Home/Federal/Federal Register/2023-22876

Proposed Rule2023-22876

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

Primary source

Metadata and text below are from the Federal Register, a public-domain U.S. government work. Always verify the official published version before relying on it for any legal matter.

Published

October 23, 2023

Issuing agencies

Environmental Protection Agency

Abstract

In this action, the Environmental Protection Agency (EPA) proposes to revise the Guideline on Air Quality Models ("Guideline"). The Guideline has been incorporated into EPA's regulations, satisfying a requirement under the Clean Air Act (CAA) section 165(e)(3)(D) for the EPA to specify, with reasonable particularity, models to be used in the Prevention of Significant Deterioration (PSD) program. It provides EPA-preferred models and other recommended techniques, as well as guidance for their use in predicting ambient concentrations of air pollutants. In this action, the EPA is proposing 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. Within this action, the EPA is also announcing the Thirteenth Conference on Air Quality Modeling and invites the public to participate in the conference. The conference will focus on the proposed revisions to the Guideline, and part of the conference will also serve as the public hearing for these revisions.

Full Text

<html>
<head>
<title>Federal Register, Volume 88 Issue 203 (Monday, October 23, 2023)</title>
</head>
<body><pre>
[Federal Register Volume 88, Number 203 (Monday, October 23, 2023)]
[Proposed Rules]
[Pages 72826-72868]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2023-22876]

[[Page 72825]]

Vol. 88

Monday,

No. 203

October 23, 2023

Part II

Environmental Protection Agency

-----------------------------------------------------------------------

40 CFR Part 51

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

Federal Register / Vol. 88, No. 203 / Monday, October 23, 2023 /
Proposed Rules

[[Page 72826]]

-----------------------------------------------------------------------

ENVIRONMENTAL PROTECTION AGENCY

40 CFR Part 51

[EPA-HQ-OAR-2022-0872; FRL-10391-01-OAR]
RIN 2060-AV92

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

AGENCY: Environmental Protection Agency (EPA).

ACTION: Proposed rule; notification of public hearing and conference.

-----------------------------------------------------------------------

SUMMARY: In this action, the Environmental Protection Agency (EPA)
proposes to revise the Guideline on Air Quality Models (``Guideline'').
The Guideline has been incorporated into EPA's regulations, satisfying
a requirement under the Clean Air Act (CAA) section 165(e)(3)(D) for
the EPA to specify, with reasonable particularity, models to be used in
the Prevention of Significant Deterioration (PSD) program. It provides
EPA-preferred models and other recommended techniques, as well as
guidance for their use in predicting ambient concentrations of air
pollutants. In this action, the EPA is proposing 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. Within this action, the
EPA is also announcing the Thirteenth Conference on Air Quality
Modeling and invites the public to participate in the conference. The
conference will focus on the proposed revisions to the Guideline, and
part of the conference will also serve as the public hearing for these
revisions.

DATES: Comments must be received on or before December 22, 2023.
Public hearing and conference: The public hearing for this action
and the Thirteenth Conference on Air Quality Modeling will be held
November 14-15, 2023, from 8:30 a.m. to 5:00 p.m. Eastern Standard Time
(EST).

ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-
OAR-2022-0872, by one of the following methods:
<bullet> Federal eRulemaking Portal: <a href="https://www.regulations.gov">https://www.regulations.gov</a>.
Follow the online instructions for submitting comments.
<bullet> Email: <a href="/cdn-cgi/l/email-protection#1b7a367a757f3669367f7478707e6f5b7e6b7a357c746d">[email&#160;protected]</a>. Include Docket ID No. EPA-
HQ-OAR-2022-0872 in the subject line of the message.
<bullet> Fax: (202) 566-9744.
<bullet> Mail: Environmental Protection Agency, EPA Docket Center,
Office of Air and Radiation Docket, Mail code 28221T, Attention Docket
No. EPA-HQ-OAR-2022-0872, 1200 Pennsylvania Ave. NW, Washington, DC
20460.
<bullet> Hand/Courier Delivery: EPA Docket Center, Room 3334, EPA
WJC West Building, 1301 Constitution Ave. NW, Washington, DC. The
Docket Center's hours of operations are 8:30 a.m.-4:30 p.m., Monday-
Friday (except Federal Holidays).
Instructions: All submissions received must include the Docket ID
No. for this rulemaking. Comments received may be posted without change
to <a href="https://www.regulations.gov">https://www.regulations.gov</a>, including any personal information
provided. For detailed instructions on sending comments and additional
information on the rulemaking process, see the ``Public Participation''
heading of the SUPPLEMENTARY INFORMATION section of this document.
The public hearing will be held at 109 T.W. Alexander Drive,
Research Triangle Park, North Carolina 27711. The hearing will convene
at 8:30 a.m. (local time) and will conclude at 5:00 p.m. (local time).
Refer to the SUPPLEMENTARY INFORMATION section below for additional
information.

