system, AERMOD, and updates to the recommendations for the development of appropriate background concentration for cumulative impact analyses.

Full Text

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[Federal Register Volume 89, Number 230 (Friday, November 29, 2024)]
[Rules and Regulations]
[Pages 95034-95075]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2024-27636]

[[Page 95033]]

Vol. 89

Friday,

No. 230

November 29, 2024

Part V

Environmental Protection Agency

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40 CFR Part 51

Guideline on Air Quality Models; Enhancements to the AERMOD Dispersion
Modeling System; Final Rule

Federal Register / Vol. 89, No. 230 / Friday, November 29, 2024 /
Rules and Regulations

[[Page 95034]]

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ENVIRONMENTAL PROTECTION AGENCY

40 CFR Part 51

[EPA-HQ-OAR-2022-0872; FRL-10391-02-OAR]
RIN 2060-AV92

Guideline on Air Quality Models; Enhancements to the AERMOD
Dispersion Modeling System

AGENCY: Environmental Protection Agency (EPA).

ACTION: Final rule.

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SUMMARY: In this action, the Environmental Protection Agency (EPA)
promulgates revisions to the Guideline on Air Quality Models
(``Guideline''). The Guideline has been incorporated into the EPA's
regulations, satisfying a requirement under the Clean Air Act (CAA),
for the EPA to specify, with reasonable particularity, models to be
used in the Prevention of Significant Deterioration (PSD) program. The
Guideline provides EPA-preferred models and other recommended
techniques, as well as guidance for their use in predicting ambient
concentrations of air pollutants. The EPA is revising the Guideline,
including enhancements to the formulation and application of the EPA's
near-field dispersion modeling system, AERMOD, and updates to the
recommendations for the development of appropriate background
concentration for cumulative impact analyses.

DATES: This rule is effective January 28, 2025.

ADDRESSES: The EPA has established a docket for this action under
Docket ID No. EPA-HQ-OAR-2022-0872. All documents in the docket are
listed on the <a href="https://www.regulations.gov">https://www.regulations.gov</a> website. Although listed in
the index, some information is not publicly available, e.g.,
Confidential Business Information (CBI) or other information whose
disclosure is restricted by statute. Certain other material, such as
copyrighted material, is not placed on the internet and will be
publicly available only in hard copy form. Publicly available docket
materials are available electronically through <a href="https://www.regulations.gov">https://www.regulations.gov</a>.

FOR FURTHER INFORMATION CONTACT: Mr. George M. Bridgers, Office of Air
Quality Planning and Standards, Air Quality Assessment Division, Air
Quality Modeling Group, U.S. Environmental Protection Agency, Mail code
C439-01, Research Triangle Park, NC 27711; telephone: (919) 541-5563;
email: <a href="/cdn-cgi/l/email-protection#f0b282999497958283deb7959f829795b0958091de979f86">[email&#160;protected]</a> (and include ``2024 Revisions to the
Guideline on Air Quality Models'' in the subject line of the message).

SUPPLEMENTARY INFORMATION:
The information in this preamble is organized as follows:

Table of Contents

I. General Information
A. Does this action apply to me?
B. Where can I get a copy of this document?
C. Judicial Review
D. List of Acronyms
II. Background
A. The Guideline on Air Quality Models and EPA Modeling
Conferences
B. The Twelfth and Thirteenth Conferences on Air Quality
Modeling
C. Alpha and Beta Categorization of Non-Regulatory Options
III. Discussion of Final Action on the Revisions to the Guideline
A. Final Action
IV. Ongoing Model Development
V. Statutory and Executive Order Reviews
A. Executive Order 12866: Regulatory Planning and Review and
Executive Order 14094: Modernizing Regulatory Review
B. Paperwork Reduction Act (PRA)
C. Regulatory Flexibility Act (RFA)
D. Unfunded Mandates Reform Act (UMRA)
E. Executive Order 13132: Federalism
F. Executive Order 13175: Consultation and Coordination With
Indian Tribal Governments
G. Executive Order 13045: Protection of Children From
Environmental Health Risks and Safety Risks
H. Executive Order 13211: Actions Concerning Regulations That
Significantly Affect Energy Supply, Distribution, or Use
I. National Technology Transfer and Advancement Act
J. Executive Order 12898: Federal Actions To Address
Environmental Justice in Minority Populations and Low-Income
Populations and Executive Order 14096: Revitalizing Our Nation's
Commitment to Environmental Justice for All
K. Congressional Review Act (CRA)

I. General Information

A. Does this action apply to me?

This action applies to Federal, State, territorial, and local air
quality management programs that conduct or review air quality modeling
as part of State Implementation Plan (SIP) submittals and revisions,
New Source Review (NSR), including new or modifying industrial sources
under Prevention of Significant Deterioration (PSD), Conformity, and
other programs in which air quality assessments are required under EPA
regulation. Categories and entities potentially regulated by this
action include:

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Category NAICS \a\ code
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Federal/State/territorial/local/Tribal government.... 924110
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\a\ North American Industry Classification System.

B. Where can I get a copy of this document?

In addition to being available in the docket, an electronic copy of
this final rule and relative supporting documentation will also be
available on the EPA's Support Center for Regulatory Atmospheric
Modeling (SCRAM) website. Following signature, these materials will be
posted on SCRAM at the following address: <a href="https://www.epa.gov/scram/2024-appendix-w-final-rule">https://www.epa.gov/scram/2024-appendix-w-final-rule</a>.

C. Judicial Review

Under section 307(b)(1) of the Clean Air Act (CAA), this final rule
is ``nationally applicable'' because it revises the Guideline on Air
Quality Models, 40 CFR part 51, Appendix W. Therefore, petitions for
judicial review of this final action must be filed in the U.S. Court of
Appeals for the District of Columbia Circuit by January 28, 2025.
Filing a petition for reconsideration by the Administrator of this
final action does not affect the finality of the action for the
purposes of judicial review, nor does it extend the time within which a
petition for judicial review must be filed, and shall not postpone the
effectiveness of such action. 42 U.S.C. 7607(b)(1). This rule is also
subject to section 307(d) of the CAA because it revises a regulation
addressing a requirement under section 165(e)(3)(D) of the CAA, which
is included in part C of title I of the CAA (relating to prevention of
significant deterioration of air quality and protection of visibility).
42 U.S.C. 7607(d)(1)(J).

D. List of Acronyms

AEDT Aviation Environmental Design Tool
AERMET Meteorological data preprocessor for AERMOD
AERMINUTE Pre-processor to AERMET to read 1-minute ASOS data to
calculate hourly average winds for input into AERMET
AERMOD American Meteorological Society (AMS)/EPA Regulatory Model
AERSCREEN Program to run AERMOD in screening mode
AERSURFACE Land cover data tool in AERMET
AQRV Air Quality Related Value
AQS Air Quality System
ARM2 Ambient Ratio Method 2
ASOS Automated Surface Observing Stations
ASTM American Society for Testing and Materials
B<INF>o</INF> Bowen ratio

[[Page 95035]]

BID Buoyancy-induced dispersion
BLP Buoyant Line and Point Source model
BOEM Bureau of Ocean Energy Management
BPIPPRM Building Profile Input Program for PRIME
CAA Clean Air Act
CAL3QHC Screening version of the CALINE3 model
CAL3QHCR Refined version of the CALINE3 model
CALINE3 CAlifornia LINE Source Dispersion Model
CALMPRO Calms Processor
CALPUFF California Puff model
CAMx Comprehensive Air Quality Model with Extensions
COARE Coupled Ocean-Atmosphere Response Experiment
CFR Code of Federal Regulations
CMAQ Community Multiscale Air Quality
CO Carbon monoxide
CTDMPLUS Complex Terrain Dispersion Model Plus Algorithms for
Unstable Situations
CTSCREEN Screening version of CTDMPLUS
CTM Chemical transport model
d[thgr]/dz Vertical potential temperature gradient
DT Temperature difference
EPA Environmental Protection Agency
FAA Federal Aviation Administration
FHWA Federal Highway Administration
FLAG Federal Land Managers' Air Quality Related Values Work Group
Phase I Report
FLM Federal Land Manager
GEP Good engineering practice
GRSM Generic Reaction Set Method
GUI Graphical user interface
IBL Inhomogeneous boundary layer
ISC Industrial Source Complex model
IWAQM Interagency Workgroup on Air Quality Modeling
km kilometer
L Monin-Obukhov length
m meter
m/s meter per second
MAKEMET Program that generates a site-specific matrix of
meteorological conditions for input to AERMOD
MCH Model Clearinghouse
MCHISRS Model Clearinghouse Information Storage and Retrieval System
MERPs Model Emissions Rates for Precursors
METPRO Meteorological Processor for dispersion models
MM5 Mesoscale Model 5
MMIF Mesoscale Model Interface program
MODELOPT Model option keyword
MPRM Meteorological Processor for Regulatory Models
NAAQS National Ambient Air Quality Standards
NCEI National Centers for Environmental Information
NH<INF>3</INF> Ammonia
NO Nitric oxide
NO<INF>X</INF> Nitrogen oxides
NO<INF>2</INF> Nitrogen dioxide
NSR New Source Review
NWS National Weather Service
OCD Offshore and Coastal Dispersion Model
OCS Outer Continental Shelf
OLM Ozone Limiting Method
PCRAMMET Meteorological Processor for dispersion models
P-G stability Pasquill-Gifford stability
PM<INF>2.5</INF> Particles less than or equal to 2.5 micrometers in
diameter
PM<INF>10</INF> Particles less than or equal to 10 micrometers in
diameter
PRIME Plume Rise Model Enhancements algorithm
PSD Prevention of Significant Deterioration
PVMRM Plume Volume Molar Ratio Method
r Albedo
RHC Robust Highest Concentration
RLINE Research LINE source model for near-surface releases
RLINEXT Research LINE source model extended
SCICHEM Second-order Closure Integrated Puff Model
SCRAM Support Center for Regulatory Atmospheric Modeling
SCREEN3 A single source Gaussian plume model which provides maximum
ground-level concentrations for point, area, flare, and volume
sources
SDM Shoreline Dispersion Model
SIP State Implementation Plan
SO<INF>2</INF> Sulfur dioxide
SRDT Solar radiation/delta-T method
TSD Technical support document
u Values for wind speed
u* Surface friction velocity
VOC Volatile organic compound
w* Convective velocity scale
WRF Weather Research and Forecasting model
z<INF>i</INF> Mixing height
Z<INF>o</INF> Surface roughness length
Z<INF>ic</INF> Convective mixing height
Z<INF>im</INF> Mechanical mixing height
[sigma]<INF>v</INF>, [sigma]<INF>w</INF> Horizontal and vertical
wind speeds

II. Background

A. The Guideline on Air Quality Models and EPA Modeling Conferences

The Guideline is used by the EPA, other Federal, State,
territorial, and local air quality agencies, and industry to prepare
and review preconstruction permit applications for new sources and
modifications, SIP submittals and revisions, determinations that
actions by Federal agencies are in conformity with SIPs, and other air
quality assessments required under EPA regulation. The Guideline serves
as a means by which national consistency is maintained in air quality
analyses for regulatory activities under CAA regulations, including 40
CFR 51.112, 51.117, 51.150, 51.160, 51.165, 51.166, 52.21, 93.116,
93.123, and 93.150.
The EPA originally published the Guideline in April 1978 (EPA-450/
2-78-027), and it was incorporated by reference in the regulations for
the PSD program in June 1978. The EPA revised the Guideline in 1986 (51
FR 32176) and updated it with supplement A in 1987 (53 FR 32081),
supplement B in July 1993 (58 FR 38816), and supplement C in August
1995 (60 FR 40465). The EPA published the Guideline as Appendix W to 40
CFR part 51 when the EPA issued supplement B. The EPA republished the
Guideline in August 1996 (61 FR 41838) to adopt the Code of Federal
Regulations (CFR) system for designating paragraphs. The publication
and incorporation of the Guideline by reference into the EPA's PSD
regulations satisfies the requirement under the CAA section
165(e)(3)(D) for the EPA to promulgate regulations that specify with
reasonable particularity models to be used under specified sets of
conditions for purposes of the PSD program.
To support the process of developing and revising the Guideline
during the period of 1977 to 1988, we held the First, Second, and Third
Conferences on Air Quality Modeling as required by CAA section 320 to
help standardize modeling procedures. These modeling conferences
provided a forum for comments on the Guideline and associated
revisions, thereby helping us introduce improved modeling techniques
into the regulatory process. Between 1988 and 1995, we conducted the
Fourth, Fifth, and Sixth Conferences on Air Quality Modeling to solicit
comments from the stakeholder community to guide our consideration of
further revisions to the Guideline, update the available modeling tools
based on the current state-of-the-science, and advise the public on new
modeling techniques.
The Seventh Conference was held in June 2000 and also served as a
public hearing for the proposed revisions to the recommended air
quality models in the Guideline (65 FR 21506). These changes included
the CALPUFF modeling system, AERMOD Modeling System, and ISC-PRIME
model. Subsequently, the EPA revised the Guideline on April 15, 2003
(68 FR 18440), to adopt CALPUFF as the preferred model for long-range
transport of emissions from 50 to several hundred kilometers and to
make various editorial changes to update and reorganize information and
remove obsolete models.
We held the Eighth Conference on Air Quality Modeling in September
2005. This conference provided details on changes to the preferred air
quality models, including available methods for model performance
evaluation and the notice of data availability that the EPA published
in September 2003, related to the incorporation of the PRIME downwash
algorithm in the AERMOD dispersion model (in response to comments
received from the Seventh Conference). Additionally, at the Eighth
Conference, a panel of experts discussed the use of state-of-the-
science prognostic

[[Page 95036]]

meteorological data for informing the dispersion models. The EPA
further revised the Guideline on November 9, 2005 (70 FR 68218), to
adopt AERMOD as the preferred model for near-field dispersion of
emissions for distances up to 50 kilometers.
The Ninth Conference on Air Quality Modeling was held in October
2008 and emphasized the following topics: reinstituting the Model
Clearinghouse, review of non-guideline applications of dispersion
models, regulatory status updates of AERMOD and CALPUFF, continued
discussions on the use of prognostic meteorological data for informing
dispersion models, and presentations reviewing the available model
evaluation methods. To further inform the development of additional
revisions to the Guideline, we held the Tenth Conference on Air Quality
Modeling in March 2012. The conference addressed updates on: the
regulatory status and future development of AERMOD and CALPUFF, review
of the Mesoscale Model Interface (MMIF) prognostic meteorological data
processing tool for dispersion models, draft modeling guidance for
compliance demonstrations of the fine particulate matter
(PM<INF>2.5</INF>) national ambient air quality standards (NAAQS),
modeling for compliance demonstration of the 1-hour nitrogen dioxide
(NO<INF>2</INF>) and sulfur dioxide (SO<INF>2</INF>) NAAQS, and new and
emerging models/techniques for future consideration under the Guideline
to address single-source modeling for ozone and secondary
PM<INF>2.5,</INF> as well as long-range transport and chemistry.
The Eleventh Conference on Air Quality Modeling was held in August
2015 and included the public hearing for a 2015 proposed revision of
the Guideline. The conference included presentations summarizing the
proposed updates to the AERMOD Modeling System, replacement of CALINE3
with AERMOD for modeling of mobile sources, incorporation of prognostic
meteorological data for use in dispersion modeling, the proposed
screening approach for long-range transport for NAAQS and PSD
increments assessments with use of CALPUFF as a screening technique
rather than an EPA-preferred model, the proposed 2-tiered screening
approach to address ozone and PM<INF>2.5</INF> in PSD compliance
demonstrations, the status and role of the Model Clearinghouse, and
updates to procedures for single-source and cumulative modeling
analyses (e.g., modeling domain, source input data, background data,
and compliance demonstration procedures).
Additionally, the 2015 proposed action included a reorganization of
the Guideline to make it easier to use and to streamline the compliance
assessment process (80 FR 45340), and also included additional clarity
in distinguishing requirements from recommendations while noting the
continued flexibilities provided within the Guideline, including but
not limited to use and approval of alternative models (82 FR 45344).
These proposed revisions were adopted and reflected in the most recent
version of the Guideline, promulgated on January 17, 2017 (82 FR 5182).

B. The Twelfth and Thirteenth Conferences on Air Quality Modeling

Following the 2017 revision of the Guideline, the Twelfth
Conference on Air Quality Modeling was held in August 2019 in
continuing compliance with CAA section 320. While not associated with a
regulatory action, the Twelfth Conference was held with the intent to
inform the ongoing development of the EPA's preferred air quality
models and potential revisions to the Guideline. The conference
included expert panel discussions and invited presentations covering
the following model/technique enhancements: treatment of low wind
conditions, overwater modeling, mobile source modeling, building
downwash, prognostic meteorological data, near-field and long-range
model evaluation criteria, NO<INF>2</INF> modeling techniques, plume
rise, deposition, and single source ozone and PM<INF>2.5</INF> modeling
techniques. At the conclusion of the expert panels and invited
presentations, there were several presentations given by the public,
including industrial trade groups, on recommended areas for additional
model development and future revision in the Guideline.
Based on the engagement and presentations from the Twelfth
Conference and continuing model formulation research and development
activities in the years since 2019, the EPA proposed new revisions to
the Guideline on October 12, 2023, including enhancements to the
formulation and application of the EPA's near-field dispersion modeling
system, AERMOD, updates to the recommendations for the development of
appropriate background concentration for cumulative impact analyses,
and various typographical updates to the existing regulation (88 FR
72826). The Thirteenth Conference on Air Quality Modeling, held on
November 14-15, 2023, provided a formal venue for EPA presentations to
the public on the October 2023 proposed revisions to the Guideline and
AERMOD. The Thirteenth Modeling Conference also served as the public
hearing for the October 2023 proposed rule.
Specific to the AERMOD Modeling System, the October 2023 Guideline
proposed rule included an update to the AERMET meteorological
preprocessor for AERMOD that would add the capability to process
measured and prognostic marine-based meteorology for offshore
applications. Additionally, the proposed rule had separate AERMOD
updates that would incorporate a new Tier 3 screening method for the
conversion of nitrogen oxides (NO<INF>X</INF>) emissions to
NO<INF>2</INF> and would add a new source type for modeling vehicle
roadway emissions. Finally, the proposed rule suggested minor revisions
to the recommendations regarding the determination of appropriate model
input data, specifically background concentration, for use in NAAQS
implementation modeling demonstrations in section 8.3 of the Guideline.
In conjunction with the October 2023 Guideline proposed rule, the EPA
developed the Draft Guidance on Developing Background Concentrations
for Use in Modeling Demonstrations.\1\ This draft guidance document
detailed the EPA-recommended framework with stepwise considerations to
assist permit applicants in characterizing a credible and appropriately
representative background concentration for cumulative impact analyses
through qualitative and semi-quantitative considerations within a
transparent process using the variety of emissions and air quality data
including the contributions from nearby sources in multi-source areas.
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\1\ U.S. Environmental Protection Agency, 2023. Draft Guidance
on Developing Background Concentrations for Use in Modeling
Demonstrations. Publication No. EPA-454/P-23-001. Office of Air
Quality Planning and Standards, Research Triangle Park, NC.
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All of the presentations, along with the transcript of the
conference and public hearing proceedings, are available in the docket
for the Thirteenth Conference on Air Quality Models (Docket ID No. EPA-
HQ-OAR-2022-0872). Additionally, all the materials associated with the
Thirteenth Conference and the public hearing are available on the EPA's
SCRAM website at <a href="https://www.epa.gov/scram/13th-conference-air-quality-modeling">https://www.epa.gov/scram/13th-conference-air-quality-modeling</a>.

