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Draft Guidance on Developing Background
Concentrations for Use in Modeling
Demonstrations


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EPA-454/P-23-001
October 2023

Draft Guidance on Developing Background Concentrations for Use in Modeling

Demonstrations

U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Quality Assessment Division
Research Triangle Park, NC


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Table of Contents

1.	Introduction	1

2.	Guidance Overview	6

2.1	Determining a Representative Background Concentration	7

2.2	Framework for Identifying a Representative Background Concentration	9

3.	Application of Framework in Isolated Single Source Scenarios	16

3.1	Defining the Scope of the Cumulath e Impact Analysis		16

3.2	Identifying Relevant and Available I-missions, Air Quality and I-n\ ironmental Data.. 17

3.3	Determining Representatheness of Ambient Monitoring Data	17

4.	Application of Framework in Multi-source Areas		23

4.1	Defining the Scope of the Cumulati\e Impact Analysis	23

4.2	Identifying Rele\ ant and A\ ailaMe I-missions, Air Quality and Environmental Data.. 24

4.3	Determining Repicscnlati\eness ol" Ambient Monitor Data	25

4.4	Determination of Nearby Sources to Explicitly Model	29

5.	Additional Considerations 	33

6.	Summary		34

7.	References	36

Appendix A: Detailed Table of Available Air Quality, Emissions, and Environmental Data... A-l


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1. Introduction

The U.S. Environmental Protection Agency (EPA) is providing this "Guidance on
Developing Background Concentrations for Use in Modeling Demonstrations" to fulfill a need
for additional guidance on developing a representative background concentration used as part of
a cumulative impact analysis for National Ambient Air Quality Standards (NAAQS)
implementation modeling demonstrations (e.g., Prevention of Significant Deterioration (PSD)
compliance demonstrations, State Implementation Plan (SIP) demonstrations for inert pollutants,
and S02 designations). Due to the complex nature of determining a representative background
concentration, the 2005 and 2017 versions of the (iiiideline on Air Quality \ lodels (U.S. EPA,
2005, 2017; hereafter referred to as the 2<~>05 and 201 7 (iimk-hiic) provided recommendations to
appropriately account for the background air quality near a new or modifying source as part of a
cumulative impact analysis for both isolated single source and multi-source situations. This
guidance provides a framework for those undertaking a eumulati\ e impact assessment for
NAAQS implementation modeling demonstrations to use in characterizing appropriately
representati\ e background concentrations for these situations with an emphasis on identifying
what nearby sources to explicitly model

Section ^ 2 3 of the 2d I 7 (iuidehne describes that a cumulative impact analysis may be
required if the single-source impact analysis shows that the impact of the new or modifying
source may equal or exceed the Significant Impact Level (SIL) for any criteria pollutant or if the
permit authority deems it is necessary to meet the PSD compliance demonstration requirement.
As such, a cumulative impact analysis needs to appropriately characterize the spatial nature of air
quality near a new or modifying PSD source to identify the potential for NAAQS or PSD
increment violations and inform the PSD compliance decisions. Characterization of local air

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quality around a new or modifying source for each pollutant and averaging period necessitates a
full and comprehensive account for all source contributions. A cumulative impact analysis
should account for the combined impacts of all direct and precursor emissions of a pollutant
from:

•	the new or modifying source,

•	direct emissions from nearby sources, and

•	monitored background concentrations accounting lor primary and/or secondary impacts
from regional background sources and nearby sources not explicitly modeled1.

Appropriately accounting for all source contributions is an inherently discretionary exercise with
use of best professional judgment in determining a i'cprcscnlali\ e background concentration and
identifying nearby sources that need to be explicitly modeled

Section 8 of the 2<> I 7 (iimleline pro\ ides recommendations on how to identify and
characterize nearby sources in modeling as part of a cumulative impact analysis for NAAQS
compliance demonstrations and PSI) permitting Section 8.3 defines what nearby sources should
be included and thus explicitly modeled in a cumulative impact analysis, while section 8.2.2 and
Table S-2 pro\ ide information on how nearby sources should be modeled. One primary focus of
this guidance is on the process for identifying nearby sources in multi-source areas to determine
an appropriately representati\ e background concentration and the potential for modeled NAAQS
or PSD increment violations in assessing whether a new or modifying source may cause or
contribute to such violations. Recommendations made in both the 2005 and 2017 versions of the
Guideline highlight the importance of the use of professional judgment in this process.

1 For a more detailed explanation of sources that should be accounted for in a cumulative impact analysis, please see
section II.5.1 of the Guidance for Ozone and Fine Particulate Matter Permit Modeling (U.S. EPA, 2022)

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Section 8.2.3 of the 2005 Guideline recommended that in multi-source areas "all sources
expected to cause a significant concentration gradient in the vicinity of the source or sources
under consideration for emission limit(s) should be explicitly modeled. The number of such
sources is expected to be small except in unusual situations" (U.S. EPA, 2005). The 2005
Guideline went on to recommend the exercise of professional judgment to identify nearby
sources because no attempt was made to comprehensive!y define the term significant
concentration gradient.

The 2017 revisions to the Background Concentration section (section 8.3) of the
Guideline built upon the recommendations made in the 2005 Guideline In providing additional
considerations emphasizing the use of significant concentration gradients to determine which
nearby sources to explicitly model and the use of monitored background to adequately represent
other sources. Section 8 3 3 a of the 201 7 (iim/c/iiic states that "|i |n multi-source areas,
determining the appropriate background concentration in\ ol\ es (I) Identification and
characterization of contributions from nearby sources through explicit modeling, and (2)
characterization of contributions from other sources through adequately representative ambient
monitoring data " In practice, the interconnectedness of these two components tends to be
overlooked and determining the nearby sources to explicitly model using a significant
concentration gradient analy si s has proven to be problematic given the lack of clear definition of
that term by EPA and concrete examples of applying it in PSD compliance demonstrations.

Thus, rather than continued reliance on the concept of significant concentration gradient,
this guidance provides a framework that starts with a determination of the representativeness of
the ambient monitoring data and then uses readily available data to inform the determination of
those nearby sources to explicitly model to best characterize local air quality and to address the

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potential NAAQS or PSD increment violations as part of a cumulative impact analysis. The
framework was developed based on the underlying recommendations in the 2005 and 2017
versions of the Guideline and provides additional clarification to assist the permitting authority's
and permit applicant's appropriate application of the inherent discretion under the Guideline. The
framework outlines several qualitative and quantitative considerations for both isolated-single
source and multi-source scenarios that are consistent with the recommendations made in section
8.3 of the 2023 proposed revisions of the Guideline on Air Quality A loilels (U.S. EPA, 2023;
hereafter referred to as the 2023 proposed Guideline-). The intended effect of applying this
framework is to assist permit applicants in identifying and documenting the determination of
nearby sources to be explicitly modeled as part of a cumulati\ e impact analysis and thereby
improve their ability to adequately represent the local air quality near the project source under
consideration. The analyses performed while applying this framework should be documented in
the modeling protocol and permit record to justify the applicable NAAQS and PSD
determinations This document presents recommended procedures to those conducting a
cumulative impact analysis to follow in de\ eloping an accurate representation of local air quality
for sources under consideration for PSD and SIP compliance demonstrations (inert pollutants)
and S02 designations This document does not apply to those conducting SIP attainment
demonstrations for ozone, I'NLs, and regional haze3 since the emissions from nearby and other
sources are included as inputs in the photochemical grid modeling and are fully accounted for in
the predicted concentrations (2017 Guideline, section 8.3.1(c)).

2	All references to the 2023 proposed Guideline will be changed to reference the 2024 Guideline after the proposed
rule has been finalized.