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#b6f4c4dfd2d1d3c4c598f1d3d9c4d1d3f6d3c6d798d1d9c0">[email&#160;protected]</a>. (and include ``2023 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?
II. Background
A. The Guideline on Air Quality Models and EPA Modeling
Conferences
B. The Twelfth Conference on Air Quality Modeling
C. Alpha and Beta Categorization of Non-Regulatory Options
III. Public Participation
A. Written Comments
B. Notice of Public Hearing and the Thirteenth Conference on Air
Quality Models
IV. Proposed Revisions to the Guideline
A. Proposed Revisions
V. Ongoing Model Development
VI. 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

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 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
air quality assessments required under EPA regulation. Categories and
entities potentially regulated by this action include:

------------------------------------------------------------------------
NAICS \a\
Category code
------------------------------------------------------------------------
Federal/State/territorial/local/Tribal government........... 924110
------------------------------------------------------------------------
\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 proposed rule and relative supporting documentation will also be
available on 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/13th-conference-air-quality-modeling">https://www.epa.gov/scram/13th-conference-air-quality-modeling</a>.

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

[[Page 72827]]

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 CFR system for
labeling 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 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 August 12-
13, 2015, and included the public hearing for the most recently
proposed version 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 at 45344).
These proposed revisions were adopted and reflected in the latest
version of the Guideline, promulgated on January 17, 2017 (82 FR 5182).

B. The Twelfth Conference on Air Quality Modeling

The most recent EPA modeling conference was the Twelfth Conference
on Air Quality Modeling, which 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 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

[[Page 72828]]

future revision in the Guideline. The proposed regulatory updates to
the AERMOD Modeling System in this action address topics on which there
was focused discussion and engagement with the stakeholder community
through these expert panels and invited and public presentations during
the Twelfth Conference.
All the presentations, along with the transcript of the conference
proceedings, are available in the docket for the Twelfth Conference on
Air Quality Models (Docket ID No. EPA-HQ-OAR-2019-0454). Additionally,
all the materials associated with the Twelfth Conference and the public
hearing are available on the EPA's SCRAM website at <a href="https://www.epa.gov/scram/12th-conference-air-quality-modeling">https://www.epa.gov/scram/12th-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 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. In addition, the EPA developed a protocol to
enable the external community to submit model updates to the EPA for
review and consideration for inclusion as new alpha or beta options. A
pathway such as this that facilitates more frequent and active
engagement with the external 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 have not yet been fully tested, evaluated, or vetted
through peer review and should not be considered for use as an
alternative model for regulatory applications of the model.
Beta options, on the other hand, have been demonstrated to be
applicable on a theoretical basis, have undergone scientific peer
review, and are supported with performance evaluations using available
and adequate databases that demonstrate unbiased, improved model
performance. 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.

III. Public Participation

Interested persons may provide the EPA with their views on the
proposed revisions to the Guideline in several ways. This includes
submitting written comments to the EPA, participating in the Thirteenth
Conference on Air Quality Modeling, and speaking at the public hearing
that will be conducted as part of the conference. Additional
information on where to submit written comments on the proposed
revisions to the Guideline is provided in the ADDRESSES section above.

A. Written Comments

Submit your comments, identified by Docket ID No. EPA-HQ-OAR-2022-
0872, at <a href="https://www.regulations.gov">https://www.regulations.gov</a> (our preferred method), or the
other methods identified in the ADDRESSES section. Once submitted,
comments cannot be edited or removed from the docket. The EPA may
publish any comment received to its public docket. Do not submit to
EPA's docket at <a href="https://www.regulations.gov">https://www.regulations.gov</a> any information you
consider to be Confidential Business Information (CBI), Proprietary
Business Information (PBI), or other information whose disclosure is
restricted by statute. Multimedia submissions (audio, video, etc.) must
be accompanied by a written comment. The written comment is considered
the official comment and should include discussion of all points you
wish to make. The EPA will generally not consider comments or comment
contents located outside of the primary submission (i.e., on the web,
cloud, or other file sharing system). Please visit <a href="https://www.epa.gov/dockets/commenting-epa-dockets">https://www.epa.gov/dockets/commenting-epa-dockets</a> for additional submission methods; the
full EPA public comment policy; information about CBI, PBI, or
multimedia submissions; and general guidance on making effective
comments.

B. Notice of Public Hearing and the Thirteenth Conference on Air
Quality Models

The public hearing for this action and the Thirteenth Conference on
Air Quality Modeling will be held on November 14-15, 2023, in the EPA
Nantahala Auditorium, Room C111, 109 T.W. Alexander Drive, Research
Triangle Park, NC 27711. The hearing and conference will convene each
day at 8:30 a.m. EST and will conclude at 5:00 p.m. EST.
The Thirteenth Conference on Air Quality Modeling will be open to
the public. No registration fee is charged. The conference will be
formally conducted and chaired by an EPA official. As required under
CAA section 320, a verbatim transcript of the conference proceedings
will be produced and placed in the docket for this proposed action. The
conference will begin with introductory remarks by the presiding EPA
official. The EPA staff and EPA invited speakers will then provide a
structured overview of the revisions to the Guideline as proposed in
this document and present on the research that supports those revisions
and supports formulation updates to the preferred models. The following
topics will be presented:

I. Overview of the Thirteenth Conference on Air Quality
Modeling;
II. Review of the proposed revisions to the preferred air
quality models; and
III. Review of the proposed revisions to the Guideline.