C. Alpha and Beta Categorization of Non-Regulatory Options

With the release of AERMOD version 18181 in 2018, the EPA adopted a
new

[[Page 95037]]

paradigm for engagement with the scientific community to facilitate the
continued development of the AERMOD Modeling System. Previously,
updates to the scientific formulation of the model were not made
available to the public for review, testing, evaluation, and comment
prior to the proposal stage of the formal rulemaking process when an
update was made to the Guideline. This limited the public's engagement
and feedback to a short, predefined comment period, typically only one
to two months. The new approach enables the EPA to release potential
formulation updates as non-regulatory ``alpha'' and ``beta'' options as
they are being developed. As non-regulatory options, they can be made
available during any release cycle, thereby enabling feedback as they
are being developed. This approach allows for more robust testing and
evaluation during development, benefitting from the experience of a
broad expert community. A pathway such as this that facilitates more
frequent and active engagement with the external modeling community
allows for a more informed and timely regulatory update process when
the EPA has determined an update has met the criteria required for
consideration as a science formulation update to the regulatory version
of the model.
In this alpha/beta construct, alpha options are updates to the
scientific formulation that are thought to have merit but are
considered experimental, still in the research and development stage.
Alpha options require further testing, performance evaluation, and/or
vetting through peer review and, thus, are not intended for regulatory
applications of the model.
Beta options, on the other hand, have been demonstrated to be
suitable and applicable to the modeling problem at hand on a
theoretical basis, have undergone scientific peer review, and are
supported with performance evaluations using available and adequate
databases that demonstrate improved model performance and no
inappropriate model biases. In general, beta options have met the
necessary criteria to be formally proposed and adopted as updates to
the regulatory version of the model but have not yet been proposed
through the required rulemaking process, which includes a public
hearing and formal comment period. Beta options are mature enough in
the development process to be considered for use as an alternative
model, provided an appropriate site-specific modeling demonstration is
completed to show the alternative model is appropriate for the site and
conditions where it will be applied and the requirements of the
Guideline, section 3.2, are fully satisfied, including formal
concurrence by the EPA's Model Clearinghouse. With the release of
AERMOD version 24142, each of the beta options that existed in version
23132 are being promulgated as regulatory updates to the formulation of
AERMOD. All previous alpha options in version 23132 are being retained
as alpha options in version 24142. No options are being added as beta
options and no alpha options are being updated to beta status.

III. Discussion of Final Action on the Revisions to the Guideline

In this action, the EPA is promulgating revisions to the Guideline
corresponding to updates to the scientific formulation of the AERMOD
Modeling System and updates to the recommendations for the development
of appropriate background concentration for cumulative impact analyses.
When and where appropriate, the EPA has engaged with our Federal
partners, including the Bureau of Ocean Energy Management (BOEM) and
the Federal Highway Administration (FHWA), to collaborate on these
updates to the Guideline. There are additional editorial changes being
made to the Guideline to correct minor typographical errors found in
the 2017 Guideline and to update website links.

A. Final Action

This section provides a detailed overview of the substantive
changes being finalized in the Guideline to improve the science of the
models and approaches used in regulatory assessments.
1. Updates to EPA's AERMOD Modeling System
Based on studies presented and discussed at the Twelfth Conference
on Air Quality Models held on October 2-3, 2019,\2\ and additional
relevant research since 2017, the EPA and other researchers have
conducted additional model evaluations and developed changes to the
model formulation of the AERMOD Modeling System to improve model
performance in its regulatory applications. One update is to the AERMET
meteorological preprocessor for AERMOD. This update provides the
capability to process measured and prognostic marine-based meteorology
for offshore applications. Separate updates are related to the AERMOD
dispersion model and include (1) a new Tier 3 screening method for the
conversion of nitrogen oxides (NO<INF>X</INF>) emissions to
NO<INF>2</INF> and (2) a new source type for modeling vehicle roadway
emissions.
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\2\ <a href="https://www.epa.gov/scram/12th-conference-air-quality-modeling">https://www.epa.gov/scram/12th-conference-air-quality-modeling</a>.
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Each of these formulation updates to the AERMOD Modeling System was
provided as a non-regulatory beta option in the version 23132 release
of the relevant AERMOD Modeling System components. With the release of
the AERMOD Modeling System version 24142, the EPA has removed the non-
regulatory beta restriction and is finalizing the following updates to
the AERMOD Modeling System to address several technical concerns
expressed by stakeholders.
a. Incorporation of COARE Algorithms Into AERMET for Use in Overwater
Marine Boundary Layer Environments
The EPA received a few specific comments in support of adding the
Coupled Ocean-Atmosphere Response Experiment (COARE) into AERMET.
Therefore, the EPA is finalizing the integration of the COARE
3 4 algorithms to AERMET for meteorological data processing
in applications using either observed or prognostic meteorological data
in overwater marine boundary layer environments.
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\3\ Fairall, C.W., E.F. Bradley, J.E. Hare, A.A. Grachev, and
J.B. Edson, 2003: ``Bulk Parameterization of Air-Sea Fluxes: Updates
and Verification for the COARE Algorithm.'' Journal of Climate, 16,
571-591.
\4\ Evaluation of the Implementation of the Coupled Ocean-
Atmosphere Response Experiment (COARE) algorithms into AERMET for
Boundary Layer Environments. EPA-2023/R-23-008, Office of Air
Quality Planning and Standards, RTP, NC.
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As discussed in the preamble to the proposed rule, the algorithms
in COARE are better suited for overwater boundary layer calculations
than the existing algorithms in AERMET that are better suited for land-
based data. The addition of the COARE algorithms to AERMET replaces the
need of the standalone AERCOARE program used for overwater applications
and ensures that the COARE algorithms are updated regularly as part of
routine AERMET updates. For prognostic applications processed through
the Mesoscale Model Interface (MMIF), the addition of COARE algorithms
to AERMET replaces the need to run MMIF for AERCOARE input, and the
user can run MMIF for AERMET input for overwater applications. The
COARE option is selected in AERMET by the user with the METHOD COARE
RUN-COARE* record in the AERMET Stage 2 input file.
We are including the COARE algorithms into AERMET as a non-default
regulatory option. This eliminates the previous alternative

[[Page 95038]]

model demonstration requirements for use of AERMOD in marine
environments, and its use is contingent upon consultation with the EPA
Regional Office and appropriate reviewing authority to ensure that
platform downwash and shoreline fumigation are adequately considered in
the modeling demonstration. Also note that since COARE is a non-default
regulatory option, the user no longer must include the BETA option with
the MODELOPT keyword in the AERMOD input file to use AERMET data
generated using the COARE algorithms.
b. Addition of a New Tier 3 Detailed Screening Technique for
NO<INF>2</INF>
As supported by the discussions in the October 2023 proposed
revisions to the Guideline, and based on the public comments received,
the EPA is finalizing adoption of the Generic Reaction Set Method
(GRSM) as a regulatory non-default, detailed Tier 3 NO<INF>2</INF>
screening option in AERMOD version 24142.
As discussed in the preamble to the October 2023 proposed revisions
to the Guideline, the functionality of the GRSM implementation in
AERMOD is similar to that of the existing PVMRM and OLM Tier 3
NO<INF>2</INF> schemes, with exception to some additional input
requirements necessary (i.e., hourly NO<INF>X</INF> inputs) for
treatment of the reverse NO<INF>2</INF> photolysis reaction during
daytime hours. Background NO<INF>2</INF> concentrations are accounted
for in the GRSM daytime equilibrium NO<INF>2</INF> concentration
estimates based on the chemical reaction balance between ozone
entrainment and NO titration, photolysis of NO<INF>2</INF> to NO, and
ambient background NO<INF>2</INF> participation in titration and
photolysis reactions. Similar to PVMRM and OLM, nighttime GRSM
NO<INF>2</INF> estimates are based on ozone entrainment and titration
of available NO in the NO<INF>X</INF> plume.
The EPA received several comments in support of the proposed
adoption of GRSM as a Tier 3 NO<INF>2</INF> screening option in AERMOD.
Several commenters requested further clarification and guidance from
the EPA on the suitability and regulatory modeling application of GRSM,
as well as the selection of GRSM instead of PVMRM and OLM for detailed
Tier 3 NO<INF>2</INF> screening modeling demonstrations. The EPA plans
to draft NO<INF>2</INF> modeling guidance in the future to respond to
these comments.
One commenter notes that the GRSM supporting documentation is
unclear on what assessment or evaluation was conducted that supports
the assertion that updates to the GRSM code in AERMOD version 23132
address NO<INF>2</INF> model overpredictions farther downwind, thereby
improving model performance. As discussed in the preamble of the
October 2023 proposed revisions to the Guideline, updates to the GRSM
formulation in AERMOD version 22112 were developed in late 2022 to
address more realistic building effects on instantaneous plume spread,
accounting of multiple plume effects on entrainment of ozone, and the
tendency of GRSM to over-predict in the far-field (e.g., beyond
approximately 0.5 to 3 km for typical point source releases). In
response to this comment, the GRSM Technical Support Document (TSD) has
been updated with clarifying information in an appendix.\5\
---------------------------------------------------------------------------

\5\ Environmental Protection Agency, 2024. Technical Support
Document (TSD) for Adoption of the Generic Reaction Set Method
(GRSM) as a Regulatory Non-Default Tier-3 NO<INF>2</INF> Screening
Option, Publication No. EPA-454/R-24-005. Office of Air Quality
Planning & Standards, Research Triangle Park, NC.
---------------------------------------------------------------------------

c. Addition of RLINE as Mobile Source Type
The EPA is finalizing RLINE as a new regulatory source type in
AERMOD for mobile source modeling. The inclusion of the RLINE source
type is in addition to the AREA, LINE, and VOLUME source types already
available for mobile source modeling, giving additional flexibility to
users in characterizing transportation projects when modeling them with
AERMOD. As stated in the preamble to the proposed rule, the addition of
RLINE as a regulatory source type is an extension of the 2017 update to
the Guideline in which AERMOD replaced CALINE3 as the Addendum A model
for mobile source modeling. The RLINE source type has undergone
significant evaluation by the EPA and FHWA as part of the Interagency
Agreement between the EPA and FHWA and, as noted in the preamble to the
proposed rule, has shown improved performance since its introduction
into AERMOD in 2019.6 7
---------------------------------------------------------------------------

\6\ Incorporation and Evaluation of the RLINE source type in
AERMOD for Mobile Source Applications. EPA-2023/R-23-011, Office of
Air Quality Planning and Standards, RTP, NC.
\7\ Owen, R., et al., 2024. Incorporation of RLINE into AERMOD:
An update and evaluation for mobile source applications. Journal of
the Air & Waste Management Association, Manuscript submitted for
publication.
---------------------------------------------------------------------------

The EPA received several comments supporting the inclusion of RLINE
as a regulatory option into AERMOD. Several commenters also mentioned
the need to update the EPA's guidance. The EPA agrees that
practitioners will need guidance for using RLINE, and we plan to update
the relevant guidance.
The EPA also received a comment supporting the retention of the
RLINEXT source type as an ALPHA option. As described below, the EPA has
retained the RLINEXT as an ALPHA option for further model development
and evaluation.
Commenters also asked whether the CAL3QHC model could continue to
be used for carbon monoxide (CO) hot-spot analyses. The EPA confirms
that the 1992 CO Guidance that employs CAL3QHC for CO screening
analyses is still an available screening approach for CO hot-spot
analyses of transportation projects.\8\ In the EPA's January 17, 2017
final rule, section 4.2.3.1(b) of the Guideline was modified, and the
1992 technical guidance (with CAL3QHC) remains in place as the
recommended approach for CO screening analyses (82 FR 5192).
---------------------------------------------------------------------------

\8\ U.S. EPA, 1992: Guideline for modeling carbon monoxide from
roadway intersections. EPA-454/R-92-005. U.S. EPA, Office of Air
Quality Planning & Standards, RTP, NC.
---------------------------------------------------------------------------

The RLINE source type includes the ability to include terrain in
AERMOD modeling as well as the urban source algorithms in AERMOD.
However, as stated in the preamble to the proposed rule, the inclusion
of RLINE with terrain use does not change the EPA's recommendation in
the PM Hot-spot Guidance \9\ to model transportation projects with FLAT
terrain. Since RLINE is now a regulatory source type, the user no
longer has to include the BETA flag with the MODELOPT keyword in the
AERMOD input file to use the RLINE source, including the use of RLINE
with the AERMOD urban option or RLINE with terrain.
---------------------------------------------------------------------------

\9\ U.S. EPA, 2021: PM Hot-spot Guidance; Transportation
Conformity Guidance for Quantitative Hot-spot Analyses in
PM<INF>2.5</INF> and PM<INF>10</INF> Nonattainment and Maintenance
Areas. EPA-42-B-21-037. U.S. EPA, Office of Transportation and Air
Quality, Ann Arbor, MI.
---------------------------------------------------------------------------

The RLINEXT source type is based on the same algorithm as the RLINE
source type but includes additional parameters to allow modeling of
other features of the source, such as solid barriers and the source
below grade. As these are not yet fully developed, the RLINEXT source
type continues to be an ALPHA option. Therefore, the ALPHA flag must be
included with MODELOPT keyword when using an RLINEXT source.
d. Support Information, Documentation, and Model Code
Model performance evaluation and peer-reviewed scientific
references for each of these three updates to the AERMOD Modeling
System are cited and placed in the docket for this action. An updated
user's guide and model formulation documents for version

[[Page 95039]]

24142 have also been placed in the docket for this action. We have
updated the summary description of the AERMOD Modeling System to
Addendum A of the Guideline to reflect these updates. The essential
codes, preprocessors, and test cases have been updated and posted to
the EPA's SCRAM website, <a href="https://www.epa.gov/scram">https://www.epa.gov/scram</a>.
2. Updates to Recommendations on the Development of Background
Concentration
Based on comments received on the 2023 proposed revisions to the
Guideline, the EPA is finalizing revisions to section 8 of the
Guideline to refine the recommendations regarding the determination of
appropriate model input data, specifically background concentration,
for use in NAAQS implementation modeling demonstrations (e.g., PSD
compliance demonstrations, SIP demonstrations for inert pollutants, and
SO<INF>2</INF> designations). These revisions include the removal of
the term ``significant concentration gradient'' and the associated
recommendations which are replaced with a more robust framework for
characterizing background concentrations for cumulative modeling with
particular attention to identifying and modeling nearby sources in
multi-source areas.
The EPA has revised the recommendations for the determination of
background concentrations in constructing the design concentration, or
total air quality concentration in multi-source areas (see section
8.3), as part of a cumulative impact analysis for NAAQS implementation
modeling demonstrations. The EPA is finalizing the proposed framework,
which includes a stepwise set of considerations to replace the narrow
recommendation of modeling nearby sources that cause a significant
concentration gradient. This framework focuses the inherent discretion
in defining representative background concentrations through
qualitative and semi-quantitative considerations within a transparent
process using the variety of emissions and air quality data available
to the permit applicant. To construct a background concentration for
model input under the framework, permit applicants should consider the
representativeness of relevant emissions, air quality monitoring, and
pre-existing air quality modeling to appropriately represent background
concentrations for the cumulative impact analysis.
The EPA received numerous comments on the proposed revisions to
section 8 of the Guideline. Multiple commenters expressed their support
of the revisions to section 8.3 and the removal of the recommendation
of identifying sources which cause a significant concentration gradient
from the Guideline. Based on this support, the EPA is removing the
recommendations which highlight the use of significant concentration
gradients and finalizing the framework of stepwise considerations.
Several commenters expressed their perspective on the contents of
the framework of stepwise considerations for developing background
concentrations and its future implementation. Some commenters expressed
their concern that the framework would limit the flexibility that has
been afforded to permitting authorities, while other commenters stated
that the framework documents steps that have been unofficially used by
air agencies and modelers for many years. Additionally, some commenters
feel that the steps detailed in the framework do not remove the
ambiguity in the process of developing a representative background
concentration. The EPA recognizes that preferred methods for developing
background concentrations vary at both the State and permit-specific
level, which explains the variety of stances on the framework of
stepwise considerations. With this action, the EPA is finalizing the
proposed revisions to section 8 of the Guideline. These revisions
strike an appropriate balance of the interests raised by comments by
more clearly documenting the general steps recommended for determining
background concentrations while leaving discretion for and recommending
the exercise of professional judgement by the reviewing authority to
ensure that the background concentration is appropriately represented
in each cumulative impact analysis. In conjunction with the finalized
revisions to section 8 of the Guideline, the EPA is also finalizing the
Guidance on Developing Background Concentrations for Use in Modeling
Demonstrations.\10\ This guidance document details the EPA-recommended
framework with illustrative examples to assist permit applicants in
characterizing a credible and appropriately representative background
concentration for cumulative impact analyses including the
contributions from nearby sources in multi-source areas. The EPA
requested that the public submit comment through the docket associated
with the October 2023 proposed revisions to the Guideline and received
many comments requesting clarification or revisions which should be
incorporated in the finalized version of the guidance. A majority of
the comments were generally requests for the EPA to include examples
and additional details in the finalized version of the guidance. The
requests for additional details ranged from minor sentence revisions to
improve clarity to requests for specific metrics that may be used in
the process and requests for how to implement the framework for
specific modeling cases. The EPA agreed with the commenters requesting
examples and has incorporated hypothetical examples in the finalized
version of the guidance to help the stakeholder community implement the
framework of stepwise considerations. Additionally, the EPA has revised
the guidance to address many of the clarification concerns stated by
commenters.
---------------------------------------------------------------------------

\10\ U.S. Environmental Protection Agency, 2024. Guidance on
Developing Background Concentrations for Use in Modeling
Demonstrations. Publication No. EPA-454/R-24-003. Office of Air
Quality Planning and Standards, Research Triangle Park, NC.
---------------------------------------------------------------------------

3. Transition Period for Applicability of Revisions to the Guideline
As noted in the DATES section above, this rule is effective
December 30, 2024. For all regulatory applications covered under the
Guideline, the changes to the Addendum A preferred models and revisions
to the requirements and recommendations of the Guideline should be
integrated into the regulatory processes of respective reviewing
authorities and followed by applicants as quickly as practicable. The
EPA encourages the transition to the revised 2024 version of the
Guideline by no later than November 29, 2025. During the 1-year period
following promulgation, protocols for modeling analyses based on the
2017 version of the Guideline, which are submitted in a timely manner,
may be approved at the discretion of the appropriate reviewing
authority.
The EPA notes that some States have approved SIP provisions that
authorize the use of revised versions of the Guideline, whereas other
States have SIP provisions that will require revision to provide for
the use of a revised Guideline, such as the version addressed in this
notice. States that have incorporated an older version of the Guideline
into their SIPs in order to satisfy an infrastructure SIP requirement
under CAA section 110(a)(2) should update their regulations as
necessary to incorporate this latest version of the Guideline as soon
as practicable into their SIPs, but must do so no later than

[[Page 95040]]