3	For more information on SIP attainment demonstrations for ozone, PM2 5, and regional haze please refer to the

Modeling Guidance for Demonstrating Air Quality Goals for Ozone, PM2.5, and Regional Haze (EPA 454/R-18-
009).

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This document is not a rule or regulation, and the guidance it contains may not apply to a
particular situation depending upon the individual facts and circumstances germane to the unique
objectives of the modeling demonstration. This guidance does not change or substitute for any
law, regulation, or any other legally binding requirement, may refer to regulatory provisions
without repeating them in their entirety, and is not legally enforceable. The use of non-
mandatory language such as "guidance", "recommend", "may". "should", and "can", is intended
to describe EPA policies and recommendations. Mandatory terminology such as "must" and
"required" are used when describing requirements under the terms of the CAA and EPA
regulations. This document does not establish or alter any legally binding requirements in and of
itself.

This guidance does not create any l ights or obligations enforceable by any party or
impose binding, enforceable requirements Since each regulatory action {e.g., PSD permit, SIP
revision, etc.) will be considered on a case-by-case basis, this document does not limit or restrict
any justifiable approach that regulatory applications and authorities may take to conduct the
required compliance demonstrations l-ach indi\idual decision must be supported by a record
sufficient to demonstrate that the action will not cause or contribute to a violation of the
applicable YV\QS and PSI) increment While this document illustrates a framework approach
that EPA considers appropriate and acceptable as a general matter, all relevant information
regarding air quality in the area of the regulatory action should be examined to determine
whether alternative or additional analysis may be necessary in a given case to demonstrate that
the appropriate regulatory criteria are satisfied. This document does not represent a conclusion or
judgment by EPA that the technical approaches recommended in this document will be sufficient
to make a successful compliance demonstration in every circumstance.

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Regulatory authorities retain the discretion to address particular issues discussed in this
document in a different manner than EPA recommends so long as the approach is adequately
justified, supported by the permitting record and relevant technical literature, and consistent with
the applicable requirements in the CAA and implementing regulations, including the terms of an
approved State Implementation Plan (SIP) or Tribal Implementation Plan (TIP). Furthermore,
this guidance is not a final agency action and does not determine applicable legal requirements or
the approvability of any particular regulatory application
2. Guidance Overview

This guidance is appropriate for proposed new, modifying, or existing sources
performing a cumulative impact analysis as part of a jN A AOS implementation modeling
demonstration (e.g., PSD compliance demonstrations. SIP demonstrations for inert pollutants,
and SO2designations) Tt pro\ ides an N\\ recommended framework with a logical progression
of steps to identify a icprcsenlalh e background concentration for the cumulative impact analysis
in situations with an isolated single source (see section 3) and multi-source areas (see section 4).
Since each modeling demonstration is considered 011 a case-by-case basis, this guidance does not
limit or restrict any justifiable approach that the modeler and reviewing authority may take to
conduct the required demonstrations Those conducting NAAQS implementation modeling
should recognize the importance of the consultation process with the appropriate reviewing
authority. This process will help the applicant best work within the EPA's recommended
framework and apply the most appropriate qualitative and quantitative considerations to
characterize an adequately representative background concentration for cumulative impact
analyses.

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2.1 Determining a Representative Background Concentration

Section 8.3 of the 2017 Guideline states that, "Background concentrations are essential in
constructing the design concentration, or total air quality concentration, as part of a cumulative
impact analysis for NAAQS and PSD increment (section 9.2.3). Background air quality should
not include the ambient impacts of the project source under consideration." Instead, it should
include nearby sources, which may or may not be adequately represented by the ambient
monitoring data. Background air quality should also include oilier sources such as natural
sources, other unidentified sources (e.g., decommissioned, new or modi lying minor and major
sources), and local transportation sources. To appropriately characterize background
concentrations for cumulative impact assessments, as defined in the 2023 proposed Guideline,
EPA is recommending a framework composed of the following steps

1.	Define scope of cumulative impact analysis lor isolated or multi-source situations

2.	Identify rele\ ant and a\ ailable emissions. air quality and cn\ironmental data

3.	Determine representati\ eness of ambient monitoring data

4.	Determine nearby sources to be explicitly modeled

This framework will facilitate applying best professional judgment to identify appropriately
representati\ e monitoring data and select nearby sources to explicitly model to inform a
cumulati\ e impact analysis that best represents the local air quality throughout the geographic
scope of the analysis in particular near the project source(s) under consideration.

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Figure 1. EPA Recommended Framework for Characterizing Representative Background
Concentrations for Cumulative Impact Assessments

Proposed new, modifying, or existing
source performing a cumulative
impact analysis

Multi -source Scenarios

Isolated Single Source Scenarios

1. Define the scope of the cumulative impact analysis.

4

2. Identify emissions, air quality, and environmental
data.

3. Determine representativeness of ambient monitoring data.

Perform visual comparison of locations of ambient monitors and emitting source(s) to the

local terrain and meteorology.

Use a representative regional
site or other representative
monitor outside the
	m,Q.d,el>ng-d,Qmain --

See recommendations in
Section 3.3 for cases where
the monitor design value may
not be appropriate.

Background concentration

may be adequate for
compliance demo modeling.

If clearly
represented, the
nearby source does

not need to be
explicitly modeled.

X

4. Determination of nearby sources to explicitly model.

Focus on the
nearby sources not
represented by

selected
monitor(s) from
step 3.

Leverage the
visual and
qualitative
assessment from
step 3.

Perform additional
quantitative
assessment to
understand spatial
overlap of nearby
and project source
impacts.

Fully document
justification for
decisions.

* for multi -source scenarios

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2.2 Framework for Identifying a Representative Background Concentration

This section discusses each step of the framework as applied to isolated and multi-source
scenarios and as applicable to each pollutant and averaging period being evaluated. As indicated
in Figure 1, the first three steps of the framework are applicable to project sources located in an
isolated location. If the project source is in a multi-source area, those first three steps are then
followed by the fourth step to determine the nearby sources to explicitly model. The details and
data considerations underlying each step of the framework relies hea\ ily upon the expert
judgment to work through each step and conduct a cumulative impact analysis that best
characterizes local air quality and, for PSD permitting, inform determination of u hether or not
the project source will cause or contribute to a Y\.\OS or PSI) increment violation. During the
application of the framework, the scope of the cumulati\ e assessment may change from an
isolated source situation to a multi-source situation or \ ice \ ersa if new permitting data is
discovered or made a\ ailahle If this occurs, each step of the framework should be reconsidered
given the new scope of the cumulati\e impact assessment.

I nder the I.IW recommended framework, the characterization of background
concentrations as part of the cumulati\ e impact analysis for each pollutant should be developed
according to the following steps

1) Define scope of the cumulati\ e impact analysis for isolated or multi-source situations.

This step involves defining and documenting the following factors4:

a) Project source location relative to other sources/facilities (i.e., to define as an isolated or
multi-source area)

4 For more information on important aspects of PSD compliance demonstrations for NAAQS and PSD increment,
please refer to EPA's Air Quality Analysis Checklist (U.S. EPA, 2016).