At the conclusion of these presentations, the EPA will convene the
public hearing on the proposed revisions to the Guideline. The public
hearing will span a portion of the afternoon of the first day and
throughout the second day of the conference. The EPA will make every
effort to follow the schedule as closely as possible on the days of the
conference; however, please plan for the public hearing to run either
ahead of schedule or behind schedule. The EPA may close the hearing 15
minutes after

[[Page 72829]]

the last pre-registered speaker has testified on November 15, if there
are no additional speakers.
Those wishing to reserve time to speak at the public hearing,
whether to offer specific comments on the proposed rule, volunteer a
presentation on a special topic, or to offer recommendations on any
regulatory modeling techniques, should contact us at the address given
in the FOR FURTHER INFORMATION CONTACT section by no later than
November 10, 2023. Such persons should identify the organization (if
any) on whose behalf they are speaking and the length of the
presentation. If a scheduled presentation is projected to be longer
than 10 minutes, the presenter should also state why a longer period is
needed. Scheduled speakers should bring extra copies of their
presentation for inclusion in the docket and for the convenience of the
recorder. Scheduled speakers will also be permitted to enter additional
written comments into the record.
Any person in attendance wishing to speak at the public hearing who
has not reserved time in advance may provide oral comments on the
proposed revisions to the Guideline during time allotted on the last
day. These parties will need to sign up to speak on the second day of
the hearing, and the EPA may need to limit the duration of
presentations to allow all participants to be heard.
The EPA may ask clarifying questions during the oral presentations
but will not respond to the presentations at that time. Information
submitted to the EPA during the public hearing will be placed in the
docket for this proposed action. Written statements and supporting
information submitted during the comment period will be considered with
the same weight as oral testimony and supporting information presented
at the public hearing.
Conference background information. Preregistration details,
additional background information, and a more detailed agenda for the
Thirteenth Conference on Air Quality Modeling are electronically
available at <a href="https://www.epa.gov/scram/13th-conference-air-quality-modeling">https://www.epa.gov/scram/13th-conference-air-quality-modeling</a>. Preregistration for the conference, while not required, is
strongly recommended due to heightened security protocols at the EPA-
RTP facility.
Access to U.S. government facility. Because this hearing is being
held at a U.S. government facility, individuals planning to attend the
conference and/or public hearing should be prepared to show valid
picture identification to the security staff in order to gain access to
the meeting room. Please note that the REAL ID Act, passed by Congress
in 2005, established new requirements for entering Federal facilities.
For purposes of the REAL ID Act, EPA will accept government-issued IDs,
including drivers' licenses, from the District of Columbia and all
States and territories except from American Samoa. If your
identification is issued by American Samoa, you must present an
additional form of identification to enter the Federal building where
the public hearing will be held. Acceptable alternative forms of
identification include Federal employee badges, passports, enhanced
driver's licenses, and military identification cards. For additional
information for the status of your State regarding REAL ID, go to:
<a href="https://www.dhs.gov/real-id-enforcement-brieffrequently-asked-questions">https://www.dhs.gov/real-id-enforcement-brieffrequently-asked-questions</a>. Any objects brought into the building need to fit through
the security screening system, such as a purse, laptop bag, or small
backpack. Demonstrations will not be allowed on Federal property for
security reasons. Attendees are encouraged to arrive at least 15
minutes prior to the start of the meeting to allow enough time for
security screening.

IV. Proposed Revisions to the Guideline

In this action, the EPA is proposing updates 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
proposed updates to the Guideline. There are additional editorial
changes proposed to the Guideline to correct minor typographical errors
found in the 2017 Guideline and update website links.

A. Proposed Revisions

This section provides a detailed overview of the substantive
proposed changes to the Guideline that are intended to improve the
science of the models and approaches used in regulatory assessments.
1. Proposed 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,\1\ 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.
---------------------------------------------------------------------------

\1\ <a href="https://www.epa.gov/scram/12th-conference-air-quality-modeling">https://www.epa.gov/scram/12th-conference-air-quality-modeling</a>.
---------------------------------------------------------------------------

Each of the proposed formulation updates to the AERMOD Modeling
System is provided as a non-regulatory beta option in the release of
the relevant modeling system components that is occurring concurrent
with this proposed rule. If EPA adopts these formulation updates in a
subsequent final rule, the beta categorization would be removed and the
respective model option(s) could be considered regulatory model
options.
The EPA proposes 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
As the number of overwater applications has increased in recent
years, the EPA is proposing to add the Coupled Ocean-Atmosphere
Response Experiment (COARE) 2 3 algorithms to AERMET for
meteorological data processing in applications using either observed or
prognostic meteorological data in overwater marine boundary layer
environments. One of the first notable uses of AERMOD for an overwater
application was an alternative model application--AERMOD-COARE was used
in 2011 in an ice-free arctic environment of Alaska.4 5 In
this

