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AERMOD Implementation Guide
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EPA-454/B-24-009
November 2024
AERMOD Implementation Guide
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Quality Assessment Division
Research Triangle Park, NC
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Preface
This document provides information on the recommended use of AERMOD to address
specific issues and concerns related to the implementation of AERMOD for regulatory
applications. The following recommendations augment the use of experience and judgment in
the proper application of dispersion models. Advanced coordination with reviewing authorities,
including the development of modeling protocols, is recommended for regulatory applications of
AERMOD.
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Table of Contents
Section Page
1.0 What's new in this document? 1
2.0 Document background and purpose 2
2.1 Background (10/2007) 2
2.2 Purpose (10/2007) 2
3.0 Meteorological data and processing 4
3.1 Determining surface characteristics (01/2008) 4
3.1.1 Meteorological data representativeness considerations (01/09/2008) 4
3.1.2 Methods for determining surface characteristics (04/2021) 5
3.1.3 Use of AERSURFACE for determining surface characteristics (11/2024,
\ 24142) 9
3.2 Selecting upper air sounding levels (11/2024, v24142) 11
3.3 Processing site-specific meteorological data for urban applications (04/2021) 12
3.4 Use of prognostic meteorological model data as inputs to AERMOD (04/2018) 13
3.5 Use of COARE algorithms in AERMET for overwater applications (11/2024, v24142)
13
4.0 Terrain data and processing 15
4.1 Modeling sources with terrain-following plumes in sloping terrain (01/2008) 15
4.2 AERMAP domain (09/2005) 16
4.3 Terrain elevation data sources for AERMAP (04/2021) 16
4.4 Manually entering terrain elevations in AERMAP (03/2009) 20
4.5 Use of AERMAP to determine source elevations (03/2009) 20
5.0 Urban applications 22
5.1 Urban/rural determination (04/2022) 22
5.2 Selecting population data for AERMOD's urban mode (4/2022, v22112) 23
5.3 Optional urban roughness length - URBANOPT keyword (5/2024, 24142) 24
5.4 Meteorological data selections for urban applications (01/09/2008) 25
5.4.1 Urban applications using NWS meteorological data (01/2008) 25
5.4.2 Urban applications using site-specific meteorological data (01/2008) 25
6.0 Source characterization 27
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6.1 Capped and horizontal stacks (12/2016, vl6216) 27
6.2 Use of area source algorithm in AERMOD (11/2024, v24142) 27
6.3 RLINE source type (5/2024, v24142) 28
7.0 REFERENCES 29
Appendix A. EPA Model Clearinghouse memorandum dated July 9, 1993 32
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1.0 What's new in this document?
Revisions Related to AERMOD Version 24142, May 21, 2023:
• Section 3.1.3 - Use of AERSURFACE for determining surface characteristics
Updated to reflect data products available with the 2024 edition of the National Land
Cover Database (NLCD). Also discusses new keywords to indicate low roughness sector
(LOWZO), high roughness sector (HIGHZO), and vary roughness sectors (VARYZO) to
replace airport sector (AP), non-airport sector (NONAP), and vary sectors (VARYAP),
respectively.
• Section 3.5 - Use of COARE algorithms in AERMET for overwater applications
Added for the use of the COARE algorithm as a new regulatory option under certain
circumstances without the need for alternative model approval as was needed to use the
AERCOARE program.
• Section 4.3 - Terrain elevation data sources for AERMAP
Updated language to reflect current elevation data types and references.
• Section 5.3 - Optional urban roughness length
Updated language for consistency with Appendix W to 40 CFR Part 51 (Guideline)
• Section 6.2 - Use of area source algorithm in AERMOD
Updated to include information on plume meander added to the AREA source type as an
alpha option in AERMOD version 24142.
• Section 6.3 - RLINE source type
Added to include information about the use of the newly promulgated RLINE source type
as a regulatory update to AERMOD for modeling mobile sources.
Note: For version 24142 and subsequent versions, refer to the document AERMOD System
Buss, Errata, and Related Guidance, available on the EPA Support Center for Regirfatory
Atmospheric Modeling (SCRAM) website, for supplemental guidance on program
bugs issues that that are reported between version releases.
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2.0 Document background and purpose
2.1 Background (10/2007)
In April 2005, the AERMOD Implementation Workgroup (AIWG) was formed in
anticipation of AERMOD's promulgation as a replacement for the Industrial Source Complex
(ISCST3) model. AERMOD fully replaced ISCST3 as the regulatory model on December 9,
2006 (EPA, 2005a), after a one-year grandfather period. The primary purpose for forming the
AIWG was to develop a comprehensive approach to address implementation issues for which
guidance is needed. The result of this initial AIWG was the publication of the first version of the
AERMOD Implementation Guide on September 27, 2005.
In 2007, a new AIWG was formed as a standing workgroup to provide support to EPA's
Office of Air Quality Planning and Standards (OAQPS). This document represents the
combined efforts of AIWG and OAQPS in relation to the implementation of the AERMOD
regulatory model.
2.2 Purpose (10/2007)
This document provides information on the recommended use of AERMOD to address a
range of issues and types of applications. Topics are organized based on implementation issues,
with additional information as appropriate on whether they impact the modules of the AERMOD
modeling system (AERMOD, AERMET, and AERMAP), or related programs (AERSURFACE,
AERSCREEN, AERMINUTE, and BPIPPRM). This document contains a section which
highlights changes from the previous version, located in Section 1.0 of the document for use as a
quick reference. Each section is also identified with month and year (mm/yyyy)it was added or
last updated. More recent updates and additions include the corresponding version number. Only
sections with substantive changes or new recommendations are identified with new revision
dates. Revision dates are not updated for sections with only minor edits to clarify the wording,
correct typographical errors, or update citations to reference the most recent version of a
document.
The recommendations contained within this document represent the current best use
practices as determined by EPA, through the implementation of AIWG. This document is
designed to provide consistent, technically sound recommendations to address specific issues and
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concerns relevant to the regulatory application of AERMOD. As always, advance coordination
with the reviewing authorities on the application of AERMOD is advisable. Modeling protocols
should be developed, and agreed upon by all parties, in advance of any modeling activity.
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3.0 Meteorological data and processing
3.1 Determining surface characteristics (01/2008)
When applying the AERMET meteorological processor (EPA, 2024d) to prepare the
meteorological data for the AERMOD model (EPA, 2024g), the user must determine appropriate
values for three surface characteristics: surface roughness length {z0}, albedo {/' J, and Bowen
ratio {Bo}. The surface roughness length is related to the height of obstacles to the wind flow
and is, in principle, the height at which the mean horizontal wind speed is zero based on a
logarithmic profile. The surface roughness length influences the surface shear stress and is an
important factor in determining the magnitude of mechanical turbulence and the stability of the
boundary layer. The albedo is the fraction of total incident solar radiation reflected by the
surface back to space without absorption. The daytime Bowen ratio, an indicator of surface
moisture, is the ratio of sensible heat flux to latent heat flux and is used for determining planetary
boundary layer parameters for convective conditions driven by the surface sensible heat flux.
This section provides recommendations regarding several issues associated with determining
appropriate surface characteristics for AERMOD modeling applications.