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i) The location of the project source should be mapped alongside other known sources
or facilities in the area to determine whether the project source is an isolated source or
located in a multi-source area. Emissions inventory lists made available by the state
may be referenced to create an initial account of emitting sources within the modeling
domain.

b)	Applicable NAAQS pollutants and averaging periods

i) The averaging period for the NAAQS pollutant should he considered when estimating
the spatial extent of the emitted plume liom the project or nearby sources. The
dispersion of an emitted plume will differ for short term vs. annual standards and will
therefore influence whether a monitor may be representative of impacts from those
emitting sources.

c)	Scope of geographic area (i e . modeling domain)

i)	In situations uhere a single-source impact analysis is a\ ailable, the 2017 Guideline
defines the modeling domain as "the most distant location where air quality modeling
predicts a significant ambient impact will occur" but this area is not to exceed 50 km
from the proposed new or modi lying source.

ii)	In situations w here a single-source impact analysis is not available and the reviewing
authority requests a cumulative impact analysis, the 2017 Guideline defines the
modeling domain to include "the nominal 50 km distance considered applicable for
Gaussian dispersion models[.]"

d)	Dispersion environment (e.g., meteorology, terrain, land/water surface characteristics,

urban or rural dispersion assumptions, etc.)

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2) Identify relevant and available emissions, air quality, and environmental data.

This step involves identifying and gathering the relevant and available emissions, monitoring,

and modeling data including but not limited to the following5:

a)	Ambient monitoring data located within the modeling domain of the project source
and/or surrounding areas (e.g., ambient monitoring data lYora state and local agency's
ambient air monitoring networks, pre- or post-construction monitoring from the project or
any nearby sources, or an EPA ambient air monitoring network)

b)	Permit action or previous dispersion modeling for the project source (e.g., the single
source impact analysis)

c)	Pre-existing dispersion modeling lor potential nearby sources (e.g., from previous
demonstrations or for similar type sources)

d)	Any other rele\ ant emissions and air quality data

i)	Annual emissions data lor potential nearby sources

ii)	Acti\ e or pending PSI) or minor source construction permits or applications for
potential nearby sources

iii)	\cti\e or pending minor modification permit applications

i\ ) Title V. minor source operating permits and other state-only issued permits for
potential nearby sources

e)	Environmental data for the modeling domain and/or surrounding area that might
influence dispersion and transport of source plumes:

i)	Meteorology (wind direction and speed)

ii)	Terrain (flat, complex, particular terrain features)

5 More information on where to retrieve relevant emissions, air quality, and environmental data can be found in
Appendix A of this document.

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iii) Land/water surface characteristics
These data will serve as the basis to inform the next two steps in determining representativeness
of the ambient monitoring data and determining what nearby sources, if any, to explicitly
model.6

3) Determine representativeness of ambient monitori ng data

The key to determining the representativeness of available ambient air quality data is to consider
the "extent to which ambient air impacts of emissions from [the project and] nearby sources are
reflected in the available ambient measurements, and the degree to u liich emissions from those
background sources during the monitoring period are representative of allowable emission levels
under the existing permits" (U.S. EPA. 2<)|<)) This step in\ol\es determining what "source mix"
the ambient monitor data represent, i e . source contributions to pollutant concentrations, and
how the monitor(s) may or may not represent the source mix near the project source. A spatial
map should be created of the a\ ailable monitor data and the location of the project source to
visually and qualilali\ ely compare the mix of emitting sources and the dispersion environment
(i.e., terrain and wind rose data) The lb I lowing factors should be considered when determining
which ambient monitor data are representative of the air quality around the project source:
a) The averaging time of the applicable NAAQS with regards to determining whether a
monitor captures emissions from the project source or nearby sources during the
applicable averaging time.

6 There are a number of tools that are commonly used to visualize the location of the applicable data elements
described in this section. Google Earth can be used to evaluate land use throughout the modeling domain, identify
terrain features, as well as map out the locations of sources, weather stations and monitors. ESRI ArcGIS may be
used to plot terrain data from the USGS National Map and the NLCD land cover data from the MRLC.

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b)	The measurement scale (e.g., neighborhood, urban, regional scale, etc.) and monitoring
objective (e.g., source oriented, population exposure, background, highest concentration,
etc.) of each individual monitor7

c)	The mixture of emitting source(s) and their magnitude of emi ssions and release height
(i.e., elevated stacks or ground level releases)

d)	Dispersion environment (e.g., meteorology, terrain, land water surface characteristics,
urban or rural dispersion assumptions, etc )

The approach for making this determination will differ depending 011 whether the project
source is an isolated source or localed in a nuilli-souive area I lowever, it relies on the same
underlying data and principles of performing a spatial com pari son of the project source and
monitoring site location

For isolated single sources, the cnmula1i\ e impact analysis will rely largely, if not solely, on
the available monitoring data to fully characterize the background concentrations near the project
source I or these situations, a \ isual and qualitati\ e assessment of the dispersion environment
(e.g., 1he terrain and wind patterns) at the location of the ambient monitors should be performed
to determine whether the ambient air at the location of the monitor is representative of the
ambient air in the project area The selected representative monitor should have terrain features
and wind patterns similar to the project area, and represent pollutant transport into the modeling
domain, i.e., background contributions from other sources. The representative monitor may not
be the closest in proximity to the project source or even be located within the modeling domain.

7 EPA provides an up-to-date monitor list of all monitors with data available in the AQS system. This list details the
"measurement scale" and "monitoring objective" for each AQS monitor when available. This information should be
used to inform the selection of a representative monitor. Monitors may be classified as micro-scale (0 m to 100 m),
middle scale (100 m to 500 m), neighborhood scale (500 m to 4 km), urban scale (4 km to 50 km), and regional
scale (50 km to hundreds of km). The link to this list can be found at:
https://aqs.epa.gov/aqsweb/airdata/download_files.html

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In situations where the monitored design value is not representative of the background
concentration and/or the design value is overly biased due to impacts from the project and
existing sources, one can consider modifying the design value data or using modeled estimates to
best characterize background air quality levels in consultation with the appropriate reviewing
authority. Further refinements to modeled estimates paired with design concentrations may be
made based on model options controlling for downwind and upwind sectors.

For multi-source areas, the cumulative impact analysis should rely upon selected monitoring
data as supplemented by explicit modeling of ncarln sources, as appropriate, to fully
characterize the background concentrations near the project source. For these situations, a visual
and qualitative assessment of the aniMenl monitor locations should be performed to understand
what they represent in terms of source mix Similar to the isolated source situation, the
dispersion environment at the locations of the monitor site(s) and the project source should be
compared along with the emitting source locations and magnitude of emissions to understand the
extenl to which the aniMenl monitor may account for the impacts of these emitting sources. In
addition to the area surrounding the project source, one should also focus on any areas where the
single source impact analysis of the project source, if available8, indicates modeled exceedances
of the SIL because nearby source contributions will be important in these areas to appropriately
represent local air quality i 11 such areas and the potential for NAAQS or PSD increment
violations.

8 Throughout this draft guidance, EPA will recommend using results from a single source impact analysis "if
available". In PSD permitting cases, there may be scenarios where the permit authority requests that the permit
applicant skip performing a single source impact analysis first and move straight to performing a cumulative impact
assessment. A cumulative impact assessment may also be performed for environmental justice purposes where a
single source impact analysis may not be available for the applicable sources.

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4) Determine nearby sources to be explicitly modeled.

