Modeling Guidelines for

Air Quality Impact Assessments

Prepared By
Robin Cobbs
Charlotte Mountain

June 2020
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 TABLE OF CONTENTS

1. Introduction ........................................................................................................................... 1
1.1 Applicability ................................................................................................................................. 1
1.2 Prevention of Significant Deterioration Modeling for Major Sources.......................................... 1
2. Emissions ................................................................................................................................ 2
2.1 Pollutants and Averaging Periods ................................................................................................. 2
2.1.1 Criteria Pollutants .................................................................................................................... 2
2.1.2 Other Pollutants ........................................................................................................................ 3
2.2 Emission Sources .......................................................................................................................... 3
2.2.1 NSR AQIA with Only New Equipment ...................................................................................... 3
2.2.2 NSR AQIA with Existing Equipment ......................................................................................... 3
2.2.3 CEQA AQIA .............................................................................................................................. 4
2.3 Emission Calculations ................................................................................................................... 4
3. Air Dispersion Model ............................................................................................................ 4
3.1 Offshore Platforms ........................................................................................................................ 5
3.2 Control Options ............................................................................................................................. 5
3.2.1 Conversion of NOX to NO2 ........................................................................................................ 5
3.2.2 Special Processing Options for the AAQS Analysis for NO2 .................................................... 6
3.2.3 Special Processing Options for the AAQS Analysis for SO2 ..................................................... 6
3.2.4 Special Processing Options for the AAQS Analysis for PM2.5 .................................................. 7
3.2.5 Annual Averaging Period Options ............................................................................................ 7
3.3 Defining Urban and Rural Conditions .......................................................................................... 7
3.4 UTM Coordinate System .............................................................................................................. 9
3.5 Source Parameters ......................................................................................................................... 9
3.5.1 Point Sources – POINT, POINTCAP, POINTHOR .................................................................. 9
3.5.2 Area Sources – AREA, AREAPOLY, AREACIRC ................................................................... 10
3.5.3 OPENPIT Sources................................................................................................................... 11
3.5.4 VOLUME Sources ................................................................................................................... 12
3.5.5 LINE Sources .......................................................................................................................... 13
3.6 Building Impacts ......................................................................................................................... 14
3.7 Terrain ......................................................................................................................................... 14
3.8 Meteorological Data.................................................................................................................... 15
3.9 Receptors..................................................................................................................................... 15
 3.9.1 Cartesian Receptor Grids ....................................................................................................... 15
3.9.2 Class I Receptors .................................................................................................................... 16
4. Results ................................................................................................................................... 17
4.1 Ambient Air Quality Standard Analysis ..................................................................................... 17
4.1.1 Background Concentration ..................................................................................................... 20
4.2 Increment Analysis ..................................................................................................................... 21
5. Air Quality Impact Assessment Report ............................................................................. 22
5.1 Facility Information .................................................................................................................... 23
5.2 Source and Emission Inventory Information .............................................................................. 23
5.3 Emission Quantification.............................................................................................................. 23
5.4 Air Dispersion Information ......................................................................................................... 24
5.5 Summary of Results .................................................................................................................... 24
5.5.1 Results of the AAQS Analysis .................................................................................................. 24
5.5.2 Results of the Increment Analysis ........................................................................................... 25
5.6 Air Quality Impact Driver Tables ............................................................................................... 26
5.7 Required Files ............................................................................................................................. 26
6. References............................................................................................................................. 27
7. Contacts ................................................................................................................................ 28
Appendix A – Variable Emissions Modeling ........................................................................... A1
A.1 Non-Continuous Emissions .....................................................................................................A1
A.2 Plant Shutdowns and Start-Ups ..............................................................................................A1
Appendix B – Modeling Specific Source Types ........................................................................ B1
B.1 Liquid Storage Tanks ..............................................................................................................B1
Appendix C – Modeling Emissions from Roadways............................................................... C1
C.1 Modeling Roadways with LINE Sources ................................................................................ C1
C.2 Modeling Roadways with RLINE Sources ............................................................................. C2
C.3 Modeling Roadways with VOLUME Sources ........................................................................ C4
C.5 References for Appendix C..................................................................................................... C7
Appendix D – Placement of Portable Equipment ................................................................... D1
 LIST OF FIGURES

Figure 3.3-1: Auer Method for Determining Urban or Rural Dispersion ....................................... 8
Figure 3.9.2-1: Class I Impact Area .............................................................................................. 17
Figure 1-8: Exact and Approximate Representations of a Line Source by Multiple Volume
Sources (Reproduced from USEPA’s ISC3 User’s Guide Volume II)......................................... C5

LIST OF TABLES

Table 2.1.1-1: Air Quality Standards and Increments for Criteria Pollutants ................................ 2
Table 2.1.2-1: Air Quality Standards for Other Pollutants ............................................................. 3
Table 3.3-1: Urban Land Use.......................................................................................................... 8
Table 3.3-2: Population Data for Urban Dispersion Modeling....................................................... 9
Table 3.5.4-1: Summary of Suggested Procedures for Estimating Initial Lateral Dimensions for
Volume Sources ............................................................................................................................ 13
Table 3.5.4-2: Summary of Suggested Procedures for Estimating Initial Vertical Dimensions for
Volume Sources ............................................................................................................................ 13
Table 3.8-1: Meteorological Data Sets in Santa Barbara County ................................................. 15
Table 3.9.2-1: Class I Receptor Lists ............................................................................................ 17
Table 4.1-1: Reporting Results for the AAQS Analysis .............................................................. 19
Table 4.1.1-1: Background Concentrations for the AAQS Analysis ........................................... 21
Table 4.2-1: Reporting Results for the Increment Analysis ......................................................... 22
Table 5.5.1-1: Example AAQS Modeling Results........................................................................ 25
Table 5.5.2-1: Example Increment Analysis Modeling Results for Class II Impacts................... 26
Table A.2-1: Example Variable Emission Scenario (Hour of Day) ........................................... A2
Table B.1.1-1: Stack Parameters for Modeling Tanks .................................................................. B1
1. Introduction
This document explains the requirements for performing air quality impact assessments for the Santa
Barbara County Air Pollution Control District (District) using AERMOD. It is assumed that the reader
has some modeling experience with this program; therefore, this document is not intended as a user’s
guide for AERMOD. The AERMOD user’s guide, written by U.S. Environmental Protection Agency
(EPA), is noted in the References section of this document and should be consulted for troubleshooting or
when background information is needed.

1.1 Applicability
An air quality impact assessment (AQIA) must be completed for any of the following situations:
1. An AQIA is required as part of the District’s New Source Review (NSR) permitting program
according to District Rule 802.F. for any new or modified stationary source that meets at least one
of the following criteria:
a. The source has a potential to emit of any pollutant or its precursors which is equal to or
greater than any threshold shown in Table 4 of District Rule 802; or
b. The Control Officer determined that the new or modified stationary source has the potential
to cause or contribute to a violation of any ambient air quality standard or increment; or
c. The new or modified stationary source has the potential to emit more than 20 pounds per hour
of any attainment pollutant or total suspended particulates (TSP).
2. An AQIA is necessary as part of the California Environmental Quality Act (CEQA) process.

An AQIA can consist of modeling one or multiple pollutants and averaging periods for an increment
analysis, ambient air quality standard (AAQS) analysis, or both. Typically, both an increment analysis
and an AAQS analysis are required for the District’s NSR permitting program, while only an AAQS
analysis is required for the CEQA process. Confirm the modeling requirements with the District before
submitting the AQIA.

1.2 Prevention of Significant Deterioration Modeling for Major Sources

Please contact the District prior to performing Prevention of Significant Deterioration (PSD) modeling for
a major source. Information on PSD modeling is provided at EPA’s Clean Air Act Permit Modeling
Guidance webpage, noted in the References section of this document.

EPA Guidance Documents regarding PSD modeling are listed below:

• EPA’s May 20, 2014 Guidance for PM2.5 Permit Modeling, available at:
https://www.epa.gov/sites/production/files/2015-07/documents/pm25guid2.pdf
• EPA’s August 2016 SO2 NAAQS Designations Modeling Technical Assistance Document (Draft),
available at: https://www.epa.gov/sites/production/files/2016-06/documents/so2modelingtad.pdf
• EPA’s June 29, 2010 Guidance Concerning the Implementation of the 1-hour NO2 NAAQS for the
Prevention of Significant Deterioration Program available at:
https://www.epa.gov/sites/production/files/2015-07/documents/appwno2.pdf

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2. Emissions
2.1 Pollutants and Averaging Periods

2.1.1 Criteria Pollutants

Table 2.1.1-1 displays the criteria pollutant 1 and averaging period combinations that may be required to
be modeled in the AQIA. The state and national ambient air quality standards are displayed for reference;
for most pollutants and averaging periods, modeling is only required for one of the standards. However,
SO2 and NO2 must be modeled for comparison to both the 1-hour state standard and 1-hour
national standard. See Section 4.1 of this document for more information. Contact the District to
confirm which pollutants and averaging periods should be included in the AQIA.

Table 2.1.1-1: Air Quality Standards and Increments for Criteria Pollutants
Maximum Allowable Ambient Air
Increase – Increments Quality Standard
(μg/m3) (μg/m3)
Pollutant:
Averaging Period Class I Area1 Class II Area2 California National
Total Suspended Particulates:
Annual Average 5 19 — —
24-Hour Maximum 10 37 — —
Sulfur Dioxide:
Annual Average 2 20 — 80
24-Hour Maximum 5 91 105 —
3-Hour Maximum 25 512 — 1,300
1-Hour Maximum — — 655 196
Nitrogen Dioxide:
Annual Average 2.5 25 57 100
1-Hour Maximum 10 100-188 339 188
Carbon Monoxide:
8-Hour Maximum 200 2,500 10,000 10,000
1-Hour Maximum 800 10,000 23,000 40,000
Reactive Organic Compounds:
3-Hour Maximum 3 40-160 — —
Particulate Matter (< 10 μm):
Annual Average 4 17 20 —
24-Hour Maximum 8 12-30 50 150
Particulate Matter (< 2.5 μm):
Annual Average 1 4 12 12
24-Hour Maximum 2 9 — 35
1
“Class I Area” means any area having air quality or air quality related values requiring special protection, and
which has been designated Class I by a federal or state authority empowered to make such designation.
2
“Class II Area” means any area not designated as a Class I or Class III Area pursuant to 40 CFR 51.166(e).

1
Although lead is a criteria pollutant, it is addressed below in Section 2.1.2, Other Pollutants.

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2.1.2 Other Pollutants
Table 4, Air Quality Impact Analysis Thresholds, in the District’s Rule 802 includes criteria and non-
criteria pollutants. District Rule 805 contains standards and increments for only the pollutants shown in
Table 2.1.1-1. Other pollutants with a State or Federal Air Quality Standard are listed in Table 2.1.2-1. If
a health risk assessment (HRA) is also being performed, then a separate analysis for H2S is not required.
The AAQS for H2S is equal to the acute reference exposure level for H2S. Furthermore, if a HRA is
performed, then a separate analysis for vinyl chloride is not required.

For toxic air contaminants included in Table 4 of District Rule 802, but not included in Table 2.1.2-1
below, a health risk assessment is required in lieu of an AAQS analysis. For other pollutants that are not
toxics, the AQIA is required for informational purposes only.

Table 2.1.2-1: Air Quality Standards for Other Pollutants

Air Quality Standard
Pollutant Averaging Period
(μg/m3)
Lead 30-Day Average 1.5
Beryllium 30-Day Average 0.01
Vinyl Chloride 24-Hour 26
Hydrogen Sulfide 1-Hour 42

Please contact the District for the applicable requirements for municipal waste combustors.

2.2 Emission Sources

Contact the District to confirm which emission sources should be included in the AQIA. Sections 2.2.1
through 2.2.3 below explain the requirements for different types of AQIAs.