3.1.1 Meteorological data representativeness considerations (01/09/2008)
When using National Weather Service (NWS) data for AERMOD, data
representativeness can be thought of in terms of constructing realistic planetary boundary layer
(PBL) similarity profiles and adequately characterizing the dispersive capacity of the
atmosphere. As such, the determination of representativeness should include a comparison of
the surface characteristics (i.e., z,,, B0, and /') between the NWS measurement site and the source
location, coupled with a determination of the importance of those differences relative to
predicted concentrations. Site-specific meteorological data are assumed to be representative of
the application site; however, the determination of representativeness of site-specific data for
AERMOD applications should also include an assessment of surface characteristics of the
measurement and source locations and cannot be based solely on proximity. The
recommendations presented in this section for determining surface characteristics for AERMET
apply to both site-specific and non-site-specific (e.g., NWS) meteorological data.
The degree to which predicted pollutant concentrations are influenced by surface
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parameter differences, between the application site and the meteorological measurement site,
depends on the nature of the application (i.e., release height, plume buoyancy, terrain influences,
downwash considerations, design metric, etc.). For example, a difference in z0 for one
application may translate into an unacceptable difference in the design concentration. For a
different application the same difference in z0 may lead to an insignificant difference in design
concentration. If the reviewing agency is uncertain as to the representativeness of a
meteorological measurement site, a site-specific sensitivity analysis may be needed to quantify,
in terms of expected changes in the design concentration, the significance of the differences in
each of the surface characteristics.
If the proposed meteorological measurement site's surface characteristics are determined
to NOT be representative of the application site, it may be possible that another nearby
meteorological measurement site may be representative of both meteorological parameters and
surface characteristics. If that is not the case, it is likely that site-specific meteorological data
will be required.
3.1.2 Methods for determining surface characteristics (04/2021)
The availability of high-resolution digitized land cover databases provides an opportunity
to apply systematic procedures to determine surface characteristics based on an objective
analysis of the gridded land cover data across a domain. A proper analysis of such data must
take into consideration the relationship between surface characteristics and the meteorological
measurements on which the surface characteristics will be applied.
Based on model formulations and model sensitivities, the relationship between the
surface roughness upwind of the measurement site and the measured wind speeds is generally the
most important consideration. The effective surface roughness length should be based on an
upwind distance that captures the net influence of surface roughness elements on the measured
wind speeds needed to properly characterize the magnitude of mechanical turbulence in the
approach flow. Studies have examined the response of the atmosphere to abrupt changes in the
surface roughness and provide some insight into the relationship between measured winds and
surface roughness [e.g., Blom and Warenta (1969), Businger (1986), Hogstrom and Hogstrom
(1978), Horst and Weil (1994), Irwin (1978), Rao, et al. (1974), and Taylor (1969)]. Such
changes in surface roughness result in the development of an internal boundary layer (IBL)
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which grows with distance downwind of the roughness change, and defines the layer influenced
by the transition in surface roughness. The size and structure of the IBL is very complex, even
for idealized cases of uniform roughness upwind and downwind of the transition. The IBL is
also affected by the magnitude and direction of the roughness change and the stability of the
upstream flow. The IBL generally grows more slowly for stable conditions than for neutral or
unstable approach flow and will also tend to grow more slowly for rough-to-smooth transitions
than for smooth-to-rough transitions. The relationship between surface roughness and measured
wind speeds is even more complex in real world applications given the typically patchy nature of
the heterogeneity of surface roughness elements.
The recommended upwind distance for surface roughness should account for the fact that
surface roughness effects in AERMOD are more important for stable atmospheric conditions
than for neutral/unstable conditions, and that meteorological monitoring sites are typically
characterized by open (low roughness) exposures to accommodate recommended siting criteria
(EPA, 2000). For typical measurement programs, including NWS stations, the reference wind
measurements will be taken for an anemometer height of approximately 10 meters above ground.
An upwind distance based on the recommended siting criterion of at least 10 times the height of
nearby obstacles (EPA, 2000), which would correspond to about 100 meters for typical obstacles
such as trees and 2-3 story buildings, is considered inadequate for this purpose. However, the
previous recommendation to use an upwind distance of 3 kilometers for surface roughness is
considered too large because the boundary layer up to typical measurement heights of 10 meters
will generally respond to changes in roughness length over much shorter distances. Including
land cover information across an upwind distance that is too large could misrepresent the amount
of mechanical turbulence present in the approach flow and bias model results, especially for low-
level releases.
The recommended upwind distance for processing land cover data to determine the
effective surface roughness for input to AERMET is 1 kilometer relative to the location of the
meteorological tower. This recommended distance is considered a reasonable balance of the
complex factors cited in the discussion above. If land cover varies significantly by direction,
then surface roughness should be determined based on sector. However, the width of the sectors
should be no smaller than a 30-degree arc. Further information on the definition of sectors for
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surface roughness is provided in the User's Guide for the AERMOD Meteorological
Preprocessor (AERMET) (AERMET User's Guide) (EPA, 2024d). Exceptions to the
recommended default distance of 1 kilometer for surface roughness may be considered on a case-
by-case basis for applications involving site-specific wind speed measurements taken at heights
well above 10 meters, in situations with significant discontinuities in land cover just beyond the
recommended 1-kilometer upwind distance, or for sites with significant terrain discontinuities
(e.g., the top of a mesa or a narrow, steep valley). Another factor that may need to be considered
in some cases for determining an effective surface roughness length, is the potential contribution
of nearby terrain or other significant surface expression, not reflected in the land cover data, to
the generation of mechanical turbulence. Use of a non-default distance for surface roughness
estimation, or modification of surface roughness estimates to account for terrain/surf ace-
expression effects, should be documented and justified in a modeling protocol submitted to the
appropriate reviewing authority prior to conducting the modeling analysis.
The dependence of meteorological measurements and plume dispersion on Bowen ratio
and albedo is very different than the dependence on surface roughness. Effective values for
Bowen ratio and albedo are used to estimate the strength of convective turbulence during
unstable conditions by determining how much of the incoming radiation is converted to sensible
heat flux. These estimates of convective turbulence are not linked as directly with tower
measurements as the linkage between the measured wind speed and the estimation of mechanical
turbulence intensities driven by surface roughness elements. While local surface characteristics
immediately upwind of the measurement site are very important for surface roughness, effective
values of Bowen ratio and albedo determined over a larger domain are more appropriate.
The recommended approach for processing digitized land cover data to determine the
effective Bowen ratio and albedo for input to AERMET is to average the surface characteristics
across a representative domain without any direction or distance dependency. The recommended
default domain is a 10 x 10-kilometer region centered on the measurement site. Use of the
measurement location to define the domain is likely to be adequate for most applications.
However, a domain representative of the application site may be more appropriate for some
applications, particularly if most of the sources are elevated releases. The use of an alternative
domain for Bowen ratio and albedo should be documented and justified in a modeling protocol
submitted to the appropriate reviewing authority prior to conducting the modeling analysis.