February 7, 2027, which is the due date for 2024 PM<INF>2.5</INF>
infrastructure SIP submittals. For States that have chosen to satisfy
the modeling and permitting requirements of CAA section 110(a)(2) by
adopting specific versions of the Guideline in their State regulations,
the EPA expects States to update their regulations to include this most
recent version of the Guideline by the infrastructure SIP submittal due
date. The EPA will at that time be evaluating infrastructure SIP
submissions for compliance with applicable infrastructure SIP
requirements under CAA section 110, including CAA sections
110(a)(2)(K), (C), (D)(i)(II), and (J). However, the need for such an
update to a State or local regulation should not, in most cases,
preclude regulatory application of the changes to the Guideline adopted
in this rule in regulatory actions.
All applicants are encouraged to consult with their respective
reviewing authority and EPA Regional office as soon as possible to
assure acceptance of their modeling protocols and/or modeling
demonstration during this period of regulatory transition.
4. Revisions by Section
a. Throughout Appendix W to Part 51--Guideline on Air Quality
Models, the EPA is revising the phrase ``Appendix A'' to ``Addendum A''
in accordance with the requirements of the Government Printing Office
(GPO).
b. Section 1.0--Introduction
During publication, in the first sentence of paragraph (i), the
phrase ``Appendix A'' was separated, thereby ending the sentence with
``Appendix'' and inadvertently creating a subparagraph (A). The EPA is
correcting paragraph (i) so that the first sentence ends with the
phrase ``Addendum A,'' and including the rest of the text from the
inadvertently created paragraph (A).
c. Section 3.0--Preferred and Alternative Air Quality Models
The EPA is updating an outdated website link in section 3.0(b).
In sections 3.1.1(c) and 3.1.2(a), the phrase ``Appendix A'' was
separated, ending the sentences with ``Appendix'' and inadvertently
creating a subparagraph (A). The EPA is correcting these sections by
combining the inadvertently created subparagraph (A) with the sentences
that end with ``Appendix,'' revising the phrase to ``Addendum A,'' and
including the rest of the text from the inadvertently created
subparagraphs (A).
d. Section 4.0--Models for Carbon Monoxide, Lead, Sulfur Dioxide,
Nitrogen Dioxide and Primary Particulate Matter
The EPA is updating reference numbers where necessary due to added
references.
In sections 4.1(b) and 4.2.2(a), the phrase ``Appendix A'' was
separated, ending the sentences with ``Appendix'' and inadvertently
creating a subparagraph (A). The EPA is correcting these sections
combining the inadvertently created subparagraph (A) with the sentences
that end with ``Appendix,'' revising the phrase to ``Addendum A,'' and
including the rest of the text from the inadvertently created
subparagraphs (A).
In section 4.2.2.1, the EPA is adding a new paragraph (f) regarding
the use of AERMOD in certain overwater situations. A typographical
correction is made in section 4.2.2.1(b).
The EPA is amending section 4.2.2.3 to account for circumstances
where OCD is available to evaluate situations where shoreline
fumigation and/or platform downwash are important.
In section 4.2.3.4, the EPA is revising paragraph (e) to adopt the
Generic Reaction Set Method (GRSM) as a regulatory Tier 3 detailed
screening technique for NO<INF>2</INF> modeling demonstrations.
Sentences in this section are being updated to incorporate GRSM with
the existing regulatory Tier 3 screening techniques OLM and PVMRM. An
additional statement is made indicating GRSM model performance may be
better than OLM and PVMRM under certain source characterization
situations. The EPA also is adding two references to the section
including one for the peer-reviewed paper on development and evaluation
of GRSM, and a second reference to the EPA Technical Support Document
(TSD) on GRSM.
The EPA is revising Table 4-1 in section 4.2.3.4(f) to include GRSM
as a Tier 3 detailed screening option.
e. Section 5.0--Models for Ozone and Secondarily Formed Particulate
Matter
The EPA is updating reference numbers where necessary due to added
references.
In section 5.2, the EPA is revising paragraph (c) to include a
reference for guidance on the use of models to assess the impacts of
emissions from single sources on secondarily formed ozone and
PM<INF>2.5</INF>.
f. Section 6.0--Modeling for Air Quality Related Values and Other
Governmental Programs
The EPA is updating reference numbers where necessary due to added
references and is updating an outdated website link in section 6.3(a).
g. Section 7.0--General Modeling Considerations
The EPA is updating reference numbers where necessary due to added
references.
In section 7.2.3, the EPA is revising paragraph (b) to include the
addition of RLINE as a source type for use in regulatory applications
of AERMOD and remove references to specific distances that receptors
can be placed from the roadway.
Also in section 7.2.3, the EPA is revising paragraph (c) to include
RLINE as a source type that can be used to model mobile sources and
clarify that an area source can be categorized in AERMOD using the
AREA, LINE, or RLINE source type.
h. Section 8.0--Model Input Data
The EPA is updating reference numbers where necessary due to added
references.
The EPA is revising Table 8-1 and Table 8-2 to correct
typographical errors and update the footnotes in each of the tables.
The EPA is revising section 8.3.1 to address current EPA practices
and recommendations for determining the appropriate background
concentration as model input data for a new or modifying source(s) or
sources under consideration for a revised permit limit. This revision
provides a stepwise framework for modeling isolated single sources and
multi-source areas as part of a cumulative impact analysis. The EPA
also is removing the term ``significant concentration gradient'' and
its related content in section 8.3.1(a)(i) due to the ambiguity and
lack of definition of this term in the context of modeling multi-source
areas.
The EPA is removing paragraph (d) in section 8.3.2 and renumber
paragraphs (e) and (f) to (d) and (e), respectively. The content of
paragraph (d) is being included in the revisions of paragraph (a) in
section 8.3.2.
In section 8.3.3, the EPA is revising the content in section
8.3.3(b) on the recommendations for determining nearby sources to
explicitly model as part of a cumulative impact analysis. The EPA is
removing the content related to the term ``significant concentration
gradient'' in section 8.3.3(b)(i), section 8.3.3(b)(ii), and section
8.3.3(b)(iii) due

[[Page 95041]]

to the lack of definition of this term in the context of modeling
multi-source areas. The EPA is also removing an undefined acronym
inadvertently included in the October 2023 Guideline proposal in
section 8.3.3(b)(ii). Finally, the EPA is revising the example given in
section 8.3.3(d) to be consistent with the discussion of other sources
in section 8.3.1(a)(ii) and the revisions to Tables 8-1 and 8-2.
In section 8.4.1, the EPA is including buoy data as an example of
site-specific data as a result of the inclusion of the Coupled-Ocean
Atmosphere Response Experiment (COARE) algorithms to AERMET for marine
boundary layer processing. The EPA is also revising the heading for
section 8.4.1(d) to correct a capitalization typographical error.
The EPA is revising paragraph (a) of section 8.4.2 to note that
MMIF should be used to process prognostic meteorological data for both
land-based and overwater applications, and is revising paragraph (b) to
clarify that AERSURFACE should be used to calculate surface
characteristics for land-based data and AERMET calculates surface
characteristics for overwater applications. Also, the EPA is revising
paragraph (e) of this section to clarify that at least 1 year of site-
specific data applies to both land-based and overwater-based data.
The EPA is revising paragraph (a) of section 8.4.3.2 to remove
references to specific Web links and to state that users should refer
to the latest guidance documents for Web links.
The EPA is adding a new section 8.4.6 to discuss the implementation
of COARE for marine boundary layer processing and to renumber the
existing section 8.4.6 (in the 2017 Guideline) to a new section 8.4.7.
References to specific wind speed thresholds are being replaced with
guidance to consult the appropriate guidance documents for the latest
thresholds.
i. Section 9.0--Regulatory Application of Models
The EPA is updating reference numbers where necessary due to added
references.
In section 9.2.3, the EPA is revising the example given in section
9.2.3(a)(ii) to be consistent with the discussion of other sources in
section 8.3.1(a)(ii) and the revisions to Tables 8-1 and 8-2.
j. Section 10.0--References
The EPA is updating references in section 10.0 to remove outdated
website links and reflect current versions of guidance documents,
user's guides, and other supporting documentation where applicable. The
EPA also is adding references to support updates to the AERMOD Modeling
System described in this update to the Guideline.
5. Revisions to Addendum A to Appendix W to Part 51
a. Section A.0
The EPA is revising section A.0 to remove references that indicate
there are ``many'' preferred models while the number is currently only
three.
b. Section A.1
The EPA is revising the References section to include additional
references that support our updates to the AERMOD Modeling System
consistent with our October 2023 proposed revisions to the Guideline
and AERMOD.
In the Abstract section, the EPA is adding line type sources as one
of the source types AERMOD can simulate.
The EPA is revising section A.1(a) to include overwater
applications for regulatory modeling where shoreline fumigation and/or
platform downwash are not important to facilitate the use of AERMOD
with COARE processing. This revision removes the need to request an
alternative model demonstration for such applications. The EPA also is
clarifying elevation data that can be used in AERMOD, specifically the
change in the name of the U.S. Geological Survey (USGS) National
Elevation Dataset (NED) to 3D Elevation Program (3DEP). For
consistency, references to NED are being updated to 3DEP throughout
section A.1.
The EPA is revising section A.1(b) to include prognostic data as
meteorological input to the AERMOD Modeling System, as applicable.
The EPA is revising section A.1(l) to include the Generic Reaction
Set Method in the discussion on chemical transformation in AERMOD. We
also are clarifying the status of the different deposition options in
A.1(l).
The EPA is revising section A.1(n) to include references to
additional evaluation studies to support our updates to the AERMOD
Modeling System.
The EPA is updating a reference added in the October 2023 Guideline
proposal in section A.1 from a manuscript to an existing EPA Technical
Support Document.
c. Section A.3
In section A.3, the EPA is removing the reference to the Bureau of
Ocean Energy Management's (BOEM) outdated guidance.

IV. Ongoing Model Development

With the release of AERMOD version 24142, no additional beta
options remain within AERMOD. The alpha options in version 23132 have
all been retained in version 24142. The EPA is committed to the
continued maintenance and development of AERMOD to expand the model's
capabilities and improve performance where needed. Ongoing model
development priorities for model improvement, many of which are
represented in the version 24142 as alpha options, are described below.
<bullet> Modifications to PRIME Building Downwash
Beginning with AERMOD version 19191, two distinct sets of alpha
options were added that modify the formulation of the building downwash
algorithm, PRIME. The two sets of options, ORD_DWNW and AWMADWNW, were
developed independently by the EPA's Office of Development and Research
(ORD) and the Air & Waste Management Association (A&WMA), respectively.
With a couple of exceptions, the options within each set can be
employed individually or combined with other options from each set. In
addition to these alpha options that modify the formulation of PRIME,
are the building input parameters required by the algorithm. In
conjunction with the assessment and evaluation of these alpha options,
the EPA is focused on improvement of the building preprocessor,
BPIPPRM, and the parameterization of the buildings that is input to
AERMOD.
<bullet> Offshore Modeling
To enhance AERMOD's offshore modeling capabilities with the goal of
replacing the Offshore Coastal Dispersion (OCD) dispersion model as the
EPA's preferred model for offshore dispersion modeling applications, a
platform downwash alpha option (PLATFORM), adapted from OCD, was
incorporated into AERMOD version 22112. This model enhancement
specifically treats building downwash effects from raised offshore
drilling platforms. The PLATFORM option continues to undergo
refinements and evaluation. In addition to the PLATFORM alpha option,
the EPA is implementing a shoreline fumigation algorithm into AERMOD,
also needed for the eventual goal of replacing the OCD model.
<bullet> Extended RLINE Source Type Including Barriers and
Depressed Roadways
The extended RLINE source type (RLINEXT) source type was
implemented in AERMOD version

[[Page 95042]]

18181 as an alpha option that allows for a more refined
characterization of an individual road segment. It accepts separate
inputs for the elevations of each end of the road segment with added
capability to model road segments that include roadway barriers
(RBARRIER) and/or are characterized as depressed roadways (RDEPRESS).
RBARRIER and RDEPRESS are also alpha options and can only be used in
conjunction with the RLINEXT source type. The development of the
RLINEXT source type and accompanying options to account for barriers
and depressed roadways is ongoing.
<bullet> Highly Buoyant Plume
A Highly Buoyant Plume (HBP) option was implemented as an alpha
option beginning with AERMOD version 23132 to explore and refine
AERMOD's treatment of the penetrated plume. A penetrated plume occurs
when a plume is released into the mixed layer, and a portion of the
plume eventually penetrates the top of the mixed layer during
convective hours as it continues to rise due to either buoyancy or
momentum. The BLP alpha option is only applicable to POINT source
types.
<bullet> Aircraft Plume Rise
Beginning with AERMOD version 23132, the ARCFTOPT alpha option was
added with the goal to extend the capabilities of AERMOD to
appropriately model emissions from aircraft on the ground and during
takeoffs and landings. The ARCFTOPT option extends the AREA and VOLUME
source type inputs to account for the buoyancy and horizontal momentum
of aircraft emissions.
<bullet> Low Wind Default Overrides (LOW_WIND)
A LOW_WIND option was first implemented as a collection of non-
regulatory beta test options in AERMOD version 12345 (LOWWIND1 and
LOWWIND2) and expanded in version 15481(LOWWIND3), before the alpha/
beta framework was implemented. Each of these options altered the
default model values for minimum sigma-v, minimum wind speed, and the
minimum meander factor with different combinations of hardcoded values.
Though the original LOW_WIND beta test options are no longer
implemented in AERMOD, the LOW_WIND option was recategorized as an
alpha option in AERMOD version 18181 to include a number of user
defined default overrides for wind data parameters. The LOW_WIND option
in version 24142 enables the user to override AERMOD default values
with user-defined values for one or more of the following parameters:
[cir] Minimum standard deviation of the lateral velocity to the
average wind direction;
[cir] Minimum mean wind speed;
[cir] Minimum and maximum meander factor;
[cir] Minimum standard deviation of the vertical wind speed; and
[cir] Time scale for random dispersion.

V. Statutory and Executive Order Reviews

Additional information about these statutes and Executive Orders
can be found at <a href="https://www.epa.gov/laws-regulations/laws-and-executive-orders">https://www.epa.gov/laws-regulations/laws-and-executive-orders</a>.

A. Executive Order 12866: Regulatory Planning and Review and Executive
Order 14094: Modernizing Regulatory Review

This action is not a significant regulatory action as defined in
Executive Order 12866, as amended by Executive Order 14094, and was,
therefore, not subject to a requirement for Executive Order 12866
review.

B. Paperwork Reduction Act (PRA)

This action does not impose an information collection burden under
the PRA. This action does not contain any information collection
activities, nor does it add any information collection requirements
beyond those imposed by existing New Source Review requirements.

C. Regulatory Flexibility Act (RFA)

I certify that this action will not have a significant economic
impact on a substantial number of small entities under the RFA. This
action will not impose any requirements on small entities. This action
finalizes revisions to the Guideline, including enhancements to the
formulation and application of the EPA's near-field dispersion modeling
system, AERMOD, and updates to the recommendations for the development
of appropriate background concentration for cumulative impact analyses.
Use of the models and/or techniques described in this action is not
expected to pose any additional burden on small entities.

D. Unfunded Mandates Reform Act (UMRA)

This action does not contain an unfunded mandate as described in
UMRA, 2 U.S.C. 1531-1538. This action imposes no enforceable duty on
any State, local or Tribal governments or the private sector.

E. Executive Order 13132: Federalism

This action does not have federalism implications. It will not have
substantial direct effects on the States, on the relationship between
the national government and the States, or on the distribution of power
and responsibilities among the various levels of government.

F. Executive Order 13175: Consultation and Coordination With Indian
Tribal Governments

This action does not have Tribal implications, as specified in
Executive Order 13175. This action provides final revisions to the
Guideline which is used by the EPA, other Federal, State, territorial,
local, and Tribal air quality agencies, and industry to prepare and
review preconstruction permit applications, SIP submittals and
revisions, determinations of conformity, and other air quality
assessments required under EPA regulation. Separate from this action,
the Tribal Air Rule implements the provisions of section 301(d) of the
CAA authorizing eligible Tribes to implement their own Tribal air
program. Thus, Executive Order 13175 does not apply to this action.
The EPA specifically solicited comments on the October 2023
proposed revisions to the Guideline from Tribal officials and did not
formally receive any Tribal comments during the public comment period
for the rule. Subsequently, the EPA provided information regarding this
final action to the Tribes during a monthly National Tribal Air
Association (NTAA) call earlier in 2024 and will continue to provide
any new or subsequent updates to EPA modeling guidance and other
regulatory compliance demonstration related topics upon request of the
NTAA.

G. Executive Order 13045: Protection of Children From Environmental
Health Risks and Safety Risks

The EPA interprets Executive Order 13045 as applying only to those
regulatory actions that concern environmental health or safety risks
that the EPA has reason to believe may disproportionately affect
children, per the definition of ``covered regulatory action'' in
section 2-202 of the Executive Order. This action does not address an
environmental health risk or safety risk that may disproportionately
affect children. Therefore, this action is not subject to Executive
Order 13045. The EPA's Policy on Children's Health also does not apply.

[[Page 95043]]

H. Executive Order 13211: Actions Concerning Regulations That
Significantly Affect Energy Supply, Distribution, or Use

This action is not subject to Executive Order 13211, because it is
not a significant regulatory action under Executive Order 12866.

I. National Technology Transfer and Advancement Act

This rulemaking does not involve technical standards.

J. Executive Order 12898: Federal Actions To Address Environmental
Justice in Minority Populations and Low-Income Populations and
Executive Order 14096: Revitalizing Our Nation's Commitment to
Environmental Justice for All

The EPA believes that this type of action cannot be evaluated with
respect to potentially disproportionate and adverse effects on
communities with environmental justice concerns because this final
action does not regulate air pollutant emissions or establish an
environmental health or safety standard. This action finalizes
revisions to the Guideline, including enhancements to the formulations
and application of EPA's near-field dispersion modeling system, AERMOD,
that would assist and expand assessment of environmental considerations
in required compliance demonstrations across various CAA programs.
The EPA identifies and addresses environmental justice concerns
through continuing efforts to improve the scientific formulations of
the EPA's air quality models, increase model overall performance, and
reduce uncertainties of model projections for regulatory applications,
which ultimately provides for protection of the environment and human
health. While the EPA does not expect this action to directly impact
air quality, the revisions are important because the Guideline is used
by the EPA, other Federal, State, territorial, local, and Tribal air
quality agencies, and industry to prepare and review preconstruction
permit applications, SIP submittals and revisions, determinations of
conformity, and other air quality assessments required under EPA
regulation and serves as a benchmark of consistency across the nation.
This consistency has value to all communities including communities
with environmental justice concerns.

K. Congressional Review Act (CRA)

This action is subject to the Congressional Review Act (CRA), and
the EPA will submit a rule report to each House of the Congress and to
the Comptroller General of the United States. This action is not a
``major rule'' as defined by 5 U.S.C. 804(2).

List of Subjects in 40 CFR Part 51

Environmental protection, Administrative practice and procedure,
Air pollution control, Carbon monoxide, Criteria pollutants,
Intergovernmental relations, Lead, Mobile sources, Nitrogen oxides,
Ozone, Particulate Matter, Reporting and recordkeeping requirements,
Stationary sources, Sulfur oxides.

Michael S. Regan,
Administrator.
For the reasons stated in the preamble, the Environmental
Protection Agency is amending title 40, chapter I of the Code of
Federal Regulations as follows:

PART 51--REQUIREMENTS FOR PREPARATION, ADOPTION, AND SUBMITTAL OF
IMPLEMENTATION PLANS

0
1. The authority citation for part 51 continues to read as follows:

Authority: 23 U.S.C. 101; 42 U.S.C. 7401-7671q.

0
2. Appendix W to part 51 is revised to read as follows:

APPENDIX W TO PART 51--GUIDELINE ON AIR QUALITY MODELS

Preface

a. Industry and control agencies have long expressed a need for
consistency in the application of air quality models for regulatory
purposes. In the 1977 Clean Air Act (CAA), Congress mandated such
consistency and encouraged the standardization of model
applications. The Guideline on Air Quality Models (hereafter,
Guideline) was first published in April 1978 to satisfy these
requirements by specifying models and providing guidance for their
use. The Guideline provides a common basis for estimating the air
quality concentrations of criteria pollutants used in assessing
control strategies and developing emissions limits.
b. The continuing development of new air quality models in
response to regulatory requirements and the expanded requirements
for models to cover even more complex problems have emphasized the
need for periodic review and update of guidance on these techniques.
Historically, three primary activities have provided direct input to
revisions of the Guideline. The first is a series of periodic EPA
workshops and modeling conferences conducted for the purpose of
ensuring consistency and providing clarification in the application
of models. The second activity was the solicitation and review of
new models from the technical and user community. In the March 27,
1980 Federal Register, a procedure was outlined for the submittal of
privately developed models to the EPA. After extensive evaluation
and scientific review, these models, as well as those made available
by the EPA, have been considered for recognition in the Guideline.
The third activity is the extensive on-going research efforts by the
EPA and others in air quality and meteorological modeling.
c. Based primarily on these three activities, new sections and
topics have been included as needed. The EPA does not make changes
to the Guideline on a predetermined schedule, but rather on an as-
needed basis. The EPA believes that revisions of the Guideline
should be timely and responsive to user needs and should involve
public participation to the greatest possible extent. All future
changes to the Guideline will be proposed and finalized in the
Federal Register. Information on the current status of modeling
guidance can always be obtained from the EPA's Regional offices.