[[Page 72830]]

application, the incorporation of the COARE bulk flux algorithm was
used as an alternative to the AERMET meteorological processor to
AERMOD. This led to the development of the AERCOARE \6\ processor that
can be used with either measured or prognostic data for overwater
applications in lieu of AERMET. AERCOARE has been approved as an
alternative model for several overwater applications since 2011.\7\
---------------------------------------------------------------------------

\2\ 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.
\3\ 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.
\4\ U.S. EPA, 2011: COARE Bulk Flux Algorithm to Generate Hourly
Meteorological Data for Use with the AERMOD dispersion program;
Section 3.2.2.e Alternative Refined Model Demonstration Herman Wong
Memorandum dated April 1, 2011, Office of Environmental Assessment,
Region 10, Seattle, Washington 98101.
\5\ U.S. EPA, 2011: Model Clearinghouse Review AERMOD-COARE as
an Alternative Model in an Arctic Ice Free Environment. George
Bridgers Memorandum dated May 6, 2011, Office of Air Quality
Planning and Standards, Research Triangle Park, North Carolina
27711.
\6\ U.S. EPA, 2012: User's Manual AERCOARE Version 1.0. EPA-910-
R-12-008. U.S. EPA, Region 10, Seattle, WA.
\7\ Please reference the EPA Model Clearinghouse Information
Storage and Retrieval System (MCHISRS) database for more information
regarding AERCOARE alternative model approvals (<a href="https://cfpub.epa.gov/oarweb/MCHISRS">https://cfpub.epa.gov/oarweb/MCHISRS</a>, text Search term ``AERCOARE'').
---------------------------------------------------------------------------

For overwater applications, 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. These
calculations include calculation of surface roughness, stability
classification, effects of moisture on Monin-Obukhov length, and the
use of Bowen ratio by AERMET for heat flux calculations.\5\ The EPA
proposes to add COARE to AERMET in order to ensure that the COARE
algorithms are updated regularly as part of routine AERMET updates, to
provide consistent data handling among land based and overwater based
meteorological data (e.g., treatment of missing data and treatment of
calms), and to have all meteorological processing for AERMOD
applications in one program.
The addition of the COARE algorithms to AERMET would replace the
standalone AERCOARE program and the AERCOARE output option in MMIF for
prognostic data overwater. This proposed option is selected by the user
with the METHOD COARE RUN-COARE record in the AERMET Stage 2 input
file. For prognostic applications processed through the MMIF, the user
can run MMIF for AERMET input for overwater applications.
The addition of COARE to AERMET would eliminate the previous
alternative model demonstration requirements for use of AERMOD in
marine environments, and this elimination is contingent upon
consultation with the EPA Regional Office and appropriate reviewing
authority. This consultation will ensure that platform downwash and
shoreline fumigation are adequately considered in the modeling
demonstration.
b. Proposed Addition of a New Tier 3 Detailed Screening Technique for
NO<INF>2</INF>
Section 4.2.3.4 of the 2017 Guideline details a 3-tiered approach
for evaluating the modeled impacts of NO<INF>X</INF> sources, which was
recommended to assess hourly and annual average NO<INF>2</INF> impacts
from point, volume, and area sources for the purposes of the PSD
program, SIP planning, and transportation general conformity. This 3-
tiered approach addresses the co-emissions of NO and NO<INF>2</INF> and
the subsequent conversion of NO to NO<INF>2</INF> in the atmosphere.
The tiered levels include:
Tier 1--assuming that all emitted NO is converted to NO<INF>2</INF>
(full conversion).
Tier 2--using the Ambient Ratio Method 2 (ARM2), which applies an
assumed equilibrium ratio of NO<INF>2</INF> to NO<INF>X</INF>, based on
analysis of and correlation with nationwide hourly observed ambient
conditions.
Tier 3--applying the Ozone Limiting Method (OLM) and Plume Volume
Molar Ratio (PVMRM) screening options based on site-specific hourly
ozone data and source-specific NO<INF>2</INF> to NO<INF>X</INF> in-
stack ratios.8 9 10 11
---------------------------------------------------------------------------

\8\ Podrez, M. 2015. An Update to the Ambient Ratio Method for
1-h NO<INF>2</INF> Air Quality Standards Dispersion Modeling.
Atmospheric Environment, 103: 163-170.
\9\ Cole, H.S. and J.E. Summerhays, 1979. A Review of Techniques
Available for Estimation of Short-Term NO<INF>2</INF>
Concentrations. Journal of the Air Pollution Control Association,
29(8): 812-817.
\10\ Hanrahan, P.L., 1999. The Polar Volume Polar Ratio Method
for Determining NO<INF>2</INF>/NO<INF>X</INF> Ratios in Modeling--
Part I: Methodology. Journal of the Air & Waste Management
Association, 49: 1324-1331.
\11\ Chu, S.H. and E.L. Meyer, 1991. Use of Ambient Ratios to
Estimate Impact of NO<INF>X</INF> Sources on Annual NO<INF>2</INF>
Concentrations. Proceedings, 84th Annual Meeting & Exhibition of the
Air & Waste Management Association, Vancouver, B.C.; 16-21 June
1991. (16pp.) (Docket No. A-92-65, II-A-9).
---------------------------------------------------------------------------

