EPA-450/2 - 78 - 027R-B
(NTIS No. PB 93-213213)
SUPPLEMENT B
TO THE
GUIDELINE ON AIR QUALITY MODELS (REVISED)
(Appendix W of 40 CFR Part 51)
PROTECTION
AGENCY
»AkkAS, TEXAS
LIBRARY
FEBRUARY 1993
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Radiation
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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NOTE
The following pages contained in Supplement B to the
Guideline on Air Quality Models (Revised) (EPA Publi-
cation No. EPA-450/2-78-027R) are to be inserted in the
Guideline, with Supplement A already having been incor-
porated. The page numbers will indicate which pages are
to be added and which are to replace previous pages. As
the ERT Air Quality Model (ERTAQ) and the Multiple Point
Source Diffusion Model (MPSDM) are being deleted from
Appendix B, pages B-19 -> B-22 and B-59 -> B-62,
respectively, should be removed from any previous
editions of the Guideline.
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PREFACE
Industry and control agencies have long expressed a need for consistency
in the application of air quality models for regulatory purposes. In the 1977
Clean Air Act, Congress mandated such consistency and encouraged the
standardization of model applications. The Guideline on Air Quality Models
was first published in April 1978 to satisfy these requirements by specifying
models and providing guidance for their use. This guideline provides a common
basis for estimating the air quality concentrations used in assessing control
strategies and developing emission limits.
The continuing development of new air quality models in response to
regulatory requirements and the expanded requirements for models to cover even
more complex problems have emphasized the need for periodic review and update
of guidance on these techniques. Four primary on-going activities provide
direct input to revisions of this modeling guideline. The first is a series
of annual EPA workshops conducted for the purpose of ensuring consistency and
providing clarification in the application of models. The second activity,
directed toward the improvement of modeling procedures, is the cooperative
agreement that EPA has with the scientific community represented by the
American Meteorological Society. This agreement provides scientific
assessment of procedures and proposed techniques and sponsors workshops on key
technical issues. The third activity is the solicitation and review of new
models from the technical and user community. In the March 27, 1980 Federal
Register, a procedure was outlined for the submittal to EPA of privately
developed models. After extensive evaluation and scientific review, these
models, as well as those made available by EPA, are considered for recognition
in this guideline. The fourth activity is the extensive on-going research
efforts by EPA and others in air quality and meteorological modeling.
Based primarily on these four activities, this document embodies
revisions to the "Guideline on Air Quality Models." Although the text has
been revised from the 1978 guide, the present content and topics are similar.
As necessary, new sections and topics are included. EPA does not make changes
to the guidance on a predetermined schedule, but rather on an as needed basis.
EPA believes that revisions to this guideline should be timely and responsive
to user needs and should involve public participation to the greatest possible
extent. All future changes to the guidance will be proposed and finalized in
the Federal Register. Information on the current status of modeling guidance
can always be obtained from EPA's Regional Offices.