Table of Contents

List of Tables

1.0 Introduction
2.0 Overview of Model Use
2.1 Suitability of Models
2.1.1 Model Accuracy and Uncertainty
2.2 Levels of Sophistication of Air Quality Analyses and Models
2.3 Availability of Models
3.0 Preferred and Alternative Air Quality Models
3.1 Preferred Models
3.1.1 Discussion
3.1.2 Requirements
3.2 Alternative Models
3.2.1 Discussion
3.2.2 Requirements
3.3 EPA's Model Clearinghouse
4.0 Models for Carbon Monoxide, Lead, Sulfur Dioxide, Nitrogen
Dioxide and Primary Particulate Matter
4.1 Discussion
4.2 Requirements
4.2.1 Screening Models and Techniques
4.2.1.1 AERSCREEN
4.2.1.2 CTSCREEN
4.2.1.3 Screening in Complex Terrain
4.2.2 Refined Models
4.2.2.1 AERMOD
4.2.2.2 CTDMPLUS
4.2.2.3 OCD
4.2.3 Pollutant Specific Modeling Requirements
4.2.3.1 Models for Carbon Monoxide
4.2.3.2 Models for Lead
4.2.3.3 Models for Sulfur Dioxide
4.2.3.4 Models for Nitrogen Dioxide
4.2.3.5 Models for PM<INF>2.5</INF>
4.2.3.6 Models for PM<INF>10</INF>
5.0 Models for Ozone and Secondarily Formed Particulate Matter
5.1 Discussion
5.2 Recommendations
5.3 Recommended Models and Approaches for Ozone
5.3.1 Models for NAAQS Attainment Demonstrations and Multi-
Source Air Quality Assessments
5.3.2 Models for Single-Source Air Quality Assessments
5.4 Recommended Models and Approaches for Secondarily Formed
PM<INF>2.5</INF>

[[Page 95044]]

5.4.1 Models for NAAQS Attainment Demonstrations and Multi-
Source Air Quality Assessments
5.4.2 Models for Single-Source Air Quality Assessments
6.0 Modeling for Air Quality Related Values and Other Governmental
Programs
6.1 Discussion
6.2 Air Quality Related Values
6.2.1 Visibility
6.2.1.1 Models for Estimating Near-Field Visibility Impairment
6.2.1.2 Models for Estimating Visibility Impairment for Long-
Range Transport
6.2.2 Models for Estimating Deposition Impacts
6.3 Modeling Guidance for Other Governmental Programs
7.0 General Modeling Considerations
7.1 Discussion
7.2 Recommendations
7.2.1 All sources
7.2.1.1 Dispersion Coefficients
7.2.1.2 Complex Winds
7.2.1.3 Gravitational Settling and Deposition
7.2.2 Stationary Sources
7.2.2.1 Good Engineering Practice Stack Height
7.2.2.2 Plume Rise
7.2.3 Mobile Sources
8.0 Model Input Data
8.1 Modeling Domain
8.1.1 Discussion
8.1.2 Requirements
8.2 Source Data
8.2.1 Discussion
8.2.2 Requirements
8.3 Background Concentrations
8.3.1 Discussion
8.3.2 Recommendations for Isolated Single Sources
8.3.3 Recommendations for Multi-Source Areas
8.4 Meteorological Input Data
8.4.1 Discussion
8.4.2 Recommendations and Requirements
8.4.3 National Weather Service Data
8.4.3.1 Discussion
8.4.3.2 Recommendations
8.4.4 Site-Specific Data
8.4.4.1 Discussion
8.4.4.2 Recommendations
8.4.5 Prognostic Meteorological Data
8.4.5.1 Discussion
8.4.5.2 Recommendations
8.4.6 Marine Boundary Layer Environments
8.4.6.1 Discussion
8.4.6.2 Recommendations
8.4.7 Treatment of Near-Calms and Calms
8.4.7.1 Discussion
8.4.7.2 Recommendations
9.0 Regulatory Application of Models
9.1 Discussion
9.2 Recommendations
9.2.1 Modeling Protocol
9.2.2 Design Concentration and Receptor Sites
9.2.3 NAAQS and PSD Increments Compliance Demonstrations for New
or Modified Sources
9.2.3.1 Considerations in Developing Emissions Limits
9.2.4 Use of Measured Data in Lieu of Model Estimates
10.0 References

Addendum A to Appendix W of Part 51--Summaries of Preferred Air Quality
Models

List of Tables

------------------------------------------------------------------------
Table No. Title
------------------------------------------------------------------------
8-1....................................... Point Source Model Emission
Inputs for SIP Revisions of
Inert Pollutants.
8-2....................................... Point Source Model Emission
Inputs for NAAQS Compliance
in PSD Demonstrations.
------------------------------------------------------------------------

1.0 Introduction

a. The Guideline provides air quality modeling techniques that
should be applied to State Implementation Plan (SIP) submittals and
revisions, to New Source Review (NSR), including new or modifying
sources under Prevention of Significant Deterioration
(PSD),1 2 3 conformity analyses,\4\ and other air quality
assessments required under EPA regulation. Applicable only to
criteria air pollutants, the Guideline is intended for use by the
EPA Regional offices in judging the adequacy of modeling analyses
performed by the EPA, by State, local, and Tribal permitting
authorities, and by industry. It is appropriate for use by other
Federal government agencies and by State, local, and Tribal agencies
with air quality and land management responsibilities. The Guideline
serves to identify, for all interested parties, those modeling
techniques and databases that the EPA considers acceptable. The
Guideline is not intended to be a compendium of modeling techniques.
Rather, it should serve as a common measure of acceptable technical
analysis when supported by sound scientific judgment.
b. Air quality measurements \5\ are routinely used to
characterize ambient concentrations of criteria pollutants
throughout the nation but are rarely sufficient for characterizing
the ambient impacts of individual sources or demonstrating adequacy
of emissions limits for an existing source due to limitations in
spatial and temporal coverage of ambient monitoring networks. The
impacts of new sources that do not yet exist, and modifications to
existing sources that have yet to be implemented, can only be
determined through modeling. Thus, models have become a primary
analytical tool in most air quality assessments. Air quality
measurements can be used in a complementary manner to air quality
models, with due regard for the strengths and weaknesses of both
analysis techniques, and are particularly useful in assessing the
accuracy of model estimates.
c. It would be advantageous to categorize the various regulatory
programs and to apply a designated model to each proposed source
needing analysis under a given program. However, the diversity of
the nation's topography and climate, and variations in source
configurations and operating characteristics dictate against a
strict modeling ``cookbook.'' There is no one model capable of
properly addressing all conceivable situations even within a broad
category such as point sources. Meteorological phenomena associated
with threats to air quality standards are rarely amenable to a
single mathematical treatment; thus, case-by-case analysis and
judgment are frequently required. As modeling efforts become more
complex, it is increasingly important that they be directed by
highly competent individuals with a broad range of experience and
knowledge in air quality meteorology. Further, they should be
coordinated closely with specialists in emissions characteristics,
air monitoring and data processing. The judgment of experienced
meteorologists, atmospheric scientists, and analysts is essential.
d. The model that most accurately estimates concentrations in
the area of interest is always sought. However, it is clear from the
needs expressed by the EPA Regional offices, by State, local, and
Tribal agencies, by many industries and trade associations, and also
by the deliberations of Congress, that consistency in the selection
and application of models and databases should also be sought, even
in case-by-case analyses. Consistency ensures that air quality
control agencies and the general public have a common basis for
estimating pollutant concentrations, assessing control strategies,
and specifying emissions limits. Such consistency is not, however,
promoted at the expense of model and database accuracy. The
Guideline provides a consistent basis for selection of the most
accurate models and databases for use in air quality assessments.
e. Recommendations are made in the Guideline concerning air
quality models and techniques, model evaluation procedures, and
model input databases and related requirements. The guidance
provided here should be followed in air quality analyses relative to
SIPs, NSR, and in supporting analyses required by the EPA and by
State, local, and Tribal permitting authorities. Specific models are
identified for particular applications. The EPA may approve the use
of an alternative model or technique that can be demonstrated to be
more appropriate than those recommended in the Guideline. In all
cases, the model or technique applied to a given situation should be
the one that provides the most accurate representation of
atmospheric transport, dispersion, and chemical transformations in
the area of interest. However, to ensure consistency, deviations
from the Guideline should be carefully documented as part of the
public record and fully supported by the appropriate reviewing
authority, as discussed later.
f. From time to time, situations arise requiring clarification
of the intent of the guidance on a specific topic. Periodic
workshops are held with EPA headquarters, EPA Regional offices, and
State, local, and Tribal agency modeling representatives to ensure
consistency in modeling guidance and to promote the use of more
accurate air quality models, techniques, and databases. The
workshops serve to provide further explanations of Guideline
requirements to the EPA Regional offices and workshop materials are
issued with this clarifying information. In addition, findings from
ongoing research programs, new model development, or results from
model

[[Page 95045]]

evaluations and applications are continuously evaluated. Based on
this information, changes in the applicable guidance may be
indicated and appropriate revisions to the Guideline may be
considered.
g. All changes to the Guideline must follow rulemaking
requirements since the Guideline is codified in Appendix W to 40
Code of Federal Regulations (CFR) part 51. The EPA will promulgate
rules in the Federal Register to amend this appendix. The EPA
utilizes the existing procedures under CAA section 320 that requires
the EPA to conduct a conference on air quality modeling at least
every 3 years (CAA 320, 42 U.S.C. 7620). These modeling conferences
are intended to develop standardized air quality modeling procedures
and form the basis for associated revisions to this Guideline in
support of the EPA's continuing effort to prescribe with
``reasonable particularity'' air quality models and meteorological
and emission databases suitable for modeling national ambient air
quality standards (NAAQS) \6\ and PSD increments. Ample opportunity
for public comment will be provided for each proposed change and
public hearings scheduled.
h. A wide range of topics on modeling and databases are
discussed in the Guideline. Section 2 gives an overview of models
and their suitability for use in regulatory applications. Section 3
provides specific guidance on the determination of preferred air
quality models and on the selection of alternative models or
techniques. Sections 4 through 6 provide recommendations on modeling
techniques for assessing criteria pollutant impacts from single and
multiple sources with specific modeling requirements for selected
regulatory applications. Section 7 discusses general considerations
common to many modeling analyses for stationary and mobile sources.
Section 8 makes recommendations for data inputs to models including
source, background air quality, and meteorological data. Section 9
summarizes how estimates and measurements of air quality are used in
assessing source impact and in evaluating control strategies.
i. Appendix W to 40 CFR part 51 contains an addendum: Addendum
A. Thus, when reference is made to ``Addendum A'' in this document,
it refers to Addendum A to Appendix W to 40 CFR part 51. Addendum A
contains summaries of refined air quality models that are
``preferred'' for particular applications; both EPA models and
models developed by others are included.

2.0 Overview of Model Use

a. Increasing reliance has been placed on concentration
estimates from air quality models as the primary basis for
regulatory decisions concerning source permits and emission control
requirements. In many situations, such as review of a proposed new
source, no practical alternative exists. Before attempting to
implement the guidance contained in this document, the reader should
be aware of certain general information concerning air quality
models and their evaluation and use. Such information is provided in
this section.

2.1 Suitability of Models

a. The extent to which a specific air quality model is suitable
for the assessment of source impacts depends upon several factors.
These include: (1) the topographic and meteorological complexities
of the area; (2) the detail and accuracy of the input databases,
i.e., emissions inventory, meteorological data, and air quality
data; (3) the manner in which complexities of atmospheric processes
are handled in the model; (4) the technical competence of those
undertaking such simulation modeling; and (5) the resources
available to apply the model. Any of these factors can have a
significant influence on the overall model performance, which must
be thoroughly evaluated to determine the suitability of an air
quality model to a particular application or range of applications.
b. Air quality models are most accurate and reliable in areas
that have gradual transitions of land use and topography.
Meteorological conditions in these areas are spatially uniform such
that observations are broadly representative and air quality model
projections are not further complicated by a heterogeneous
environment. Areas subject to major topographic influences
experience meteorological complexities that are often difficult to
measure and simulate. Models with adequate performance are available
for increasingly complex environments. However, they are resource
intensive and frequently require site-specific observations and
formulations. Such complexities and the related challenges for the
air quality simulation should be considered when selecting the most
appropriate air quality model for an application.
c. Appropriate model input data should be available before an
attempt is made to evaluate or apply an air quality model. Assuming
the data are adequate, the greater the detail with which a model
considers the spatial and temporal variations in meteorological
conditions and permit-enforceable emissions, the greater the ability
to evaluate the source impact and to distinguish the effects of
various control strategies.
d. There are three types of models that have historically been
used in the regulatory demonstrations applicable in the Guideline,
each having strengths and weaknesses that lend themselves to
particular regulatory applications.
i. Gaussian plume models use a ``steady-state'' approximation,
which assumes that over the model time step, the emissions,
meteorology and other model inputs, are constant throughout the
model domain, resulting in a resolved plume with the emissions
distributed throughout the plume according to a Gaussian
distribution. This formulation allows Gaussian models to estimate
near-field impacts of a limited number of sources at a relatively
high resolution, with temporal scales of an hour and spatial scales
of meters. However, this formulation allows for only relatively
inert pollutants, with very limited considerations of transformation
and removal (e.g., deposition), and further limits the domain for
which the model may be used. Thus, Gaussian models may not be
appropriate if model inputs are changing sharply over the model time
step or within the desired model domain, or if more advanced
considerations of chemistry are needed.
ii. Lagrangian puff models, on the other hand, are non-steady-
state, and assume that model input conditions are changing over the
model domain and model time step. Lagrangian models can also be used
to determine near- and far-field impacts from a limited number of
sources. Traditionally, Lagrangian models have been used for
relatively inert pollutants, with slightly more complex
considerations of removal than Gaussian models. Some Lagrangian
models treat in-plume gas and particulate chemistry. However, these
models require time and space varying concentration fields of
oxidants and, in the case of fine particulate matter
(PM<INF>2.5</INF>), neutralizing agents, such as ammonia. Reliable
background fields are critical for applications involving secondary
pollutant formation because secondary impacts generally occur when
in-plume precursors mix and react with species in the background
atmosphere.7 8 These oxidant and neutralizing agents are
not routinely measured, but can be generated with a three-
dimensional photochemical grid model.
iii. Photochemical grid models are three-dimensional Eulerian
grid-based models that treat chemical and physical processes in each
grid cell and use diffusion and transport processes to move chemical
species between grid cells.\9\ Eulerian models assume that emissions
are spread evenly throughout each model grid cell. At coarse grid
resolutions, Eulerian models have difficulty with fine scale
resolution of individual plumes. However, these types of models can
be appropriately applied for assessment of near-field and regional
scale reactive pollutant impacts from specific
sources7 10 11 12 or all sources.13 14 15
Photochemical grid models simulate a more realistic environment for
chemical transformation,7 12 but simulations can be more
resource intensive than Lagrangian or Gaussian plume models.
e. Competent and experienced meteorologists, atmospheric
scientists, and analysts are an essential prerequisite to the
successful application of air quality models. The need for such
specialists is critical when sophisticated models are used or the
area has complicated meteorological or topographic features. It is
important to note that a model applied improperly or with
inappropriate data can lead to serious misjudgments regarding the
source impact or the effectiveness of a control strategy.
f. The resource demands generated by use of air quality models
vary widely depending on the specific application. The resources
required may be important factors in the selection and use of a
model or technique for a specific analysis. These resources depend
on the nature of the model and its complexity, the detail of the
databases, the difficulty of the application, the amount and level
of expertise required, and the costs of manpower and computational
facilities.

2.1.1 Model Accuracy and Uncertainty

a. The formulation and application of air quality models are
accompanied by several sources of uncertainty. ``Irreducible''
uncertainty stems from the ``unknown'' conditions, which may not be
explicitly accounted for in the model (e.g., the turbulent velocity
field). Thus, there are likely to be deviations from the observed

[[Page 95046]]

concentrations in individual events due to variations in the unknown
conditions. ``Reducible'' uncertainties \16\ are caused by: (1)
uncertainties in the ``known'' input conditions (e.g., emission
characteristics and meteorological data); (2) errors in the measured
concentrations; and (3) inadequate model physics and formulation.
b. Evaluations of model accuracy should focus on the reducible
uncertainty associated with physics and the formulation of the
model. The accuracy of the model is normally determined by an
evaluation procedure which involves the comparison of model
concentration estimates with measured air quality data.\17\ The
statement of model accuracy is based on statistical tests or
performance measures such as bias, error, correlation, etc.\18\ \19\
c. Since the 1980's, the EPA has worked with the modeling
community to encourage development of standardized model evaluation
methods and the development of continually improved methods for the
characterization of model performance.\16\ \18\ \20\ \21\ \22\ There
is general consensus on what should be considered in the evaluation
of air quality models. Namely, quality assurance planning,
documentation and scrutiny should be consistent with the intended
use and should include:
<bullet> Scientific peer review;
<bullet> Supportive analyses (diagnostic evaluations, code
verification, sensitivity analyses);
<bullet> Diagnostic and performance evaluations with data
obtained in trial locations; and
<bullet> Statistical performance evaluations in the
circumstances of the intended applications.
Performance evaluations and diagnostic evaluations assess
different qualities of how well a model is performing, and both are
needed to establish credibility within the client and scientific
community.
d. Performance evaluations allow the EPA and model users to
determine the relative performance of a model in comparison with
alternative modeling systems. Diagnostic evaluations allow
determination of a model capability to simulate individual processes
that affect the results, and usually employ smaller spatial/temporal
scale data sets (e.g., field studies). Diagnostic evaluations enable
the EPA and model users to build confidence that model predictions
are accurate for the right reasons. However, the objective
comparison of modeled concentrations with observed field data
provides only a partial means for assessing model performance. Due
to the limited supply of evaluation datasets, there are practical
limits in assessing model performance. For this reason, the
conclusions reached in the science peer reviews and the supportive
analyses have particular relevance in deciding whether a model will
be useful for its intended purposes.

2.2 Levels of Sophistication of Air Quality Analyses and Models

a. It is desirable to begin an air quality analysis by using
simplified and conservative methods followed, as appropriate, by
more complex and refined methods. The purpose of this approach is to
streamline the process and sufficiently address regulatory
requirements by eliminating the need of more detailed modeling when
it is not necessary in a specific regulatory application. For
example, in the context of a PSD permit application, a simplified
and conservative analysis may be sufficient where it shows the
proposed construction clearly will not cause or contribute to
ambient concentrations in excess of either the NAAQS or the PSD
increments.\2\ \3\
b. There are two general levels of sophistication of air quality
models. The first level consists of screening models that provide
conservative modeled estimates of the air quality impact of a
specific source or source category based on simplified assumptions
of the model inputs (e.g., preset, worst-case meteorological
conditions). In the case of a PSD assessment, if a screening model
indicates that the increase in concentration attributable to the
source could cause or contribute to a violation of any NAAQS or PSD
increment, then the second level of more sophisticated models should
be applied unless appropriate controls or operational restrictions
are implemented based on the screening modeling.
c. The second level consists of refined models that provide more
detailed treatment of physical and chemical atmospheric processes,
require more detailed and precise input data, and provide spatially
and temporally resolved concentration estimates. As a result, they
provide a more sophisticated and, at least theoretically, a more
accurate estimate of source impact and the effectiveness of control
strategies.
d. There are situations where a screening model or a refined
model is not available such that screening and refined modeling are
not viable options to determine source-specific air quality impacts.
In such situations, a screening technique or reduced-form model may
be viable options for estimating source impacts.
i. Screening techniques are differentiated from a screening
model in that screening techniques are approaches that make
simplified and conservative assumptions about the physical and
chemical atmospheric processes important to determining source
impacts, while screening models make assumptions about conservative
inputs to a specific model. The complexity of screening techniques
ranges from simplified assumptions of chemistry applied to refined
or screening model output to sophisticated approximations of the
chemistry applied within a refined model.
ii. Reduced-form models are computationally efficient simulation
tools for characterizing the pollutant response to specific types of
emission reductions for a particular geographic area or background
environmental conditions that reflect underlying atmospheric science
of a refined model but reduce the computational resources of running
a complex, numerical air quality model such as a photochemical grid
model.
In such situations, an attempt should be made to acquire or
improve the necessary databases and to develop appropriate
analytical techniques, but the screening technique or reduced-form
model may be sufficient in conducting regulatory modeling
applications when applied in consultation with the EPA Regional
office.
e. Consistent with the general principle described in paragraph
2.2(a), the EPA may establish a demonstration tool or method as a
sufficient means for a user or applicant to make a demonstration
required by regulation, either by itself or as part of a modeling
demonstration. To be used for such regulatory purposes, such a tool
or method must be reflected in a codified regulation or have a well-
documented technical basis and reasoning that is contained or
incorporated in the record of the regulatory decision in which it is
applied.