As further discussed in section 4.2.3.4(e) of the Guideline,
regulatory application of Tier 3 screening options shall occur in
consultation with the EPA Regional Office and appropriate reviewing
authority.
The EPA proposes to include the Generic Reaction Set Method (GRSM)
as a regulatory non-default Tier 3 NO<INF>2</INF> screening option.
Following a peer-reviewed publication in 2017, GRSM was added to AERMOD
as an alpha option in version 21112 and updated as a beta option in
version 22112.\12\ The primary motivation behind the formulation and
development of the GRSM NO<INF>2</INF> screening option was to address
photolytic conversion of NO<INF>2</INF> to NO and to address the time-
of-travel necessary for NO<INF>X</INF> plumes to convert the NO portion
of the plume to NO<INF>2</INF> via titration and entrainment of ambient
ozone. The existing regulatory non-default Tier 3 NO<INF>2</INF>
screening options, PVMRM and OLM, do not address or provide for
treatment of these mechanisms, and have been shown to over-predict for
some source characterizations and model configurations at project
source ambient air boundaries and within the first 1-3 km.\13\
---------------------------------------------------------------------------

\12\ David J. Carruthers, Jenny R. Stocker, Andrew Ellis, Martin
D. Seaton & Stephen E. Smith (2017) Evaluation of an explicit
NO<INF>X</INF> chemistry method in AERMOD, Journal of the Air &
Waste Management Association, 67:6, 702-712, DOI: 10.1080/
10962247.2017.1280096.
\13\ Jenny Stocker, Martin Seaton, Stephen Smith, James O'Neill,
Kate Johnson, Rose Jackson, David Carruthers (CERC). Evaluation of
the Generic Reaction Set Method for NO<INF>2</INF> conversion in
AERMOD. The modification of AERMOD to include ADMS chemistry. August
8, 2023. Cambridge Environmental Research Consultants (CERC)
Technical Report.
---------------------------------------------------------------------------

The functionality of the GRSM implementation in AERMOD is similar
to that of the PVMRM and OLM schemes, with exception to some additional
input requirements necessary for treatment of the reverse
NO<INF>2</INF> photolysis reaction during daytime hours. Modeled source
inputs for GRSM require NO<INF>2</INF>/NO<INF>X</INF> in-stack ratios,
with similar assumptions as applied to PVMRM and OLM according to
section 4.2.3.4 of the Guideline. Ambient inputs for GRSM require
hourly ozone concentrations taken from an appropriately representative
monitoring station or selection of monitoring stations for varying
upwind sector concentrations. GRSM also requires hourly NO<INF>X</INF>
concentration inputs to resolve the daytime photolysis of
NO<INF>2</INF> reaction in equilibrium with ozone titration conversion
of the NO portion of the NO<INF>X</INF> plume. GRSM hourly
NO<INF>X</INF> concentration inputs can also vary by upwind sector
concentration, as appropriate. 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. Nighttime GRSM NO<INF>2</INF> estimates are based
on ozone entrainment and titration of available NO in the
NO<INF>X</INF> plume. Note that all hourly ozone and NO<INF>X</INF>
ambient inputs to GRSM must coincide with the hourly meteorological

[[Page 72831]]

data records for the period of the modeling analysis (i.e., minimum of
1 year for on-site data, 3 years of prognostic data, and 5 years of
airport data).
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 3 km for typical point source
releases). Sensitivity testing and model performance evaluations of
these updates to GRSM in AERMOD version 23132 have shown consistent or
improved model behavior and performance.\14\
---------------------------------------------------------------------------

\14\ Environmental Protection Agency, 2023. Technical Support
Document (TSD) for Adoption of the Generic Reaction Set Method
(GRSM) as a Regulatory Non-Default Tier-3 NO2 Screening Option,
Publication No. EPA-454/R-23-009. Office of Air Quality Planning &
Standards, Research Triangle Park, NC.
---------------------------------------------------------------------------

c. Proposed Addition of RLINE as Mobile Source Type
As a culmination of an Interagency Agreement between EPA and FHWA,
the EPA proposes to add the RLINE source type as a new source type
applicable for regulatory modeling of mobile sources. This is in
addition to the AREA, LINE, and VOLUME source types already available
for mobile source modeling. The proposed addition of RLINE as a mobile
source type is an extension of the 2017 update to the Guideline in
which AERMOD replaced CALINE3 as the addendum A \15\ model for mobile
source modeling. At that time, AERMOD's AREA, LINE, and VOLUME sources
were available for mobile source modeling. The basis of the RLINE
source type is the EPA's Office of Research and Development (ORD)
Research LINE (RLINE) model \16\ released in 2013. The RLINE model was
designed for near-surface releases to simulate mobile source dispersion
with an emphasis on the near-road environment. The RLINE model was
first incorporated into AERMOD as a beta source type in AERMOD version
19191 in 2019.
---------------------------------------------------------------------------