2.2.1 NSR AQIA with Only New Equipment

An AQIA for an NSR project at a stationary source with no existing equipment must include all permitted
emitting equipment at its maximum potential to emit (PTE), which is calculated as part of the NSR
permitting process. Emissions from permit-exempt equipment are not included in NSR AQIAs. Both an
increment analysis and an AAQS analysis are required.

2.2.2 NSR AQIA with Existing Equipment

For an NSR project at a stationary source with existing equipment, an increment analysis and an AAQS
analysis are required. The entire project emissions must be evaluated in the AQIA. The project
emissions include the PTE for the newly-permitted equipment, as well as emissions from any equipment
that is already under a District permit, if the District determines that those emissions are also part of the
project. Any increase in emissions from the existing operating conditions (averaged over the three
consecutive years immediately preceding the date of application) is considered part of the project and
must be included in the AQIA for existing equipment that will emit more air pollution as a result of the
project. Other existing equipment emissions may also be required to be included in the AQIA if the
District determines that they are related to the new project (e.g., a steam generator installed within the
past three years that the District understands to be part of the project).

Existing equipment at the stationary source that is determined by the District to not be part of the project
should not be included in the AAQS analysis or the increment analysis. The air quality impacts of

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existing equipment not related to the project are accounted for in the background concentration in the
AAQS analysis.

2.2.3 CEQA AQIA

Increment analyses are not required for CEQA AQIAs; only AAQS analyses are required for CEQA. For
the CEQA AAQS analysis, all emissions from the NSR AAQS analysis must be included. Just as for
District NSR AQIAs, emissions from existing equipment at the stationary source beyond the historical
baseline level must be included in the CEQA AAQS analysis. In addition, ongoing unpermitted
emissions (i.e., not construction-related) must be included. For example, ongoing fugitive dust emissions
(e.g., from driving on unpaved roads), combustion emissions from vehicles, and combustion emissions
from drill rigs (e.g., at an oil and gas lease) must be included in the CEQA AAQS analysis. Additionally,
all operational mobile emissions in a 1,000-foot line extending outside the property boundary must be
modeled. An AQIA for CEQA should not include emissions from site grading, paving, welding, or other
activities associated with construction. Emissions from oil and gas well drilling must be included in the
CEQA analysis; the District does not consider drilling wells on an oil and gas lease to be a construction
activity because it occurs over the life of the project.

2.3 Emission Calculations

Once the applicant has determined which emission sources, pollutants and averaging periods must be
evaluated in the AQIA, the emissions must be calculated. Detailed emission calculation spreadsheets,
containing all calculation assumptions, for each pollutant and averaging period must be submitted to the
District with the AQIA. All calculations within spreadsheets must contain formulas (i.e., spreadsheets
showing only values in the cells will be returned to the applicant for revision).

Because AERMOD requires the emission rates to be entered in units of grams per second (g/s), it is useful
to first calculate the emissions on an annual, 24-hour, 8-hour, 3-hour or 1-hour basis, and then convert to
g/s. The maximum possible emissions during each averaging period should be used to model the impacts.
For example, an emergency flare is installed at an oilfield, resulting in SO2 emission higher than normal
during certain short term operations. The worst case short term flaring scenario is when produced sour
gas is routed to the emergency flare for a maximum of 5 minutes in a day. For modeling purposes, the
24-hour, the 3-hour and the 1 hour-SO2 mass emissions from the flare are all equal (e.g., 1 lb) because the
flaring event occurs within 5 minutes. However, the emission rate (g/s) varies for each averaging period.

If the ratio of PM2.5 to PM10 is not known, all PM10 can be assumed to be PM2.5. This is a conservative
assumption that should be refined if the PM2.5 impacts exceed an AAQS or increment threshold. The use
of a PM2.5/PM10 ratio less than 1 requires justification from the applicant and is subject to approval by the
District.

3. Air Dispersion Model

The District requires that EPA’s AERMOD be used to perform the air dispersion modeling for AQIAs,
except for offshore platforms. The current version of AERMOD at the time of writing this document is
dated 19191. The AERMOD executable is available for free from EPA. There are also many software
options that incorporate AERMOD in a more user-friendly interface, such as Lakes Environmental’s
(Lake’s) AERMOD View and Providence/Oris’ BEEST. While the District does not recommend any one
particular software product, the District primarily uses Lakes’ AERMOD View. The use of Lakes’
AERMOD View by the applicant may help with the ease of review and sharing of files. Furthermore, the
District will not accept AQIAs performed using HARP 2.

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Because there are multiple pollutants and averaging periods required for AQIAs, it is helpful to create a
separate AERMOD project file for each pollutant and averaging period. However, if the maximum g/s
emission rate for a pollutant on an annual and 24-hour basis were the same, for example, it would save
time to run the two averaging periods within the same AERMOD project file.

3.1 Offshore Platforms

In general, the District requires the OCD model for offshore platforms. The Offshore and Coastal
Dispersion Model (OCD) is a straight line Gaussian model developed by EPA to determine the impact of
offshore emissions from point, area or line sources on the air quality of coastal regions. OCD
incorporates overwater plume transport and dispersion as well as changes that occur as the plume crosses
the shoreline. Hourly meteorological data are needed from both offshore and onshore locations.
Applicants should contact the District if they have a project that requires the use of the OCD model.

3.2 Control Options

AERMOD contains several regulatory options, which are set by default, as well as non-regulatory
options. The District requires that the regulatory options are used. The use of any non-regulatory default
options must be justified with a discussion in the AQIA report and approved by the District.

3.2.1 Conversion of NOX to NO2

Although the NO2 National Ambient Air Quality Standard (NAAQS) is based on NO2 concentrations, the
majority of nitrogen oxides (NOX) emissions are in the form of nitric oxide (NO) rather than NO2. The
resultant NO2 concentrations are largely driven by the ambient chemical environment (i.e., the reaction of
NO with ambient ozone to form NO2) and the initial NO2/NOX ratio of the emissions (i.e., the in-stack
ratio). The EPA outlines a three tiered approach to estimating modeled NO2 concentrations.

For most projects, the District recommends using the Tier 2 Ambient Ratio Method Version 2
(ARM2), which uses the EPA polynomial equation to predict NO2/NOX ratios and does not require
additional site-specific information. Please contact the District for approval prior to using any
other Tier or method.

EPA provides additional clarification on the conversion of NOX species to NO2 in the following
document:
• EPA’s July 2015 Technical support document (TSD) for NO2-related AERMOD modifications,
available at: https://www3.epa.gov/scram001/11thmodconf/AERMOD_NO2_changes_TSD.pdf.

The California Air Pollution Control Officers Association (CAPCOA) provides guidance on
demonstrating compliance with the 1-hour NAAQS, but does not discuss the new Tier 2 ARM2 or Tier 3
PVMRM2:
• CAPCOA’s October 2011 Guidance Document, Modeling Compliance of The Federal 1-Hour
NO2 NAAQS, available at:
http://www.valleyair.org/busind/pto/tox_resources/CAPCOANO2GuidanceDocument10-27-
11.pdf.

The methods available in AERMOD to account for the conversion of NOX species to NO2 are described
in Sections 3.2.1.1 through 3.2.1.4 below.

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3.2.1.1 Tier 1
Tier 1 assumes full conversion of NOX species to NO2 (i.e., 100 percent of NOX emissions = NO2
emissions). This method is the most conservative. No special parameters or options are required to be
selected.

3.2.1.2 Tier 2 ARM2 (Recommended by the District)

The Tier 2 Ambient Ratio Method Version 2 (ARM2) must be selected prior to running AERMOD. This
option may only be selected if the user specifies that NO2 is the pollutant being modeled in AERMOD.
The ARM2 applies a 6th order polynomial equation to predict the NO2/NOX ratio.

For more information on the Tier 2 ARM2, see EPA’s Technical support document (TSD) for NO2-
related AERMOD modifications and Section 3.2.4, Input parameters for NO2 conversion options, of the
AERMOD user’s guide, noted in the References section of this document.

The ARM2 options in AERMOD have the following parameters:

• Minimum NO2/NOX Ratio: Use the default value of 0.50.
• Maximum NO2/NOX Ratio: Use the default value of 0.90.

3.2.1.3 Tier 3
The two Tier 3 methods for estimating the conversion of NOX to NO2 are the Ozone Limiting Method
(OLM) and the Plume Volume Molar Ratio Method Version 2 (PVMRM2).

The Tier 3 methods require background ozone concentrations. Other parameters for the Tier 3 methods
are:
• Equilibrium NO2/NOX Ratio: The default value used by the model is 0.90. A user-specified value
can be defined here between 0.10 and 1.00.
• Default In-Stack NO2/NOX Ratio: A default value of 0.50 will be used for all sources unless a
user-specified value is provided for the source in the NO2 Ratios screen of the Source Pathway
dialog. The default value specified will also be used if the user did not specify a value for a
specific source in Source Pathway - NO2 Ratios.

3.2.2 Special Processing Options for the AAQS Analysis for NO2
To meet the 1-hour NAAQS, the 3-year average of the annual 98th percentile of the 1-hour daily
maximum concentrations must not exceed 100 ppb (188 µg/m3). If Lakes’ AERMOD View is used to
complete the AQIA, select the option for 1-hour NO2 NAAQS processing in the Control pathway, which
will prompt the model to display the 8th Highest High (98th percentile) of the maximum daily 1-hour
results. If Lakes’ AERMO View is not used, the user may directly enter the appropriate
keywords/parameters in the AERMOD input file. See Section 3.2.15, Processing for 1-hour NO2 and SO2
NAAQS, of the AERMOD user’s guide for more information on the NO2 processing in AERMOD.

3.2.3 Special Processing Options for the AAQS Analysis for SO2
To meet the 1-hour NAAQS, the 3-year average of the annual 99th percentile of the 1-hour daily
maximum concentrations must not exceed 75 ppb (196 µg/m3). If Lakes’ AERMOD View is used to
complete the AQIA, select the option for 1-hour SO2 NAAQS processing in the Control pathway, which
will prompt the model to display the 4th Highest High (99th percentile) of the maximum daily 1-hour
results. If Lakes’ AERMOD View is not used, the user may directly enter the appropriate

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keywords/parameters in the AERMOD input file. For more information on specific modeling guidance
for the 1-hour SO2 NAAQS, see EPA’s Memorandum, Applicability of Appendix W Modeling Guidance
for the 1-hour SO2 National Ambient Air Quality Standard, noted in the References section of this
document. See Section 3.2.15, Processing for 1-hour NO2 and SO2 NAAQS, of the AERMOD user’s
guide for more information on the SO2 processing in AERMOD.

The 3-hour NAAQS for SO2 is not to be exceeded more than once a year. For that reason, report the 2nd
Highest High for the 3-hour SO2 value. In Lakes’ AERMOD View, the 2nd Highest High can be selected
under the Output Options, Tabular Outputs Screen. If Lakes’ AERMOD View is not used, the user may
directly enter the appropriate keywords/parameters in the AERMOD input file.

In addition to the special processing options noted above, AERMOD will automatically apply a 4-hour
half-life decay coefficient for urban SO2 sources.

3.2.4 Special Processing Options for the AAQS Analysis for PM2.5
To meet the 24-hour NAAQS for PM2.5, the 3-year average of the annual 98th percentile of the 24-hour
concentration must be equal to or less than 35 μg/m3. If Lakes’ AERMOD View is used to complete the
AQIA, select the option for 24-hour PM2.5 NAAQS processing in the Control pathway, which will prompt
the model to display the 8th Highest High (98th percentile) of the 24-hour results averaged over 5 years
(assuming a 5-year meteorological data set is used). If Lakes’ AERMOD View is not used, the user may
directly enter the appropriate keywords/parameters in the AERMOD input file. See Section 3.2.14.1,
Processing for fine particulate matter (PM-2.5), of the AERMOD user’s guide for more information on
the PM2.5 processing in AERMOD.