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Beyond defining the appropriate domains to use for processing digitized land cover data,
additional considerations are needed regarding the computational methods for processing of the
data. Since the width of a sector increases with distance from the measurement site, the land
cover farther from the site would receive a higher effective weight than land cover closest to the
site if a direct area-weighted averaging approach were used to calculate an effective surface
roughness. An inverse-distance weighting is recommended for determining surface roughness
from digitized land cover data to adjust for this factor, since the length of an arc (across a sector)
is proportional to the distance from the center. In addition, a geometric mean is recommended
for calculating the effective surface roughness since the AERMOD formulations are dependent
on the ln(z0). Note that the arithmetic average of the ln(za) is mathematically equivalent to the
geometric mean of z0. Since the Bowen ratio represents the ratio between sensible heat flux and
latent heat flux, the use of a geometric mean is also recommended for calculating effective
values of Bowen ratio. Geometric means are more appropriate for calculating "average" values
of ratios; for example, the "average" for Bowen ratios of 0.5 and 2.0 should be 1.0, which is
accomplished with the use of a geometric mean. A simple arithmetic average is recommended
for calculating effective values of albedo.
These recommendations for determining surface characteristics supersede previous
recommendations and should be followed unless case-by-case justification can be provided for
an alternative method. The recommendations described above are briefly summarized below:
1. The determination of the surface roughness length should be based on an inverse-
distance weighted geometric mean for a default upwind distance of 1 kilometer relative to
the measurement site. Surface roughness length may be varied by sector to account for
variations in land cover near the measurement site; however, the sector widths should be
no smaller than 30 degrees.
2. The determination of the Bowen ratio should be based on a simple unweighted
geometric mean (i.e., no direction or distance dependency) for a representative domain,
with a default domain defined by a 10 x 10 km region centered on the measurement site.
3. The determination of the albedo should be based on a simple unweighted arithmetic
mean (i.e., no direction or distance dependency) for the same representative domain as
defined for Bowen ratio, with a default domain defined by a 10 x 10 km region centered
on the measurement site.
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An important aspect of determining surface characteristics from digitized land cover data
is the assignment of surface characteristic values for each of the parameters (surface roughness,
Bowen ratio and albedo) to the land cover categories contained in the dataset. Several references
are available to guide those assignments, including the User's Guide for AERSURFACE Tool
(AERSURFACE User's Guide) (EPA, 2024f), the AERMET User's Guide (EPA, 2024d),
Garrett (1992), Gifford (1968), Oke (1978), Randerson (1984), and Stull (1988). Due to the
somewhat subjective nature of this process, and the fact that specific land cover categories may
include a wide range of values for some surface characteristics, the methods and assumptions
used to assign surface characteristics based on land cover categories should be thoroughly
documented and justified.
3.1.3 Use of AERSURFACE for determining surface characteristics (11/2024. v24142)
EPA has developed a tool called AERSURFACE (EPA, 2024f) that can be used in
determining reproducible surface characteristic values, including albedo, Bowen ratio, and
surface roughness length, for input to AERMET. The current version of AERSURFACE,
version 24142, supports the use of land cover data from the Multi-Resolution Land
Characteristics (MRLC) Consortium National Land Cover Database (NLCD) including years
representative of 1985 through 2023. More information on the NLCD data products available
from the MRLC and downloading instructions can be found in the "NLCD Sources for
AERSURFACE" document available on SCRAM.1 The NLCD provides land cover data at a
spatial resolution of 30 meters. In 2024, new annual NLCD products were released for the
contiguous U.S. Coverage of the NLCD for Alaska, Hawaii, and Puerto Rico is limited to select
years of legacy NLCD. The NLCD for all years are based on 16 categories with an additional
four categories that are specific only to Alaska, for a total of 20 distinct categories. This is the
same classification scheme used by the legacy post-1992 NLCD. Further, the NLCD includes
separate data files of percent impervious for all years (i.e., 1985 to 2023) and percent canopy
data for years representative of 2011 through 2021 which can be input to AERSURFACE to
supplement the land cover data. EPA recommends supplementing land cover data with both
percent impervious and percent canopy data when both are available for the same NLCD year.
In cases where only one is available or neither are available, EPA recommends processing the
'httpsV/gaftp.epa.gov/Air/aamg/SCRAM/models/related/aersurface/NLCD Sources for AERSURFACE.pdf
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land cover data without supplementation of percent impervious or percent canopy data.
AERSURFACE incorporates look-up tables of representative surface characteristic
values by land cover category and seasonal category. Further details regarding application of the
AERSURFACE tool are provided in the AERSURFACE User's Guide (EPA, 2024f). The
AERSURFACE tool incorporates the recommended methods for determining surface
characteristics from digitized land cover data described in Section 3.1.2. While the
AERSURFACE tool is not currently considered to be part of the AERMOD regulatory modeling
system, the recommended methodology described in Section 3.1.2 should be followed unless
case-by-case justification can be provided for an alternative method. The methods described in
the AERSURFACE User's Guide for supplementing land cover data with percent impervious
and percent canopy where both data products are available, should also be followed.
Beginning with AERSURFACE version 20060, wind sectors used for determining
surface roughness length around the meteorological tower can be specified individually as an
airport (AP) or non-airport (NONAP) sector based on whether areas within a sector categorized
as developed (21-24) consists of large impervious areas represented by runways with grassy
areas in between or the impervious areas are primarily buildings or other structures. Impervious
areas in sectors specified as airport sectors are more heavily weighted toward lower roughness
length values than those that are specified as non-airport sectors.
With the release of AERSURFACE version 24142, new keywords were added to extend
this weighting of higher and lower roughness for developed categories to the area around site-
specific meteorological towers that are not located at airports. These new keywords include
LOWZO and HIGHZO, and can be used interchangeably with AP and NONAP, respectively, to
indicate whether a sector should be weighted toward a higher or lower roughness value based on
the land use within areas characterized as developed, regardless if the area is at or near an
airport. Similarly, the VARYZO keyword (analogous to the VARYAP keyword) has been added
to indicate that wind sectors will be assigned individually. Consult the AERSURFACE User's
Guide (EPA, 2024f) for additional information on defining wind sectors for determining surface
roughness length. Additionally, the way AERSURFACE reads the DATAFILE keyword has
been updated to accept all NLCD release years that are available to download from the MRLC.
However, users should note that AERSURFACE version 24142 cannot process the newly
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available pre-1993 NLCD years (i.e., 1985 to 1992) if the corresponding 4-digit year (e.g.,
"NLCD1985", "NLCD1992", etc.) is used due to differences in the land cover classification
system used in the latest edition of these NLCD years and those hard coded in AERSURFACE.
Therefore, users should use the 1993 DATAFILE keyword (i.e., "NLCD1993") to process
annual NLCD for years 1985 to 1992 until an updated version of AERSURFACE is released. If
processing an older edition of the 1992 NLCD, the 1992 DATAFILE keyword (i.e.,
"NLCD 1992") should be used to ensure this data is processed using the 1992 NLCD
classification scheme with 21 classes. Be sure to clearly document the representative NLCD year
and edition that is processed (i.e., newly released annual NLCD or legacy NLCD).