2.3 Availability of Models

a. For most of the screening and refined models discussed in the
Guideline, codes, associated documentation and other useful
information are publicly available for download from the EPA's
Support Center for Regulatory Atmospheric Modeling (SCRAM) website
at <a href="https://www.epa.gov/scram">https://www.epa.gov/scram</a>. This is a website with which air
quality modelers should become familiar and regularly visit for
important model updates and additional clarifications and revisions
to modeling guidance documents that are applicable to EPA programs
and regulations. Codes and documentation may also be available from
the National Technical Information Service (NTIS), <a href="https://www.ntis.gov">https://www.ntis.gov</a>, and, when available, is referenced with the
appropriate NTIS accession number.

3.0 Preferred and Alternative Air Quality Models

a. This section specifies the approach to be taken in
determining preferred models for use in regulatory air quality
programs. The status of models developed by the EPA, as well as
those submitted to the EPA for review and possible inclusion in this
Guideline, is discussed in this section. The section also provides
the criteria and process for obtaining EPA approval for use of
alternative models for individual cases in situations where the
preferred models are not applicable or available. Additional sources
of relevant modeling information are: the EPA's Model Clearinghouse
\23\ (section 3.3); EPA modeling conferences; periodic Regional,
State, and Local Modelers' Workshops; and the EPA's SCRAM website
(section 2.3).
b. When approval is required for a specific modeling technique
or analytical procedure in this Guideline, we refer to the
``appropriate reviewing authority.'' Many States and some local
agencies administer NSR permitting under programs approved into
SIPs. In some EPA regions, Federal authority to administer NSR
permitting and related activities has been delegated to State or
local agencies. In these cases, such agencies ``stand in the shoes''
of the respective EPA Region. Therefore, depending on the
circumstances, the appropriate reviewing authority may be an EPA
Regional office, a State, local, or Tribal agency, or perhaps the
Federal Land Manager (FLM). In some cases, the Guideline requires
review and approval of the use of an alternative model by the EPA
Regional office (sometimes stated as ``Regional Administrator'').
For all approvals of alternative models or

[[Page 95047]]

techniques, the EPA Regional office will coordinate and seek
concurrence with the EPA's Model Clearinghouse. If there is any
question as to the appropriate reviewing authority, you should
contact the EPA Regional office modeling contact (<a href="https://www.epa.gov/scram/air-modeling-regional-contacts">https://www.epa.gov/scram/air-modeling-regional-contacts</a>), whose
jurisdiction generally includes the physical location of the source
in question and its expected impacts.
c. In all regulatory analyses, early discussions among the EPA
Regional office staff, State, local, and Tribal agency staff,
industry representatives, and where appropriate, the FLM, are
invaluable and are strongly encouraged. Prior to the actual
analyses, agreement on the databases to be used, modeling techniques
to be applied, and the overall technical approach helps avoid
misunderstandings concerning the final results and may reduce the
later need for additional analyses. The preparation of a written
modeling protocol that is vetted with the appropriate reviewing
authority helps to keep misunderstandings and resource expenditures
at a minimum.
d. The identification of preferred models in this Guideline
should not be construed as a determination that the preferred models
identified here are to be permanently used to the exclusion of all
others or that they are the only models available for relating
emissions to air quality. The model that most accurately estimates
concentrations in the area of interest is always sought. However,
designation of specific preferred models is needed to promote
consistency in model selection and application.

3.1 Preferred Models

3.1.1 Discussion

a. The EPA has developed some models suitable for regulatory
application, while other models have been submitted by private
developers for possible inclusion in the Guideline. Refined models
that are preferred and required by the EPA for particular
applications have undergone the necessary peer scientific reviews
\24\ \25\ and model performance evaluation exercises \26\ \27\ that
include statistical measures of model performance in comparison with
measured air quality data as described in section 2.1.1.
b. An American Society for Testing and Materials (ASTM)
reference \28\ provides a general philosophy for developing and
implementing advanced statistical evaluations of atmospheric
dispersion models, and provides an example statistical technique to
illustrate the application of this philosophy. Consistent with this
approach, the EPA has determined and applied a specific evaluation
protocol that provides a statistical technique for evaluating model
performance for predicting peak concentration values, as might be
observed at individual monitoring locations.\29\
c. When a single model is found to perform better than others,
it is recommended for application as a preferred model and listed in
Addendum A. If no one model is found to clearly perform better
through the evaluation exercise, then the preferred model listed in
Addendum A may be selected on the basis of other factors such as
past use, public familiarity, resource requirements, and
availability. Accordingly, the models listed in Addendum A meet
these conditions:
i. The model must be written in a common programming language,
and the executable(s) must run on a common computer platform.
ii. The model must be documented in a user's guide or model
formulation report which identifies the mathematics of the model,
data requirements and program operating characteristics at a level
of detail comparable to that available for other recommended models
in Addendum A.
iii. The model must be accompanied by a complete test dataset
including input parameters and output results. The test data must be
packaged with the model in computer-readable form.
iv. The model must be useful to typical users, e.g., State air
agencies, for specific air quality control problems. Such users
should be able to operate the computer program(s) from available
documentation.
v. The model documentation must include a robust comparison with
air quality data (and/or tracer measurements) or with other well-
established analytical techniques.
vi. The developer must be willing to make the model and source
code available to users at reasonable cost or make them available
for public access through the internet or National Technical
Information Service. The model and its code cannot be proprietary.
d. The EPA's process of establishing a preferred model includes
a determination of technical merit, in accordance with the above six
items, including the practicality of the model for use in ongoing
regulatory programs. Each model will also be subjected to a
performance evaluation for an appropriate database and to a peer
scientific review. Models for wide use (not just an isolated case)
that are found to perform better will be proposed for inclusion as
preferred models in future Guideline revisions.
e. No further evaluation of a preferred model is required for a
particular application if the EPA requirements for regulatory use
specified for the model in the Guideline are followed. Alternative
models to those listed in Addendum A should generally be compared
with measured air quality data when they are used for regulatory
applications consistent with recommendations in section 3.2.

3.1.2 Requirements

a. Addendum A identifies refined models that are preferred for
use in regulatory applications. If a model is required for a
particular application, the user must select a model from Addendum A
or follow procedures in section 3.2.2 for use of an alternative
model or technique. Preferred models may be used without a formal
demonstration of applicability as long as they are used as indicated
in each model summary in Addendum A. Further recommendations for the
application of preferred models to specific source applications are
found in subsequent sections of the Guideline.
b. If changes are made to a preferred model without affecting
the modeled concentrations, the preferred status of the model is
unchanged. Examples of modifications that do not affect
concentrations are those made to enable use of a different computer
platform or those that only affect the format or averaging time of
the model results. The integration of a graphical user interface
(GUI) to facilitate setting up the model inputs and/or analyzing the
model results without otherwise altering the preferred model code is
another example of a modification that does not affect
concentrations. However, when any changes are made, the Regional
Administrator must require a test case example to demonstrate that
the modeled concentrations are not affected.
c. A preferred model must be operated with the options listed in
Addendum A for its intended regulatory application. If the
regulatory options are not applied, the model is no longer
``preferred.'' Any other modification to a preferred model that
would result in a change in the concentration estimates likewise
alters its status so that it is no longer a preferred model. Use of
the modified model must then be justified as an alternative model on
a case-by-case basis to the appropriate reviewing authority and
approved by the Regional Administrator.
d. Where the EPA has not identified a preferred model for a
particular pollutant or situation, the EPA may establish a multi-
tiered approach for making a demonstration required under PSD or
another CAA program. The initial tier or tiers may involve use of
demonstration tools, screening models, screening techniques, or
reduced-form models; while the last tier may involve the use of
demonstration tools, refined models or techniques, or alternative
models approved under section 3.2.

3.2 Alternative Models

3.2.1 Discussion

a. Selection of the best model or techniques for each individual
air quality analysis is always encouraged, but the selection should
be done in a consistent manner. A simple listing of models in this
Guideline cannot alone achieve that consistency nor can it
necessarily provide the best model for all possible situations. As
discussed in section 3.1.1, the EPA has determined and applied a
specific evaluation protocol that provides a statistical technique
for evaluating model performance for predicting peak concentration
values, as might be observed at individual monitoring locations.\29\
This protocol is available to assist in developing a consistent
approach when justifying the use of other-than-preferred models
recommended in the Guideline (i.e., alternative models). The
procedures in this protocol provide a general framework for
objective decision-making on the acceptability of an alternative
model for a given regulatory application. These objective procedures
may be used for conducting both the technical evaluation of the
model and the field test or performance evaluation.
b. This subsection discusses the use of alternate models and
defines three situations when alternative models may be used. This
subsection also provides a procedure for implementing 40 CFR
51.166(l)(2) in PSD permitting. This provision requires written
approval of the Administrator for any modification or substitution
of an applicable model. An applicable model for purposes of 40 CFR
51.166(l) is a preferred model in

[[Page 95048]]

Addendum A to the Guideline. Approval to use an alternative model
under section 3.2 of the Guideline qualifies as approval for the
modification or substitution of a model under 40 CFR 51.166(l)(2).
The Regional Administrators have delegated authority to issue such
approvals under section 3.2 of the Guideline, provided that such
approval is issued after consultation with the EPA's Model
Clearinghouse and formally documented in a concurrence memorandum
from the EPA's Model Clearinghouse which demonstrates that the
requirements within section 3.2 for use of an alternative model have
been met.

3.2.2 Requirements

a. Determination of acceptability of an alternative model is an
EPA Regional office responsibility in consultation with the EPA's
Model Clearinghouse as discussed in paragraphs 3.0(b) and 3.2.1(b).
Where the Regional Administrator finds that an alternative model is
more appropriate than a preferred model, that model may be used
subject to the approval of the EPA Regional office based on the
requirements of this subsection. This finding will normally result
from a determination that: (1) a preferred air quality model is not
appropriate for the particular application; or (2) a more
appropriate model or technique is available and applicable.
b. An alternative model shall be evaluated from both a
theoretical and a performance perspective before it is selected for
use. There are three separate conditions under which such a model
may be approved for use:
i. If a demonstration can be made that the model produces
concentration estimates equivalent to the estimates obtained using a
preferred model;
ii. If a statistical performance evaluation has been conducted
using measured air quality data and the results of that evaluation
indicate the alternative model performs better for the given
application than a comparable model in Addendum A; or
iii. If there is no preferred model.
Any one of these three separate conditions may justify use of an
alternative model. Some known alternative models that are applicable
for selected situations are listed on the EPA's SCRAM website
(section 2.3). However, inclusion there does not confer any unique
status relative to other alternative models that are being or will
be developed in the future.
c. Equivalency, condition (1) in paragraph (b) of this
subsection, is established by demonstrating that the appropriate
regulatory metric(s) are within +/- 2 percent of the estimates
obtained from the preferred model. The option to show equivalency is
intended as a simple demonstration of acceptability for an
alternative model that is nearly identical (or contains options that
can make it identical) to a preferred model that it can be treated
for practical purposes as the preferred model. However,
notwithstanding this demonstration, models that are not equivalent
may be used when one of the two other conditions described in
paragraphs (d) and (e) of this subsection are satisfied.
d. For condition (2) in paragraph (b) of this subsection,
established statistical performance evaluation procedures and
techniques 28 29 for determining the acceptability of a
model for an individual case based on superior performance should be
followed, as appropriate. Preparation and implementation of an
evaluation protocol that is acceptable to both control agencies and
regulated industry is an important element in such an evaluation.
e. Finally, for condition (3) in paragraph (b) of this
subsection, an alternative model or technique may be approved for
use provided that:
i. The model or technique has received a scientific peer review;
ii. The model or technique can be demonstrated to be applicable
to the problem on a theoretical basis;
iii. The databases which are necessary to perform the analysis
are available and adequate;
iv. Appropriate performance evaluations of the model or
technique have shown that the model or technique is not
inappropriately biased for regulatory application; \a\ and
---------------------------------------------------------------------------

\a\ For PSD and other applications that use the model results in
an absolute sense, the model should not be biased toward
underestimates. Alternatively, for ozone and PM<INF>2.5</INF> SIP
attainment demonstrations and other applications that use the model
results in a relative sense, the model should not be biased toward
overestimates.
---------------------------------------------------------------------------

v. A protocol on methods and procedures to be followed has been
established.
f. To formally document that the requirements of section 3.2 for
use of an alternative model are satisfied for a particular
application or range of applications, a memorandum will be prepared
by the EPA's Model Clearinghouse through a consultative process with
the EPA Regional office.

3.3 EPA's Model Clearinghouse

a. The Regional Administrator has the authority to select models
that are appropriate for use in a given situation. However, there is
a need for assistance and guidance in the selection process so that
fairness, consistency, and transparency in modeling decisions are
fostered among the EPA Regional offices and the State, local, and
Tribal agencies. To satisfy that need, the EPA established the Model
Clearinghouse \23\ to serve a central role of coordination and
collaboration between EPA headquarters and the EPA Regional offices.
Additionally, the EPA holds periodic workshops with EPA
Headquarters, EPA Regional offices, and State, local, and Tribal
agency modeling representatives.
b. The appropriate EPA Regional office should always be
consulted for information and guidance concerning modeling methods
and interpretations of modeling guidance, and to ensure that the air
quality model user has available the latest most up-to-date policy
and procedures. As appropriate, the EPA Regional office may also
request assistance from the EPA's Model Clearinghouse on other
applications of models, analytical techniques, or databases or to
clarify interpretation of the Guideline or related modeling
guidance.
c. The EPA Regional office will coordinate with the EPA's Model
Clearinghouse after an initial evaluation and decision has been
developed concerning the application of an alternative model. The
acceptability and formal approval process for an alternative model
is described in section 3.2.

4.0 Models for Carbon Monoxide, Lead, Sulfur Dioxide, Nitrogen Dioxide
and Primary Particulate Matter

4.1 Discussion

a. This section identifies modeling approaches generally used in
the air quality impact analysis of sources that emit the criteria
pollutants carbon monoxide (CO), lead, sulfur dioxide
(SO<INF>2</INF>), nitrogen dioxide (NO<INF>2</INF>), and primary
particulates (PM<INF>2.5</INF> and PM<INF>10</INF>).
b. The guidance in this section is specific to the application
of the Gaussian plume models identified in Addendum A. Gaussian
plume models assume that emissions and meteorology are in a steady-
state, which is typically based on an hourly time step. This
approach results in a plume that has an hourly-averaged distribution
of emission mass according to a Gaussian curve through the plume.
Though Gaussian steady-state models conserve the mass of the primary
pollutant throughout the plume, they can still take into account a
limited consideration of first-order removal processes (e.g., wet
and dry deposition) and limited chemical conversion (e.g., OH
oxidation).
c. Due to the steady-state assumption, Gaussian plume models are
generally considered applicable to distances less than 50 km, beyond
which, modeled predictions of plume impact are likely conservative.
The locations of these impacts are expected to be unreliable due to
changes in meteorology that are likely to occur during the travel
time.
d. The applicability of Gaussian plume models may vary depending
on the topography of the modeling domain, i.e., simple or complex.
Simple terrain is considered to be an area where terrain features
are all lower in elevation than the top of the stack(s) of the
source(s) in question. Complex terrain is defined as terrain
exceeding the height of the stack(s) being modeled.
e. Gaussian models determine source impacts at discrete
locations (receptors) for each meteorological and emission scenario,
and generally attempt to estimate concentrations at specific sites
that represent an ensemble average of numerous repetitions of the
same ``event.'' Uncertainties in model estimates are driven by this
formulation, and as noted in section 2.1.1, evaluations of model
accuracy should focus on the reducible uncertainty associated with
physics and the formulation of the model. The ``irreducible''
uncertainty associated with Gaussian plume models may be responsible
for variation in concentrations of as much as +/- 50 percent.\30\
``Reducible'' uncertainties \16\ can be on a similar scale. For
example, Pasquill \31\ estimates that, apart from data input errors,
maximum ground-level concentrations at a given hour for a point
source in flat terrain could be in error by 50 percent due to these
uncertainties. Errors of 5 to 10 degrees in the measured wind
direction can result in concentration errors of 20 to 70 percent for
a particular time and location, depending on stability and station
location. Such uncertainties do not

[[Page 95049]]

indicate that an estimated concentration does not occur, only that
the precise time and locations are in doubt. Composite errors in
highest estimated concentrations of 10 to 40 percent are found to be
typical.32 33 However, estimates of concentrations paired
in time and space with observed concentrations are less certain.
f. Model evaluations and inter-comparisons should take these
aspects of uncertainty into account. For a regulatory application of
a model, the emphasis of model evaluations is generally placed on
the highest modeled impacts. Thus, the Cox-Tikvart model evaluation
approach, which compares the highest modeled impacts on several
timescales, is recommended for comparisons of models and
measurements and model inter-comparisons. The approach includes
bootstrap techniques to determine the significance of various
modeled predictions and increases the robustness of such comparisons
when the number of available measurements are
limited.34 35 Because of the uncertainty in paired
modeled and observed concentrations, any attempts at calibration of
models based on these comparisons is of questionable benefit and
shall not be done.

4.2 Requirements

a. For NAAQS compliance demonstrations under PSD, use of the
screening and preferred models for the pollutants listed in this
subsection shall be limited to the near-field at a nominal distance
of 50 km or less. Near-field application is consistent with
capabilities of Gaussian plume models and, based on the EPA's
assessment, is sufficient to address whether a source will cause or
contribute to ambient concentrations in excess of a NAAQS. In most
cases, maximum source impacts of inert pollutants will occur within
the first 10 to 20 km from the source. Therefore, the EPA does not
consider a long-range transport assessment beyond 50 km necessary
for these pollutants if a near-field NAAQS compliance demonstration
is required.\36\
b. For assessment of PSD increments within the near-field
distance of 50 km or less, use of the screening and preferred models
for the pollutants listed in this subsection shall be limited to the
same screening and preferred models approved for NAAQS compliance
demonstrations.
c. To determine if a compliance demonstration for NAAQS and/or
PSD increments may be necessary beyond 50 km (i.e., long-range
transport assessment), the following screening approach shall be
used to determine if a significant ambient impact will occur with
particular focus on Class I areas and/or the applicable receptors
that may be threatened at such distances.
i. Based on application in the near-field of the appropriate
screening and/or preferred model, determine the significance of the
ambient impacts at or about 50 km from the new or modifying source.
If a near-field assessment is not available or this initial analysis
indicates there may be significant ambient impacts at that distance,
then further assessment is necessary.
ii. For assessment of the significance of ambient impacts for
NAAQS and/or PSD increments, there is not a preferred model or
screening approach for distances beyond 50 km. Thus, the appropriate
reviewing authority (paragraph 3.0(b)) and the EPA Regional office
shall be consulted in determining the appropriate and agreed upon
screening technique to conduct the second level assessment.
Typically, a Lagrangian model is most appropriate to use for these
second level assessments, but applicants shall reach agreement on
the specific model and modeling parameters on a case-by-case basis
in consultation with the appropriate reviewing authority (paragraph
3.0(b)) and EPA Regional office. When Lagrangian models are used in
this manner, they shall not include plume-depleting processes, such
that model estimates are considered conservative, as is generally
appropriate for screening assessments.
d. In those situations where a cumulative impact analysis for
NAAQS and/or PSD increments analysis beyond 50 km is necessary, the
selection and use of an alternative model shall occur in agreement
with the appropriate reviewing authority (paragraph 3.0(b)) and
approval by the EPA Regional office based on the requirements of
paragraph 3.2.2(e).