\15\ Under the codification requirements of the Administrative
Committee of the Federal Register (ACFR), only subparts, parts,
subchapters, and chapters may have appendices. Therefore, we have
changed the naming convention from ``appendix A'' to ``addendum A''.
\16\ Snyder, M.G., Venkatram, A., Heist, D.K., Perry, S.G.,
Petersen, W.B. and Isakov, V., 2013. RLINE: A line source dispersion
model for near-surface releases. Atmospheric environment, 77,
pp.748-756.
---------------------------------------------------------------------------

The RLINE source type for this proposed action has undergone
significant evaluation by the EPA and the FHWA as part of the
Interagency Agreement and has shown improved
performance.17 18 This proposed option is selected by the
model user with the SOURCE type ``RLINE''. In addition to proposing
RLINE as a new source type, the EPA is also proposing the use of the
AERMOD urban option (accounting for urban heat island effect in stable
conditions) and terrain with the RLINE source type. However, the
inclusion of terrain with RLINE does not supersede the EPA's PM Hot-
spot guidance where FLAT terrain is recommended for modeling
applications.\19\ The EPA also emphasizes that the inclusion of RLINE
as a source type for mobile source modeling does not preclude the use
of the existing AREA, LINE, and VOLUME source types thereby extending
the flexibility of users in best characterizing mobile source for
regulatory modeling.
---------------------------------------------------------------------------

\17\ 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.
\18\ Heist, D., et al., 2023. Integration of RLINE dispersion
model into EPA's AERMOD: updated formulation and evaluations.
Journal of the Air & Waste Management Association, Manuscript
submitted for publication.
\19\ 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.
---------------------------------------------------------------------------

d. Support Information, Documentation, and Model Code
Model performance evaluation and peer-reviewed scientific
references for each of these three proposed updates to the AERMOD
Modeling System are cited and placed in the docket, as appropriate. An
updated user's guide and model formulation documents for version 23132
have also been placed in the docket. We have updated the summary
description of the AERMOD Modeling System to addendum A of the
Guideline to reflect these proposed 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. Proposed Updates to Recommendations on the Development of Background
Concentration
Based on permit modeling experiences since the 2017 revisions to
the Guideline, the EPA proposes 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). The Guideline recommends that a
representative background concentration should include contributions
from all sources, including both nearby and other sources. When
identifying nearby sources that may not be adequately represented by
ambient monitoring data, the Guideline recommends selecting sources
``that cause a significant concentration gradient in the vicinity of
the source(s) under consideration.'' The EPA recognizes that the
recommended method for identifying nearby sources lacks specificity, is
used and referenced inconsistently, and may lead to overly conservative
modeling exercises. The proposed revisions to section 8 are intended to
provide 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 proposes to revise 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's proposed framework 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-exiting air quality modeling to appropriately represent background
concentrations for the cumulative impact analysis.
In conjunction with the proposed revisions to section 8 of the
Guideline, the EPA developed the Draft Guidance on Developing
Background Concentrations for Use in Modeling Demonstrations.\20\ This
draft guidance

[[Page 72832]]

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.
---------------------------------------------------------------------------

\20\ 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.
---------------------------------------------------------------------------

3. Transition Period for Applicability of Revisions to the Guideline
In previous rulemakings to revise the Guideline, we have
traditionally communicated that it would be appropriate to provide 1-
year to transition to the use of new models, techniques and procedures
in the context of PSD permit applications and other regulatory modeling
applications. We invite comments whether it would be appropriate to
apply a 1-year transition after promulgation of the revised Guideline
(i.e., from its effective date) such that applications conducted under
the existing Guideline with approved protocols would be acceptable
during that period, but new requirements and recommendations should be
used for applications submitted after that period or protocols approved
after that period.
Such a transition period is consistent with previous revisions to
the Guideline and appropriate to avoid the time and expense of
revisiting modeling that is substantially complete, which would cause
undue delays to permit applications that are pending when the proposed
revisions to the Guideline are finalized. The proposed revisions to the
Guideline are intended as incremental improvements to the Guideline,
and such improvements do not necessarily invalidate past practices
under the previous editions of the Guideline. The requirements and
recommendations in the existing (2017) version of the Guideline were
previously identified as acceptable by the EPA, and they will continue
to be acceptable for air quality assessments during the period of
transition to the revised version of the Guideline, if finalized.
Where a proposed revision to the Guideline does raise questions
about the acceptability of a requirement or recommendation that it
replaces, model users and applicants are encouraged to consult with the
appropriate reviewing authority as soon as possible to assure the
acceptability of modeling used to support permit applications during
this period.
4. Proposed Revisions by Section
a. Section 1.0--Introduction
The EPA proposes to correct paragraph (i) by combining the
inadvertently created paragraph (A), which is actually part of the
phrase ``addendum A'' in the first sentence.
b. Section 3.0--Preferred and Alternative Air Quality Models
The EPA proposes to revise an outdated website link in section
3.0(b).
In sections 3.1.1(c) and 3.1.2(a), the EPA proposes to correct the
sections by combining the inadvertently created paragraph (A), which is
actually part of the phrase ``addendum A'' in the first sentence.
c. Section 4.0--Models for Carbon Monoxide, Lead, Sulfur Dioxide,
Nitrogen Dioxide and Primary Particulate Matter
The EPA proposes to update reference numbers where necessary due to
added references.
In sections 4.1(b) and 4.2.2(a), the EPA proposes to correct the
sections by combining the inadvertently created paragraph (A), which is
actually part of the phrase ``addendum A'' in the first sentence.
In section 4.2.2.1, the EPA proposes to add a new paragraph (f)
regarding the use of AERMOD in certain overwater situations. A
typographical correction is proposed in section 4.2.2.1(b).
The EPA proposes amendments to 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 proposes to revise 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 would be updated to
incorporate GRSM with the existing regulatory Tier 3 screening
techniques OLM and PVMRM. An additional statement is proposed
indicating GRSM model performance may be better than OLM and PVMRM
under certain source characterization situations. The EPA also proposes
to add 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 proposes to revise Table 4-1 in section 4.2.3.4(f) to
include GRSM as a Tier 3 detailed screening option.
d. Section 5.0--Models for Ozone and Secondarily Formed Particulate
Matter
The EPA proposes to update reference numbers where necessary due to
added references. In section 5.2, the EPA proposes to revise 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>.
e. Section 6.0--Modeling for Air Quality Related Values and Other
Governmental Programs
The EPA proposes to update reference numbers where necessary due to
added references and revise an outdated website link in section 6.3(a).
f. Section 7.0--General Modeling Considerations
The EPA proposes to update reference numbers where necessary due to
added references.
In section 7.2.3, the EPA proposes to revise 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 proposes to revise 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.
g. Section 8.0--Model Input Data
The EPA proposes to update reference numbers where necessary due to
added references.
The EPA proposes to revise Table 8-1 and Table 8-2 to correct
typographical errors and update the footnotes in each of the tables.
The EPA proposes to revise 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 would provide a stepwise framework for modeling isolated
single sources and multi-source areas as part of a cumulative impact
analysis. The EPA also proposes to remove 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 proposes to remove paragraph (d) in section 8.3.2 and
renumber paragraphs (e) and (f) to (d) and (e), respectively. The
content of