3.2.5 Annual Averaging Period Options

The annual standards listed in Table 1 of District Rule 805 for “Annual Arithmetic Mean” must be
compared to the annual average concentration from each individual year of met data. Run the annual
averaging period by selecting the ANNUAL averaging time options. In addition, select the “Report
Maximum Annual Average for Each Met Year” that is available in Lakes’ AERMOD View (or use the
appropriate AERMOD keywords if a different interface is used to run AERMOD). This option will allow
the modeler to compare the highest annual average from an individual year to the annual standards in
Table 1 of District Rule 805. Do not select the PERIOD option in AERMOD, which computes a single
multi-year average concentration. The PERIOD option may give slightly different results than the multi-
year average of individual ANNUAL mean concentrations due to differences in the number of calms
and/or missing data from year to year. The ANNUAL average output is based on the average of the
ANNUAL values across the years of meteorological data processed.

3.3 Defining Urban and Rural Conditions

The Auer method for classifying a site as urban or rural is specified in EPA’s 40 CFR Part 51 Appendix
W, noted in the References section of this document. Follow the Auer method, explained below, for the
selection of either urban or rural dispersion coefficients:
1. Draw a circle with a radius of 3 km from the center of the emission source or centroid of the
polygon formed by the facility emission sources.
2. If the industrial, commercial, dense single/multi-family, and multi-family two-story land use
types account for 50% or more of the area within the circle, then the area is classified as urban;
otherwise, the area is classified as rural.
3. To verify if the area within the 3 km circle is predominantly rural or urban, overlay a grid on top
of the circle and identify each square as primarily urban or rural. If more than 50% of the total

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 number of squares is urban, then the area is classified as urban; otherwise, the area is rural. See
Figure 3.3-1 for an example of this grid method.

Figure 3.3-1: Auer Method for Determining Urban or Rural Dispersion

From the Auer method, areas typically defined as rural include:

• Residences with large grass lawns and trees
• Large estates
• Metropolitan parks and golf courses
• Agricultural areas
• Undeveloped land
• Water surfaces

Auer defines an area as urban if it has less than 35% vegetation coverage or if the area falls into one of the
land use types described in Table 3.3-1.

Table 3.3-1: Urban Land Use

Use and Structures Vegetation Coverage
Heavy industrial Less than 5%
Light/moderate industrial Less than 5%
Commercial Less than 15%
Dense single/multi-family Less than 30%
Multi-family two-story Less than 35%

After the site classification has been determined, apply it to all sources (i.e., do not model some sources as
rural and other sources as urban). If the urban option is selected, enter the population of the city where
the project is located. If the facility is located in an unincorporated area, use the closest city listed in
Table 3.3-2. The default value of 1 meter for urban surface roughness length is appropriate for most
urban sites. Use of any value other than 1 meter for the urban surface roughness is considered a non-
regulatory option, and requires appropriate documentation and justification.

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 Table 3.3-2: Population Data for Urban Dispersion Modeling
City Name Population in 2010
Buellton 4,828
Carpinteria 13,040
Goleta 29,888
Guadalupe 7,080
Lompoc 42,434
New Cuyama 517
Santa Barbara 88,410
Santa Maria 99,553
Solvang 5,245

3.4 UTM Coordinate System

The coordinate system that should be used in AERMOD is Universal Transverse Mercator (UTM).
Ensure all modeled sources, buildings, and receptors are defined in the same datum. In the AQIA report,
state the datum used in the model.

3.5 Source Parameters

The primary source types and their input requirements are outlined in Sections 3.5.1 through 3.5.5.
Detailed descriptions of the input fields are found in the AERMOD user’s guide, noted in the References
section of this document. All source parameter units specified in brackets are the default units in the
AERMOD executable.

After entering all the source information into AERMOD, the user should create a separate source group
for each source, as well as including a source group containing all the sources in the model. The source
group of all sources will allow the impact from all sources to be easily identified. The separate source
groups for each source will help identify the air quality impact driving devices.

3.5.1 Point Sources – POINT, POINTCAP, POINTHOR

A point source is the most common type of release and is characterized by a traditional stack or isolated
vent. Examples of point sources include combustion equipment with stacks and closed fixed roof tanks.
AERMOD includes three options for point sources: the POINT source is used for a non-capped vertical
stack; the POINTCAP source is used for a vertical stack with a rain cap; and the POINTHOR source is
used for a horizontal stack.

The point source parameter inputs are:

• X Coordinate [m]: Easting UTM at the center of the point source.
• Y Coordinate [m]: Northing UTM at the center of the point source.
• Release Height [m]: Source release height (or stack height) above the ground.
• Stack Diameter [m]: Inner diameter of the stack.
• Exit Velocity [m/s]: Stack gas exit velocity.
• Stack Temperature [K]: Stack gas exit temperature.
• Emission Rate [g/s]: Pollutant emission rate.

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3.5.2 Area Sources – AREA, AREAPOLY, AREACIRC
Area sources are used to model releases that occur over an area. Examples of area sources include
landfills, open tanks, slag dumps and lagoons. AERMOD includes three options for specifying the shape
of an area source: the AREA source is used to specify rectangular areas that may also have a rotation
angle specified relative to a north-south orientation; the AERAPOLY source is used to specify an area
source as an irregularly-shaped polygon; and the AREACIRC source is used to specify a circular-shaped
area source. All three of the area source types use the same calculations for estimating impacts from area
sources, and are merely different options for specifying the shape of the area source.

The source parameter inputs for each of the area source types are described in Sections 3.5.2.1 through
3.5.2.3 below.

3.5.2.1 AREA Sources Options

AERMOD accepts rectangular areas that may have a rotational angle specified relative to a north-south
orientation. The AREA source parameter inputs are:
• X Coordinate [m]: Easting UTM for the southwest corner of the area source.
• Y Coordinate [m]: Northing UTM for the southwest corner of the area source.
• Release Height [m]: Release height above ground. For example, a tank open to the atmosphere
would have a release height equal to the tank height.
• Xinit [m]: Length of X side of the area (in the east-west direction if Angle is 0 degrees).
• Yinit [m]: Length of Y side of the area (in the north-south direction if Angle is 0 degrees). This
parameter is optional; if no value is entered, AERMOD sets Yinit equal to Xinit.
• Szinit [m]: Initial vertical dimension of the area source plume. For more passive area source
emissions, such as evaporation or wind erosion, the Szinit parameter is typically omitted, which is
equivalent to using a Szinit of 0 meters.
• Angle [degrees]: Orientation angle for the rectangular area from North, measured positive in the
clockwise direction. If the Angle is not zero, the model will rotate the AREA source clockwise
around the southwest corner.
• Emission Rate [g/s/m2]: Pollutant emission rate. Note that the g/s emission rate must be divided
by the area of the area source to calculate the emission rate in units of g/s/m2.

The only option for defining the area is a rectangle or square. The maximum length/width aspect ratio for
area sources is 10 to 1. If the aspect ratio is greater than 10, use the AREAPOLY source type. See
Section 3.3.2.4, AREA source inputs, of the AERMOD user’s guide for more information on the AREA
source inputs.

3.5.2.2 AREAPOLY Sources Options

The AREAPOLY source type is used to specify an area source as an arbitrarily-shaped polygon with
between 3 and 20 sides. This source type option provides the user with flexibility for specifying the
shape of an area source. The AREAPOLY source parameter inputs are:
• X Coordinate [m]: Easting UTM for the first vertex point of the area source.
• Y Coordinate [m]: Northing UTM for the first vertex point of the area source.

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 • Release Height [m]: Release height above ground. For example, a tank open to the atmosphere
would have a release height equal to the tank height.
• Number of Vertices: Number of vertices (or sides) of the area source polygon.
• Xv(1), Xv(2) … Xv(i) [m]: Easting UTM values of the vertices of the area source polygon.
Xv(1) must match the X coordinate identified for the source.
• Yv(1), Yv(2) … Yv(i) [m]: Northing UTM values of the vertices of the area source polygon.
Yv(1) must match the Y coordinate identified for the source.
• Szinit [m]: Initial vertical dimension of the area source plume. For more passive area source
emissions, such as evaporation or wind erosion, the Szinit parameter is typically omitted, which is
equivalent to using a Szinit of 0 meters.
• Emission Rate [g/s/m2]: Pollutant emission rate. Note that the g/s emission rate must be divided
by the area of the area source to calculate the emission rate in units of g/s/m2.

3.5.2.3 AREACIRC Sources Options

The AREACIRC source type is used to specify an area source as a circular shape. AERMOD will
automatically generate a regular polygon of up to 20 sides to approximate the circular area source. The
polygon will have the same area as that specified for the circle. The AREACIRC source parameter inputs
are:
• X Coordinate [m]: Easting UTM at the center of the area source.
• Y Coordinate [m]: Northing UTM at the center of the area source.
• Release Height [m]: Release height above ground. For example, a tank open to the atmosphere
would have a release height equal to the tank height.
• Radius [m]: Radius of the circular area source.
• Number of Vertices: Number of vertices (or sides) of the area source polygon. This parameter is
optional; if no value is entered, AERMOD will generate a polygon with 20 sides.
• Szinit [m]: Initial vertical dimension of the area source plume. For more passive area source
emissions, such as evaporation or wind erosion, the Szinit parameter is typically omitted, which is
equivalent to using a Szinit of 0 meters.
• Emission Rate [g/s/m2]: Pollutant emission rate. Note that the g/s emission rate must be divided
by the area of the area source to calculate the emission rate in units of g/s/m2.

3.5.3 OPENPIT Sources

The OPENPIT algorithm uses an effective area for modeling emissions from open pits, based on
meteorological conditions. AERMOD then treats the effective area as an area source to determine the
impact of emissions. The OPENPIT source parameter inputs are:
• X Coordinate [m]: Easting UTM for the southwest corner of the open pit.
• Y Coordinate [m]: Northing UTM for the southwest corner of the open pit.
• Release Height [m]: Average release height above the base of the pit. The release height cannot
exceed the effective depth of the pit, which is calculated by the model based on the length, width
and volume of the pit. A release height of 0 indicates emissions that are released from the base of
the pit. For example, an asphalt holding pit that is 1 meter in depth, filled with an average height
of 0.6 meters of asphalt, would have a release height of 0.6 m.

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 • Xinit [m]: Length of X side of the open pit (in the east-west direction if Angle is 0 degrees).
• Yinit [m]: Length of Y side of the open pit (in the north-south direction if Angle is 0 degrees).
• Pitvol [m3]: Volume of the open pit.
• Angle: Orientation angle for the rectangular area from North, measured positive in the clockwise
direction. If the Angle is not zero, the model will rotate the OPENPIT source clockwise around
the southwest corner.
• Emission Rate [g/s/m2]: Pollutant emission rate. Note that the g/s emission rate must be divided
by the area of the open pit source to calculate the emission rate in units of g/s/m2.

The only option for defining the open pit is a rectangle or square. The maximum length/width aspect
ratio for open pit sources is 10 to 1. Because the open pit algorithm generates an effective area for
modeling emissions from the pit, and the size, shape and location of the effective area is a function of
wind direction, an open pit cannot be divided into a series of smaller sources. If the aspect ratio is greater
than 10, the user should model the pit as a rectangular shape of equal area. See Section 3.3.2.7,
OPENPIT source inputs, of the AERMOD user’s guide for more information on the OPENPIT source
inputs.

3.5.4 VOLUME Sources

The VOLUME source type is used to model releases that occur over a three-dimensional volume.
Examples of volume sources include fugitive leaks, multiple vents, sloped conveyor belts, wipe cleaning
and general solvent usage. The VOLUME source parameters inputs are:
• X Coordinate [m]: Easting UTM at the center of the volume source.
• Y Coordinate [m]: Northing UTM at the center of the volume source.
• Release Height [m]: Release height above ground at the center of volume. For example, a
building with solvent releases from various open windows and doors should be modeled as a
volume source with a release height equal to half the building height.
• Length of Side [m]: Length of the side of the volume source. The volume source cannot be
rotated, and the X side is equal to the Y side (i.e., a square surface area).
• Syinit [m]: The initial lateral dimension is calculated by dividing the Length of Side in meters by
4.3. However, if a series of adjacent volume sources is used to represent a line source, the initial
lateral dimension is calculated as shown in Table 3.5.4-1. See Appendix C for additional
information on modeling adjacent volume sources.
• Szinit [m]: The initial vertical dimension is calculated differently for different types of volume
sources, explained in Table 3.5.4-2.
• Emission Rate [g/s]: Pollutant emission rate.