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IV
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TABLE OF CONTENTS
Page
PREFACE iii
TABLE OF CONTENTS v
LIST OF TABLES ix
1.0 INTRODUCTION 1-1
2.0 OVERVIEW OF MODEL USE 2-1
2.1 Suitability of Models 2-2
2.2 Classes of Models 2-4
2.3 Levels of Sophistication of Models 2-6
3.0 RECOMMENDED AIR QUALITY MODELS 3-1
3.1 Preferred Modeling Techniques 3-3
3.1.1 Discussion 3-3
3.1.2 Recommendations 3-5
3.2 Use of Alternative Models 3-6
3.2.1 Discussion 3-6
3.2.2 Recommendations 3-7
3.3 Availability of Supplementary Modeling Guidance 3-9
3.3.1 The Model Clearinghouse 3-10
3.3.2 Regional Meteorologists Workshops 3-12
4.0 SIMPLE-TERRAIN STATIONARY-SOURCE MODELS 4-1
4.1 Discussion 4-1
4.2 Recommendations 4-2
4.2.1 Screening Techniques 4-2
4.2.2 Refined Analytical Techniques 4-3
5.0 MODEL USE IN COMPLEX TERRAIN 5-1
5.1 Discussion 5-1
5.2 Recommendations 5-3
5.2.1 Screening Techniques 5-4
5.2.2 Refined Analytical Techniques 5-7
6.0 MODELS FOR OZONE, CARBON MONOXIDE AND NITROGEN DIOXIDE 6-1
6.1 Discussion 6-1
6.2 Recommendations 6-3
6.2.1 Models for Ozone 6-3
6.2.2 Models for Carbon Monoxide 6-4
6.2.3 Models for Nitrogen Dioxide (Annual Average) . . . 6-5
Revised 2/93
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Page
7.0 OTHER MODEL REQUIREMENTS 7-1
7.1 Discussion 7-1
7.2 Recommendations 7-3
7.2.1 Fugitive Dust/Fugitive Emissions 7-3
7.2.2 Particulate Matter 7-4
7.2.3 Lead 7-5
7.2.4 Visibility 7-6
7.2.5 Good Engineering Practice Stack Height 7-7
7.2.6 Long Range Transport (LRT) (i.e., beyond 50km) . . 7-8
7.2.7 Modeling Guidance for Other Governmental Programs . 7-9
7.2.8 Air Pathway Analyses (Air Toxics and Hazardous
Waste 7-10
8.0 GENERAL MODELING CONSIDERATIONS 8-1
8.1 Discussion 8-1
8.2 Recommendations 8-2
8.2.1 Design Concentrations 8-2
8.2.2 Critical Receptor Sites 8-4
8.2.3 Dispersion Coefficients 8-5
8.2.4 Stability Categories 8-6
8.2.5 Plume Rise 8-7
8.2.6 Chemical Transformation 8-8
8.2.7 Gravitational Settling and Deposition 8-9
8.2.8 Urban/Rural Classification 8-10
8.2.9 Fumigation 8-11
8.2.10 Stagnation 8-12
8.2.11 Calibration of Models 8-13
9 .0 MODEL INPUT DATA 9-1
9.1 Source Data 9-2
9.1.1 Discussion 9-2
9.1.2 Recommendations 9-3
9.2 Background Concentrations 9-7
9.2.1 Discussion 9-7
9.2.2 Recommendations (Isolated Single Source) 9-8
9.2.3 Recommendations (Multi-Source Areas) 9-8
9.3 Meteorological Input Data 9-10
9.3.1 Length of Record of Meteorological Data 9-11
9.3.2 National Weather Service Data 9-13
9.3.3 Site-Specific Data 9-15
9.3.4 Treatment of Calms 9-23
vi Revised 2/93
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Page
10.0 ACCuliicY Alto tJNCERTAINTY OF MODELS 10-1
10.1 Dicussion 10-1
10.1.1 Overview of Model Uncertainty 10-1
10.1.2 Studies of Model Accuracy 10-3
10.1.3 Use of Uncertainty in Decision-Making 10-4
10.1.4 Evaluation of Models 10-6
10.2 Recommendations 10-8
11.0 REGULATORY APPLICATION OF MODELS 11-1
11.1 Discussion 11-1
11.2 Recommendations 11-3
11.2.1 Analysis Requirements 11-3
11.2.2 Use of Measured Data in Lieu of Model Estimates . 11-5
11.2.3 Emission Limits 11-7
12.0 REFERENCES 12-1
13.0 BIBLIOGRAPHY 13-1
14.0 GLOSSARY OF TERMS 14-1
APPENDIX A TO APPENDIX W OF PART 51 - SUMMARIES OF PREFERRED
AIR QUALITY MODELS A-l
APPENDIX B TO APPENDIX W OF PART 51 - SUMMARIES OF ALTERNATIVE
AIR QUALITY MODELS B-l
APPENDIX C TO APPENDIX W OF PART 51 - EXAMPLE AIR QUALITY ANALYSIS
CHECKLIST . ' C-l
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Vlll
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LIST OF TABLES
Table No. Title Page
4-1 Preferred Models for Selected Applications in
Simple Terrain 4-4
5-la Neutral/Stable Meteorological Matrix for CTSCREEN .... 5-9
5-lb Unstable/Convective Meteorological Matrix for
CTSCREEN 5-9
5-2 Preferred Options for the SHORTZ/LONGZ Computer
Codes When Used in a Screening Mode 5-10
5-3 Preferred Options for the RTDM Computer Code When
Used in a Screening Mode 5-11
9-1 Model Emission Input Data for Point Sources 9-5
9-2 Point Source Model Input Data (Emissions) for
PSD NAAQS Compliance Demonstrations 9-6
9-3 Averaging Times for Site-Specific Wind and
Turbulence Measurements 9-19
ix Revised 2/93
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Recommendations are made in this guide concerning air quality models,
data bases, requirements for concentration estimates, the use of measured data
in lieu of model estimates, and model evaluation procedures. Models are
identified for some specific applications. The guidance provided here should
be followed in all air quality analyses relative to State Implementation Plans