This step is applicable to multi-source areas and involves determination of nearby sources to
explicitly model in conjunction with the selected monitoring data to appropriately characterize
the background concentration for the cumulative impact analysis. As noted in the Guideline, this
step is interconnected to the selection of representative monitoring data since the sources deemed
to be represented by the monitoring data in step 3 will help determine which sources should be
explicitly modeled since they are not accounted for in the monitored background concentration.
When determining what nearby sources to explicitly model, one should consider the following
factors:

a)	The averaging time of the applicable NAAQS. i e . spatial extent of the source impacts
per plume travel time

b)	The measurement scale fe g., neighborhood, urban, regional scale, etc.) and monitoring
objective (e.g.. source oriented, population exposure, background, highest concentration,
etc.) of the selected monitor(s)

c)	The mixture of emitting souive(s) and their magnitude of emissions and release height
(i e.. ele\ ated stacks or ground lex el releases) at the selected monitoring site, near the
project source, and areas that the project source modeling shows impacts above the SIL

d)	Permit action or pre\ ious dispersion modeling for the project source (e.g., single source
impact analysis)

e)	Pre-existing dispersion modeling for potential nearby sources (e.g., from previous permit
actions or for similar type sources)

f)	Dispersion environment (e.g., meteorology, terrain, land/water surface characteristics,
etc.) at the selected monitoring site and project source

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Basically, to determine which nearby sources are not adequately accounted for by the
selected monitoring data, one needs to consider the nature of sources near the project source as
well as the areas within modeling domain where the project source has impacts equal to or above
the SIL, if known. If a nearby source is not adequately accounted for by the selected monitoring
data, then one should consider explicitly modeling those nearby sources to fully characterize air
quality impacts and best account for potential NAAQS or PSI) increment violations.
3. Application of Framework in Isolated Single Source Scenarios

Section 8.3.2 of the 2023 proposed Guideline makes recommendations for isolated single
source situations and provides the context, specificity, and flexibility sufficient to determine total
air quality concentrations for modeling domains where only contributions from the project
source and representative ambient monitoring data arc necessary and deemed sufficient. Nearby
or neighboring emission sources should not he considered under these isolated-source scenarios.
The relative isolation ofia particular project source should he hased on professional judgment,
and the pollutant species and a\ erauinu period being assessed. The flow-chart presented in
Figure 1 therefore emphasizes the lust three steps of the EPA recommended framework to
determine reprcsenlati\ e ambient monitoring data as relevant for isolated source scenarios.
3.1 Defining (lie Scope of I lie Cumulative Impact Analysis

The first step is to de\ clop an overall understanding of the project source and surrounding
area that should be accounted for in the cumulative impact assessment. The location of the
isolated project source should be mapped within the modeling domain alongside the relevant
factors provided in section 2.2 that are gathered in step 2 with an emphasis on the monitoring
data within the modeling domain. As stated earlier, in terms of geographic scope of the
cumulative impact analysis, in situations where a single-source impact analysis is available, the

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2017 Guideline defines the modeling domain as "the most distant location where air quality
modeling predicts a significant ambient impact will occur" but this area is not to exceed 50 km
from the proposed new or modifying source. When a single-source impact analysis for the
project source is not available and the reviewing authority requests a cumulative impact analysis,
the 2017 Guideline defines the modeling domain to include "the nominal 50 km distance
considered applicable for Gaussian dispersion models[ ]"

3.2	Identifying Relevant and Available Emissions. Air Quality and Environmental Data

For areas with an isolated source(s), section N.3.2(a) of the 2<)23 proposed Guideline
states that"... determining the appropriate background concentration should focus on
characterization of contributions from all other sources through adequately representative
ambient monitoring data." So, the emphasis lor isolated source situations is on the ambient
monitoring data along with en\ ironniental data for the modeling domain and surrounding areas
that will inform the next step of determining representing e hiickground concentrations based on
the appropriate ambient monitoring data

3.3	Determining Representativeness of Ambient Monitoring Data

Section 8.3.2(h) of the 2< >23 proposed Guideline provides EPA's recommendations for
selecting representative amhient monitoring data to characterize the total air quality near an
isolated single source l-IW recommends selecting "the most recent quality assured air quality
monitoring data collected in the \ icinity of the source to determine the background concentration
for the averaging times of concern". The ambient monitoring data may come from a number of
sources such as a state and local ambient air monitoring network, an EPA ambient monitoring
network, or any pre- or post-construction monitoring data that may be available. The selected
ambient monitoring data should be current (i.e., measured in the previous three years) and meet

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EPA's recommended methods for data collection and processing9 in addition to the quality
assurance, and quality control requirements10. EPA recognizes that the identification and
determination of representativeness of ambient monitoring data may be an iterative process when
all air quality data relevant to the modeling domain is assessed.

The cumulative impact assessment for isolated sources largely relies on the
"characterization of contributions from all oilier sources through adequately representative
ambient monitoring data," as stated in the 202} proposed Guideline. To identify whether there is
ambient monitoring data in the vicinity of the source. N\\ recommends \isualJy and
qualitatively assessing the modeling domain and its a\ ailaMe characteristics (e.g., monitor
locations and scales, terrain features, wind rose data, etc ) In cases where there are one or more
monitors within the \ icinily of the project area, one should exercise the use of professional
judgment to determine whether the selected monitor is representative of the background
concentration in the project area N\\ generally recommends using data from the closest upwind
monitor lo the project. howe\ er. one needs to assess the representativeness of the monitor
location and not solely choose bused 011 proximity. Permit applicants should gather data on the
location (i e . urban \ s rural). wind patterns, and terrain features at both the monitor and the
project source to inform the selection of representative background concentration data. Any
meteorological data used to identify an upwind monitor should be representative11 of the area
near the monitor and the nearby source affecting the monitor. Monitoring sites may have co-

9	For PSD compliance demonstrations, the collection and processing of the ambient air data should follow the
recommendations of the Ambient Monitoring Guidelines for Prevention of Significant Deterioration (EPA-450/4-87-
007).

10	The quality assurance and quality control methods for the selected ambient monitor should be consistent with the

EPA's Quality Assurance Handbook for Air Pollution Measurement Systems, Volume II - Ambient Air Quality
Monitoring Program (EPA-454/B-13-003).

11	Additional information regarding determining representativeness of meteorological data can be found in EPA's
Meteorological Monitoring Guidance for Regulatory Modeling Applications (EPA-454/R-99-005).

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located wind field measurements; however, these measurements may not have undergone proper
QA/QC to be suitable for this type of analysis.

The following questions should be considered when determining what the ambient
monitor represents and how that may differ from the background air quality in the project area:

•	Is the monitor located in an urban or rural setting similar to the project area?

•	Are the wind and terrain patterns at the monitor consistent with the project area?

•	Is the monitor representative of pollutant transport IV0111 other sources located outside of
the modeling domain?

•	Has ambient data from this monitor been used in previous cumulati\ e impact analysis for
the project area or surrounding areas0

In addition to these questions, one should keep in mind that the proximity of a monitor to the
project source is not inherently linked to how repiesentati \ e that monitor may be of the
background concentration in the project area Therefore, it is critical to understand what the
ambient monitor may he representing and how the dispersion environment around the monitor is
similar to or differs from that of the project area I-'or isolated source locations, it is important to
note the extent to w liich the monitor location in closest proximity to the project area differs from
the projecl area, i e . w hether the monitor location is influenced by nearby source emissions
outside of the project area, w hether the monitor is in an urban area when the project is in a rural
area or vice versa, or w here the monitor is located in a different type of terrain from the project
area, such as complex terrain or flat terrain. In such cases where the closest monitor(s) are not
representative of the background concentration in the project area, it may be appropriate to
identify monitors outside of the modeling domain. Any ambient monitor may be selected if there
is reasonable evidence as to why the selected monitor is most representative of the background

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concentration in the project area. If there are no monitors within the vicinity of the source, the
2023 proposed Guideline recommends that a regional site12 monitor may be used to determine
background concentrations. Alternatively, as listed in section 2(a) any pre-construction
monitoring data that may be available for the project source may be considered as the ambient
background monitor if the data is still representative of the project area. Finally, section 8.3.2(f)
of the 2023 proposed Guideline recommends that "it may he appropriate to use results from a
regional-scale photochemical grid model, or other icprcsentath e model application" in
consultation with the appropriate reviewing authority.