4.2.1 Screening Models and Techniques

a. Where a preliminary or conservative estimate is desired,
point source screening techniques are an acceptable approach to air
quality analyses.
b. As discussed in paragraph 2.2(a), screening models or
techniques are designed to provide a conservative estimate of
concentrations. The screening models used in most applications are
the screening versions of the preferred models for refined
applications. The two screening models, AERSCREEN 37 38
and CTSCREEN, are screening versions of AERMOD (American
Meteorological Society (AMS)/EPA Regulatory Model) and CTDMPLUS
(Complex Terrain Dispersion Model Plus Algorithms for Unstable
Situations), respectively. AERSCREEN is the recommended screening
model for most applications in all types of terrain and for
applications involving building downwash. For those applications in
complex terrain where the application involves a well-defined hill
or ridge, CTSCREEN \39\ can be used.
c. Although AERSCREEN and CTSCREEN are designed to address a
single-source scenario, there are approaches that can be used on a
case-by-case basis to address multi-source situations using
screening meteorology or other conservative model assumptions.
However, the appropriate reviewing authority (paragraph 3.0(b))
shall be consulted, and concurrence obtained, on the protocol for
modeling multiple sources with AERSCREEN or CTSCREEN to ensure that
the worst case is identified and assessed.
d. As discussed in section 4.2.3.4, there are also screening
techniques built into AERMOD that use simplified or limited
chemistry assumptions for determining the partitioning of NO and
NO<INF>2</INF> for NO<INF>2</INF> modeling. These screening
techniques are part of the EPA's preferred modeling approach for
NO<INF>2</INF> and do not need to be approved as an alternative
model. However, as with other screening models and techniques, their
usage shall occur in agreement with the appropriate reviewing
authority (paragraph 3.0(b)).
e. As discussed in section 4.2(c)(ii), there are screening
techniques needed for long-range transport assessments that will
typically involve the use of a Lagrangian model. Based on the long-
standing practice and documented capabilities of these models for
long-range transport assessments, the use of a Lagrangian model as a
screening technique for this purpose does not need to be approved as
an alternative model. However, their usage shall occur in
consultation with the appropriate reviewing authority (paragraph
3.0(b)) and the EPA Regional office.
f. All screening models and techniques shall be configured to
appropriately address the site and problem at hand. Close attention
must be paid to whether the area should be classified urban or rural
in accordance with section 7.2.1.1. The climatology of the area must
be studied to help define the worst-case meteorological conditions.
Agreement shall be reached between the model user and the
appropriate reviewing authority (paragraph 3.0(b)) on the choice of
the screening model or technique for each analysis, on the input
data and model settings, and the appropriate metric for satisfying
regulatory requirements.

4.2.1.1 AERSCREEN

a. Released in 2011, AERSCREEN is the EPA's recommended
screening model for simple and complex terrain for single sources
including point sources, area sources, horizontal stacks, capped
stacks, and flares. AERSCREEN runs AERMOD in a screening mode and
consists of two main components: (1) the MAKEMET program which
generates a site-specific matrix of meteorological conditions for
input to the AERMOD model; and (2) the AERSCREEN command-prompt
interface.
b. The MAKEMET program generates a matrix of meteorological
conditions, in the form of AERMOD-ready surface and profile files,
based on user-specified surface characteristics, ambient
temperatures, minimum wind speed, and anemometer height. The
meteorological matrix is generated based on looping through a range
of wind speeds, cloud covers, ambient temperatures, solar elevation
angles, and convective velocity scales (w*, for convective
conditions only) based on user-specified surface characteristics for
surface roughness (Z<INF>o</INF>), Bowen ratio (B<INF>o</INF>), and
albedo (r). For unstable cases, the convective mixing height
(Z<INF>ic</INF>) is calculated based on w*, and the mechanical
mixing height (Z<INF>im</INF>) is calculated for unstable and stable
conditions based on the friction velocity, u*.
c. For applications involving simple or complex terrain,
AERSCREEN interfaces with AERMAP. AERSCREEN also interfaces with
BPIPPRM to provide the necessary building parameters for
applications involving building downwash using the Plume Rise Model
Enhancements (PRIME) downwash algorithm. AERSCREEN generates inputs
to AERMOD via MAKEMET, AERMAP, and BPIPPRM and invokes AERMOD in a
screening mode. The screening mode of AERMOD forces the AERMOD model
calculations to represent values for the plume

[[Page 95050]]

centerline, regardless of the source-receptor-wind direction
orientation. The maximum concentration output from AERSCREEN
represents a worst-case 1-hour concentration. Averaging-time scaling
factors of 1.0 for 3-hour, 0.9 for 8-hour, 0.60 for 24-hour, and
0.10 for annual concentration averages are applied internally by
AERSCREEN to the highest 1-hour concentration calculated by the
model for non-area type sources. For area type source concentrations
for averaging times greater than one hour, the concentrations are
equal to the 1-hour estimates.37 40

4.2.1.2 CTSCREEN

a. CTSCREEN 39 41 can be used to obtain conservative,
yet realistic, worst-case estimates for receptors located on terrain
above stack height. CTSCREEN accounts for the three-dimensional
nature of plume and terrain interaction and requires detailed
terrain data representative of the modeling domain. The terrain data
must be digitized in the same manner as for CTDMPLUS and a terrain
processor is available.\42\ CTSCREEN is designed to execute a fixed
matrix of meteorological values for wind speed (u), standard
deviation of horizontal and vertical wind speeds ([sigma]v,
[sigma]w), vertical potential temperature gradient (d[thgr]/dz),
friction velocity (u*), Monin-Obukhov length (L), mixing height
(z<INF>i</INF>) as a function of terrain height, and wind directions
for both neutral/stable conditions and unstable convective
conditions. The maximum concentration output from CTSCREEN
represents a worst-case 1-hour concentration. Time-scaling factors
of 0.7 for 3-hour, 0.15 for 24-hour and 0.03 for annual
concentration averages are applied internally by CTSCREEN to the
highest 1-hour concentration calculated by the model.

4.2.1.3 Screening in Complex Terrain

a. For applications utilizing AERSCREEN, AERSCREEN automatically
generates a polar-grid receptor network with spacing determined by
the maximum distance to model. If the application warrants a
different receptor network than that generated by AERSCREEN, it may
be necessary to run AERMOD in screening mode with a user-defined
network. For CTSCREEN applications or AERMOD in screening mode
outside of AERSCREEN, placement of receptors requires very careful
attention when modeling in complex terrain. Often the highest
concentrations are predicted to occur under very stable conditions,
when the plume is near or impinges on the terrain. Under such
conditions, the plume may be quite narrow in the vertical, so that
even relatively small changes in a receptor's location may
substantially affect the predicted concentration. Receptors within
about a kilometer of the source may be even more sensitive to
location. Thus, a dense array of receptors may be required in some
cases.
b. For applications involving AERSCREEN, AERSCREEN interfaces
with AERMAP to generate the receptor elevations. For applications
involving CTSCREEN, digitized contour data must be preprocessed \42\
to provide hill shape parameters in suitable input format. The user
then supplies receptor locations either through an interactive
program that is part of the model or directly, by using a text
editor; using both methods to select receptor locations will
generally be necessary to assure that the maximum concentrations are
estimated by either model. In cases where a terrain feature may
``appear to the plume'' as smaller, multiple hills, it may be
necessary to model the terrain both as a single feature and as
multiple hills to determine design concentrations.
c. Other screening techniques may be acceptable for complex
terrain cases where established procedures \43\ are used. The user
is encouraged to confer with the appropriate reviewing authority
(paragraph 3.0(b)) if any unforeseen problems are encountered, e.g.,
applicability, meteorological data, receptor siting, or terrain
contour processing issues.

4.2.2 Refined Models

a. Addendum A provides a brief description of each preferred
model for refined applications. Also listed in that addendum are
availability, the model input requirements, the standard options
that shall be selected when running the program, and output options.

4.2.2.1 AERMOD

a. For a wide range of regulatory applications in all types of
terrain, and for aerodynamic building downwash, the required model
is AERMOD.44 45 The AERMOD regulatory modeling system
consists of the AERMOD dispersion model, the AERMET meteorological
processor, and the AERMAP terrain processor. AERMOD is a steady-
state Gaussian plume model applicable to directly emitted air
pollutants that employs best state-of-practice parameterizations for
characterizing the meteorological influences and dispersion.
Differentiation of simple versus complex terrain is unnecessary with
AERMOD. In complex terrain, AERMOD employs the well-known dividing-
streamline concept in a simplified simulation of the effects of
plume-terrain interactions.
b. The AERMOD Modeling System has been extensively evaluated
across a wide range of scenarios based on numerous field studies,
including tall stacks in flat and complex terrain settings, sources
subject to building downwash influences, and low-level non-buoyant
sources.\27\ These evaluations included several long-term field
studies associated with operating plants as well as several
intensive tracer studies. Based on these evaluations, AERMOD has
shown consistently good performance, with ``errors'' in predicted
versus observed peak concentrations, based on the Robust Highest
Concentration (RHC) metric, consistently within the range of 10 to
40 percent (cited in paragraph 4.1(e)).
c. AERMOD incorporates the PRIME algorithm to account for
enhanced plume growth and restricted plume rise for plumes affected
by building wake effects.\46\ The PRIME algorithm accounts for
entrainment of plume mass into the cavity recirculation region,
including re-entrainment of plume mass into the wake region beyond
the cavity.
d. AERMOD incorporates the Buoyant Line and Point Source (BLP)
Dispersion model to account for buoyant plume rise from line
sources. The BLP option utilizes the standard meteorological inputs
provided by the AERMET meteorological processor.
e. The state-of-the-science for modeling atmospheric deposition
is evolving, new modeling techniques are continually being assessed,
and their results are being compared with observations.
Consequently, while deposition treatment is available in AERMOD, the
approach taken for any purpose shall be coordinated with the
appropriate reviewing authority (paragraph 3.0(b)).
f. The AERMET meteorological processor incorporates the COARE
algorithms to derive marine boundary layer parameters for overwater
applications of AERMOD.47 48 AERMOD is applicable for
some overwater applications when platform downwash and shoreline
fumigation are adequately considered in consultation with the
Regional office and appropriate reviewing authority. Where the
effects of shoreline fumigation and platform downwash need to be
assessed, the Offshore and Coastal Dispersion (OCD) model is the
applicable model (paragraph 4.2.2.3).

4.2.2.2 CTDMPLUS

a. If the modeling application involves an elevated point source
with a well-defined hill or ridge and a detailed dispersion analysis
of the spatial pattern of plume impacts is of interest, CTDMPLUS is
available. CTDMPLUS provides greater resolution of concentrations
about the contour of the hill feature than does AERMOD through a
different plume-terrain interaction algorithm.

4.2.2.3 OCD

a. The OCD (Offshore and Coastal Dispersion) model is a
straight-line Gaussian model that incorporates overwater plume
transport and dispersion as well as changes that occur as the plume
crosses the shoreline. The OCD model can determine the impact of
offshore emissions from point, area, or line sources on the air
quality of coastal regions. The OCD model is also applicable for
situations that involve platform building downwash.

4.2.3 Pollutant Specific Modeling Requirements

4.2.3.1 Models for Carbon Monoxide

a. Models for assessing the impact of CO emissions are needed to
meet NSR requirements to address compliance with the CO NAAQS and to
determine localized impacts from transportations projects. Examples
include evaluating effects of point sources, congested roadway
intersections and highways, as well as the cumulative effect of
numerous sources of CO in an urban area.
b. The general modeling recommendations and requirements for
screening models in section 4.2.1 and refined models in section
4.2.2 shall be applied for CO modeling. Given the relatively low CO
background concentrations, screening techniques are likely to be
adequate in most cases. In applying these recommendations and
requirements, the existing 1992 EPA guidance for screening CO
impacts from highways may be consulted.\49\

[[Page 95051]]

4.2.3.2 Models for Lead

a. In January 1999 (40 CFR part 58, appendix D), the EPA gave
notice that concern about ambient lead impacts was being shifted
away from roadways and toward a focus on stationary point sources.
Thus, models for assessing the impact of lead emissions are needed
to meet NSR requirements to address compliance with the lead NAAQS
and for SIP attainment demonstrations. The EPA has also issued
guidance on siting ambient monitors in the vicinity of stationary
point sources.\50\ For lead, the SIP should contain an air quality
analysis to determine the maximum rolling 3-month average lead
concentration resulting from major lead point sources, such as
smelters, gasoline additive plants, etc. The EPA has developed a
post-processor to calculate rolling 3-month average concentrations
from model output.\51\ General guidance for lead SIP development is
also available.\52\
b. For major lead point sources, such as smelters, which
contribute fugitive emissions and for which deposition is important,
professional judgment should be used, and there shall be
coordination with the appropriate reviewing authority (paragraph
3.0(b)). For most applications, the general requirements for
screening and refined models of section 4.2.1 and 4.2.2 are
applicable to lead modeling.

4.2.3.3 Models for Sulfur Dioxide

a. Models for SO<INF>2</INF> are needed to meet NSR requirements
to address compliance with the SO<INF>2</INF> NAAQS and PSD
increments, for SIP attainment demonstrations,\53\ and for
characterizing current air quality via modeling.\54\ SO<INF>2</INF>
is one of a group of highly reactive gases known as ``oxides of
sulfur'' with largest emissions sources being fossil fuel combustion
at power plants and other industrial facilities.
b. Given the relatively inert nature of SO<INF>2</INF> on the
short-term time scales of interest (i.e., 1-hour) and the sources of
SO<INF>2</INF> (i.e., stationary point sources), the general
modeling requirements for screening models in section 4.2.1 and
refined models in section 4.2.2 are applicable for SO<INF>2</INF>
modeling applications. For urban areas, AERMOD automatically invokes
a half-life of 4 hours \55\ to SO<INF>2</INF>. Therefore, care must
be taken when determining whether a source is urban or rural (see
section 7.2.1.1 for urban/rural determination methodology).

4.2.3.4 Models for Nitrogen Dioxide

a. Models for assessing the impact of sources on ambient
NO<INF>2</INF> concentrations are needed to meet NSR requirements to
address compliance with the NO<INF>2</INF> NAAQS and PSD increments.
Impact of an individual source on ambient NO<INF>2</INF> depends, in
part, on the chemical environment into which the source's plume is
to be emitted. This is due to the fact that NO<INF>2</INF> sources
co-emit NO along with NO<INF>2</INF> and any emitted NO may react
with ambient ozone to convert to additional NO<INF>2</INF> downwind.
Thus, comprehensive modeling of NO<INF>2</INF> would need to
consider the ratio of emitted NO and NO<INF>2</INF>, the ambient
levels of ozone and subsequent reactions between ozone and NO, and
the photolysis of NO<INF>2</INF> to NO.
b. Due to the complexity of NO<INF>2</INF> modeling, a multi-
tiered screening approach is required to obtain hourly and annual
average estimates of NO<INF>2</INF>.\56\ Since these methods are
considered screening techniques, their usage shall occur in
agreement with the appropriate reviewing authority (paragraph
3.0(b)). Additionally, since screening techniques are conservative
by their nature, there are limitations to how these options can be
used. Specifically, modeling of negative emissions rates should only
be done after consultation with the EPA Regional office to ensure
that decreases in concentrations would not be overestimated. Each
tiered approach (see Figure 4-1) accounts for increasingly complex
considerations of NO<INF>2</INF> chemistry and is described in
paragraphs c through e of this subsection. The tiers of
NO<INF>2</INF> modeling include:
i. A first-tier (most conservative) ``full'' conversion
approach;
ii. A second-tier approach that assumes ambient equilibrium
between NO and NO<INF>2</INF>; and
iii. A third-tier consisting of several detailed screening
techniques that account for ambient ozone and the relative amount of
NO and NO<INF>2</INF> emitted from a source.
c. For Tier 1, use an appropriate refined model (section 4.2.2)
to estimate nitrogen oxides (NO<INF>X</INF>) concentrations and
assume a total conversion of NO to NO<INF>2</INF>.
d. For Tier 2, multiply the Tier 1 result(s) by the Ambient
Ratio Method 2 (ARM2), which provides estimates of representative
equilibrium ratios of NO<INF>2</INF>/NO<INF>X</INF> value based
ambient levels of NO<INF>2</INF> and NO<INF>X</INF> derived from
national data from the EPA's Air Quality System (AQS).\57\ The
national default for ARM2 includes a minimum ambient NO<INF>2</INF>/
NO<INF>X</INF> ratio of 0.5 and a maximum ambient ratio of 0.9. The
reviewing agency may establish alternative minimum ambient
NO<INF>2</INF>/NO<INF>X</INF> values based on the source's in-stack
emissions ratios, with alternative minimum ambient ratios reflecting
the source's in-stack NO<INF>2</INF>/NO<INF>X</INF> ratios.
Preferably, alternative minimum ambient NO<INF>2</INF>/
NO<INF>X</INF> ratios should be based on source-specific data which
satisfies all quality assurance procedures that ensure data accuracy
for both NO<INF>2</INF> and NO<INF>X</INF> within the typical range
of measured values. However, alternate information may be used to
justify a source's anticipated NO<INF>2</INF>/NO<INF>X</INF> in-
stack ratios, such as manufacturer test data, State or local agency
guidance, peer-reviewed literature, and/or the EPA's NO<INF>2</INF>/
NO<INF>X</INF> ratio database.
e. For Tier 3, a detailed screening technique shall be applied
on a case-by-case basis. Because of the additional input data
requirements and complexities associated with the Tier 3 options,
their usage shall occur in consultation with the EPA Regional office
in addition to the appropriate reviewing authority. The Ozone
Limiting Method (OLM),\58\ the Plume Volume Molar Ratio Method
(PVMRM),\59\ and the Generic Set Reaction Method
(GRSM),60 61 are three detailed screening techniques that
may be used for most sources. These three techniques use an
appropriate section 4.2.2 model to estimate NO<INF>X</INF>
concentrations and then estimate the conversion of primary NO
emissions to NO<INF>2</INF> based on the ambient levels of ozone and
the plume characteristics. OLM only accounts for NO<INF>2</INF>
formation based on the ambient levels of ozone while PVMRM and GRSM
also accommodate distance-dependent conversion ratios based on
ambient ozone. GRSM, PVMRM and OLM require explicit specification of
the NO<INF>2</INF>/NO<INF>X</INF> in-stack ratios and that ambient
ozone concentrations be provided on an hourly basis. GRSM requires
hourly ambient NO<INF>X</INF> concentrations in addition to hourly
ozone.
f. Alternative models or techniques may be considered on a case-
by-case basis and their usage shall be approved by the EPA Regional
office (section 3.2). Such models or techniques should consider
individual quantities of NO and NO<INF>2</INF> emissions,
atmospheric transport and dispersion, and atmospheric transformation
of NO to NO<INF>2</INF>. Dispersion models that account for more
explicit photochemistry may also be considered as an alternative
model to estimate ambient impacts of NO<INF>X</INF> sources.