An irregularly-shaped volume can be represented by dividing the volume source into multiple smaller
volume sources. The user should create volume sources that cover approximately the same area where
the emissions actually occur.

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 Table 3.5.4-1: Summary of Suggested Procedures for Estimating Initial Lateral Dimensions
for Volume Sources
Procedure for Obtaining
Type of Source
Initial Lateral Dimension
Single Volume Source (Length of Side)
4.3
Line Source Represented by Adjacent (Length of Side)
Volume Sources 2 2.15
Line Source Represented by Separated (Center to Center Distance)
Volume Sources 3 2.15

Table 3.5.4-2: Summary of Suggested Procedures for Estimating Initial Vertical Dimensions
for Volume Sources
Procedure for Obtaining
Type of Source
Initial Vertical Dimension
Surface-Based Source (Vertical dimension of source in meters)
(he ~ 0) 2.15
Elevated Source (Building height in meters)
(he > 0) on or adjacent to a building 2.15
Elevated Source (Vertical dimension of source in meters)
(he > 0) NOT on or adjacent to a building 4.3

3.5.5 LINE Sources

The LINE source type is used to model releases from a variety of sources, such as horizontal conveyor
belts, rail lines and roadways. See Appendix C for more information on modeling roadways. AERMOD
allows a LINE source to be entered by specifying one line segment with a start point, end point and width.
AERMOD uses the same algorithms for LINE sources that are used for AREA sources, and will give
identical results for equivalent source parameter inputs. The LINE source parameter inputs are:
• X Coordinate [m]: Easting UTM for the start of the line source.
• Y Coordinate [m]: Northing UTM for the start of the line source.
• X End [m]: Easting UTM for the end of the line source.
• Y End [m]: Northing UTM for the end of the line source.
• Release Height [m]: Source release height above the ground.
• Width [m]: Width of the source (minimum width is 1 m).
• Szinit [m]: Initial vertical dimension of the line source.
• Emission Rate [g/s/m2]: Pollutant emission rate. Note that the g/s emission rate must be divided
by the area of the line source to calculate the emission rate in units of g/s/m2.

2
See Figure 1-8 (a) of USEPA’s User’s Guide for the Industrial Source Complex (ISC3) Dispersion Models,
Volume II – Description of Model Algorithms. Figure 1-8 (a) is reproduced in Appendix C of this document.
3
See Figure 1-8 (b) of USEPA’s User’s Guide for the Industrial Source Complex (ISC3) Dispersion Models,
Volume II – Description of Model Algorithms. Figure 1-8 (b) is reproduced in Appendix C of this document.

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UTM coordinates for the start and end points should reflect the center of the width of the line. The Szinit
parameter may be important for a line source that is meant to represent mechanically generated emission
sources, such as mobile sources. In these cases, the emissions may be turbulently mixed near the source
by the process that is generating the emissions, and therefore occupy some initial vertical depth. For
more passive line source emissions, such as a horizontal conveyor belt, the Szinit parameter is typically
omitted, which is equivalent to using a Szinit of 0 m.

3.6 Building Impacts

Buildings and other structures near a relatively short stack can have a substantial effect on plume
transport and dispersion, and on the resulting ground-level concentrations. Building downwash for point
sources that are within the area of influence of a building must be considered when running AERMOD.
A building is considered sufficiently close to a stack to cause wake effects when the distance between the
stack and the nearest part of the building is less than or equal to five times the lesser of the building height
or the projected building width (PBW), as described in Equation 3.6-1.
𝑫𝑫 ≤ 𝟓𝟓𝟓𝟓 Eq. 3.6-1
where: D = shortest distance from the exhaust stack to the building
L = lesser of the building height and projected building width (PBW)
PBW = maximum cross-sectional length of the building;
for rectangular buildings, PBW = �(𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙ℎ2 + 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤ℎ2 )

The PBW is the maximum length of a building that could affect air flow around and over the structure.
For more information on building downwash and PBW, see EPA’s Guideline for Determination of Good
Engineering Practice Stack Height (Technical Support Document For the Stack Height Regulations),
noted in the References section of this document.

AERMOD requires the user to input the UTM coordinates for all building corners and the height of each
building. For buildings with more than one height or roofline, the UTM coordinates and height are
required for each building tier.

3.7 Terrain
All sources, buildings and receptors are required to have a base elevation, which is affected by the terrain
of the site. Terrain elevations can have a large impact on the air dispersion modeling results. Elevation
data can be obtained from digital elevation map (DEM) files by running AERMAP in AERMOD.

Alternatively, if the site will be graded and post-grading elevations are known, those elevations should be
entered when defining the source parameters and building information in AERMOD. Do not import
source and building elevation data from the DEM file(s) when running AERMAP if graded elevations are
used. Furthermore, the AQIA report must clearly identify that graded elevations were used, and include a
spreadsheet with the graded elevations. The preferred format for submitting these graded elevations to
the District is the Lakes’ AERMOD View source file (*_Sources.xlsx) and the building file
(*_Buildings.xlsx) that are generated when the user exports the source data and the building data from
AERMOD View. If Lakes’ AERMOD View was not used for the AQIA, spreadsheets should be
submitted to the District that show the graded elevations for each source and building with the
corresponding Source IDs and Building IDs.

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3.8 Meteorological Data
District-processed AERMOD meteorological data should be used, and is available online at the District’s
Meteorological Data webpage, noted in the References section of this document, as well as in Table 3.8-1
below. All years of data should be used when running AERMOD. Please contact the District if you have
any questions about which data to use or if you wish to use alternative meteorological data. For approval
to use alternative meteorological data, submit a justification for the data use, including information
regarding representativeness and quality assurance, along with the meteorological data to the District for
review.

The PROFBASE parameter is used to specify the base elevation above mean sea level of the primary met
tower. The elevations of the Santa Barbara County sites are displayed in Table 3.8-1. All coordinates in
Table 3.8-1 are in the NAD83 datum.

Table 3.8-1: Meteorological Data Sets in Santa Barbara County

Latitude Longitude Elevation
Met Data Set Name Met Data Files
(degrees) (degrees) (m)
Carpinteria 34.403 -119.459 137.0 Carp12-16.zip
El Capitan 34.462 -120.026 42.0 ElCap12-16.zip
Ellwood 34.430 -119.911 20.0 Ellwood12-16.zip
Goleta 34.446 -119.828 14.0 Goleta12-16.zip
Las Flores Canyon 34.490 -120.047 184.0 LFC12-16.zip
Lompoc H Street 34.638 -120.457 41.0 Lompoc12-16.zip
Lompoc Watt Rd 34.781 -120.607 48.0 WattRd93-96.zip
Nojoqui Pass 34.527 -120.196 303.0 Nojoqui12-16.zip
Paradise Road 34.542 -119.791 371.0 Paradise12-16.zip
Santa Barbara Airport1 34.426 -119.842 4.0 SBA12-16Ustar.zip
SB National Guard 34.428 -119.691 20.0 SBNG12-16.zip
Santa Maria Airport1 34.899 -120.448 79.6 SMX12-16Ustar.zip
Santa Maria Broadway 34.949 -120.438 76.0 SMBroadway12-16.zip
UCSB West Campus 34.415 -119.879 9.0 UCSB12-16.zip
VAFB South 34.596 -120.631 104.0 VAFB12-16.zip
1
The Santa Barbara Airport and Santa Maria Airport meteorological data sets were processed using the U star
adjustment option (ADJ_U*). The ADJ_U* option was used for these data sets because they do not include
turbulence, or sigma-theta, measurements. AERMOD automatically detects that the meteorological data was
processed using the ADJ_U* option.

3.9 Receptors
The receptor network must provide adequate coverage to capture the maximum pollutant concentrations.
The receptor network shall include a Cartesian grid, property boundary receptors and Class I receptors (if
applicable). The flagpole height of all receptors shall be set to 0 meters.

3.9.1 Cartesian Receptor Grids

AERMOD can create grids of Cartesian receptors that are defined by an origin with receptor points in x
and y directions. The following grid spacing is required for most projects:
• 25-meter spacing on the property boundary

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 • 25-meter spacing from property boundary out to 200 meters
• 50-meter spacing from 200 meters to 500 meters
• 100-meter spacing from 500 meters to 2000 meters

If it appears that the grid receptors are not close enough to capture the maximum pollutant concentrations,
the District may require the AQIA to be rerun with a finer grid. For facilities with a large number of
emitting sources and a large property boundary, fine grid spacing will significantly impede the model run
time. It may be necessary to run the AQIA with a coarse grid to determine the areas of highest
concentration and then rerun the AQIA with finer grids in those areas. If this method is used, finer grids
shall be used for all areas with high concentrations, not just the single area with the highest concentration.
AERMOD allows for multiple grids to be included in one dispersion run.

3.9.2 Class I Receptors

If the project is in a Class I Impact Area 4, or if the District determines the project has the potential to
impact a Class I Area, the NSR increment analysis must include an evaluation of the Class I Area
impacts; therefore, the applicant must include receptors in the Class I Area in the model. Contact the
District to confirm whether or not a Class I Area increment analysis is required.

Class I Areas include national parks, national wilderness areas, and national monuments. These areas are
granted special air quality protections under Section 162(a) of the federal Clean Air Act. The only Class I
Area in Santa Barbara County is the San Rafael Wilderness in the northeastern section of the county. The
Class I Impact Area extends 10 kilometers from the wilderness in all directions, as shown in
Figure 3.9.2-1.

4
“Class I Impact Area” means all lands outside of a Class I Area but within 10 kilometers (6.2 miles) of the
boundary of a Class I Area, or other areas established by the Control Officer based on standard meteorological
techniques such as hourly wind roses, frequency distribution of atmospheric wind classes, morning and afternoon
mixing depths and any other meteorological or geographical considerations needed to establish the Class I Impact
Area.

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 Figure 3.9.2-1: Class I Impact Area

The District has generated Class I receptors 25 meters apart around the entire San Rafael Wilderness
boundary in UTM coordinates, in the NAD83 datum. The list of Class I receptors is available in Zone 10
and Zone 11, in a simple .xlsx format and in a .csv format compatible with Lakes’ AERMOD View.
Table 3.9.2-1 contains links to download the receptor lists. This information is also available online at
the District’s AQIA: Class I Area webpage, noted in the References section of this document.

Table 3.9.2-1: Class I Receptor Lists

Zone
Format
10 11
Excel spreadsheet Class_I_Receptors_Zone10.xlsx Class_I_Receptors_Zone11.xlsx
Lakes’ receptor file Class_I_Receptors_Zone10.csv Class_I_Receptors_Zone11.csv

4. Results
Once all the AERMOD runs are complete, the results should be compiled into tables for ease of review.
Explanations of how each concentration was determined from the AERMOD output files should be
included in the AQIA report.

4.1 Ambient Air Quality Standard Analysis

For an ambient air quality standard (AAQS) analysis, the reportable concentration for each pollutant and
averaging period modeled by AERMOD should be added to the background concentration for that

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pollutant and averaging period. This sum is then compared to the AAQS. The form, or reportable
concentration, for the standards that must be analyzed are shown in Table 4.1-1.