When determining an appropriate background concentration to be used in conjunction with
the dispersion modeling for the cunuilati\ e impact analysis, it is important to consider how the
monitor-based background contribution will he combined iill the modeled impact from the
project and other sources to represent the design concentration, or total air quality concentration.
Section 8.2.3(c) of the 2<)23 proposed Guideline outlines several options that are available for the
reviewing authority to consider I-PA recommends starting with the current design value from
the selected monitor for the applicable NAAQS as a uniform monitored background contribution
across the project area TTo\\e\ er. ui\ en the case-by-case nature of this practice, the uniform
background contribution may not he appropriate in all cases, and it may be necessary to modify
the ambient data record in consultation with the appropriate reviewing authority. These cases
may include but are not limited to the following scenarios:

• Under PSD permitting, if the project source is a modification where the existing facility's
emissions affect the ambient monitor(s), monitored values may be excluded from the
design value calculation when the existing source is affecting the monitor. To identify

12 The 2023 proposed Guideline defines a regional site as "one that is located away from the area of interest but is
impacted by similar or adequately representative sources."

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values to exclude, one should first determine the area of impact for the existing source by
comparing emissions information to the monitoring sites within a 90-degree sector
downwind of the source in question. The existing source's emissions should then be
paired with hourly wind rose data to identify specific hours the existing source is
affecting the monitor.

•	Data may also be modified or excluded from the aniMenl data record when the monitor is
impacted by atypical activities13 (i.e., impacts thai will not occur again in the future).
Examples of this may include but are nol limited to construction, roadway repairs, forest
fires, or unusual agricultural activities. In these cases, one should determine whether it is
appropriate to scale the monitored concentrations In a factor, adjust the data by adding or
subtracting a constant value from the monitored concentrations, or omit the specific hours
or days of the atypical acti\ itv all together The newly modified concentrations should be
compared against a historical record of aniMenl data from the monitor to determine

w hether "such adjustments would make the monitored background concentrations more
temporally and or spatially representative of the area around the [project source] for the
purposes of the regulatory assessment"' (U.S. EPA, 2023).

•	For demonstrations regarding slum-term standards, the diurnal or seasonal patterns
captured in the air quality monitoring data may differ significantly from the diurnal or
seasonal patterns used to estimate modeled concentrations. When this occurs, one should

13 For more information on modifying ambient data please refer to EPA's guidance on Additional Methods,
Determinations, and Analyses to Modify Air Quality Data Beyond Exceptional Events (EPA-457/B-19-002).

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pair the air quality monitoring data in a temporal manner that reflects these patterns and
follows the recommendations provided for the specific standard14.

• When multiple monitors are present in the project area and monitored air quality

concentrations appear to vary across the modeling domain, it may be appropriate to use
data from multiple monitors within the project area The manner in which data from
multiple monitors may be analyzed and considered in the background concentration is a
case-by-case determination based on factors unique to the project area.

These options provide flexibility to relieve challenges that may arise when combining the
monitor-based background contribution with the modeled impacts from the project source and
allows for the consideration of spatial and temporal \ariability throughout the modeling domain.
However, given thai these \ ariahililies can occur 011 an hourly basis and the possible limitations
of hourly observations from the ambient monitoring network, "the EPA does not recommend
hourly or daily pairing of monitored background and modeled concentrations except in rare cases
of relati\ el\ isolated sources w here the available monitor can be shown to be representative of
the ambient concentration levels in the areas of maximum impact from the proposed new source"
(U.S. EPA, 202.1) I lour-by-hour pairing is not recommended because this approach assumes that
the hourly monitored background concentration is spatially uniform for the hour and that the
monitored values are representative of background levels at each receptor. In the 2023 proposed
Guideline, EPA recommends the use of seasonal or quarterly pairing of monitored and modeled

14 The guidance on Additional Clarification Regarding Application of Appendix W Modeling Guidance for the 1-
hour NO2 National Ambient Standard recommends "that an appropriate methodology for incorporating background
concentrations in the cumulative impact assessment for the 1-hour NO2 standard would be to use multiyear averages
of the 98th percentile of the available background concentrations by season and hour-of-day, excluding periods when
the source in question is expected to impact the monitored concentration (which is only relevant for modified
sources)." The 99th-percentile should be used for the 1-hour SO2 standard.

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concentrations as that should sufficiently capture situations where the modeled emissions are not
temporally correlated with background monitored levels.

4. Application of Framework in Multi-source Areas

Section 8.3.3 of the 2023 proposed Guideline makes recommendations for multi-source
areas and provides the context, specificity, and flexibility sufficient to determine total air quality
concentrations for modeling domains that are adequately predicted by contributions from the
project source, representative ambient monitoring data. and the explicit modeling of a few
nearby sources. The determination of which nearby sources, if any, thai will be explicitly
modeled to fully characterize background air quality in a multi-source situation should be based
on professional judgment consistent with F.P.V's framework, and the pollutant species and
averaging period being assessed. As highlighted in Section X 3 3 of the 2023 proposed Guideline,
"[a] key point here is the inleivonnecledness of each component in that the question of which
nearby sources to include in the cumulati\ e modeling is iiiextricahl\ linked to the question of
what the ambient monitoring data represents within the project area." The flow-chart presented
in Figure I adds this additional fourth step of" Determination of Nearby Sources to Explicitly
Model" rele\ ant to multi-source areas in applying the EPA recommended framework.
4.1 Defining (lie Scope of (lie Cumulative Impact Analysis

The goal of step I is to de\ elop an overall understanding of the project source and
surrounding area that should be accounted for in the cumulative impact assessment. The location
of the project source should be mapped within the modeling domain alongside the relevant
factors provided in section 2.2 that are gathered in step 2 with an emphasis on emission sources
within the modeling domain in proximity to the project source and monitoring locations. As
stated earlier, in terms of geographic scope of the cumulative impact analysis, in situations where

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a single-source impact analysis is available, the 2023 proposed Guideline defines the modeling
domain as "the most distant location where air quality modeling predicts a significant ambient
impact will occur" but this area is not to exceed 50 km from the proposed new or modifying
source. When a single-source impact analysis for the project source is not available and the
reviewing authority requests a cumulative impact analysis, the 2023 proposed Guideline defines
the modeling domain to include "the nominal 50 km distance considered applicable for Gaussian
dispersion models[.]"

4.2 Identifying Relevant and Available Emissions, Air Quality and Environmental Data

For areas with multiple source(s), section S 3 3(a) of the 2023 proposed Cmideline states
that"[...] determining the appropriate background concentration involves: (1) Identification and
characterization of contributions from nearby sources through explicit modeling, and (2)
characterization of contributions from other sources through adequately representative ambient
monitoring data." So. the emphasis for multi-source situations is on the emissions data and
existing modeling for emitting sources and ambient monitoring data along with environmental
data for the modeling domain and surrounding areas that will inform the next two steps of
determining representati\ e background concentrations and what nearby sources to explicitly
model.

In multi-source situations, the added focus is in gathering the relevant data related to
characterizing potential nearby sources in the areas near the monitor locations, project source,
and areas for which the project source has modeled impacts above the SIL, if known. These data
should include the location, release height, emissions rates, and any other available emissions
data or observed meteorological data. The emissions data used for further analysis should be
representative of "normal" operating conditions at the nearby source. A survey of multiple years

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of emissions data may be necessary to identify any years of data that may not be representative
of "normal" operating condition for the source. For PSD modeling demonstrations, the emissions
data generally is available from the applicable operating permits. In addition, a PSD permit
applicant should be aware of any of the following that may be present in the project area:

•	Active or pending PSD or minor source construction permits or applications

•	Active or pending minor modification permit applications

•	Title V, minor source operating permits, and tiny oilier slate-only issued permits for
potential nearby sources

Documentation on these permit applications can usually be obtained ill rough the applicable
state environmental agency's permitting website. Appendix A provides a more comprehensive
list of the emissions, air quality, and en\ iionmcnlal data lo consider when determining an
appropriate background concentration.