[[Page 72833]]

paragraph (d) is proposed to be included in the proposed revision of
paragraph (a) in section 8.3.2.
In section 8.3.3, the EPA proposes revisions to 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
proposes to remove 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 to the lack of definition of this term in
the context of modeling multi-source areas. The EPA also proposes to
revise 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 proposed
revisions to Tables 8-1 and 8-2.
In section 8.4.1, the EPA proposes to include 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 proposes to revise
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 to revise 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 proposes to revise 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 proposes to revise paragraph (a) of section 8.4.3.2 to
remove references to specific weblinks and to state that users should
refer to the latest guidance documents for weblinks.
The EPA proposes to add 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
proposed to be replaced with guidance to consult the appropriate
guidance documents for the latest thresholds.
h. Section 9.0--Regulatory Application of Models
The EPA proposes to update reference numbers where necessary due to
added references.
In section 9.2.3, the EPA proposes to revise 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 proposed revisions to Tables 8-
1 and 8-2.
i. Section 10.0--References
The EPA proposes updates to 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 proposes to add references to support proposed
updates to the AERMOD Modeling System described in this proposed update
to the Guideline.
5. Proposed Revisions to Addendum A \21\ to Appendix W to Part 51
---------------------------------------------------------------------------

\21\ Formerly designated as appendix A.
---------------------------------------------------------------------------

a. Section A.0
The EPA proposes to revise 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 proposes to revise the References section to include
additional references that support our proposed updates to the AERMOD
Modeling System.
In the Abstract section, the EPA proposes to add line type sources
as one of the source types AERMOD can simulate.
The EPA proposes to revise 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 would remove the need to request
an alternative model demonstration for such applications. The EPA also
proposes to clarify elevation data that can be used in AERMOD,
specifically the change in the name of the U.S. Geological Survey
(USGS) National Dataset (NED) to 3D Elevation Program (3DEP). For
consistency, references to NED would be updated to 3DEP throughout
section A.1.
The EPA proposes to revise section A.1(b) to include prognostic
data as meteorological input to the AERMOD Modeling System, as
applicable.
The EPA proposes to revise section A.1(l) to include the proposed
Generic Reaction Set Method in the discussion on chemical
transformation in AERMOD. We also propose to clarify the status of the
different deposition options in A.1(l).
The EPA proposes to revise section A.1(n) to include references to
additional evaluation studies to support our proposed updates to the
AERMOD Modeling System.
c. Section A.3
In section A.3, the EPA proposes to remove the reference to the
Bureau of Ocean Energy Management's (BOEM) outdated guidance.