The highest modeled result (i.e., 1st Highest High) is not required to be compared to the NAAQS for all
averaging periods and pollutants. For example, the reportable concentration for the 24-hour averaging
period for PM2.5 is the 98th percentile, multi-year average. This means that the 8th Highest High can be
reported and compared to the NAAQS for PM2.5 for the 24-hour averaging period. California Ambient
Air Quality Standards (CAAQS) for CO, SO2 (1-hour and 24-hour), NO2, and particulate matter (PM10
and PM2.5), are values that are not to be exceeded. This means that the 1st Highest High is reported and
compared to the CAAQS. Because the form, or reportable concentration, of the CAAQS is different from
the NAAQS for 1-hour SO2 and 1-hour NO2, and the concentration for the NAAQS is lower than the
CAAQS, it is possible for the 1-hour SO2 or 1-hour NO2 to meet either one of the standards but exceed
the other. Therefore, SO2 and NO2 must be modeled for comparison to both the 1-hour CAAQS and the
1-hour NAAQS.

The NAAQS for PM2.5 is based on the annual mean, averaged over 3 years. The NAAQS for SO2 and
NO2 are based on the highest annual average from an individual year, rather than an average across the
years modeled.

For convenience, the modeler may choose to report the most conservative result, the highest
modeled concentration (i.e., 1st Highest High) for the specified averaging period. This option may be
preferable in situations with very low concentrations, as it will avoid the requirement of multiple runs for
the same pollutant and averaging period (e.g., 1 hour SO2 is run only once and the 1st Highest High is
compared to the lowest AAQS, 196 µg/m3). When this option is used, the result must be clearly
presented as the 1st Highest High, with language explaining that performing separate runs for the NAAQS
and CAAQS is not necessary due to the low concentration.

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 Table 4.1-1: Reporting Results for the AAQS Analysis

Averaging CAAQS NAAQS1 Form (Reportable

Pollutant Form Description
Period (µg/m3) (µg/m3) Concentration)
CAAQS: Not to be exceeded 1st Highest High
1-hour 655 196 NAAQS: 99th percentile of 1-hour
daily maximum concentrations, 4th Highest High2
multi-year average
SO2 NAAQS: Not to be exceeded
3-hour — 1,300 2nd Highest High
more than once per year
24-hour 105 — CAAQS: Not to be exceeded 1st Highest High
NAAQS: Annual average for
Annual — 80 1st Highest High
individual year
CAAQS: Not to be exceeded 1st Highest High
1-hour 339 188 NAAQS: 98th percentile of 1-hour
daily maximum concentrations, 8th Highest High3
NO2 multi-year average
CAAQS: Annual average for
Annual 57 NA 1st Highest High
individual year
1-hour 23,000 NA CAAQS: Not to be exceeded 1st Highest High
CO
8-hour 10,000 NA CAAQS: Not to be exceeded 1st Highest High
24-hour 50 NA CAAQS: Not to be exceeded 1st Highest High
PM10 CAAQS: Annual average for
Annual 20 — 1st Highest High
individual year
NAAQS: 98th percentile, multi-
24-hour — 35 8th Highest High4
year average
PM2.5
CAAQS: Annual average for
Annual 12 NA 1st Highest High
individual year
1
“NA” is shown if a lower or equivalent state standard exists for that pollutant and averaging period. “—” is shown
if no federal standard exists for that pollutant and averaging period.
2
For more information about the reportable concentration for the 1-hour SO2 NAAQS and method to obtain it, see
Section 3.2.3 of this document.
3
For more information about the reportable concentration for the 1-hour NO2 NAAQS and method to obtain it, see
Section 3.2.2 of this document.
4
For more information about the reportable concentration for the 24-hour PM2.5 NAAQS and method to obtain it,
see Section 3.2.4 of this document.

Santa Barbara County is currently in nonattainment status for PM10 on both an annual and 24-hour basis.
Because the background concentrations for annual PM10 and 24-hour PM10 are above the AAQS, all
projects emitting PM10 will result in a PM10 concentration in exceedance of the AAQS. The District has
determined that projects will not contribute significantly to an exceedance of an AAQS if the project’s
contribution is less than ten percent of the AAQS. Therefore, the District typically approves projects with
annual and 24-hour PM10 impacts less than ten percent of the AAQS.

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4.1.1 Background Concentration
The background concentrations of each pollutant in ambient air can be obtained by analyzing data from
sources such as CARB’s Air Quality Data Statistics, the District’s Annual Air Quality Reports, and the
EPA’s Air Data, all of which are noted in the References section of this document. The methods by
which the background concentrations were determined should be clearly explained and the sources should
be referenced in the AQIA report, with supporting documentation submitted to the District. The
background concentrations for different AAQS are not all determined in the same manner. Table 4.1.1-1
describes the appropriate methodology to determine the background concentration for each AAQS.
However, for convenience, the modeler may choose to use the more conservative method of reporting
the background concentration as the highest recorded concentration (i.e., 1st Highest High) for the
most recent three years of data for the specified averaging period.

If the EPA’s Air Data is used to determine the background concentrations, exceptional events5 may be
excluded from the data set. The pre-generated .csv data files available for download on the EPA’s Air
Data website contain a column that indicates whether exceptional events are included or excluded from
the data (or if there were no exceptional events during that year for a given pollutant).

Please note that although older EPA guidance recommended the use of the maximum 24-hour monitored
PM2.5 concentration, current guidance 6,7 recommends that the three-year average of 98th percentile
24-hour monitored PM2.5 concentrations be used to determine compliance with the NAAQS. However, as
previously mentioned in this section, the modeler may choose to use the more conservative method of
reporting the background concentration as the highest recorded concentration from the most recent three
years of data.

5
Exceptional events are unusual or naturally occurring events that can affect air quality but are not reasonably
controllable using techniques that tribal, state or local air agencies may implement; exceptional events may include
wildfires, high wind dust events, prescribed fires, stratospheric ozone intrusions, and volcanic and seismic activities.
More information about exceptional events may be found here: https://www.epa.gov/air-quality-analysis/treatment-
air-quality-data-influenced-exceptional-events-homepage-exceptional.
6
U.S. Environmental Protection Agency. Memorandum. May 20, 2014. Guidance for PM2.5 Permit Modeling.
https://www3.epa.gov/ttn/scram/guidance/guide/Guidance_for_PM25_Permit_Modeling.pdf
7
U.S. Environmental Protection Agency. Memorandum. February 10, 2020. DRAFT Guidance for Ozone and Fine
Particulate Matter Permit Modeling.
https://www3.epa.gov/ttn/scram/guidance/guide/Draft_Guidance_for_O3_PM25_Permit_Modeling.pdf

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 Table 4.1.1-1: Background Concentrations for the AAQS Analysis

Averaging
Pollutant Form Description Background Concentration
Period
Highest recorded hourly concentration
CAAQS: Not to be exceeded
from the most recent three years of data
1-hour NAAQS: 99th percentile of 1-hour Average of the 4th highest hourly
daily maximum concentrations, concentrations for the most recent three
multi-year average years of data

SO2 Maximum of the second highest recorded

NAAQS: Not to be exceeded
3-hour 3-hour concentration for the most recent
more than once per year
three years of data
Highest recorded daily concentration
24-hour CAAQS: Not to be exceeded
from the most recent three years of data
NAAQS: Annual average for Maximum average annual concentration
Annual
individual year from the most recent three years of data
Highest recorded hourly concentration
CAAQS: Not to be exceeded
from the most recent three years of data
1-hour NAAQS: 98th percentile of 1-hour Average of the 8th highest hourly
NO2 daily maximum concentrations, concentrations for the most recent three
multi-year average years of data
CAAQS: Annual average for Maximum average annual concentration
Annual
individual year from the most recent three years of data
Highest recorded hourly concentration
1-hour CAAQS: Not to be exceeded
from the most recent three years of data
CO
Highest recorded 8-hour concentration
8-hour CAAQS: Not to be exceeded
from the most recent three years of data
Highest recorded daily concentration
24-hour CAAQS: Not to be exceeded
from the most recent three years of data
PM10
CAAQS: Annual average for Maximum average annual concentration
Annual
individual year from the most recent three years of data
Average of the 8th highest daily
NAAQS: 98th percentile, multi-
24-hour concentrations for the most recent three
year average
PM2.5 years of data
CAAQS: Annual average for Maximum average annual concentration
Annual
individual year from the most recent three years of data

4.2 Increment Analysis

The increment analysis is only required for the District’s NSR permitting program, not the CEQA
process. The reportable concentration modeled by AERMOD for each pollutant and averaging period in
the Class I and Class II Impact Areas should be compared to the maximum allowable increase or
“increment” threshold for the corresponding class. The forms or reportable concentrations for the
increment analysis, with the applicable increment threshold, are described in Table 4.2-1. For increments

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based on EPA’s current thresholds, the 2nd Highest High may be reported for short term averaging
periods 8. For all other increments, the 1st Highest High must be reported.

The applicant may consume the full increment range for 1-hour NO2, 3-hour ROC and 24-hour PM10;
mitigation fees for consuming part or all of the increment are required and discussed in Section F.3 of the
District’s Rule 805, noted in the References section of this document.

Table 4.2-1: Reporting Results for the Increment Analysis

Class I Class II
Averaging Form (Reportable
Pollutant Increment Increment Form Description
Period Concentration)
(µg/m3) (µg/m3)
24-hour 10 37 Not to be exceeded 1st Highest High
TSP Annual average for
Annual1 5 19 1st Highest High
individual year
Not to be exceeded more
3-hour 25 512 2nd Highest High
than once per year
SO2 Not to be exceeded more
24-hour 5 91 2nd Highest High
than once per year
Annual average for
Annual 2 20 1st Highest High
individual year
1-hour 10 100-188 Not to be exceeded 1st Highest High
NO2
Annual 2.5 25 Not to be exceeded 1st Highest High
1-hour 800 10,000 Not to be exceeded 1st Highest High
CO
8-hour 200 2,500 Not to be exceeded 1st Highest High
ROC 3-hour 3 40-160 Not to be exceeded 1st Highest High
Not to be exceeded more
24-hour 8 12-30 2nd Highest High
than once per year
PM10
Annual average for
Annual 4 17 1st Highest High
individual year
Not to be exceeded more
24-hour 2 9 2nd Highest High
than once per year
PM2.5
Annual average for
Annual 1 4 1st Highest High
individual year
1
The form of the annual increment threshold for TSP is the “Annual Geometric Mean.” AERMOD calculates the
annual arithmetic mean, not the annual geometric mean. However, the District will accept the annual arithmetic
mean as an approximation of the annual geometric mean.

5. Air Quality Impact Assessment Report

The applicant is required to perform the AQIA and submit the AQIA report and electronic files for the
District’s review. The District will assess fees for the AQIA review on the cost reimbursement basis
specified in Section I.C of the District’s Rule 210.

8
Section 163(a) of the Clean Air Act stipulates that EPA’s short-term increments “can be exceeded during one such
period per year”.

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The required elements of the AQIA report are discussed in Sections 5.1 through 5.7 below.