and in analyses required by EPA, State and local agency air programs. The EPA
may approve the use of another technique that can be demonstrated to be more
appropriate than those recommended in this guide. This is discussed at greater
length in Section 3.0. In all cases, the model applied to a given situation
should be the one that provides the most accurate representation of
atmospheric transport, dispersion, and chemical transformations in the area of
interest. However, to ensure consistency, deviations from this guide should
be carefully documented and fully supported.
From time to time situations arise requiring clarification of the intent
of the guidance on a specific topic. Periodic workshops are held with the EPA
Regional Meteorologists to ensure consistency in modeling guidance and to
promote the use of more accurate air quality models and data bases. The
workshops serve to provide further explanations of guideline requirements to
the Regional Offices and workshop reports are issued with this clarifying
information. In addition, findings from on-going research programs, new model
submittals, or results from model evaluations and applications are
continuously evaluated. Based on this information, changes in the guidance
may be indicated.
All changes to this guidance must follow rulemaking requirements since
the guideline is codified in Appendix W of part 51. EPA will promulgate
proposed and final rules in the Federal Register to amend this Appendix.
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Ample opportunity for public comment will be provided for each proposed change
and public hearings scheduled if requested. Final rule changes will be made
available through the National Technical Information Service (NTIS).
A wide range of topics on modeling and data bases are discussed in the
remainder of this guideline. Chapter 2 gives an overview of models and their
appropriate use. Chapter 3 provides specific guidance on the use of
"preferred" air quality models and on the selection of alternative techniques.
Chapters 4 through 7 provide recommendations on modeling techniques for
application to simple-terrain stationary source problems, complex terrain
problems, and mobile source problems. Specific modeling requirements for
selected regulatory issues are also addressed. Chapter 8 discusses issues
common to many modeling analyses, including acceptable model components.
Chapter 9 makes recommendations for data inputs to models including source,
meteorological and background air quality data. Chapter 10 covers the
uncertainty in model estimates and how that information can be useful to the
regulatory decision-maker. The last chapter summarizes how estimates and
measurements of air quality are used in assessing source impact and in
evaluating control strategies.
Appendix W to 40 CFR part 51 (the "Guideline on Air Quality Models
(Revised)") itself contains three appendices: A, B, and C. Thus, when
reference is made to "appendix A" in this document, it refers to the appendix
A to appendix W to 40 CFR part 51. Appendices B and C are referenced in the
same way.
Appendix A contains summaries of refined air quality models that are
"preferred" for specific applications; both EPA models and models developed by
others are included. Appendix B contains summaries of other refined models
1-4 Revised 2/93
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that may be considered with a case-specific justification. Appendix C
contains a checklist of requirements for an air quality analysis.
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3.2 Use of Alternative Models
3.2.1 Discussion
Selection of the best techniques for each individual air
quality analysis is always encouraged, but the selection should be done in a
consistent manner. A simple listing of models in this guide cannot alone
achieve that consistency nor can it necessarily provide the best model for all
possible situations. An EPA document, "Interim Procedures for Evaluating Air
Quality Models",13-16 has been prepared to assist in developing a consistent
approach when justifying the use of other than the preferred modeling tech-
niques recommended in this guide. An alternative to be considered to the
performance measures contained in Chapter 3 of this document is set forth in
another EPA document "Protocol for Determining the Best Performing Model".17
The procedures in both documents provide a general framework for objective
decision-making on the acceptability of an alternative model for a given
regulatory application. The documents contain procedures for conducting both
the technical evaluation of the model and the field test or performance
evaluation.