V. Ongoing Model Development

In addition to the proposed beta options above, AERMOD version
23132 also includes alpha options that are thought to have scientific
merit and that are still being developed or evaluated and peer
reviewed. These alpha options are not being proposed as updates to the
regulatory formulation of the AERMOD Modeling System, and the EPA is
not taking comment on the alpha options during this rulemaking. A list
of alpha options on which the EPA has placed a high priority for
continued research and development for model improvement is included
below. Refer to the AERMOD User's Guide for details and usage of each
option.
The AERMOD Modeling System, version 23131, includes but is not
limited to the following alpha options:
<bullet> Low Wind Default Overrides (LOW_WIND).
LOW_WIND 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). 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. The LOW_WIND option in version
23132 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.
<bullet> Modifications to PRIME Building Downwash (AWMADWNW and
ORD_DWNW).
Beginning with AERMOD version 19191, two distinct sets of alpha
options were added that modify the building downwash algorithm, PRIME.
The two sets of options were developed

[[Page 72834]]

independently by EPA's ORD (ORD_DWNW) and the Air & Waste Management
Association (A&WMA) (AWMADWNW). With a couple of exceptions, the
options within each set can be employed individually or combined with
other options from each set.
<bullet> Downwash from Offshore Drilling Platforms (PLATFORM).
To enhance AERMOD's offshore modeling capabilities, the platform
downwash algorithm, adapted from the Offshore Coastal Dispersion (OCD)
dispersion model, was incorporated in AERMOD version 22112 and requires
further development, testing, and evaluation. The PLATFORM option
simulates the building downwash effect from platforms commonly used for
offshore drilling, made up of both porous and solid structures and
which are elevated with airflow beneath them.
<bullet> Extended RLINE Source Type Including Barriers and
Depressed Roadways (RLINEXT).
The RLINEXT source type was implemented in AERMOD version 18181 and
is an extended version of the RLINE source type that allows for a more
refined characterization of a road segment. It accepts separate inputs
for the elevations of each end of the road segment and extended options
for modeling with roadway barriers (RBARRIER) and depressed roadways
(RDEPRESS).
<bullet> TTRM and TTRM2 for Conversion of NO<INF>X</INF> to
NO<INF>2</INF>.
The Travel Time Reaction Method (TTRM) was implemented in AERMOD
version 21112 as a stand-alone NO<INF>X</INF>-to-NO<INF>2</INF>
conversion option that accounts for plume travel time, applicable only
in the near field. TTRM was further integrated in AERMOD version 22112
as TTRM2 which can be paired with any one of the Ambient Ration Method
(ARM2), OLM, or PVMRM. When paired with one of these, TTRM is applied
in the near field and the other specified option is applied in the far
field where travel time is not as relevant.
<bullet> Highly Buoyant Plume (HBP).
A Highly Buoyant Plume (HBP) option was implemented as an alpha
option that can be applied to POINT source types beginning with AERMOD
version 23132 to further explore AERMOD's treatment of the penetrated
plume. A penetrated plume occurs when a plume 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.
<bullet> Aircraft Plume Rise (AREA/VOLUME Source Types).
Beginning with AERMOD version 23132, the characterization of AREA
and VOLUME sources was extended to account for the buoyancy and
horizontal momentum of aircraft emissions. The aircraft plume rise
formulation and code for AREA and VOLUME sources was independently
developed and provided by the Federal Aviation Administration (FAA).
EPA continues to collaborate with FAA on model evaluation and peer
review of the aircraft plume rise formulations.

VI. 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
proposes 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 any unfunded mandate as described in
UMRA, 2 U.S.C. 1531-1538, and does not significantly or uniquely affect
small governments. 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 proposed 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 provided information regarding this action to the Tribes
during a monthly National Tribal Air Association (NTAA) call 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. Additionally, the EPA specifically solicits
any comments on this proposed action from Tribal officials.

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

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

[[Page 72835]]

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 action does not have disproportionate
and adverse human health or environmental effects on communities with
environmental justice concerns because it does not establish an
environmental health or safety standard. This action proposes 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 options in Environmental
Justice determinations. While the EPA does not expect this action to
directly impact air quality, the proposed revisions are important
because the Guideline is used by air permitting authorities and
industry to prepare and review NSR permits and serves as a benchmark of
consistency across the nation. This consistency has value to all
communities including communities with environmental justice concerns.

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
to the EPA of privately developed models. 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 guidance 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 guidance 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>
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

[[Page 72836]]

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 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
proposed and final 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.

[[Page 72837]]

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 sources
7 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
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

[[Page 72838]]

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 techniques, the EPA
Regional Office will coordinate and shall 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

[[Page 72839]]

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 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

[[Page 72840]]

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:
1. If a demonstration can be made that the model produces
concentration estimates equivalent to the estimates obtained using a
preferred model;
2. 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
3. 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 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

[[Page 72841]]

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 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 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

[[Page 72842]]

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[theta]/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. A brief description of each preferred model for refined
applications is found in addendum A. 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. OCD can determine the impact of offshore
emissions from point, area, or line sources on the air quality of
coastal regions. OCD 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\

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

[[Page 72843]]

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 72844]]

[GRAPHIC] [TIFF OMITTED] TP23OC23.000

Figure 4-1: Multi-Tiered Approach for Estimating NO2 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 72845]]

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 PM2.5

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 72846]]

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 72847]]

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 72848]]

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 72849]]

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 w

[…truncated; see source link]

View on FederalRegister.gov →Plain-text source

Indexed from Federal Register on October 23, 2023.

This is legal information, not legal advice. Laws vary by jurisdiction and change frequently. Always verify current law with official sources and consult a licensed attorney in your jurisdiction for advice on your specific situation.