5.1 Facility Information

Report the following information regarding the facility and its surroundings:
• Facility name
• Stationary source identification number (SSID)
• Location (street address and UTM coordinates, including datum)
• Description of facility operations and a list identifying emitted substances, including a table of the
emissions for the modeled pollutants and averaging periods

5.2 Source and Emission Inventory Information

Report the following information for each emission source in table format:
• Source identification number
• Source name
• Source type (point, area, open pit, volume, line)
• Device identification number(s) for any devices emitting at this source (use District device
identification numbers when available)
• Source UTM coordinates
• Source parameters

The description and operating schedule for each device should be reported in table format including the
following information:
• Device name and identification number
• Number of operating hours per day and per year, including which hours the device operates in a
24-hour day
• Number of operating days per week, including which days the device operates in a 7-day week
• Number of operating days or weeks per year
• Source identification number(s) for the AERMOD sources where emissions are released

5.3 Emission Quantification

Report the following information for each device in table format:
• Emission control equipment and efficiency by source and by pollutant, if efficiency varies by
pollutant
• Emission rates for each pollutant, grouped by source, including the following information:
o Device name and identification number
o Pollutant name
o Emission factors for each pollutant

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 o Emissions in g/s for each modeled averaging period, including explanations of the
assumptions used for each averaging period

5.4 Air Dispersion Information

The following information must be identified:
• Name and version number of the software used to run AERMOD
• Selected control options
• Urban/rural dispersion (including the values entered for roughness length and population, if the
urban option was selected)
• Building information (UTM coordinates and tier heights)
• Terrain information (which DEM files were used, graded elevations)
• Meteorological data (which station and years were used in the air dispersion model)
• Receptor placement discussion and justification:
o Modeling domain
o Spacing of receptor grid(s)
o Property boundary receptor spacing
o Location (UTM coordinates) of any Class I Impact Area receptors

5.5 Summary of Results

5.5.1 Results of the AAQS Analysis

Present the AAQS results in table format, including the following information:
• Reportable concentrations modeled by AERMOD for the project for each appropriate pollutant
and averaging period reported according to Table 4.1-1 of this document
• Receptor numbers corresponding to where the reported concentrations occur
• Location (UTM coordinates) of receptors where the reported concentrations occur (may be
included in separate table)
• Background concentrations for each appropriate pollutant and averaging period
• Sum of the background concentration and modeled project impacts
• AAQS for each appropriate pollutant and averaging period

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An example AAQS results table is shown below (Table 5.5.1-1).

Table 5.5.1-1: Example AAQS Modeling Results

Modeled Ambient Total

Averaging Receptor AAQS Percent of
Pollutant Impact Conc.1 Background Conc.
Period Number (µg/m3) AAQS
(µg/m3) (µg/m3) (µg/m3)
1-hour 565 24.8 16.3 41.1 655 6.3%
1-hour2 567 20.4 13.1 33.5 196 17%
SO2 3-hour3 1121 13.1 8.0 21.1 1,300 1.6%
24-hour 2356 1.97 5.2 7.2 105 6.9%
Annual 2725 0.29 2.6 2.9 80 3.6%
1-hour 743 92.7 98.0 190.7 339 56%
NO24 1-hour5 689 81.5 92.1 173.6 188 92%
Annual 2725 1.84 14.4 16.2 57 28%
1-hour 784 443.5 3565 4009 23,000 17%
CO
8-hour 653 212.9 1311 1524 10,000 15%
24-hour 845 7.86 76.2 84.0 50 168%
PM10
Annual 365 1.76 24.2 26.0 20 130%
24-hour6 448 1.71 17.3 19.0 35 54%
PM2.5
Annual 365 0.27 7.0 7.3 12 61%
1
Unless otherwise noted, all values reported are the 1st Highest High.
2
This 1-hour SO2 concentration is reported as the 4th Highest High (i.e., the 99th percentile, five-year average) for the
NAAQS analysis.
3
The 3-hour SO2 concentration is reported as the 2nd Highest High (i.e., standard shall not be exceeded more than once
per year).
4
The 1-hour and annual NO2 concentrations were determined using the ARM2.
5
This 1-hour NO2 concentration is reported as the 8th Highest High (i.e., the 98th percentile, five-year average) for the
NAAQS analysis.
6
The 24-hour PM2.5 concentration is reported as the 8th Highest High (i.e., the 98th percentile, five-year average).

5.5.2 Results of the Increment Analysis

Present the increment results in table format, including the following information:
• Reportable concentrations modeled by AERMOD for the project for each appropriate pollutant
and averaging period reported according to Table 4.2-1 of this document
• If required, the reportable concentrations modeled by AERMOD for the project for each
appropriate pollutant and averaging period in the Class I Impact Area
• Receptor numbers corresponding to where the reported concentrations occur
• Location (UTM coordinates) of receptors where the reported concentrations occur (may be
included in separate table)
• Increment threshold for each appropriate pollutant and averaging period

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An example increment analysis results table is shown below (Table 5.5.2-1).

Table 5.5.2-1: Example Increment Analysis Modeling Results for Class II Impacts

Modeled Impact Class II Percent of

Averaging Receptor
Pollutant Concentration1 Increment Maximum
Period Number
(µg/m3) (µg/m3) Increment
24-hour 845 7.86 37 21%
TSP
Annual 365 1.76 19 9%
3-hour2 1121 13.1 512 3%
SO2 24-hour2 3546 1.23 91 1%
Annual 2725 0.29 20 1%
1-hour 853 98.1 100-1884 52%
NO23
Annual 2725 1.84 25 7%
1-hour 784 443.5 10,000 4%
CO
8-hour 653 212.9 2,500 9%
ROC 3-hour 986 152.3 40-1604 95%
24-hour2 778 6.8 12-304 23%
PM10
Annual 365 1.76 17 10%
24-hour2 778 1.93 9 21%
PM2.5
Annual 365 0.27 4 7%
1
Unless otherwise noted, all values reported are the 1st Highest High.
2
The modeled concentration reported is the 2nd Highest High.
3
The 1-hour and annual NO2 concentrations were determined using the ARM2.
4
The applicant may consume the full increment range pursuant to the requirements of Rule 805, Section F.3.

5.6 Air Quality Impact Driver Tables

For any AAQS or increment that is exceeded or within five percent of the standard/threshold, provide a
table of the air quality impacts for each pollutant and averaging period from each source included in the
model. If there are many sources included in the model, include those sources that contribute at least five
percent of the air quality impacts in the table. This will allow the District to identify which devices are
contributing most to the air quality impacts. For each table, include a statement indicating which of the
devices or operations contributes most to the air quality impacts.

5.7 Required Files

The following files are required to be submitted electronically:
• AQIA report (*.pdf)
• Emission calculations spreadsheet (*.xlsx)
• Surface meteorological data file (*.sfc)
• Profile meteorological data file (*.pfl)
• Digital elevation map files (*.dem)
• AERMAP receptor file
• AERMAP source file

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 • BPIP input file
• BPIP summary file
• BPIP output file
• AERMOD input file for each pollutant/averaging period
• AERMOD output file for each pollutant/averaging period
• AERMOD error file
• Plotfiles for each source group (*.plt)

If the AQIA or AQIA report fail to comply with these guidelines, the AQIA and AQIA report will be
returned, with District comments, to the applicant for revision.

6. References
• California Air Resources Board. Accessed June 29, 2020. ADAM: Air Quality Data Statistics.
https://www.arb.ca.gov/adam/index.html.
• California Air Resources Board. Accessed June 29, 2020. California Ambient Air Quality
Standards. https://ww2.arb.ca.gov/resources/california-ambient-air-quality-standards.
• California Air Resources Board. Accessed June 29, 2020. National Ambient Air Quality
Standards. https://ww2.arb.ca.gov/resources/national-ambient-air-quality-standards.
• Lakes Environmental. 1995-2020. AERMOD ViewTM.
• Providence Oris. 2020. BEEST Suite.
• Santa Barbara County Air Pollution Control District. March 17, 2005. Rule 210. Fees.
https://www.ourair.org/wp-content/uploads/rule210.pdf.
• Santa Barbara County Air Pollution Control District. August 25, 2016. Rule 802. New Source
Review. https://www.ourair.org/wp-content/uploads/rule802.pdf.
• Santa Barbara County Air Pollution Control District. August 25, 2016. Rule 805. Air Quality
Impact Analysis, Modeling, Monitoring, and Air Quality Increment Consumption.
https://www.ourair.org/wp-content/uploads/rule805.pdf.
• Santa Barbara County Air Pollution Control District. 2020. AQIA: Class I Area.
https://www.ourair.org/aqia-class-i-area/.
• Santa Barbara County Air Pollution Control District. 2020. Annual Air Quality Report.
https://www.ourair.org/sbc/annual-air-quality-report/.
• Santa Barbara County Air Pollution Control District. 2020. Meteorological Data.
http://www.ourair.org/metdata/.
• U.S. Environmental Protection Agency. June 1985. Guideline for Determination of Good
Engineering Practice Stack Height (Technical Support Document For the Stack Height
Regulations). https://www3.epa.gov/scram001/guidance/guide/gep.pdf.
• U.S. Environmental Protection Agency. November 9, 2005. 40 CFR Part 51 Appendix W. Federal
Register. https://www3.epa.gov/ttn/scram/guidance/guide/appw_05.pdf.

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 • U.S. Environmental Protection Agency. Memorandum. August 23, 2010. Applicability of
Appendix W Modeling Guidance for the 1-hour SO2 National Ambient Air Quality Standard.
https://www3.epa.gov/ttn/scram/guidance/clarification/ClarificationMemo_AppendixW_Hourly-
SO2-NAAQS_FINAL_08-23-2010.pdf.
• U.S. Environmental Protection Agency. Memorandum. March 1, 2011. Additional Clarification
Regarding Application of Appendix W Modeling Guidance for the 1-hour NO2 National Ambient
Air Quality Standard.
https://www3.epa.gov/scram001/guidance/clarification/Additional_Clarifications_AppendixW_H
ourly-NO2-NAAQS_FINAL_03-01-2011.pdf.
• U.S. Environmental Protection Agency. Memorandum. May 20, 2014. Guidance for PM2.5 Permit
Modeling.
https://www3.epa.gov/ttn/scram/guidance/guide/Guidance_for_PM25_Permit_Modeling.pdf.
• U.S. Environmental Protection Agency. July 2015. Technical support document (TSD) for NO2-
related AERMOD modifications.
https://www3.epa.gov/scram001/11thmodconf/AERMOD_NO2_changes_TSD.pdf.
• U.S. Environmental Protection Agency. August 2019. User’s Guide for the AMS/EPA Regulatory
Model (AERMOD). https://www3.epa.gov/ttn/scram/models/aermod/aermod_userguide.pdf.
• U.S. Environmental Protection Agency. August 2019. AERMOD Implementation Guide.
https://www3.epa.gov/ttn/scram/models/aermod/aermod_implementation_guide.pdf.
• U.S. Environmental Protection Agency. August 7, 2019. Treatment of Air Quality Data
Influenced by Exception Events (Homepage for Exceptional Events). https://www.epa.gov/air-
quality-analysis/treatment-air-quality-data-influenced-exceptional-events-homepage-exceptional.
• U.S. Environmental Protection Agency. Memorandum. February 10, 2020. DRAFT Guidance for
Ozone and Fine Particulate Matter Permit Modeling.
https://www3.epa.gov/ttn/scram/guidance/guide/Draft_Guidance_for_O3_PM25_Permit_Modeli
ng.pdf.
• U.S. Environmental Protection Agency. April 30, 2020. Air Quality Dispersion Modeling –
Preferred and Recommended Models. https://www.epa.gov/scram/air-quality-dispersion-
modeling-preferred-and-recommended-models.
• U.S. Environmental Protection Agency. May 28, 2020. Air Data: Air Quality Data Collected at
Outdoor Monitors Across the US. https://www.epa.gov/outdoor-air-quality-data.
• U.S. Environmental Protection Agency. June 4, 2020. Clean Air Act Permit Modeling Guidance.
https://www.epa.gov/scram/clean-air-act-permit-modeling-guidance.
• U.S. Environmental Protection Agency. June 5, 2020. Air Quality Analysis: Region 9 Federal
Class 1 Areas. https://www3.epa.gov/region9/air/maps/r9_clss1.html.

7. Contacts
For questions about the District’s requirements for modeling, contact the District at:
phone: 805-961-8800
email: engr@sbcapcd.org
For questions about AERMOD, contact EPA’s Region IX Modeling Contact, Carol Bohnenkamp, at:
phone: 415-947-4130
email: bohnenkamp.carol@epa.gov

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Appendix A – Variable Emissions Modeling
During some air quality studies, modelers may encounter certain emitting scenarios that require the use of
variable emissions modeling. This appendix outlines modeling techniques to account for special
operating schedules.