[[Page 95052]]

[GRAPHIC] [TIFF OMITTED] TR29NO24.004

Figure 4-1: Multi-Tiered Approach for Estimating NO<INF>2</INF>
Concentrations

4.2.3.5 Models for PM<INF>2.5</INF>

a. PM<INF>2.5</INF> is a mixture consisting of several diverse
components.\62\ Ambient PM<INF>2.5</INF> generally consists of two
components: (1) the primary component, emitted directly from a
source; and (2) the secondary component, formed in the atmosphere
from other pollutants emitted from the source. Models for
PM<INF>2.5</INF> are needed to meet NSR requirements to address
compliance with the PM<INF>2.5</INF> NAAQS and PSD increments and
for SIP attainment demonstrations.
b. For NSR modeling assessments, the general modeling
requirements for screening models in section 4.2.1 and refined
models in section 4.2.2 are applicable for the primary component of
PM<INF>2.5</INF>, while the methods in section 5.4 are applicable
for addressing the secondary component of PM<INF>2.5</INF>. Guidance
for PSD assessments is available for determining the best approach
to handling sources of primary and secondary PM<INF>2.5</INF>.\63\
c. For SIP attainment demonstrations and regional haze
reasonable progress goal analyses, effects of a control strategy on
PM<INF>2.5</INF> are estimated from the sum of the effects on the
primary and secondary components composing PM<INF>2.5</INF>. Model
users should refer to section 5.4.1 and associated SIP modeling
guidance \64\ for further details concerning appropriate modeling
approaches.
d. The general modeling requirements for the refined models
discussed in section 4.2.2 shall be applied for PM<INF>2.5</INF>
hot-spot modeling for mobile sources. Specific guidance is available
for analyzing direct PM<INF>2.5</INF> impacts from highways,
terminals, and other transportation projects.\65\

4.2.3.6 Models for PM<INF>10</INF>

a. Models for PM<INF>10</INF> are needed to meet NSR
requirements to address compliance with the PM<INF>10</INF> NAAQS
and PSD increments and for SIP attainment demonstrations.
b. For most sources, the general modeling requirements for
screening models in section 4.2.1 and refined models in section
4.2.2 shall be applied for PM<INF>10</INF> modeling. In cases where
the particle size and its effect on ambient concentrations need to
be considered, particle deposition may be used on a case-by-case
basis and their usage shall be coordinated with the appropriate
reviewing authority. A SIP development guide \66\ is also available
to assist in PM<INF>10</INF> analyses and control strategy
development.
c. Fugitive dust usually refers to dust put into the atmosphere
by the wind blowing over plowed fields, dirt roads, or desert or
sandy areas with little or no vegetation. Fugitive emissions include
the emissions resulting from the industrial process that are not
captured and vented through a stack, but may be released from
various locations within the complex. In some unique cases, a model
developed specifically for the situation may be needed. Due to the
difficult nature of characterizing and modeling fugitive dust and
fugitive emissions, the proposed procedure shall be determined in
consultation with the appropriate reviewing authority (paragraph
3.0(b)) for each specific situation before the modeling exercise is
begun. Re-entrained dust is created by vehicles driving over dirt
roads (e.g., haul roads) and dust-covered roads typically found in
arid areas. Such sources can be characterized as line, area or
volume sources.\65\ \67\ Emission rates may be based on site-
specific data or values from the general literature.
d. Under certain conditions, recommended dispersion models may
not be suitable to appropriately address the nature of ambient
PM<INF>10</INF>. In these circumstances, the alternative modeling
approach shall be approved by the EPA Regional office (section 3.2).
e. The general modeling requirements for the refined models
discussed in section 4.2.2 shall be applied for PM<INF>10</INF> hot-
spot modeling for mobile sources. Specific guidance is available for
analyzing direct PM<INF>10</INF> impacts from highways, terminals,
and other transportation projects.\65\

5.0 Models for Ozone and Secondarily Formed Particulate Matter

5.1 Discussion

a. Air pollutants formed through chemical reactions in the
atmosphere are referred to as secondary pollutants. For example,
ground-level ozone and a portion of PM<INF>2.5</INF> are secondary
pollutants formed through photochemical reactions. Ozone and
secondarily formed particulate matter are closely related to each
other in that they share common sources of emissions and are formed
in the atmosphere from chemical reactions with similar precursors.
b. Ozone formation is driven by emissions of NO<INF>X</INF> and
volatile organic compounds (VOCs). Ozone formation is a complicated
nonlinear process that requires favorable meteorological conditions
in addition to VOC and NO<INF>X</INF> emissions. Sometimes complex
terrain features also contribute to the build-up of precursors and
subsequent ozone formation or destruction.
c. PM<INF>2.5</INF> can be either primary (i.e., emitted
directly from sources) or secondary in nature. The fraction of
PM<INF>2.5</INF> which is primary versus secondary varies by
location and season. In the United States, PM<INF>2.5</INF> is
dominated by a variety of chemical species or components of
atmospheric particles, such as ammonium sulfate, ammonium nitrate,
organic carbon mass, elemental carbon, and other soil compounds and
oxidized metals. PM<INF>2.5</INF> sulfate, nitrate, and ammonium
ions are predominantly the result of chemical reactions of the
oxidized products of SO<INF>2</INF> and NO<INF>X</INF> emissions
with direct ammonia emissions.\68\
d. Control measures reducing ozone and PM<INF>2.5</INF>
precursor emissions may not lead to proportional reductions in ozone
and PM<INF>2.5</INF>. Modeled strategies designed to reduce ozone or
PM<INF>2.5</INF> levels typically need to consider the chemical
coupling between these pollutants. This coupling is important in
understanding processes that control the levels of both pollutants.
Thus, when feasible, it is important to use models that take into
account the chemical coupling between ozone and PM<INF>2.5</INF>. In
addition, using such a multi-pollutant modeling system can reduce
the resource burden associated with applying and evaluating separate
models for each pollutant and promotes consistency among the
strategies themselves.
e. PM<INF>2.5</INF> is a mixture consisting of several diverse
chemical species or components of

[[Page 95053]]

atmospheric particles. Because chemical and physical properties and
origins of each component differ, it may be appropriate to use
either a single model capable of addressing several of the important
components or to model primary and secondary components using
different models. Effects of a control strategy on PM<INF>2.5</INF>
is estimated from the sum of the effects on the specific components
comprising PM<INF>2.5</INF>.

5.2 Recommendations

a. Chemical transformations can play an important role in
defining the concentrations and properties of certain air
pollutants. Models that take into account chemical reactions and
physical processes of various pollutants (including precursors) are
needed for determining the current state of air quality, as well as
predicting and projecting the future evolution of these pollutants.
It is important that a modeling system provide a realistic
representation of chemical and physical processes leading to
secondary pollutant formation and removal from the atmosphere.
b. Chemical transport models treat atmospheric chemical and
physical processes such as deposition and motion. There are two
types of chemical transport models, Eulerian (grid based) and
Lagrangian. These types of models are differentiated from each other
by their frame of reference. Eulerian models are based on a fixed
frame of reference and Lagrangian models use a frame of reference
that moves with parcels of air between the source and receptor
point.\9\ Photochemical grid models are three-dimensional Eulerian
grid-based models that treat chemical and physical processes in each
grid cell and use diffusion and transport processes to move chemical
species between grid cells.\9\ These types of models are appropriate
for assessment of near-field and regional scale reactive pollutant
impacts from specific sources \7\ \10\ \11\ \12\ or all sources.\13\
\14\ \15\ In some limited cases, the secondary processes can be
treated with a box model, ideally in combination with a number of
other modeling techniques and/or analyses to treat individual source
sectors.
c. Regardless of the modeling system used to estimate secondary
impacts of ozone and/or PM<INF>2.5</INF>, model results should be
compared to observation data to generate confidence that the
modeling system is representative of the local and regional air
quality. For ozone related projects, model estimates of ozone should
be compared with observations in both time and space. For
PM<INF>2.5</INF>, model estimates of speciated PM<INF>2.5</INF>
components (such as sulfate ion, nitrate ion, etc.) should be
compared with observations in both time and space.\69\
d. Model performance metrics comparing observations and
predictions are often used to summarize model performance. These
metrics include mean bias, mean error, fractional bias, fractional
error, and correlation coefficient.\69\ There are no specific levels
of any model performance metric that indicate ``acceptable'' model
performance. The EPA's preferred approach for providing context
about model performance is to compare model performance metrics with
similar contemporary applications.\64\ \69\ Because model
application purpose and scope vary, model users should consult with
the appropriate reviewing authority (paragraph 3.0(b)) to determine
what model performance elements should be emphasized and presented
to provide confidence in the regulatory model application.
e. There is no preferred modeling system or technique for
estimating ozone or secondary PM<INF>2.5</INF> for specific source
impacts or to assess impacts from multiple sources. For assessing
secondary pollutant impacts from single sources, the degree of
complexity required to assess potential impacts varies depending on
the nature of the source, its emissions, and the background
environment. The EPA recommends a two-tiered approach where the
first tier consists of using existing technically credible and
appropriate relationships between emissions and impacts developed
from previous modeling that is deemed sufficient for evaluating a
source's impacts. The second tier consists of more sophisticated
case-specific modeling analyses. The appropriate tier for a given
application should be selected in consultation with the appropriate
reviewing authority (paragraph 3.0(b)) and be consistent with EPA
guidance.\70\

5.3 Recommended Models and Approaches for Ozone

a. Models that estimate ozone concentrations are needed to guide
the choice of strategies for the purposes of a nonattainment area
demonstrating future year attainment of the ozone NAAQS.
Additionally, models that estimate ozone concentrations are needed
to assess impacts from specific sources or source complexes to
satisfy requirements for NSR and other regulatory programs. Other
purposes for ozone modeling include estimating the impacts of
specific events on air quality, ozone deposition impacts, and
planning for areas that may be attaining the ozone NAAQS.

5.3.1 Models for NAAQS Attainment Demonstrations and Multi-Source Air
Quality Assessments

a. Simulation of ozone formation and transport is a complex
exercise. Control agencies with jurisdiction over areas with ozone
problems should use photochemical grid models to evaluate the
relationship between precursor species and ozone. Use of
photochemical grid models is the recommended means for identifying
control strategies needed to address high ozone concentrations in
such areas. Judgment on the suitability of a model for a given
application should consider factors that include use of the model in
an attainment test, development of emissions and meteorological
inputs to the model, and choice of episodes to model. Guidance on
the use of models and other analyses for demonstrating attainment of
the air quality goals for ozone is available.63 64 Users
should consult with the appropriate reviewing authority (paragraph
3.0(b)) to ensure the most current modeling guidance is applied.

5.3.2 Models for Single-Source Air Quality Assessments

a. Depending on the magnitude of emissions, estimating the
impact of an individual source's emissions of NO<INF>X</INF> and VOC
on ambient ozone is necessary for obtaining a permit. The simulation
of ozone formation and transport requires realistic treatment of
atmospheric chemistry and deposition. Models (e.g., Lagrangian and
photochemical grid models) that integrate chemical and physical
processes important in the formation, decay, and transport of ozone
and important precursor species should be applied. Photochemical
grid models are primarily designed to characterize precursor
emissions and impacts from a wide variety of sources over a large
geographic area but can also be used to assess the impacts from
specific sources.7 11 12
b. The first tier of assessment for ozone impacts involves those
situations where existing technical information is available (e.g.,
results from existing photochemical grid modeling, published
empirical estimates of source specific impacts, or reduced-form
models) in combination with other supportive information and
analysis for the purposes of estimating secondary impacts from a
particular source. The existing technical information should provide
a credible and representative estimate of the secondary impacts from
the project source. The appropriate reviewing authority (paragraph
3.0(b)) and appropriate EPA guidance \70\ \71\ should be consulted
to determine what types of assessments may be appropriate on a case-
by-case basis.
c. The second tier of assessment for ozone impacts involves
those situations where existing technical information is not
available or a first tier demonstration indicates a more refined
assessment is needed. For these situations, chemical transport
models should be used to address single-source impacts. Special
considerations are needed when using these models to evaluate the
ozone impact from an individual source. Guidance on the use of
models and other analyses for demonstrating the impacts of single
sources for ozone is available.\70\ This guidance document provides
a more detailed discussion of the appropriate approaches to
obtaining estimates of ozone impacts from a single source. Model
users should use the latest version of the guidance in consultation
with the appropriate reviewing authority (paragraph 3.0(b)) to
determine the most suitable refined approach for single-source ozone
modeling on a case-by-case basis.

5.4 Recommended Models and Approaches for Secondarily Formed
PM<INF>2.5</INF>

a. Models that estimate PM<INF>2.5</INF> concentrations are
needed to guide the choice of strategies for the purposes of a
nonattainment area demonstrating future year attainment of the
PM<INF>2.5</INF> NAAQS. Additionally, models that estimate
PM<INF>2.5</INF> concentrations are needed to assess impacts from
specific sources or source complexes to satisfy requirements for NSR
and other regulatory programs. Other purposes for PM<INF>2.5</INF>
modeling include estimating the impacts of specific events on air
quality,

[[Page 95054]]

visibility, deposition impacts, and planning for areas that may be
attaining the PM<INF>2.5</INF> NAAQS.

5.4.1 Models for NAAQS Attainment Demonstrations and Multi-Source Air
Quality Assessments

a. Models for PM<INF>2.5</INF> are needed to assess the adequacy
of a proposed strategy for meeting the annual and 24-hour
PM<INF>2.5</INF> NAAQS. Modeling primary and secondary
PM<INF>2.5</INF> can be a multi-faceted and complex problem,
especially for secondary components of PM<INF>2.5</INF> such as
sulfates and nitrates. Control agencies with jurisdiction over areas
with secondary PM<INF>2.5</INF> problems should use models that
integrate chemical and physical processes important in the
formation, decay, and transport of these species (e.g.,
photochemical grid models). Suitability of a modeling approach or
mix of modeling approaches for a given application requires
technical judgment as well as professional experience in choice of
models, use of the model(s) in an attainment test, development of
emissions and meteorological inputs to the model, and selection of
days to model. Guidance on the use of models and other analyses for
demonstrating attainment of the air quality goals for
PM<INF>2.5</INF> is available.\63\ \64\ Users should consult with
the appropriate reviewing authority (paragraph 3.0(b)) to ensure the
most current modeling guidance is applied.

5.4.2 Models for Single-Source Air Quality Assessments

a. Depending on the magnitude of emissions, estimating the
impact of an individual source's emissions on secondary particulate
matter concentrations may be necessary for obtaining a permit.
Primary PM<INF>2.5</INF> components shall be simulated using the
general modeling requirements in section 4.2.3.5. The simulation of
secondary particulate matter formation and transport is a complex
exercise requiring realistic treatment of atmospheric chemistry and
deposition. Models should be applied that integrate chemical and
physical processes important in the formation, decay, and transport
of these species (e.g., Lagrangian and photochemical grid models).
Photochemical grid models are primarily designed to characterize
precursor emissions and impacts from a wide variety of sources over
a large geographic area and can also be used to assess the impacts
from specific sources.\7\ \10\ For situations where a project source
emits both primary PM<INF>2.5</INF> and PM<INF>2.5</INF> precursors,
the contribution from both should be combined for use in determining
the source's ambient impact. Approaches for combining primary and
secondary impacts are provided in appropriate guidance for single
source permit related demonstrations.\70\
b. The first tier of assessment for secondary PM<INF>2.5</INF>
impacts involves those situations where existing technical
information is available (e.g., results from existing photochemical
grid modeling, published empirical estimates of source specific
impacts, or reduced-form models) in combination with other
supportive information and analysis for the purposes of estimating
secondary impacts from a particular source. The existing technical
information should provide a credible and representative estimate of
the secondary impacts from the project source. The appropriate
reviewing authority (paragraph 3.0(b)) and appropriate EPA guidance
\70\ \71\ should be consulted to determine what types of assessments
may be appropriate on a case-by-case basis.
c. The second tier of assessment for secondary PM<INF>2.5</INF>
impacts involves those situations where existing technical
information is not available or a first tier demonstration indicates
a more refined assessment is needed. For these situations, chemical
transport models should be used for assessments of single-source
impacts. Special considerations are needed when using these models
to evaluate the secondary particulate matter impact from an
individual source. Guidance on the use of models and other analyses
for demonstrating the impacts of single sources for secondary
PM<INF>2.5</INF> is available.\70\ This guidance document provides a
more detailed discussion of the appropriate approaches to obtaining
estimates of secondary particulate matter concentrations from a
single source. Model users should use the latest version of this
guidance in consultation with the appropriate reviewing authority
(paragraph 3.0(b)) to determine the most suitable single-source
modeling approach for secondary PM<INF>2.5</INF> on a case-by-case
basis.

6.0 Modeling for Air Quality Related Values and Other Governmental
Programs

6.1 Discussion

a. Other Federal government agencies and State, local, and
Tribal agencies with air quality and land management
responsibilities have also developed specific modeling approaches
for their own regulatory or other requirements. Although such
regulatory requirements and guidance have come about because of EPA
rules or standards, the implementation of such regulations and the
use of the modeling techniques is under the jurisdiction of the
agency issuing the guidance or directive. This section covers such
situations with reference to those guidance documents, when they are
available.
b. When using the model recommended or discussed in the
Guideline in support of programmatic requirements not specifically
covered by EPA regulations, the model user should consult the
appropriate Federal, State, local, or Tribal agency to ensure the
proper application and use of the models and/or techniques. These
agencies have developed specific modeling approaches for their own
regulatory or other requirements. Most of the programs have, or will
have when fully developed, separate guidance documents that cover
the program and a discussion of the tools that are needed. The
following paragraphs reference those guidance documents, when they
are available.

6.2 Air Quality Related Values

a. The 1990 CAA Amendments give FLMs an ``affirmative
responsibility'' to protect the natural and cultural resources of
Class I areas from the adverse impacts of air pollution and to
provide the appropriate procedures and analysis techniques. The CAA
identifies the FLM as the Secretary of the department, or their
designee, with authority over these lands. Mandatory Federal Class I
areas are defined in the CAA as international parks, national parks
over 6,000 acres, and wilderness areas and memorial parks over 5,000
acres, established as of 1977. The FLMs are also concerned with the
protection of resources in federally managed Class II areas because
of other statutory mandates to protect these areas. Where State or
Tribal agencies have successfully petitioned the EPA and lands have
been redesignated to Class I status, these agencies may have
equivalent responsibilities to that of the FLMs for these non-
Federal Class I areas as described throughout the remainder of
section 6.2.
b. The FLM agency responsibilities include the review of air
quality permit applications from proposed new or modified major
pollution sources that may affect these Class I areas to determine
if emissions from a proposed or modified source will cause or
contribute to adverse impacts on air quality related values (AQRVs)
of a Class I area and making recommendations to the FLM. AQRVs are
resources, identified by the FLM agencies, that have the potential
to be affected by air pollution. These resources may include
visibility, scenic, cultural, physical, or ecological resources for
a particular area. The FLM agencies take into account the particular
resources and AQRVs that would be affected; the frequency and
magnitude of any potential impacts; and the direct, indirect, and
cumulative effects of any potential impacts in making their
recommendations.
c. While the AQRV notification and impact analysis requirements
are outlined in the PSD regulations at 40 CFR 51.166(p) and 40 CFR
52.21(p), determination of appropriate analytical methods and
metrics for AQRV's are determined by the FLM agencies and are
published in guidance external to the general recommendations of
this paragraph.
d. To develop greater consistency in the application of air
quality models to assess potential AQRV impacts in both Class I
areas and protected Class II areas, the FLM agencies have developed
the Federal Land Managers' Air Quality Related Values Work Group
Phase I Report (FLAG).\72\ FLAG focuses upon specific technical and
policy issues associated with visibility impairment, effects of
pollutant deposition on soils and surface waters, and ozone effects
on vegetation. Model users should consult the latest version of the
FLAG report for current modeling guidance and with affected FLM
agency representatives for any application specific guidance which
is beyond the scope of the Guideline.