3.2 Upper air data (11/2024, v24142)
The AERMET meteorological processor requires full upper air soundings (radiosonde
data) representing the vertical potential temperature profile near sunrise, to calculate convective
mixing heights. For AERMOD applications within the U.S., the early morning sounding,
nominally collected at 12Z (or UTC/GMT), is typically used for this purpose. The formats that
AERMET can process are TD-6201, FSL, and IGRA (Integrated Global Radiosonde Archive)
Prior to the autumn of 2024, historical and current upper air data in the FSL format were
available for download, free of charge, from the online NOAA/ESRL Radiosonde Database
(https://ruc.noaa.gov/raobs/). However, beginning in the autumn of 2024, historical and current
upper air data in the FSL format are no longer available. For any applications that require a
download of upper air data after the autumn of 2024, IGRA data will be the only available data.
The IGRA data and specifications can be downloaded free of charge from the NCEI ftp server
(ftp://ftp.ncei.noaa.gov/pub/data/igra and https://www.ncei.noaa.gov/pub/data/igra/).
Beginning with AERMET version 24142, the user is now required to enter the upper air
station's elevation or AERMET will issue an error and abort processing. In previous versions of
AERMET, the user did not have to enter the elevation. However, recent years of IGRA data
have missing heights for the surface level of some soundings. The surface level height is needed
by AERMET to convert the sounding levels to height above ground. If the surface level height is
missing, AERMET will issue a warning and skip the sounding. If the skipped sounding is the
early morning sounding used to calculate the convective mixing heights for the day, that day will
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have missing convective mixing heights and associated parameters (w* and potential
temperature lapse rate) and concentrations will not be calculated for those hours.
3.3 To alleviate this issue, AERMET 24142 has been modified to substitute the most
recent non-missing surface level in the sounding file or station elevation entered via
the LOCATION keyword in the UPPERAIR pathway for missing surface levels.
Processing site-specific meteorological data for urban applications (04/2021)
The use of site-specific meteorological data obtained from an urban setting may require
some special processing if the measurement site is located within the influence of the urban heat
island and site-specific turbulence measurements are available (e.g., go and/or ow). As discussed
in Section 5.4, the urban algorithms in AERMOD are designed to enhance the turbulence levels
relative to the nearby rural setting during nighttime stable conditions to account for the urban
heat island effect. Since the site-specific turbulence measurements will reflect the enhanced
turbulence associated with the heat island, site-specific turbulence measurements should not be
used when applying AERMOD's urban option, in order to avoid double counting the effects of
enhanced turbulence due to the urban heat island. If site-specific measurements are available for
the site, the user can choose to not include them in AERMET or they can be processed in
AERMET and the new turbulence options, NOTURB or NOTURBST can be used to ignore the
turbulence measurements. The NOTURB option will reset non-missing turbulence to missing
when reading the profile file for all hours and the NOTURBST option will reset the non-missing
turbulence values to missing for stable hours only, when the enhanced turbulence due to the
urban heat island is applied in the model. See Section 3.5.9 of the User's Guide for the
AMS/EPA Regulatory Model (AERMOD) (AERMOD User's Guide) (EPA, 2024g) for more
information about the options.
As also discussed in Section 5.4 of this document, the AERMOD urban option
(URB ANOPT) should be selected for urban applications, regardless of whether the
meteorological measurement site is in an urban setting since the limited surface meteorological
measurements available from the meteorological measurement program (even with measured
turbulence) will not adequately account for the meteorological characteristics of the urban
boundary layer included in the AERMOD urban algorithms.
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3.4 Use of prognostic meteorological model data as inputs to AERMOD (04/2018)
In recent years, interest has grown in the use of prognostic meteorological data, such as
the Weather Research and Forecasting (WRF) model to create inputs for dispersion modeling
with AERMOD. This is especially true in locations where it can be difficult to find an
adequately representative NWS station or cost-prohibitive or not feasible to set up a site-specific
meteorological monitoring tower. As part of the recent update to Appendix W to 40 CFR Part 51
{Guideline) (EPA,2024c), the use of prognostic data is allowed for regulatory applications of
AERMOD where it is cost-prohibitive or not feasible to collect site-specific data and there is no
representative NWD or comparable station nearby. EPA developed the Mesoscale Model
Interface Program, or MMIF for processing prognostic meteorological data for AERMOD
(Ramboll Environ, 2022). For more information see Section 8.4.5 of the Guideline (EPA,
2024c) and the Guidance on the Use of the Mesoscale Model Interface Program (MMIF) for
AERMOD Applications (MMIF guidance document) (EPA, 2024b) that offers recommendations
on the use of prognostic data and MMIF.
3.5 Use of COARE algorithms in AERMET for overwater applications (11/2024, v24142)
In recent years, applications of AERMOD in a marine boundary layer have increased.
These applications have involved the use of the AERCOARE pre-processor as an alternative
model to process observed buoy data or overwater prognostic data to generate the meteorological
inputs for AERMOD. AERCOARE is a pre-processor that invokes the Coupled Ocean-
Atmosphere Response Experiment algorithms to calculate boundary layer parameters such as
surface friction velocity and Monin-Obukhov length for AERMOD, rather than using AERMET
to process the data. The algorithms from COARE are more representative of the marine
boundary layer rather than the algorithms in AERMET which are more appropriate for land-
based stations (i.e., NWS stations or meteorological towers) or land-based prognostic data. The
use of AERCOARE with AERMOD has been considered an alternative model approach under
the guise of the Guideline, because the Offshore Coastal Dispersion model (OCD) is the
preferred model for overwater applications per Addendum A of the Guideline.
As AERMOD use in overwater applications has increased, the COARE algorithms were
incorporated into AERMET/AERMOD version 23132 as a beta option as part of the 2023
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proposed update to the Guideline. With version 24142 of AERMET and AERMOD, the
COARE algorithms are now considered a regulatory non-default option and the use of
AERCOARE is no longer needed to process overwater meteorological data for AERMOD.
COARE was included in AERMET to eliminate the alternative model approval when using
AERMOD for overwater applications. This is because AERMET is the regulatory
meteorological pre-processor for AERMOD per Addendum A in the Guideline. Also, inclusion
of the COARE algorithms in AERMET ensure that the COARE algorithms will be routinely
updated with routine AERMET updates. Note, the alternative model approval that is not needed
for AERMOD applications overwater is contingent that shoreline fumigation and platform
downwash are adequately addressed and there is consultation with the appropriate reviewing
authority and Regional Office.
COARE is invoked in AERMET via the METPREP pathway in Stage 2 of AERMET using
the METHOD keyword along with COARE and RUN COARE options. Additionally, there are
recommended options for running COARE in AERMET, and these recommendations are listed
in Section 3.14 of the AERMET User's Guide for either observed buoy data or prognostic
overwater data. The user is urged to check the most recent AERMET User's Guide for current
recommendations.
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4.0 Terrain data and processing
4.1 Modeling sources with terrain-following plumes in sloping terrain (01/2008)
Under the regulatory default mode (DFAULT option on the MODELOPT keyword), for
all situations in which there is a difference in elevation between the source and receptor,
AERMOD simulates the total concentration as the weighted sum of two plume states (Cimorelli,
et al., 2004): 1) a horizontal plume state (where the plume's elevation is assumed to be
determined by release height and plume rise effects only, and thereby allowing for impingement
if terrain rises to the elevation of the plume); and 2) a terrain-responding plume state (where the
plume is assumed to be entirely terrain following).