AERMOD includes options for modeling source emissions that fluctuate over time. With the variable
emissions option, the modeler can select the hours of operation and the emission rate for each individual
source. Emission variations can be characterized across many different periods, including hourly, daily,
monthly and seasonally. If variable emissions are used, the applicant must submit documentation with
the AQIA that justifies using that variable emissions scenario. The District may require permit conditions
to enforce the operating hours, days, months, etc. selected in the variable emissions scenario.

A.1 Non-Continuous Emissions

Emissions can be modeled with varying rates over time within AERMOD by applying factors to different
time periods. For example, for a source that is non-continuous, a factor of 0 is entered for the periods
when the source is not operating or is inactive, and a factor of 1 is entered for the periods when the source
is operating. Model inputs for variable emissions rates can include the following time periods:
• Seasonally
• Monthly
• Hour of day
• Wind speed
• Season and hour of day
• Hour of day, day of week
• Hour of day, 7 days of the week
• Season, hour of day, day of week
• Season, hour of day, 7 days of the week
• Month, hour of day, day of week
• Month, hour of day, 7 days of the week

A.2 Plant Shutdowns and Start-Ups

Plant start-ups and shutdowns can occur periodically due to maintenance or designated vacation periods.
The shutdown and subsequent startup processes impact emissions over the related time periods. As an
example, process upsets in the combustion units or air pollution control system can also impact
emissions; these upsets can often result in the release of uncontrolled emissions through the emissions
sources. As a result, over short periods of time, upset emissions are often expected to be greater than
normal source emissions 1. AERMOD can account for these differences in emission rates by using
variable emission factors.

1
EPA - Office of Solid Waste and Emergency Response, July 1998. Human Health Risk Assessment Protocol for
Hazardous Waste Combustion Facilities. EPA530-D-98-001A. U. S. Environmental Protection Agency, Research
Triangle Park, NC.

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Example Variable Emissions Scenario: A turbine operates from 6AM to 8PM (1 hour for startup, 1 hour
for shutdown, and 12 hours of normal operation) every day. The startup/shutdown emissions are twice
that of normal operating emissions. The emission rate during normal operation should be entered in g/s in
the source parameters window in AERMOD. The emission rate factors that reflect this operating
schedule should be entered in the variable emissions scenario in AERMOD as shown in Table A.2-1.

It is important to note that the hours of the day displayed in AERMOD correspond to the hour ending at
the time displayed. Therefore, hour 7 corresponds to the hour from 6AM to 7AM, and hour 20
corresponds to the hour from 7PM to 8PM.

Table A.2-1: Example Variable Emission Scenario (Hour of Day)

Emission Rate Factor Emission Rate Factor

Hour of Day Hour of Day
by Hour by Hour

1 0 13 1
2 0 14 1
3 0 15 1
4 0 16 1
5 0 17 1
6 0 18 1
7 2 19 1
8 1 20 2
9 1 21 0
10 1 22 0
11 1 23 0
12 1 24 0

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Appendix B – Modeling Specific Source Types
This appendix will be updated with additional source types in the future.

B.1 Liquid Storage Tanks

Storage tanks are generally of two types—fixed roof tanks and floating roof tanks. In the case of fixed
roof tanks, most of the pollutant emissions escape from a vent, with some additional contribution from
hatches and other fittings. In the case of floating roof tanks, most of the pollutant emissions escape
through the seals between the roof and the wall and between the deck and the wall, with some additional
emissions from fittings, such as ports and hatches.

Approaches for modeling emission impacts from various types of storage tanks are outlined in Sections
B.1.1 and B.1.2 below.

B.1.1 Fixed Roof Tanks

Model a fixed roof tank as a point source (i.e., a stack). The point source location and release height
should represent the tank vent, which is usually in the center of the tank. The tank should also be
represented as a building for downwash modeling. Table B.1.1-1 shows the values that should be entered
for the velocity, diameter and temperature.

Table B.1.1-1: Stack Parameters for Modeling Tanks

Velocity Diameter Temperature
Near zero, Nero zero, Ambient – a value of 0 prompts the
i.e., 0.001 m/s i.e., 0.001 m model to use the ambient temperature

There is virtually no plume rise from tanks. Therefore, the stack parameters for the stack gas exit velocity
and stack diameter should be set to near zero for the stacks representing the emissions. In addition, stack
temperature should be set equal to the ambient temperature. This can be accomplished in AERMOD by
inputting a value of 0 for the stack gas temperature.

Note that it is very important for the diameter to be at or near zero. With low exit velocities and larger
diameters, stack tip downwash will be calculated. A very small stack diameter effectively eliminates the
stack tip downwash. Because all downwash effects are being modeled with the building downwash
algorithm, the additional stack tip downwash calculations would be inappropriate.

B.1.2 Floating Roof Tanks

Model a floating roof tank as an area source. The area source inputs should represent the diameter of the
tank and the height of the tank. The tank should also be represented as a building for downwash
modeling if there are nearby point sources that may be affected.

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Appendix C – Modeling Emissions from Roadways
Roadways may be modeled as LINE sources, RLINE sources, a series of VOLUME sources, or a series of
AREA sources. LINE sources are recommended for modeling vehicle exhaust emissions in urban areas
and in rural areas where the elevation may have significant impacts on the dispersion results. The RLINE
source may be used to model vehicle exhaust emissions in rural areas with minimal elevation changes.
Adjacent VOLUME sources are recommended for modeling fugitive dust from haul roads.

Groups of idling vehicles may also be modeled as one or more VOLUME sources. In those cases, the
initial dimensions of the source, dispersion coefficients, and release heights should be calculated
assuming that the vehicles themselves are inducing no turbulence. Source characterization should be
based on the type of vehicles idling; e.g., if the vehicles idling are primarily heavy-duty trucks, then the
release height would be 4 meters. Furthermore, sources should be placed in the location(s) where the
majority of emissions occur. For example, if buses enter and exit a bus terminal from a single driveway,
the bus exhaust emissions should be modeled using one or more VOLUME sources at the location of that
driveway, rather than spreading the emissions across the entire terminal yard.

C.1 Modeling Roadways with LINE Sources

AERMOD can represent rectangular area sources using the LINE or AREA keywords. The three area
source types and the LINE source type use the same numerical integration algorithm for estimating
impacts from area sources. These are merely different options for specifying the shape of the area source.
The LINE source type utilizes the same routines as the AREA source type and will give identical results
for equivalent source inputs.

Sources that may be modeled as LINE sources may include roadways and areas within which emissions
occur relatively evenly. USEPA recommends that the LINE source keyword be used for modeling
roadway sources as it greatly simplifies defining the physical location and orientation of sources. The
LINE source type option allows users to specify line-type sources based on a start-point and end-point of
the line and the width of the line.

The LINE source parameter inputs are:

• Emission Rate [g/s]: Pollutant emission rate.
• UTM coordinates of midpoint of the start and end of the lines (X1,Y1; X2,Y2) [m].
• Width [m]: Width of the source; e.g., the width of a lane or multiple lanes, depending on how the
source is defined.
• Szinit [m]: Initial vertical dimension coefficient. Default: 1.2 m for light-duty vehicles; 3.2 m for
heavy-duty vehicles.
• Release Height [m]: Release height above the ground. Default: 1.3 m for light-duty vehicles;
3.4 m for heavy-duty vehicles.

The District’s recommended method for calculating LINE source modeling parameters is described in
Sections C.1.1 through C.1.3 below.

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C.1.1 Determining Width for LINE Sources
To estimate the width of the LINE source for a roadway, use one of the following options:
1. The width of the traveled way, typically 3.7 m (12 ft) per lane for a high-speed, high volume
roadway and 3.3 m (11 ft) per lane for an arterial/collector; or
2. The width of the traveled way (all travel lanes) + 6 meters.

C.1.2 Determining Szinit for LINE Sources

To account for the effects of vehicle-induced turbulence, assume the Top of Plume Height is 1.7 times
the average vehicle height. For light-duty vehicles, this is about 2.6 meters, using an average vehicle
height of 1.53 meters (5.0 feet). For heavy-duty vehicles, this is about 6.8 meters, using an average
vehicle height of 4.0 meters (13.1 feet). Since most roadways will experience a combination of light-duty
and heavy-duty traffic, the Top of Plume Height should be a combination of their respective values.
There are two options available to estimate the Top of Plume Height:
1. Estimate the Top of Plume Height using an emissions-weighted average 1. For example, if
light-duty and heavy-duty vehicles contribute 40 percent and 60 percent of the emissions of a
given volume source, respectively, the Top of Plume Height would be calculated as:
(0.4 * 2.6) + (0.6 * 6.8) = 5.1 meters.
2. Alternatively, the Top of Plume Height may be estimated using a traffic volume weighted
approach based on light-duty and heavy-duty vehicle fractions.

The initial vertical dimension coefficient, Szinit, is then estimated by dividing the Top of Plume
Height by 2.15. For typical light-duty vehicles, this corresponds to a Szinit of 1.2 meters. For typical
heavy-duty vehicles, the value of Szinit is 3.2 meters.

C.1.3 Determining Release Height for LINE Sources

The release height, which is the height at which wind effectively begins to affect the plume, may be
estimated as the midpoint of the Top of Plume Height. In other words, the release height is the Top of
Plume Height multiplied by 0.5. As noted above, most roadways will experience a combination of
light-duty and heavy-duty traffic. For each roadway source, the release height should be based on the
same Top of Plume Height used for calculating its Szinit, as described above. This value is 1.3 m for
light-duty vehicles, and it is 3.4 m for heavy-duty vehicles.

An alternate method to determine source parameters that vary with different fractions of light-duty and
heavy-duty traffic is to create two overlapping versions of each roadway source, corresponding to either
light-duty or heavy-duty traffic. These two sources would be superimposed in the same space, but would
have emission rates, initial vertical dimensions and release heights that are specific to light-duty or heavy-
duty vehicles.

C.2 Modeling Roadways with RLINE Sources

The AERMOD RLINE source algorithm is used to model near-surface releases from mobile sources and
can be used to represent a travelled roadway with either single or multiple lanes of traffic. The AERMOD
model simulates mobile source emissions using Romberg numerical integration of POINT sources, with
the number of points included in the integration determined by error analysis.

1
If multiple pollutants are being modeled and the emission factors vary significantly for different vehicle types, then
determine the Top of Plume Height based on the traffic volume weighted approach.

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Beginning with version 19191, use of the RLINE source type requires the use of the non-regulatory
BETA flag for the Control pathway MODELOPT keyword. As the BETA flag is required for RLINE, the
RLINE source type is currently non-regulatory and cannot be used with the DFAULT option. In
addition, the FLAT MODELOPT flag is also required if any RLINE sources are included in the
AERMOD run. Note that FLAT and ELEV may be specified in the same model run to allow specifying
the non-regulatory FLAT terrain option on a source-by-source basis. If FLAT and ELEV are used, Zs
(optional elevation of the source above sea-level) for all RLINE sources needs to be set =0.0 or =’FLAT’.
As RLINE was formulated as a flat terrain model, receptor flagpole heights are used as receptor heights,
while elevation and hill heights are currently ignored. RLINE should not be used in locations with severe
elevation changes which are expected to impact the modeled concentration (e.g., large elevation
difference between roadway and receptor).

The URBAN option applied to the RLINE source type is an ALPHA feature and shall not be used in
Santa Barbara County at this time.

The RLINE source parameter inputs are:

• Emission Rate [g/s]: Pollutant emission rate.
• Width [m]: Width of the source; e.g., the width of a lane or multiple lanes, depending on how the
source is defined.
• Szinit [m]: Initial vertical dimension coefficient. Default: 1.2 m for light-duty vehicles; 3.2 m for
heavy-duty vehicles.
• Release Height [m]: Release height above the ground. Default: 1.3 m for light-duty vehicles;
3.4 m for heavy-duty vehicles.

The District’s recommended method for calculating RLINE source modeling parameters is described in
Sections C.2.1 through C.2.3 below.