4.3 Determining Representativeness orAinhienl Monitor Data

As highlighted in the 2<)2.i proposed (imilclmc. lor a project source located in a multi-
source area, there is an inleivonnectediiess between this step and the next step in that "the
question of w liicli nearby sources lo include in the cumulative modeling is inextricably linked to
the question of w hat the ambient monitoring data represents within the project area." Thus, the
review of the source emissions and monitoring data in this step is an iterative process with two
main questions to consider (I) what does the ambient monitor represent, and (2) which nearby
sources are or are not represented by the ambient monitoring data? Working through the visual
and qualitative assessment of these data with these questions in mind should help one account for
the inherent interconnectedness in fully representing background concentrations for use in the
cumulative impact analysis. For each ambient monitor in consideration here, determining which

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nearby sources are or are not represented by that monitor will necessitate working through the
qualitative considerations of the data gathered in step 2 and, as appropriate, quantitative analysis
of the emissions, monitoring and pre-existing modeling data.

In multi-source situations, the visual and qualitative assessment should include maps of
the monitor locations, environmental data such as terrain features and wind patterns, and the
locations and magnitude of emitting sources within the first 11) to 2<"> km of the project source
(2017 Guideline, section 8.3.3(b)(iii)) and, if a\ ailahle, the area where the project source impacts
are greater than the SIL based on pre-existing modeling (i.e., the single source impact analysis)15.
It is recommended to start with consideration of the closest monitors since the closer the monitor
is to those sources, the more likely it is to he representati\ e of the source mix in those areas.
Focusing on monitors near the project source and the area with possible exceedances of the SIL
is an appropriate narrowing of the scope to rele\ ant nearby sources for consideration rather than
looking across the entire modeling domain The ambient concentration data at the selected
monitor(s) along with the source and emissions data can be mapped with the wind patterns and
terrain features to gain insights 011 the potential for these sources to be contributing to the
monitor and the degree to w liich these contributions may be represented by the monitor data.
Therefore, a \ isual assessment and qualitative comparisons of the data and their spatial patterns
and relationships can be quite informative in understanding what sources are or are not
represented by the monitoring data.

15 The modeling results from the project source's single source impact analysis can be spatially plotted with EPA's
AERPLOT tool to post-process any AERMOD dispersion modeling results that are available. The tool converts
AERMOD plot file (.PLT) output to a .KMZ format for convenient plotting of the receptor field of ground level
concentrations, contours, and concentration gradients. The executable for this tool can be found at:
https://www.epa.gOv/scram/air-quality-dispersion-modeling-related-model-support-programs#aerplot

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For certain pollutants and averaging times, the dispersion of the emitted plume will play
an influential role as to whether the source contributions may be accounted for by the monitoring
data. As stated in section 8.3.3(b)(i) of the 2017 Guideline, "[t]he pattern of concentration
gradients can vary significantly based on the averaging period being assessed. In general,
concentration gradients will be smaller and more spatially uniform for annual averages than for
short-term averages, especially for hourly averages. The spatial distribution of annual impacts
around a source will often have a single peak downwind of the source based on the prevailing
wind direction, except in cases where terrain or other geographic effects are important. By
contrast, the spatial distribution of peak shorl-lcrm impacts will typically show several localized
concentration peaks with more significant gradient." To qualitatively assess the potential
contributions of emission sources to the monitor location, the source emissions data may be
paired with wind rose data using the applicable a\ erauinu times (i e . short term vs. long term) to
understand the extent of plume dispersion and contributions to the monitor. As such, selecting a
representative monitor for annual a\ erauinu times may be similar to the monitor selection in
isolated source situations that relied the uniform background contributions from other sources
outside the modeling domain with some account for those smaller point and non-point sources
within the project area \lternati\ el\. selecting a representative monitor for short-term averaging
times should be based upon ambient monitoring data that reflects the higher variability expected
from emission sources near the project source, while avoiding or minimizing a conservative
account of such contributions if the number of such sources and their emissions are higher near
the monitor than the project source. Selection of a representative short-term monitor could be
expanded to more than one monitor based on consideration of realistic upwind sectors that would
improve representation of higher variabilities and reduce conservatism from double counting of

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modeled nearby sources. Note that emission inventories are generally made up of annual totals of
source emissions. Information on the operating hours for a source or hourly emission rates may
be more informative for shorter term standards (i.e., 1-hr CO, NO2, and SO2).

The dispersion environment is also important here because the impact from an emitted
plume is heavily influenced by local meteorology and the presence of terrain, bodies of water,
and land surface characteristics. Visual assessment of the situation using terrain maps and wind
roses will be extremely valuable to the qualitative assessment of u hat nearby source impacts are
expected to be reflected in the monitoring data Depending on the geographic location (i.e., urban
vs. rural) of the project source and the ambient monitor location, one should use professional
judgment to consider upwind sector i niluences from urhan or rural non-point sources and rule
out any lower emitting sources willi impacts that are likely reflected in the monitor data and
therefore adequately represented in those measured concentration data.

While selecting the monitor data for use in a multi-source situation, keep in mind that a
degree of conservatism may he used to select a monitor that is biased high with respect to the
project area in cases u here it is unclear or uncertain what source mix a monitor is representing.
A conser\ alive assumption may he selecting a monitor that is clearly impacted by a large
emitting source or multiple sources thai are not reflected in the source mix near the project
source, or selecting a monitor located in an urban area when the project source is in a more rural
location. In addition, the options lor modifying the ambient data record detailed in section 3.3
also apply to multi-source situations; however, additional data analysis may be necessary to
make these modifications given the added complexity of distinguishing source contributions in
multi-source areas.

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In summary, the visual and qualitative assessment of the available data described above
should result in the selection of a monitor (or monitors) and a detailed understanding of what
those monitoring data represent. The selected monitoring data should meet EPA's recommended
methods for data collection and processing9, and the quality assurance and quality control
requirements10. These monitoring data should generally represent contributions from other
sources within and outside of the modeling domain, and the identified emission sources near the
selected monitor. This full and documented under standing of what the selected monitor(s)
represents should then inform and facilitate the next step of identification of those nearby sources
that are not adequately represented by the monitored data and need to be explicitly modeled.

4.4 Determination of Nearby Sources lo Explicitly Model

The fourth and final step of the framework, as applied to multi-source situations, is to
determine which nearby sources to explicitly model This step hniIds 011 the visual and
qualitath e re\ ieu that is performed u hile selecting the monitor in step 3. As stated in the 2023
proposed (iiinlc/uic. "Nearby sources not adequately represented by the ambient monitor through
visual assessment should undergo further qualitali\ e and quantitative analysis before being
explicitly modeled "" Thus, the nearby sources identified in step 3 that are not accounted for in
the monitored data should be further analyzed to determine whether to explicitly model them as
part of the cumulati\ e impact analysis. The additional analysis in this step should build on the
visual and qualitath e assessment completed in step 3 with the result of this iterative process
being the identification of few, if any, nearby sources whose contributions are not adequately
represented by the selected ambient monitoring data. Note that there may be no nearby sources to
explicitly model if they are all adequately represented in the background monitoring data.