For cases in which receptor elevations are lower than the base elevation of the source
{i.e., receptors that are down-slope of the source), AERMOD will predict concentrations that are
less than what would be estimated from an otherwise identical flat terrain situation. While this is
appropriate and realistic in most cases, for cases of down-sloping terrain where expert judgment
suggests that the plume is terrain-following {e.g., down-slope gravity/drainage flow), AERMOD
will tend to underestimate concentrations when terrain effects are taken into account. AERMOD
may also tend to underestimate concentrations relative to flat terrain results for cases involving
low-level, non-buoyant sources with up-sloping terrain since the horizontal plume component
will pass below the receptor elevation. Sears (2003) has examined these situations for low-level
area sources and has shown that as terrain slope increases the ratio of estimated concentrations
from AERMOD to ISC (which assumes flat terrain for area sources) decreases substantially.
To avoid underestimating concentrations in such situations, it may be reasonable in cases
of terrain-following plumes in sloping terrain to apply the non-DFAULT option to assume flat,
level terrain. This determination should be made on a case-by-case basis, relying on the
modeler's experience and knowledge of the surrounding terrain and other factors that affect the
air flow in the study area, characteristics of the plume (release height and buoyancy), and other
factors that may contribute to a terrain-following plume, especially under worst-case
meteorological conditions associated with the source. The decision to use the non-DFAULT
option for flat terrain, and details regarding how it will be applied within the overall modeling
analysis, should be documented and justified in a modeling protocol submitted to the appropriate
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reviewing authority prior to conducting the analysis.
4.2 AERMAP domain (09/2005)
Section 2.1.2 of the User's Guide for the AERMOD Terrain Preprocessor (AERMAP)
(AERMAP User's Guide) (EPA, 2024e) states that the AERMAP domain must include all terrain
features that exceed a 10% elevation slope from any given receptor. The 10% slope rule may
lead to excessively large domains in areas with considerable terrain features (e.g., fjords,
successive mountain ranges, etc.). In these situations, the reviewing authority may make a case-
by-case determination regarding the domain size needed for AERMAP to determine the critical
dividing streamline height for each receptor.
4.3 Terrain elevation data sources for AERMAP (04/2021)
AERMAP was revised (beginning with version 09040) to support processing of terrain
elevations from the National Elevation Dataset (NED) developed by the U.S. Geological Survey,
which has transitioned to the USGS 3D Elevation Program (3DEP) (Sugarbaker, et al., 2017).
More information about the USGS 3DEP can be found at https://www.usgs.gov/3d-elevation-
program. 3DEP data can be downloaded using the USGS National Map downloader at
https://apps.nationalmap.gov/downloader/. For the purposes of this guide, the terms NED and
3DEP will be used interchangeably.
AERMAP still supports terrain elevations in the older formats referenced as Digital
Elevation Model (DEM) files (e.g., 7.5-minute and 1-degree DEM files) and has also been
enhanced to process DEM files of mixed format in the same run. AERMAP currently does not
support processing of elevation data in both the DEM format and the GeoTIFF format for 3DEP
data in the same run.
The USGS DEM archives are now static and will not be updated in the future, while the
3DEP data are being actively supported and checked for quality. Therefore, 3DEP represents a
more up-to-date and improved resource for terrain elevations for use with AERMAP. Due to
problems that have been encountered with DEM data, AERMOD users are encouraged to use
3DEP data. Problems encountered with DEM data include incorrect geo-referencing information
for entire DEM files and elevations that reflect the tops of buildings and trees in some cases.
The use of 3DEP data should avoid these issues and provide additional advantages over the use
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of DEM data, including consistent horizontal resolution and reference datum (generally NAD83
or WGS84). Some applications of AERMAP using DEM data may involve inconsistent
reference datums for adjacent DEM files, which can result in receptors being located within gaps
between files due to the datum shift. Gaps may also occur within DEM files generated by
various software tools to convert from one format to another when a NAD conversion is
involved, e.g., converting 1-degree DEM data to the 7.5-minute DEM format to fill areas not
covered by available 7.5-minute data. The AERMAP User's Guide (EPA, 2024e) provides a
more detailed discussion of issues associated with gaps between DEM files or within DEM files
and describes how these cases are handled by AERMAP.
While 3DEP is considered an improvement in the quality and consistency of elevation
data for use with AERMAP, there have been some issues associated with the GeoTIFF format
supported by AERMAP of which users should be aware. One issue of importance to AERMAP
users is that the 3DEP GeoTIFF files currently available from the USGS may not include the
GeoKey specifying the units for the elevation data. The USGS documentation for NED data
(now 3DEP) (USGS, 2002) indicates that elevations are in units of meters and are provided in
floating point format. AERMAP will therefore assume units of meters if the elevation units
GeoKey is absent. However, non-standard (i.e., non-USGS) elevation data in GeoTIFF format
may not be in units of meters. AERMAP provides an option for users to specify elevation units
in these cases. However, users must exercise caution in using such data unless the correct units
can be confirmed. The AERMAP User's Guide (EPA, 2024e) provides a more detailed
discussion of these and other potential issues associated with the GeoTIFF format supported for
3DEP data.
A second issue is the elevation data downloaded from the USGS National Map download
site in GeoTIFF format cannot be read directly by AERMAP and most be converted to remove
the internal compression of the data. Instructions for removing the compression are provided at
https://gaftp.epa.gov/Air/aqmg/SCRAM/models/related/aermap/Access and Conversion of Ele
vation Data for AERMAP.pdf.
The 3DEP elevation data are currently available as GeoTIFF files for the conterminous
United States, Hawaii, Puerto Rico, and the Virgin Islands at a horizontal resolution of 1 arc-
second (approximately 30 meters), and at a resolution of 2 arc-seconds for Alaska. Higher
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resolution data at l/3rd arc-second (about 10 meters) are available for most areas outside of
Alaska, and even l/9th arc-second data (about 3 meters) are available for some areas but do not
appear to be available for download as GeoTIFF files. The appropriate horizontal resolution for
the input terrain data and receptor network should be determined in consultation with the
reviewing authority based on the specific needs of the project. Higher resolutions for both the
terrain data and receptor network may be necessary in areas with significant terrain relief than
for areas with relatively flat terrain. While acceptable, using the highest resolution elevation data
available for determining receptor elevations and hill height scales may not always be justified.
Since spatial coverage of terrain data for some resolutions may not be complete, it is also worth
noting that use of a single resolution across the domain has advantages, and AERMAP places
some restrictions on the order of DEM or 3DEP file inputs when mixed resolution data are used.
Regardless of the receptor and terrain data resolutions used in AERMAP, it is advisable
to check the accuracy of receptor elevations and hill height scales being input to AERMOD for
significant terrain features that are likely to be associated with peak concentrations based on
proximity and elevation in relation to the sources. Elevations for fence line or other nearby
receptors located within areas that have been altered due to facility construction may require
special consideration since these changes in local topography may not be reflected in the USGS
terrain files. Use of receptor elevations derived from plant survey data may be an acceptable
alternative in these cases. The option available in AERMAP for the user to provide elevations
may be utilized to determine hill height scales for these special cases, rather than the default
option of determining elevations and hill height scales based on the input terrain data. However,
care should be exercised to ensure that the hill height scales determined by AERMAP are also
representative of the modified topography. If alternative data sources and/or methods are used to
estimate receptor elevations, users must recognize that receptor elevations input to AERMOD
should represent the best estimate of the actual terrain elevation at the receptor location. Use of a
"conservative" estimate of the maximum elevation in the vicinity of the receptor location, such
as the maximum within a "grid cell" centered on the receptor, is not appropriate for use in
AERMOD based on the formulation of the terrain algorithms in the model and may not result in
a conservative estimate of concentrations.