C.2.1 Determining Width for RLINE Sources

To estimate the width of the RLINE source for a roadway, use one of the following options:
1. The width of the traveled way, typically 3.7 m (12 ft) per lane for a high-speed, high volume
roadway and 3.3 m (11 ft) per lane for an arterial/collector; or
2. The width of the traveled way (all travel lanes) + 6 meters.

C.2.2 Determining Szinit for RLINE Sources

To account for the effects of vehicle-induced turbulence, assume the Top of Plume Height is 1.7 times
the average vehicle height. For light-duty vehicles, this is about 2.6 meters, using an average vehicle
height of 1.53 meters (5.0 feet). For heavy-duty vehicles, this is about 6.8 meters, using an average
vehicle height of 4.0 meters (13.1 feet). Since most roadways will experience a combination of light-duty
and heavy-duty traffic, the Top of Plume Height should be a combination of their respective values.
There are two options available to estimate the Top of Plume Height:
1. Estimate the Top of Plume Height using an emissions-weighted average 2. For example, if light-
duty and heavy-duty vehicles contribute 40 percent and 60 percent of the emissions of a given

2
If multiple pollutants are being modeled and the emission factors vary significantly for different vehicle types, then
determine the Top of Plume Height based on the traffic volume weighted approach.

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 volume source, respectively, the Top of Plume Height would be calculated as:
(0.4 * 2.6) + (0.6 * 6.8) = 5.1 meters.
2. Alternatively, the Top of Plume Height may be estimated using a traffic volume weighted
approach based on light-duty and heavy-duty vehicle fractions.

The initial vertical dimension coefficient, Szinit, is then estimated by dividing the Top of Plume
Height by 2.15. For typical light-duty vehicles, this corresponds to a Szinit of 1.2 meters. For typical
heavy-duty vehicles, the value of Szinit is 3.2 meters.

C.2.3 Determining Release Height for RLINE Sources

The release height, which is the height at which wind effectively begins to affect the plume, may be
estimated as the midpoint of the Top of Plume Height. In other words, the release height is the Top of
Plume Height multiplied by 0.5. As noted above, most roadways will experience a combination of
light-duty and heavy-duty traffic. For each roadway source, the release height should be based on the
same Top of Plume Height used for calculating its Szinit, as described above. This value is 1.3 m for
light-duty vehicles, and it is 3.4 m for heavy-duty vehicles.

An alternate method to determine source parameters that vary with different fractions of light-duty and
heavy-duty traffic is to create two overlapping versions of each roadway source, corresponding to either
light-duty or heavy-duty traffic. These two sources would be superimposed in the same space, but would
have emission rates, initial vertical dimensions and release heights that are specific to light-duty or heavy-
duty vehicles.

C.3 Modeling Roadways with VOLUME Sources

Another option for modeling roadways is to use VOLUME sources. However, when modeling highways
and intersections, LINE sources may be easier to characterize than VOLUME sources. Furthermore, the
VOLUME source type requires significantly longer computational time compared to the LINE or RLINE
source types, as more sources are required to simulate the same distance.

The VOLUME source algorithms are applicable to line sources with some initial plume depth, such haul
roads, areas designated for truck or bus queuing or idling, driveways and pass-throughs in transit or
freight terminals, and locomotive emissions. USEPA recommends modeling fugitive dust from haul
roads as adjacent VOLUME sources, unless there are receptors located within the volume source
exclusion area, which is further explained in Section C.3.3.

The goal of using VOLUME sources to represent a roadway is to create a uniform emissions
characterization. Ensure that VOLUME sources are not spaced too widely along the roadway. Adjacent
VOLUME sources should overlap and the distance between the center of one VOLUME source to the
next should be equal to the width of each source, as described in the AERMOD user’s guide and
represented in Figure 1-8(a) of USEPA’s September 1995 User’s Guide for the Industrial Source
Complex (ISC3) Dispersion Models, Volume II – Description of Model Algorithms (and reproduced on the
following page). Any other approximation of roadways with VOLUME sources will result in nearby
receptors being over or under-estimated depending on their proximity to the center of the volume source.

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 Figure 1-8 Reproduced from Section 1.2.2 of USEPA’s September 1995 User’s Guide for the Industrial
Source Complex (ISC3) Dispersion Models, Volume II – Description of Model Algorithms.

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The VOLUME source parameter inputs are:
• Emission Rate [g/s]: Pollutant emission rate.
• X Coordinate [m]: Easting UTM at the center of the volume source.
• Y Coordinate [m]: Northing UTM at the center of the volume source.
• Syinit [m]: Initial lateral dimension of the volume.
• Szinit [m]: Initial vertical dimension of the volume.
• Release Height [m]: Release height above ground at the center of volume.

The District’s recommended method for calculating VOLUME source modeling parameters is described
in Sections C.3.1 through C.3.3 below.

C.3.1 Determining Syinit for VOLUME Sources

USEPA recommends that Syinit is calculated by dividing the Plume Width by 2.15, where the Plume
Width is calculated as:
• Plume Width for Single Lane Roadways = Vehicle Width + 6m;
• Plume Width for Two-Lane Roadways = Road Width + 6m for two-lane roadways.
Two-lane roadways are for cases with heavy two-way traffic where the combined plume
needs to be approximated; not typically used for haul roads.

C.3.2 Determining Szinit for VOLUME Sources

To account for the effects of vehicle-induced turbulence, assume the Top of Plume Height is 1.7 times
the average vehicle height. For light-duty vehicles, this is about 2.6 meters, using an average vehicle
height of 1.53 meters (5.0 feet). For heavy-duty vehicles, this is about 6.8 meters, using an average
vehicle height of 4.0 meters (13.1 feet). Since most roadways will experience a combination of light-duty
and heavy-duty traffic, the Top of Plume Height should be a combination of their respective values.
There are two options available to estimate the Top of Plume Height:
1. Estimate the Top of Plume Height using an emissions-weighted average 3. For example, if light-
duty and heavy-duty vehicles contribute 40 percent and 60 percent of the emissions of a given
volume source, respectively, the Top of Plume Height would be calculated as:
(0.4 * 2.6) + (0.6 * 6.8) = 5.1 meters.
2. Alternatively, the Top of Plume Height may be estimated using a traffic volume weighted
approach based on light-duty and heavy-duty vehicle fractions.

The initial vertical dimension coefficient, Szinit, is then estimated by dividing the Top of Plume Height
by 2.15. For typical light-duty vehicles, this corresponds to a Szinit of 1.2 meters. For typical heavy-duty
vehicles, the value of Szinit is 3.2 meters.

C.3.3 Determining Release Height for VOLUME Sources

The release height, which is the height at which wind effectively begins to affect the plume, may be
estimated as the midpoint of the Top of Plume Height. In other words, the release height is the Top of
Plume Height multiplied by 0.5. As noted above, most roadways will experience a combination of

3
If multiple pollutants are being modeled and the emission factors vary significantly for different vehicle types, then
determine the Top of Plume Height based on the traffic volume weighted approach.

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light-duty and heavy-duty traffic. For each roadway source, the release height should be based on the
same Top of Plume Height used for calculating its Szinit, as described above. This value is 1.3 m for
light-duty vehicles, and it is 3.4 m for heavy-duty vehicles.

In addition, when the source-receptor spacing in AERMOD is shorter than the distance between adjacent
volume sources, AERMOD may produce aberrant results. Therefore, ensure that no receptors are placed
within a distance of (2.15 x Syinit + 1 meter) of the center of a VOLUME source, known as the “receptor
exclusion zone.” 4 As a practical recommendation, when using VOLUME sources to simulate a roadway
where receptors are placed five meters from the edge of the roadway, the width of a volume source should
be less than eight meters. This will ensure that no receptors fall within the receptor exclusion zone. If the
width of the roadway is larger than eight meters, it is recommended that additional VOLUME sources be
defined (e.g., separate each lane of traffic), or LINE sources be used.

C.5 References for Appendix C

• U.S. Environmental Protection Agency. September 1995. User’s Guide for the Industrial Source
Complex (ISC3) Dispersion Models Volume II – Description of Model Algorithms.
https://www3.epa.gov/scram001/userg/regmod/isc3v2.pdf.
• U.S. Environmental Protection Agency. Memorandum. March 2, 2012. Haul Road Workgroup
Final Report Submission to EPA-OAQPS.
https://www3.epa.gov/scram001/reports/Haul_Road_Workgroup-Final_Report_Package-
20120302.pdf.
• U.S. Environmental Protection Agency. November 2015. Transportation Conformity Guidance
for Quantitative Hot-spot Analyses in PM2.5 and PM10 Nonattainment and Maintenance Areas.
https://nepis.epa.gov/Exe/ZyPdf.cgi?Dockey=P100NN22.pdf.
• U.S. Environmental Protection Agency. August 2019. User’s Guide for the AMS/EPA Regulatory
Model (AERMOD). https://www3.epa.gov/ttn/scram/models/aermod/aermod_userguide.pdf.
• U.S. Environmental Protection Agency. September 2019. Guidance on New R-LINE Additions to
AERMOD 19191 for Refined Transportation Project Analyses.
https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100XI3C.pdf.

4
Ambient air receptors, including Cartesian grid receptors and property boundary receptors must not be excluded.
If any ambient air receptors fall within the “receptor exclusion zone” and using adjacent VOLUME sources results
in aberrant modeled concentrations, then the LINE source type must be used instead of adjacent VOLUME sources.

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Appendix D – Placement of Portable Equipment
Modeling portable equipment presents the challenge of determining the appropriate locations to model the
equipment and distributing emissions to these locations in a representative and health protective manner.
If portable equipment will operate at specific locations on a consistent schedule, the portable equipment’s
emissions can be modeled at multiple locations using an appropriate variable emission scenario for each
AERMOD source. More information on variable emissions modeling can be found in Appendix A of this
document.

If there is no consistent operational schedule for the portable equipment, use the following methodology
to apportion the emissions:
1. The annual emissions should be distributed evenly throughout all locations where the equipment
emits throughout the year.
2. When determining the short-term (i.e., 24-hour, 8-hour, 3-hour and 1-hour) impacts, the model
should first be run with the short-term emissions from any portable equipment set to zero. After
the point of maximum impact (PMI) is determined, a second analysis should be performed with
the short-term emissions for all portable equipment assigned to the closest location to the PMI
that the equipment will operate.
3. If there is concern that emissions from the portable equipment may be the main contributor to a
short-term averaging period concentration for any of the pollutants, a third short-term modeling
run should be performed. In this modeling run, the portable equipment should be placed at the
location closest to the property boundary that it will operate. The short-term impacts at the PMI
from this run should be compared to the short-term impacts at the PMI for the second modeling
run as described in Step 2, with the higher of the two values reported as the PMI for that pollutant
and averaging period.

An example of the methodology described above is well drilling at an oil and gas facility. In this
example, a total of 50 wells will be drilled over a 10-year period:
1. One volume source is modeled at each well location. The average annual emissions for each
volume source are equal to the total well drilling emissions over the lifetime of the project
divided by 10 years and by 50 wells.
2. Next, the short-term impacts are analyzed without any short-term emissions from well drilling.
The initial PMI for each pollutant and averaging period for this analysis is determined, and then
the short-term emissions for each pollutant are assigned to the well located closest to the PMI for
that pollutant and averaging period, as there will be only one drilling rig in operation at a time.
For this second analysis, the closest well location to the PMI for 24-hour PM10 is approximately
300 meters from the property boundary, and the resulting 24-hour PM10 concentration at the PMI
is 3.7 μg/m3.
3. Additionally, a 24-hour PM10 modeling run is performed with the maximum 24-hour well drilling
PM10 emissions assigned to the well located closest to the property boundary, which is
approximately 60 meters from the property boundary. The resulting 24-hour PM10 concentration
at the PMI is 3.0 μg/m3. Therefore, the reported modeled 24-hour PM10 concentration is the PMI
from the second analysis, 3.7 μg/m3, which must be added to the background concentration for
comparison to the AAQS. This same methodology must be implemented for each pollutant
and short-term averaging period.

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