6.2.1 Visibility

a. Visibility in important natural areas (e.g., Federal Class I
areas) is protected under a number of provisions of the CAA,
including sections 169A and 169B (addressing impacts primarily from
existing sources) and section 165 (new source review). Visibility
impairment is caused by light scattering and light absorption
associated with particles and gases in the atmosphere. In most areas
of the country, light scattering by PM<INF>2.5</INF> is the most

[[Page 95055]]

significant component of visibility impairment. The key components
of PM<INF>2.5</INF> contributing to visibility impairment include
sulfates, nitrates, organic carbon, elemental carbon, and crustal
material.\72\
b. Visibility regulations (40 CFR 51.300 through 51.309) require
State, local, and Tribal agencies to mitigate current and prevent
future visibility impairment in any of the 156 mandatory Federal
Class I areas where visibility is considered an important attribute.
In 1999, the EPA issued revisions to the regulations to address
visibility impairment in the form of regional haze, which is caused
by numerous, diverse sources (e.g., stationary, mobile, and area
sources) located across a broad region (40 CFR 51.308 through
51.309). The state of relevant scientific knowledge has expanded
significantly since that time. A number of studies and reports \73\
\74\ have concluded that long-range transport (e.g., up to hundreds
of kilometers) of fine particulate matter plays a significant role
in visibility impairment across the country. Section 169A of the CAA
requires States to develop SIPs containing long-term strategies for
remedying existing and preventing future visibility impairment in
the 156 mandatory Class I Federal areas, where visibility is
considered an important attribute. In order to develop long-term
strategies to address regional haze, many State, local, and Tribal
agencies will need to conduct regional-scale modeling of fine
particulate concentrations and associated visibility impairment.
c. The FLAG visibility modeling recommendations are divided into
two distinct sections to address different requirements for: (1)
near field modeling where plumes or layers are compared against a
viewing background, and (2) distant/multi-source modeling for plumes
and aggregations of plumes that affect the general appearance of a
scene.\72\ The recommendations separately address visibility
assessments for sources proposing to locate relatively near and at
farther distances from these areas.\72\

6.2.1.1 Models for Estimating Near-Field Visibility Impairment

a. To calculate the potential impact of a plume of specified
emissions for specific transport and dispersion conditions (``plume
blight'') for source-receptor distances less than 50 km, a screening
model and guidance are available.\72\ \75\ If a more comprehensive
analysis is necessary, a refined model should be selected. The model
selection, procedures, and analyses should be determined in
consultation with the appropriate reviewing authority (paragraph
3.0(b)) and the affected FLM(s).

6.2.1.2 Models for Estimating Visibility Impairment for Long-Range
Transport

6.2.2 Models for Estimating Deposition Impacts

a. For many Class I areas, AQRVs have been identified that are
sensitive to atmospheric deposition of air pollutants. Emissions of
NO<INF>X</INF>, sulfur oxides, NH<INF>3</INF>, mercury, and
secondary pollutants such as ozone and particulate matter affect
components of ecosystems. In sensitive ecosystems, these compounds
can acidify soils and surface waters, add nutrients that change
biodiversity, and affect the ecosystem services provided by forests
and natural areas.\72\ To address the relationship between
deposition and ecosystem effects, the FLM agencies have developed
estimates of critical loads. A critical load is defined as, ``A
quantitative estimate of an exposure to one or more pollutants below
which significant harmful effects on specified sensitive elements of
the environment do not occur according to present knowledge.'' \76\
b. The FLM deposition modeling recommendations are divided into
two distinct sections to address different requirements for: (1)
near field modeling, and (2) distant/multi-source modeling for
cumulative effects. The recommendations separately address
deposition assessments for sources proposing to locate relatively
near and at farther distances from these areas.\72\ Where the source
and receptors are not in close proximity, chemical transport (e.g.,
photochemical grid) models generally should be applied for an
assessment of deposition impacts due to one or a small group of
sources. Over these distances, chemical and physical transformations
can change atmospheric residence time due to different propensity
for deposition to the surface of different forms of nitrate and
sulfate. Users should consult the latest version of the FLAG report
\72\ and relevant FLM representatives for guidance on the use of
models for deposition. Where source and receptors are in close
proximity, users should contact the appropriate FLM for application-
specific guidance.

6.3 Modeling Guidance for Other Governmental Programs

a. Dispersion and photochemical grid modeling may need to be
conducted to ensure that individual and cumulative offshore oil and
gas exploration, development, and production plans and activities do
not significantly affect the air quality of any State as required
under the Outer Continental Shelf Lands Act (OCSLA). Air quality
modeling requires various input datasets, including emissions
sources, meteorology, and pre-existing pollutant concentrations. For
sources under the reviewing authority of the Department of Interior,
Bureau of Ocean Energy Management (BOEM), guidance for the
development of all necessary Outer Continental Shelf (OCS) air
quality modeling inputs and appropriate model selection and
application is available from the BOEM's website: <a href="https://www.boem.gov/about-boem/regulations-guidance/guidance-portal">https://www.boem.gov/about-boem/regulations-guidance/guidance-portal</a>.
b. The Federal Aviation Administration (FAA) is the appropriate
reviewing authority for air quality assessments of primary pollutant
impacts at airports and air bases. The Aviation Environmental Design
Tool (AEDT) is developed and supported by the FAA, and is
appropriate for air quality assessment of primary pollutant impacts
at airports or air bases. AEDT has adopted AERMOD for treating
dispersion. Application of AEDT is intended for estimating the
change in emissions for aircraft operations, point source, and
mobile source emissions on airport property and quantify the
associated pollutant level- concentrations. AEDT is not intended for
PSD, SIP, or other regulatory air quality analyses of point or
mobile sources at or peripheral to airport property that are
unrelated to airport operations. The latest version of AEDT may be
obtained from the FAA at: <a href="https://aedt.faa.gov">https://aedt.faa.gov</a>.

7.0 General Modeling Considerations

7.1 Discussion

a. This section contains recommendations concerning a number of
different issues not explicitly covered in other sections of the
Guideline. The topics covered here are not specific to any one
program or modeling area, but are common to dispersion modeling
analyses for criteria pollutants.

7.2 Recommendations

7.2.1 All Sources

7.2.1.1 Dispersion Coefficients

a. For any dispersion modeling exercise, the urban or rural
determination of a source

[[Page 95056]]

is critical in determining the boundary layer characteristics that
affect the model's prediction of downwind concentrations.
Historically, steady-state Gaussian plume models used in most
applications have employed dispersion coefficients based on
Pasquill-Gifford \77\ in rural areas and McElroy- Pooler \78\ in
urban areas. These coefficients are still incorporated in the BLP
and OCD models. However, the AERMOD model incorporates a more up-to-
date characterization of the atmospheric boundary layer using
continuous functions of parameterized horizontal and vertical
turbulence based on Monin-Obukhov similarity (scaling)
relationships.\44\ Another key feature of AERMOD's formulation is
the option to use directly observed variables of the boundary layer
to parameterize dispersion.\44\ \45\
b. The selection of rural or urban dispersion coefficients in a
specific application should follow one of the procedures suggested
by Irwin \79\ to determine whether the character of an area is
primarily urban or rural (of the two methods, the land use procedure
is considered more definitive.):
i. Land Use Procedure: (1) Classify the land use within the
total area, A<INF>o</INF>, circumscribed by a 3 km radius circle
about the source using the meteorological land use typing scheme
proposed by Auer; \80\ (2) if land use types I1, I2, C1, R2, and R3
account for 50 percent or more of A<INF>o</INF>, use urban
dispersion coefficients; otherwise, use appropriate rural dispersion
coefficients.
ii. Population Density Procedure: (1) Compute the average
population density, p per square kilometer with A<INF>o</INF> as
defined above; (2) If p is greater than 750 people per square
kilometer, use urban dispersion coefficients; otherwise use
appropriate rural dispersion coefficients.
c. Population density should be used with caution and generally
not be applied to highly industrialized areas where the population
density may be low and, thus, a rural classification would be
indicated. However, the area is likely to be sufficiently built-up
so that the urban land use criteria would be satisfied. Therefore,
in this case, the classification should be ``urban'' and urban
dispersion parameters should be used.
d. For applications of AERMOD in urban areas, under either the
Land Use Procedure or the Population Density Procedure, the user
needs to estimate the population of the urban area affecting the
modeling domain because the urban influence in AERMOD is scaled
based on a user-specified population. For non-population oriented
urban areas, or areas influenced by both population and industrial
activity, the user will need to estimate an equivalent population to
adequately account for the combined effects of industrialized areas
and populated areas within the modeling domain. Selection of the
appropriate population for these applications should be determined
in consultation with the appropriate reviewing authority (paragraph
3.0(b)) and the latest version of the AERMOD Implementation
Guide.\81\
e. It should be noted that AERMOD allows for modeling rural and
urban sources in a single model run. For analyses of whole urban
complexes, the entire area should be modeled as an urban region if
most of the sources are located in areas classified as urban. For
tall stacks located within or adjacent to small or moderate sized
urban areas, the stack height or effective plume height may extend
above the urban boundary layer and, therefore, may be more
appropriately modeled using rural coefficients. Model users should
consult with the appropriate reviewing authority (paragraph 3.0(b))
and the latest version of the AERMOD Implementation Guide \81\ when
evaluating this situation.
f. Buoyancy-induced dispersion (BID), as identified by
Pasquill,\82\ is included in the preferred models and should be used
where buoyant sources (e.g., those involving fuel combustion) are
involved.

7.2.1.2 Complex Winds

a. Inhomogeneous local winds. In many parts of the United
States, the ground is neither flat nor is the ground cover (or land
use) uniform. These geographical variations can generate local winds
and circulations, and modify the prevailing ambient winds and
circulations. Typically, geographic effects are more apparent when
the ambient winds are light or calm, as stronger synoptic or
mesoscale winds can modify, or even eliminate the weak geographic
circulations.\83\ In general, these geographically induced wind
circulation effects are named after the source location of the
winds, e.g., lake and sea breezes, and mountain and valley winds. In
very rugged hilly or mountainous terrain, along coastlines, or near
large land use variations, the characteristics of the winds are a
balance of various forces, such that the assumptions of steady-state
straight-line transport both in time and space are inappropriate. In
such cases, a model should be chosen to fully treat the time and
space variations of meteorology effects on transport and dispersion.
The setup and application of such a model should be determined in
consultation with the appropriate reviewing authority (paragraph
3.0(b)) consistent with limitations of paragraph 3.2.2(e). The
meteorological input data requirements for developing the time and
space varying three-dimensional winds and dispersion meteorology for
these situations are discussed in paragraph 8.4.1.2(c). Examples of
inhomogeneous winds include, but are not limited to, situations
described in the following paragraphs:
i. Inversion breakup fumigation. Inversion breakup fumigation
occurs when a plume (or multiple plumes) is emitted into a stable
layer of air and that layer is subsequently mixed to the ground
through convective transfer of heat from the surface or because of
advection to less stable surroundings. Fumigation may cause
excessively high concentrations, but is usually rather short-lived
at a given receptor. There are no recommended refined techniques to
model this phenomenon. There are, however, screening procedures \40\
that may be used to approximate the concentrations. Considerable
care should be exercised in using the results obtained from the
screening techniques.
ii. Shoreline fumigation. Fumigation can be an important
phenomenon on and near the shoreline of bodies of water. This can
affect both individual plumes and area-wide emissions. When
fumigation conditions are expected to occur from a source or sources
with tall stacks located on or just inland of a shoreline, this
should be addressed in the air quality modeling analysis. The EPA
has evaluated several coastal fumigation models, and the evaluation
results of these models are available for their possible application
on a case-by-case basis when air quality estimates under shoreline
fumigation conditions are needed.\84\ Selection of the appropriate
model for applications where shoreline fumigation is of concern
should be determined in consultation with the appropriate reviewing
authority (paragraph 3.0(b)).
iii. Stagnation. Stagnation conditions are characterized by calm
or very low wind speeds, and variable wind directions. These
stagnant meteorological conditions may persist for several hours to
several days. During stagnation conditions, the dispersion of air
pollutants, especially those from low-level emissions sources, tends
to be minimized, potentially leading to relatively high ground-level
concentrations. If point sources are of interest, users should note
the guidance provided in paragraph (a) of this subsection. Selection
of the appropriate model for applications where stagnation is of
concern should be determined in consultation with the appropriate
reviewing authority (paragraph 3.0(b)).

7.2.1.3 Gravitational Settling and Deposition

a. Gravitational settling and deposition may be directly
included in a model if either is a significant factor. When
particulate matter sources can be quantified and settling and dry
deposition are problems, use professional judgment along with
coordination with the appropriate reviewing authority (paragraph
3.0(b)). AERMOD contains algorithms for dry and wet deposition of
gases and particles.\85\ For other Gaussian plume models, an
``infinite half-life'' may be used for estimates of particle
concentrations when only exponential decay terms are used for
treating settling and deposition. Lagrangian models have varying
degrees of complexity for dealing with settling and deposition and
the selection of a parameterization for such should be included in
the approval process for selecting a Lagrangian model. Eulerian grid
models tend to have explicit parameterizations for gravitational
settling and deposition as well as wet deposition parameters already
included as part of the chemistry scheme.

7.2.2 Stationary Sources

7.2.2.1 Good Engineering Practice Stack Height

a. The use of stack height credit in excess of Good Engineering
Practice (GEP) stack height or credit resulting from any other
dispersion technique is prohibited in the development of emissions
limits by 40 CFR 51.118 and 40 CFR 51.164. The definition of GEP
stack height and dispersion technique are contained in 40 CFR
51.100. Methods and procedures for making the appropriate stack
height calculations, determining stack height credits and an example
of applying those

[[Page 95057]]

techniques are found in several references,\86\ \87\ \88\ \89\ that
provide a great deal of additional information for evaluating and
describing building cavity and wake effects.
b. If stacks for new or existing major sources are found to be
less than the height defined by the EPA's refined formula for
determining GEP height, then air quality impacts associated with
cavity or wake effects due to the nearby building structures should
be determined. The EPA refined formula height is defined as H +
1.5L.\88\ Since the definition of GEP stack height defines excessive
concentrations as a maximum ground-level concentration due in whole
or in part to downwash of at least 40 percent in excess of the
maximum concentration without downwash, the potential air quality
impacts associated with cavity and wake effects should also be
considered for stacks that equal or exceed the EPA formula height
for GEP. The AERSCREEN model can be used to obtain screening
estimates of potential downwash influences, based on the PRIME
downwash algorithm incorporated in the AERMOD model. If more refined
concentration estimates are required, AERMOD should be used (section
4.2.2).

7.2.2.2 Plume Rise

a. The plume rise methods of Briggs 90 91 are
incorporated in many of the preferred models and are recommended for
use in many modeling applications. In AERMOD,44 45 for
the stable boundary layer, plume rise is estimated using an
iterative approach, similar to that in the CTDMPLUS model. In the
convective boundary layer, plume rise is superposed on the
displacements by random convective velocities.\92\ In AERMOD, plume
rise is computed using the methods of Briggs, except in cases
involving building downwash, in which a numerical solution of the
mass, energy, and momentum conservation laws is performed.\93\ No
explicit provisions in these models are made for multistack plume
rise enhancement or the handling of such special plumes as flares.
b. Gradual plume rise is generally recommended where its use is
appropriate: (1) in AERMOD; (2) in complex terrain screening
procedures to determine close-in impacts; and (3) when calculating
the effects of building wakes. The building wake algorithm in AERMOD
incorporates and exercises the thermodynamically based gradual plume
rise calculations as described in paragraph (a) of this subsection.
If the building wake is calculated to affect the plume for any hour,
gradual plume rise is also used in downwind dispersion calculations
to the distance of final plume rise, after which final plume rise is
used. Plumes captured by the near wake are re-emitted to the far
wake as a ground-level volume source.
c. Stack tip downwash generally occurs with poorly constructed
stacks and when the ratio of the stack exit velocity to wind speed
is small. An algorithm developed by Briggs \91\ is the recommended
technique for this situation and is used in preferred models for
point sources.
d. On a case-by-case basis, refinements to the preferred model
may be considered for plume rise and downwash effects and shall
occur in agreement with the appropriate reviewing authority
(paragraph 3.0(b)) and approval by the EPA Regional office based on
the requirements of section 3.2.2.

7.2.3 Mobile Sources

a. Emissions of primary pollutants from mobile sources can be
modeled with an appropriate model identified in section 4.2.
Screening of mobile sources can be accomplished by using screening
meteorology, e.g., worst-case meteorological conditions. Maximum
hourly concentrations computed from screening modeling can be
converted to longer averaging periods using the scaling ratios
specified in the AERSCREEN User's Guide.\37\
b. Mobile sources can be modeled in AERMOD as either line (i.e.,
elongated area) sources or as a series of volume sources. Line
sources can be represented in AERMOD with the following source
types: LINE, AREA, VOLUME or RLINE. However, since mobile source
modeling usually includes an analysis of very near-source impacts,
the results can be highly sensitive to the characterization of the
mobile emissions. Important characteristics for both line/area and
volume sources include the plume release height, source width, and
initial dispersion characteristics, and should also take into
account the impact of traffic-induced turbulence that can cause
roadway sources to have larger initial dimensions than might
normally be used for representing line sources.
c. The EPA's quantitative PM hot-spot guidance \65\ and Haul
Road Workgroup Final Report \67\ provide guidance on the appropriate
characterization of mobile sources as a function of the roadway and
vehicle characteristics. The EPA's quantitative PM hot-spot guidance
includes important considerations and should be consulted when
modeling roadway links. Area and line sources, which can be
characterized as AREA, LINE, and RLINE source types in AERMOD, or
volume sources, may be used for modeling mobile sources. However,
experience in the field has shown that area sources (characterized
as AREA, LINE, or RLINE source types) may be easier to characterize
correctly compared to volume sources. If volume sources are used, it
is particularly important to ensure that roadway emissions are
appropriately spaced when using volume source so that the emissions
field is uniform across the roadway. Additionally, receptor
placement is particularly important for volume sources that have
``exclusion zones'' where concentrations are not calculated for
receptors located ``within'' the volume sources, i.e., less than
2.15 times the initial lateral dispersion coefficient from the
center of the volume.\65\ Therefore, placing receptors in these
``exclusion zones'' will result in underestimates of roadway
impacts.

8.0 Model Input Data

a. Databases and related procedures for estimating input
parameters are an integral part of the modeling process. The most
appropriate input data available should always be selected for use
in modeling analyses. Modeled concentrations can vary widely
depending on the source data or meteorological data used. This
section attempts to minimize the uncertainty associated with
database selection and use by identifying requirements for input
data used in modeling. More specific data requirements and the
format required for the individual models are described in detail in
the user's guide and/or associated documentation for each model.

8.1 Modeling Domain

8.1.1 Discussion

a. The modeling domain is the geographic area for which the
required air quality analyses for the NAAQS and PSD increments are
conducted.

8.1.2 Requirements

a. For a NAAQS or PSD increments assessment, the modeling domain
or project's impact area shall include all locations where the
emissions of a pollutant from the new or modifying source(s) may
cause a significant ambient impact. This impact area is defined as
an area with a radius extending from the new or modifying source to:
(1) the most distant location where air quality modeling predicts a
significant ambient impact will occur, or (2) the nominal 50 km
distance considered applicable for Gaussian dispersion models,
whichever is less. The required air quality analysis shall be
carried out within this geographical area with characterization of
source impacts, nearby source impacts, and background
concentrations, as recommended later in this section.
b. For SIP attainment demonstrations for ozone and
PM<INF>2.5</INF>, or regional haze reasonable progress goal
analyses, the modeling domain is determined by the nature of the
problem being modeled and the spatial scale of the emissions that
impact the nonattainment or Class I area(s). The modeling domain
shall be designed so that all major upwind source areas that
influence the downwind nonattainment area are included in addition
to all monitor locations that are currently or recently violating
the NAAQS or close to violating the NAAQS in the nonattainment area.
Similarly, all Class I areas to be evaluated in a regional haze
modeling application shall be included and sufficiently distant from
the edge of the modeling domain. Guidance on the determination of
the appropriate modeling domain for photochemical grid models in
demonstrating attainment of these air quality goals is
available.\64\ Users should consult the latest version of this
guidance for the most current modeling guidance and the appropriate
reviewing authority (paragraph 3.0(b)) for any application specific
guidance that is beyond the scope of this section.

8.2 Source Data

8.2.1 Discussion

a. Sources of pollutants can be classified as point, line, area,
and volume sources. Poin

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