Beginning with the version dated 09040, AERMAP can also process terrain elevations
derived from the Shuttle Radar Topography Mission (SRTM) data, provided they are stored as
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GeoTIFF files that are compatible with AERMAP. 3DEP data represent the ground ("bare
earth") elevation, which is a more appropriate input for determining receptor elevations and hill
height scales for use in AERMOD. AERMOD users should therefore avoid the use of SRTM
data to determine elevations for use in AERMOD. However, SRTM data are available for most
of the globe, and may be the only practical alternative for applications beyond the U. S. While
AERMAP can process both 3DEP and SRTM data in GeoTIFF format in the same run, the only
situation that might warrant such an approach would be applications along a border that extends
beyond the domain covered by the 3DEP data. The SRTM elevation data are typically based on
the WGS84 horizontal datum, rather than the NAD83 datum used for most 3DEP data. While
AERMAP treats the WGS84 and NAD83 datums as equivalent, AERMAP will issue a warning
message for any terrain file input as NED data that is not in the NAD83 datum to flag the
possibility that non-NED data (or non-standard NED data) are being used.
Given the number of options available for elevation data inputs to AERMAP, and the
range of issues associated with elevation data, users are encouraged to clearly document the
source of elevation data used for AERMOD applications in the modeling protocol, including the
resolution and horizontal reference datum for the data and any pre-processing that might have
been done, such as converting from one format to another. Since the 3DEP data are being
checked for quality and updated as needed, AERMAP users should also consider acquiring
updated terrain files on a periodic basis before use in regulatory modeling applications. If the
option to provide receptor elevations to AERMAP is utilized, rather than using the default option
of determining elevations based on the input terrain data, the sources and methods used to
determine the provided elevations should be clearly documented along with a justification for
use of that option.
As changes have occurred over time regarding availability of the elevation data and file
formats provided by the USGS, refer to the AERMAP User's Guide (EPA, 2024e) and the EPA
SCRAM website (https://www.epa.gov/scram) for current information on data coverage,
resolution, format, and access to elevation data. Additional information on NED/3DEP data
products and specifications can be found at the USGS National Map website at
https://www.usgs.gov/3d-elevation-program.
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4.4 Manually entering terrain elevations in AERMAP (03/2009)
AERMAP currently does not have the capability of accepting hand-entered terrain data in
an "xyz" format. AERMAP only accepts terrain data from digitized elevation files in the DEM
or 3DEP/GeoTIFF formats. Therefore, if no DEM or 3DEP /GeoTIFF data are available for a
particular application, terrain elevations may need to be determined through other means. One
option may be to manually enter gridded terrain elevations in a form that mimics the DEM data
format. Instructions for how to accomplish this can be found on the SCRAM web site
https://www.epa.gov/scram in a document titled "On inputting XYZ data into AERMAP."
As noted in Section 4.3, if alternative sources and/or methods are used to estimate
receptor elevations, users must recognize that receptor elevations input to AERMOD should
represent the best estimate of the actual terrain elevation at the receptor location, and these
alternative sources and methods should be documented in the modeling protocol. As also noted
in Section 4.3, SRTM elevation data in GeoTIFF format is available for most of the globe, which
may provide another alternative source of elevation data for use in AERMAP. However, SRTM
data represents the heights of obstacles, such as buildings and trees, rather than ground
elevations, and should be used with caution and only as a last resort.
4.5 Use of AERMAP to determine source elevations (03/2009)
AERMAP includes the capability of estimating terrain elevations for sources based on the
same data and procedures used to estimate receptor elevations. However, the requirements for
determining source elevations are somewhat different than the requirements for determining
receptor elevations since a greater emphasis is placed on the accuracy of elevations at specific
locations in the case of sources. While the accuracy of specific receptor elevations is also
important, the main focus for receptors should be on how well the terrain features are defined by
the receptor network as a whole, which is based on both the accuracy of the terrain data and the
horizontal resolution of the receptor network. As noted in Section 4.3, it is advisable to check
the accuracy of receptor elevations and hill height scales for significant terrain features that are
likely to be associated with peak concentrations. These accuracy checks should also account for
the relative elevation differences between the source and receptor since that will determine the
elevation of the plume in relation to the terrain.
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Given the issues and uncertainties associated with estimating the elevation at a specific
location, and the potential sensitivity of AERMOD model results to differences in the relative
elevations of sources and nearby receptors, users are discouraged from relying solely on
AERMAP-derived source elevations in regulatory applications of AERMOD, especially for
emission sources within the facility being permitted. These concerns are particularly important
with newer facilities since regrading, typical with new construction, may not be reflected in the
digitized terrain data. Source elevations taken from a reliable plant survey are generally
considered to be the preferred option. If AERMAP-derived source elevations are used for the
permitted facility, then some effort should be made to verify the accuracy of the elevations based
on other reliable information, such as up-to-date topographic maps, taking into account
adjustments for the horizontal datum if necessary. Use of AERMAP-derived elevations for other
background sources included in the modeled inventory is generally of less concern than their use
for the permitted facility, depending on the complexity of the terrain and the distances between
sources within the modeled inventory. To facilitate proper review, the modeling protocol should
clearly document the data and method(s) used to determine source elevations for input to
AERMOD.
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5.0 Urban applications
5.1 Urban/rural determination (04/2022)
The URBANOPT keyword on the CO pathway in AERMOD, coupled with the
URBANSRC keyword on the SO pathway, should be used to identify sources to be modeled
using the urban algorithms in AERMOD (EPA, 2024g). To account for the dispersive nature of
the "convective-like" boundary layer that forms during nighttime conditions due to the urban
heat island effect, AERMOD enhances the turbulence for urban nighttime conditions over that
which is expected in the adjacent rural, stable boundary layer. Additionally, it defines an urban
boundary layer height to account for limited mixing that may occur under these conditions. The
magnitude of the urban heat island effect is driven by the urban-rural temperature difference that
develops at night. AERMOD currently uses the population input on the URBANOPT keyword
as a surrogate to define the magnitude of this differential heating effect. Details regarding the
adjustments in AERMOD for the urban boundary layer are provided in Section 5.9 of the
AERMOD model formulation document (EPA 2024a) and Cimorelli et al. (2004).
Section 7.2.1.1.b of the Guideline (EPA, 2024c) provides the basis for determining the
urban/rural status of a source. For most applications the Land Use Procedure described in
Section 7.2.1.1(b)(i) is sufficient for determining the urban/rural status. However, there may be
sources located within an urban area, but located close enough to a body of water or to other
non-urban land use categories to result in a predominately rural land use classification within 3
kilometers of the source following that procedure. Users are, therefore, cautioned against
applying the Land Use Procedure on a source-by-source basis but should also consider the
potential for urban heat island influences across the full modeling domain. Furthermore, Section
7.2.1.1(e) of Appendix W recommends modeling all sources within an urban complex using the
urban option even if some sources may be defined as rural based on the procedures outlined in
Section 7.2.1.1. Such an approach is consistent with the fact that the urban heat island is not a
localized effect but is more regional in character.