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The nearby sources under consideration will typically be within the first 10 to 20 km from
the project source and the area where the project source's impacts equal or exceed the SIL.
Those emission sources located in proximity to areas where the project source's single source
impact analysis indicates modeled exceedances of the SIL are important to consider in order to
appropriately represent local air quality for the cumulative impact analysis. This is especially
true in PSD compliance demonstrations because identifying potential NAAQS and PSD
increment violations is essential to determine if a new source may cause or contribute to such
violations. An initial approach to determine whether to explicitly model those sources identified
in step 3 as not being represented in the selecled monitoring data that arc in close proximity to
the project source and the area where the project source impacts exceed the Sll. Such an
approach would be the most straightforward determination consistent with the outcome of step 3
and not necessitate additional qualitali\ e or quantilali\ e analysis to inform the determination
here.

However, if there is uncertainty as to w hether the sources identified in step 3 should be
modeled, this section |iro\ ides information on how to further evaluate the spatial extent of these
nearby source impacts to in form determining the need for explicit modeling of these sources to
fully and credibly estimate background concentrations. The following questions will assist in
assessing the representation and resulting dispersion of emissions from the nearby sources. In
cases where existing modeling of the nearby source(s) may not be available, these questions
should still be considered to understand the spatial nature of the emitted plumes from each
source.

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•	How far are the nearby sources from the project source?

o The 2017 Guideline states that "[i]n most cases, the few nearby sources will be
located within the first 10 to 20 km from the source(s) under consideration."

•	What terrain features are present around the nearby sources and project source?

o Terrain maps can show what features may influence overlapping project and
nearby source impacts. For example, large terrain features that may obstruct the
emissions from a nearby source from impacting the project source's significant
impact area.

•	What are the wind patterns influencing plume dispersion from the nearby sources?

o A wind rose may be useful for this question to assess the frequency that the
prevailing wind blo^s from the nearby source toward the project source.

•	If the nearby sources have stacks, u hat are the stack parameters (height, temperature, exit
velocity, and diameter) '

- A short stack (eg. less than I no fi) may have localized impacts at the ambient
air boundary (e g . lenceline). while a tall stack (e.g., greater than -100 ft) will
likely ha\e impacts farther away.

•	Would clow nwash play a role in the dispersion of a pollutant from the nearby sources
such that they may cause elevated concentrations in the vicinity of the project source?

Leveraging the visual and qualitative assessment completed in step 3, these questions should be
used to further evaluate the relevant monitoring, emissions, and modeled data and help inform
the determination in this step.

In cases where pre-existing modeling of a nearby source is available, post-processing and
additional analysis of emissions data and existing modeling results can provide an understanding

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of the spatial extent of each source's impacts and how they overlap with the project source's
impacts. These modeling results may be available from previous permit actions through the state
or local agency's inventory. If available, these results should be spatially plotted to visualize how
those source impacts overlap with the project source's impacts and the selected monitor(s) from
step 3. If modeling results are not available, existing dispersion modeling of similar types of
sources (e.g., an elevated source in a rural, flat terrain area or a ground release in an urban area
with a similar wind pattern) could provide insights 011 the potential dispersion of an emitted
plume from a nearby source. The spatial plols generated from the project source and nearby
source's dispersion modeling can be used to identify any areas where their concentration impacts
overlap. If a monitor has been selected, one should combine the design value from the selected
monitor, concentration impacts from the project source, and the estimated concentration impacts
from the nearby souive(s) to calculate a preliminary design concentration to see if the resulting
air quality level may threaten or exceed the YV\OS or PSI) increment. If impacts from the
nearby source(s) contribute to estimated air quality levels that may threaten or exceed the
NAAOS or PSI) increment, then these nearby sources should be strongly considered for explicit
modeling as part of the cumulati\ e impact assessment. When using pre-existing modeling, one
should use their best professional judgment to determine whether the nearby source and
dispersion en\ ironment are properly represented in the modeling that was previously performed.
In general, consideration of quantitative approaches to inform the determination of which nearby
sources to explicit model should be determined in consultation with the appropriate reviewing
authority and fully described in the modeling protocol and technical documentation of the
cumulative impact analysis.

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The visual, qualitative, and quantitative assessments completed as part of this step in
determining those nearby sources to explicitly model should be fully documented to provide the
basis for justification in the decisions. Such documentation will be particularly important for
nearby sources that are not explicitly modeled, so EPA recommends including the rationale for
that decision as well as for those nearby sources that arc explicitly modeled.

In regard to the use of the explicit modeling of nearby sources in the cumulative impact
analysis, unlike the recommendation to not hourly pair the monitoring data for this purpose, we
do recommend hourly pairing on the explicit modeling of nearby sources with the project source
modeling results because the use of the same meteorological inputs within the preferred air
quality model provide a credible and appropriate basis to do so
5. Additional Considerations

Additional considerations in determining background concentrations may include
accounting for at-risk communities in ensuring the adequacy of local air quality characterization
in these communities, especially in the case of multi-source areas where there is the potential for
modeled \ iolations of the YV\OS or PSI) increment as part of the cumulative impact
assessment The following tools may he used in defining those communities of focus here:
• EPA's En\ ironmental Justice Screening and Mapping Tool16: EJScreen can be used to
characterize the nature of the demographics for population living near the new or
modifying source and use the demographic index (or other indicators) to define
communities of concern that would be the focus of air quality impacts.

16 For more information on EPA's Environmental Screening and Mapping Tool please refer to: EJScreen:
Environmental Justice Screening and Mapping Tool 1 US EPA

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•	The Climate and Economic Justice Screening Tool17: CEJEST is a geospatial mapping
tool that identifies areas across the nation where communities are faced with significant
burdens. It can be used to identify communities in the project area that may be burdened
by climate change, energy, health, housing, legacy pollution, transportation, water and
wastewater, and workforce development.

•	Any other tool that can be utilized to enhance understandings of nearby source control
strategies and EJ intersections relevant lo the project at hand, and whether to expand
inclusion of certain nearby sources in mulli-source areas. This can include tools
developed by state and local air agencies.

These tools may be used to determine the o\ erlap of such communities with the project source
impacts, selected representative monitor location and or determination of nearby sources to
include in the cumulati\ e impact assessment and confirm the adequacy of the characterization of
background concentrations to represent local air quality in these communities.

6. Siiiiiiiisii'y

This guidance pro\ ides the EIWs recommended framework that offers clear and logical
steps to he used with inherent professional judgment and discretion to develop a representative
account for background concentration in the modeling domain of the source(s) under
consideration. The framework should be applied in both isolated single source and multi-source
area situations. Specifically in multi-source areas, the framework will assist in the identification
of nearby sources that should be explicitly modeled as part of a cumulative impact assessment.
The aim of this framework is to foster consistency across permit demonstrations with sufficient
documentation to justify NAAQS and PSD determinations as part of the modeling protocol and

17 For more information on the Climate and Economic Justice Screening Tool please refer to: Climate and Economic
Justice Screening Tool 1 U.S. Climate Resilience Toolkit

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permit record. Consistent with the EPA framework, permit applicants can consider qualitative
and quantitative approaches that may not be explicitly noted in this guidance document to better
inform their determination and EPA recommends such pursuit is done in consultation with the
appropriate permit authority.

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7. References

U.S. EPA, 2005. Guideline on Air Quality Models. 40 CFR part 51 Appendix W (70 FR 68218,
Nov. 9, 2005). https://www.epa.eov/sites/defaiilt/files/2020-09/dociiments/appw 05.pdf.