Another aspect of the urban/rural determination that may require special consideration on
a case-by-case basis relates to tall stacks located within or adjacent to small and up to moderate
size urban areas. In such cases, the stack height, or effective plume height for very buoyant
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plumes, may extend above the urban boundary layer height. The urban boundary layer height,
Zmc, can be calculated from the population input on the URBANOPT keyword, I\ based on
Equation 110 of the AERMOD formulation document (EPA, 2024a):
**=2»,(PlPj" (1)
where ziu0 is the reference height of 400 meters corresponding to the reference population, P0, of
2,000,000.
Prior to version 15181 of AERMOD, application of the urban option for these types of
sources may have artificially limited the plume height resulting in anomalously high
concentrations. Use of the urban option may not have been appropriate for such sources, since
the actual plume was likely to be transported over the urban boundary layer and not be affected
by urban enhanced dispersion. However, the potential for such anomalous results has been
mitigated beginning with version 15181 of AERMOD, which has incorporated a formulation bug
fix that modifies the treatment of plume rise for urban sources. Beginning with version 15181,
AERMOD emulates the plume rise approach used for penetrated plumes during convective
conditions if the initial plume height estimate is greater than or equal to the urban mixing height.
An additional change was made in version 22112, in which the penetrated plume approach is
used when the initial plume height is greater than or equal to the urban mixing height and the
stack height is less than the urban mixing height. This follows more with the penetrated plume
approach for convective hours and avoids dividing by zero issues. With the introduction of this
formulation bug fix in version 15181 (and modification in 22112) of AERMOD, a more
thorough case-specific justification will be needed, in consultation with the appropriate
reviewing authority, to support excluding these elevated sources from application of the urban
option.
5.2 Selecting population data for AERMOD's urban mode (4/2022, v22112)
For relatively isolated urban areas, the user may use published census data corresponding
to the Metropolitan Statistical Area (MSA) for that location. For urban areas adjacent to or near
other urban areas, or part of urban corridors, the user should attempt to identify that part of the
urban area that will contribute to the urban heat island plume affecting the source(s). If this
approach results in the identification of clearly defined MSAs, then census data may be used as
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above to determine the appropriate population for input to AERMOD. Use of population based
on the Consolidated MSA (CMSA) for applications within urban corridors is not recommended,
since this may tend to overstate the urban heat island effect. Similarly, for application sites that
are in isolated areas of dense population but are not representative of the larger MSA, care
should be taken to determine the extent of the area the urban area that will contribute to the urban
heat island plume affecting the source(s).
For situations where MS As cannot be clearly identified, the user may determine the
extent of the area, including the source(s) of interest, where the population density exceeds 750
people per square kilometer. The combined population within this identified area may then be
used for input to the AERMOD model. Users should avoid using a very fine spatial resolution of
population density for this purpose as this could result in significant gaps within the urban area
due to parks and other unpopulated areas, making it more difficult to define the extent of the
urban area. Population densities by census tract should provide adequate resolution in most
cases and may still be finer resolution than desired in some cases. Since census tracts vary in
size and shape, another acceptable approach would be to develop gridded estimates of population
data based on census block or block group data. In such cases, a grid resolution on the order of 6
kilometers is suggested. Plotting population density with multiple "contour" levels, such as 0-
500, 500-750, 750-1000, 1000-1500, etc., may also be beneficial in identifying which areas near
the edge of the urban complex to include even though the population density may fall below the
750 threshold. The user should also bear in mind that the urban algorithms in AERMOD are
dependent on population to the one-fourth power and are therefore not highly sensitive to
variations in population. Population estimates to two significant figures should be sufficiently
accurate for application of AERMOD.
5.3 Optional urban roughness length - URBANOPT keyword (5/2024, 24142)
The URBANOPT keyword on the CO pathway in AERMOD (EPA, 2024g) includes an
optional parameter to specify the urban surface roughness length which has a default value of 1
m when no length is specified in the input file. The urban surface roughness parameter is used to
define a reference height for purposes of adjusting dispersion for surface and low-level releases
to account for the enhanced turbulence associated with the nighttime urban heat island. This
optional urban roughness length is not used to adjust for differences in roughness length between
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the meteorological measurement site, used in processing the meteorological data, and the urban
application site. Details regarding the adjustments in AERMOD for the urban boundary layer,
including the use of the urban roughness length parameter, are provided in Section 5.9 of the
AERMOD model formulation document (EPA, 2024a) and Cimorelli et al. (2004).
The default value of 1 meter for urban surface roughness length is considered appropriate
for most applications. Any application of AERMOD that utilizes a value other than 1 meter for
the urban roughness length should be based upon agreement reached between the model user and
appropriate reviewing authority in accordance with Section 4.2.1(f) and pursuant to
recommendations discussed in Section 7.2.1.1 of the Guideline (EPA, 2024c).
5.4 Meteorological data selections for urban applications (01/09/2008)
5.4.1 Urban applications using NWS meteorological data (01/2008)
When modeling urban sources, the urban algorithms in AERMOD are designed to
enhance the turbulence levels relative to the nearby rural setting during nighttime stable
conditions to account for the urban heat island effect (Cimorelli, et al., 2004). For urban
applications using representative NWS meteorological data, the AERMOD urban option
(URBANOPT) should be selected (EPA, 2024g), regardless of whether the NWS site is in a
nearby rural or an urban setting. This is because the limited surface meteorological
measurements available from NWS stations will not account for the enhanced turbulence or
other meteorological characteristics of the urban boundary layer included in the AERMOD urban
algorithms. The determination of surface characteristics for processing NWS meteorological
data for urban applications should conform to the recommendations presented in Section 3.1.
5.4.2 Urban applications using site-specific meteorological data (01/2008)
In most cases, site-specific meteorological data used for urban applications should be
treated in a manner similar to NWS data described in Section 5.4.1, regardless of whether the
measurement site is located in a nearby rural or an urban setting. That is, the AERMOD urban
option should be selected and the surface characteristics should be determined based on the
recommendations in Section 3.1. This is due to the fact that the limited surface meteorological
measurements available from the meteorological measurement program will not adequately
account for the meteorological characteristics of the urban boundary layer included in the
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AERMOD urban algorithms. However, if the measurement site is located in an urban setting
and site-specific turbulence measurements are available (e.g., go or ow), some adjustments to the
meteorological data input to AERMOD may be necessary, as discussed in Section 3.3.
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6.0 Source characterization
6.1 Capped and horizontal stacks (12/2016, vl6216)
Beginning with version 16216, AERMOD includes regulatory options for modeling
capped and horizontal stacks using the POINTCAP and POINTHOR source types, respectively.
For capped and horizontal sources that are not subject to building downwash, the options are
consistent with the approach that was approved by the Model Clearinghouse in July 1993 (see
Appendix A). This approach uses an effective stack diameter to maintain the flow rate to
maintain plume buoyancy, while suppressing plume momentum by setting the exit velocity to
0.001 m/s.