U.S. EPA, 2010. Applicability of Appendix W Modeling Guidance for the 1-hour SO2 National
Ambient Air Quality Standard, https://www.epa.gov/sites/default/files/2020-
10/documents/clarificationmemo appendixw hourly-so2-naaqs final 08-23-2010.pdf

U.S. EPA, 2016. Air Quality Analysis Checklist, https://www.epa.gov/sites/default/files/2020-

09/documents/air quality analysis checklis '	EO.pdf.

U.S. EPA, 2017. Guideline on Air Quality Models. 4<) CI R pai l 5 I Appendix W (82 FR 5182,
Jan. 17, 2017). https://www.epa.gov/sites/pr	320-

09/docum ents/app\ if.

U.S. EPA, 2022. Guidance for Ozone and Fine Paniculate Matter Permit Modeling. July 29,

2022. Publication No. EPA 454/R-22-<)i)^ Office of Air Quality Planning and Standards,
Research Triangle Park, NC. https:/A	..gov/system/file	;nts/2022~

08/2022%20Guidance%20030/"on°"d%:	'*^?0Mode >df

U.S. EPA, 2023. Proposed Revisions to the Guideline 011 \ii Quality Models. 40 CFR part 51
Appendix W (October 2023)	y	"!A°3-appendix-w-proposed-

rule.

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Appendix A: Detailed Table of Available Air Quality, Emissions, and Environmental Data
Air Quality Data
Ambient monitoring data

Ambient monitoring data can come from a number of different sources such as the applicable state and local agency's ambient air
monitoring networks, pre- or post-construction monitoring, or an EPA ambient air monitoring network. Any data that is selected for
use as the design concentration should meet the QA/QC requirements detailed in the Ambient Monitoring Guidelines for Prevention
of Significant Deterioration (EPA-45 0/4-87-007).

Ambient monitoring data from state and local agencies may be made available through their websites or through contact with the
appropriate reviewing authority. Additionally, the reviewing authority may have knowledge on any existing pre- or post-
construction monitoring that is available for the project or nearby source.

EPA has various platforms to access ambient air monitoring data depending on the data needed based on the NAAQS pollutant
standard. Please visit the following website for access and information to outdoor air monitoring data:

Information and access to air quality design value data for NAAQS pollutants can be found at:

EPA's AirData Air Quality Monitors app - Interactive Map of Air Quality Monitors (active and inactive) (measurement scales:
micro-scale (0 m to 100 m), middle scale (100 m to 500 m), neighborhood scale (500 m to 4 km), urban scale (4 km to 50 km), and
regional scale (50 km to hundreds of km)):

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Does not represent final Agency action. Draft guidance for review and comment.

Emissions Data

Emissions information and modeling files for existing PSD sources

The applicable state or local environmental agency may provide lists of all sources or air permits (e.g., Title V, minor source, and
other state-only issued permits) in their jurisdiction or even have some sort of PSD inventory tool containing permit and modeling
information. EPA recommends searching the state or local environmental agency's website first to investigate what information and
tools may be available. One may also contact the appropriate reviewing authority (and potentially adjacent authority) to obtain
additional data on nearby sources such as relevant modeling files and emissions and stack parameter data if they are tracked by the
state or local agency. Emission inventories and modeled emission rates may also be constructed from nearby source air quality
operating permits, recent permit applications, and appropriate emission limits. PSD permit applications for proposed or new sources
should also be reviewed for any emissions data relevant to the cumulative modeling demonstration and nearby sources inventory.

Power plant NOx and SO2 emissions data can be found at EPA's Clean Air Markets Program Data page:

Source operating hours and short-term emissions rates may be available through facility-level Continuous Emissions Monitoring
Systems (CEMS) and EPA's Clean Air Market Division Field Audit Checklist Tool: : -	^

Source emissions and stack information may be found in EPA's Emissions Inventory System (E1S):

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Does not represent final Agency action. Draft guidance for review and comment.

Environmental Data
Terrain data

The primary site for accessing the most up-to-date elevation data is the USGS National Map. This data should be used to assess the
presence of terrain features in the modeling domain that may affect the dispersion and potential overlap of emitted plumes from the
project or nearby sources.

USGS National Map: https://www.usgs.gov/programs/national-eeospatial-program/national-map
USGS National Map - Data Download Map:	= -

Information on how the national elevation data can be converted for use in the AERMOD modeling system can be found at:

Land use data

Land cover data can be retrieved from the National Land Cover Database (NLCD). The primary site where you can get the most up-
to-date information is the Multi-Resolution Land Characteristics (MRLC) Consortium website. NLCD data can be plotted or viewed
using the MRLC's viewer to review the land cover characteristics for the modeling domain. Review of this data will provide
knowledge on the location (urban vs. rural) of the project source and how the land use may impact surface characteristics and the
dispersion of emitted plumes.

Multi-Resolution Land Characteristics (MRLC) Consortium: !

Multi-Resolution Land Characteristics (MRLC) Consortium NI.CD Viewer:

For more information on the use of land cover data in the AERMOD Modeling System:

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Does not represent final Agency action. Draft guidance for review and comment.

Local meteorological data

For the purposes of determining an appropriate background concentration, there are a number of meteorological datasets and
resources that may be used (see section 8.4 of the Guideline). In some cases, there may be observed on-site or site-specific
meteorological observations for the project source or nearby sources that can be accessed through the appropriate reviewing
authority. The National Oceanic and Atmospheric Administration (NOAA) also have databases of hourly surface observations that
are generally collected at airports by the National Weather Service and/or the Federal Aviation Administration (Integrated Surface
Dataset). There are also datasets with 1-minute and 5-minute wind data from ASOS sites across the country. Finally, prognostic
meteorology data generated by the Weather Research and Forecasting (WRF) model and processed for input to AERMET by the
Mesoscale Model Interface Program (M.M..IF), may be used in cases where the monitored meteorological data is not representative
of the project source area. Local meteorological data, more specifically wind speed and direction, may be used to estimate plume
dispersion and determine monitor representativeness. Wind speed and direction data may be used to generate a wind rose using one
of the many data visualization tools on the market including a tool from Iowa State University that quickly generates wind rose
plots.

NOAA/NCE1 Integrated Surface Dataset (1SD):

NOAA/NCEI 1 -Minute ASOS Wind Data: https://www.iicei.noaa.gov/data/automated-surface-observing-SYStem-one-minute-
NOAA/NCEI 5-Minute ASOS Wind Data: https://www.ncei.noaa.gov/data/automated-surface-observing-svstem-five-
lowa State University Wind Rose Tool: https://mesonet.agron.iastate.edu/sites/locate.php?network=GA_ASOS
For more information on the use of meteorological data in the AERMOD Modeling System:

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Does not represent final Agency action. Draft guidance for review and comment.

Additional Useful Data

Information on demographic characteristics of population and/or existence of disadvantaged communities

EPA's Environmental Justice Screening and Mapping Tool (EJScreen) and the Climate and Economic Justice Screening Tool
(CEJEST) are two tools that can be used to collect information on the demographic characteristics and presence of disadvantaged
communities in the project area. EJScreen is an environmental justice mapping and screening tool that provides a nationally
consistent dataset and approach for combining environmental and demographic socioeconomic indicators. CEJEST has an
interactive mapping tool that can be used to identify communities experiencing burdens in eight categories: climate change, energy,
health, housing, legacy pollution, transportation, water and wastewater, and workforce development.

EJScreen: https://www.epa.gov/eiscreen

CEJEST: https://screemngtool.geoplatform.gOv/en/#3/33.47/-97.5

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Does not represent final Agency action. Draft guidance for review and comment.

United States	Office of Air Quality Planning and Standards	Publication No. EPA-454/P-23-001

Environmental Protection	Air Quality Assessment Division	October 2023

Agency	Research Triangle Park, NC


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