For capped and horizontal sources that are subject to building downwash, the options
have been adapted to account for the PRIME algorithm. Since the PRIME component in
AERMOD incorporates a numerical plume rise algorithm that simulates the full trajectory of the
plume, AERMOD sets the initial plume trajectory angle as horizontal for the POINTHOR
option. For the POINTCAP option, AERMOD assigns the initial diameter of the plume to be 2
times the actual stack diameter to account for initial spread of the plume associated with the cap.
AERMOD also assigns the initial horizontal velocity of the plume for the POINTCAP option to
be the initial exit velocity specified by the user divided by 4.
6.2 Use of area source algorithm in AERMOD (11/2024, v24142)
Plume meander for area sources was added to AERMOD version 23132 as an alpha
option and retained as an alpha option in version 24142. Because of issues related to excessive
run times and technical issues with model formulation, the approach has not been implemented
as a regulatory option for area sources. As a result, concentration predictions for area sources
may be overestimated under very light wind conditions {i.e., u < 1.0 m/s). The problem could
arise with meteorological data derived from very low threshold instruments, such as sonic
anemometers as well as data from a gridded meteorological model. Meteorological grid models
can at times produce extremely light winds. During such conditions time-averaged plumes tend
to spread primarily as a result of low frequency eddy translation rather than eddy diffusion.
AERMOD treats this meander effect by estimating the concentration from two limiting states: 1)
a coherent plume state that considers lateral diffusive turbulence only (the mean wind direction is
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well defined) and 2) a random plume state (mean wind direction is poorly defined) that allows
the plume to spread uniformly, about the source, in the x-y plane. The final concentration
predicted by AERMOD is a weighted sum of these two bounding concentrations. Interpolation
between the coherent and random plume concentrations is accomplished by assuming that the
total horizontal "energy" is distributed between the wind's mean and turbulent components.
In order to avoid overestimates for area sources during light wind conditions, it is
recommended that, where possible, a volume source approximation be used to model area
sources. This approach can be applied with confidence for situations in which the receptors are
displaced from the source. However, for applications where receptors are located either directly
adjacent to, or inside the area source, AERMOD's area source algorithm will need to be used.
For these circumstances, caution should be exercised if excessive concentrations are predicted
during extremely light wind conditions. On a case-by-case basis, the reviewing authority should
decide whether such low-wind predictions are unrealistic and refine modeled emissions estimates
for area sources, as appropriate.
6.3 RLINE source type (5/2024, v24142)
The RLINE source type was first implemented as a beta option for characterizing mobile
sources (i.e., roadways) in AERMOD vl9191, and it's use in a regulatory air modeling
demonstration required alternative model approval by the Regional Office and concurrence from
the Model Clearinghouse (MCH). AERMOD also limited the use of the RLINE source type to
FLAT terrain only. In AERMOD version 23132, the capability to account for elevated terrain
was added to the RLINE source type, and the source type was maintained as a beta option. The
RLINE source type was formally promulgated as a regulatory formulation update to AERMOD
beginning in version 24142 in the 2024 update to the Guideline (EPA, 2024c). As a regulatory
option, the RLINE source type can now be used to characterize mobile sources without
alternative model approval and MCH concurrence. However, when modeling for project level
transportation conformity and hot-spot analyses, refer to the EPA's Office of
Transportation and Air Quality (OTAQ) for current guidance on how to model and
configure roadway sources (https://www.epa.gov/state-and-local-transportation/proiect-
level-conformitv-and-hot-spot-analvses).
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7.0 REFERENCES
Blom, J. and L. Wartena, 1969. The Influence of Changes in Surface Roughness on the
Development of the Turbulent Boundary Layer in the Lower Layers of the Atmosphere. J.
Atmos. Sci., 26, 255-265.
Businger, J. A., 1986. Evaluation of the Accuracy with Which Dry Deposition Can Be Measured
with Current Micrometeorological Techniques. J. Climate Appl. Meteor., 25, 1100-1124.
Cimorelli, A. J., S. G. Perry, A. Venkatram, J. C. Weil, R. J. Paine, R. B. Wilson, R. F. Lee, W.
D. Peters, R. W. Brode, and J. O. Paumier, 2004. AERMOD: Description of Model
Formulation, EPA-454/R-03-004. U.S. Environmental Protection Agency, Research
Triangle Park, NC.2
EPA, 2000. Meteorological Monitoring Guidance for Regulatory Modeling Applications.
Publication No. EPA-454/R-99-005. Office of Air Quality Planning & Standards, Research
Triangle Park, NC. (PB 2001-103606). 1
EPA, 2005a. Revision to the Guideline on Air Quality Models: Adoption of a Preferred General
Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule.
40 CFR Part 51, Appendix W. Federal Register, Volume 70, Page 68218.
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Agency, Research Triangle Park, NC.1
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AERMOD Applications. EPA-454/B-24-005. U.S. Environmental Protection Agency,
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EPA, 2024c. Guideline on Air Quality Models: Ehancements to the AERMOD Dispersion
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Stull, R. B., 1988. An Introduction to Boundary Layer Meteorology. Kluwer Academic
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Appendix A. EPA Model Clearinghouse memorandum dated July 9,1993
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July 9, 1993
MEMORANDUM
SUBJECT: Proposal for Calculating Plume Rise for Stacks with Horizontal
Releases or Rain Caps for Cookson Pigment, Newark, New Jersey
FROM: Joseph A. Tikvart, Chief
Source Receptor Analysis Branch, TSD (MD-14)
TO: Ken Eng, Chief
Air Compliance Branch, Region II
In response to your request, the Model Clearinghouse has reviewed your
proposal for treating horizontal and capped stacks at Cookson Pigment so
that the model (SCREEN or ISC2) will properly treat plume rise from the
Cookson Pigment stacks. We concur in principle with the approach, with
some relatively minor changes.
First, the analysis provided by New Jersey Department of Environmental
Protection is technically correct. We suggest, however, that the exit
velocity for horizontal and capped stacks be set to a lower figure than 0.1
m/s. A 0.1 m/s exit velocity may still result in significant momentum
plume rise being calculated, even though these kinds of sources should have
zero momentum rise. We therefore suggest setting the stack exit velocity
to a lower value, such as .001.
For horizontal stacks that are not capped, we suggest turning stack
tip downwash off, whether there are buildings or not. Stack tip downwash
calculations are inappropriate for horizontal stacks.
For vertical stacks that are capped, turn stack tip downwash off and
reduce the stack height by three times the actual stack diameter. The cap
will probably force stack tip downwash most of the time. The maximum
amount of the stack tip downwash (as calculated in ISC2) is three times the
stack diameter. Reducing the stack height by this amount, while turning
off the stack tip downwash option, causes the maximum stack tip downwash
effect. The resulting concentrations may err slightly on the high side.
For stacks with small diameters, such as those at Cookson Pigment, the
error should be quite small. Note, however, that this approach may not be
valid for large diameter stacks (say, several meters).
cc: A. Colecchia
D. Wilson
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United States Office of Air Quality Planning and Standards Publication No. EPA-454/B-24-009
Environmental Protection Air Quality Assessment Division November 2024
Agency Research Triangle Park, NC
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