This section discusses the use of alternate modeling tech-
niques and defines three situations when alternative models may be used.
3-6 Revised 2/93
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3.2.2 Recommendations
Determination of acceptability of a model is a
Regional Office responsibility. Where the Regional Administrator finds that
an alternative model is more appropriate than a preferred model, that model
may be used subject to the recommendations below. This finding will normally
result from a determination that (1) a preferred air quality model is not
appropriate for the particular application; or (2) a more appropriate model or
analytical procedure is available and is applicable.
An alternative model should be evaluated from both a theoret-
ical and a performance perspective before it is selected for use. There are
three separate conditions under which such a model will normally be approved
for use: (1) if a demonstration can be made that the model produces concen-
tration estimates equivalent to the estimates obtained using a preferred
model; (2) if a statistical performance evaluation has been conducted using
measured air quality data and the results of that evaluation indicate the
alternative model performs better for the application than a comparable model
in Appendix A; and (3) if there is no preferred model for the specific
application but a refined model is needed to satisfy regulatory requirements.
Any one of these three separate conditions may warrant use of an alternative
model. Some known alternative models that are applicable for selected
situations are contained in Appendix B. However, inclusion there does not
infer any unique status relative to other alternative models that are being or
will be developed in the future.
Equivalency is established by demonstrating that the maximum
or highest, second highest concentrations are within 2 percent of the esti-
mates obtained from the preferred model. The option to show equivalency is
intended as a simple demonstration of acceptability for an alternative model
that is so nearly identical (or contains options that can make it identical)
to a preferred model that it can be treated for practical purposes as the
preferred model. Two percent was selected as the basis for equivalency since
it is a rough approximation of the fraction that PSD Class I increments are of
the NAAQS for SO2, i.e., the difference in concentrations that is judged to be
significant. However, notwithstanding this demonstration, use of models that
are not equivalent may be used when one of the two other conditions identified
below are satisfied.
The procedures and techniques for determining the acceptabil-
ity of a model for an individual case based on superior performance is con-
tained in the document entitled "Interim Procedures for Evaluating Air Quality
Models",15 and should be followed, as appropriate." Preparation and implemen-
tation of an evaluation protocol which is acceptable to both control agencies
and regulated industry is an important element in such an evaluation.
"Another EPA document, "Protocol for Determining the Best Performing
Model,"17 contains advanced statistical techniques for determining which model
performs better than other competing models. In many cases, this protocol
should be considered by users of the "Interim Procedures for Evaluating Air
Quality Models" in preference to the material currently in Chapter 3 of that
document.
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When no Appendix A model is applicable to the modeling
problem, an alternative refined model may be used provided that:
1. the model can be demonstrated to be applicable to the
problem on a theoretical basis, and
2. the data bases which are necessary to perform the
analysis are available and adequate, and
3a. performance evaluations of the model in similar circum-
stances have shown that the model is not biased toward underestimates, or
3b. after consultation with the EPA Regional Office, a second
model is selected as a baseline or reference point for performance and the
interim procedures'/protocol17 are then used to demonstrate that the proposed
model performs better than the reference model.
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4.2 Recommendations
4.2.1 Screening Techniques
Point source screening techniques are an acceptable approach
to air quality analyses. One such approach is contained in the EPA document
"Screening Procedures for Estimating the Air Quality Impact of Stationary
Sources".18 A computerized version of the screening technique, SCREEN2, is
available.19-20
All screening procedures should be adjusted to the site and
problem at hand. Close attention should be paid to whether the area should be
classified urban or rural in accordance with Section 8.2.8. The climatology
of the area should be studied to help define the worst-case meteorological
conditions. Agreement should be reached between the model user and the
reviewing authority on the choice of the screening model for each analysis,
and on the input data as well as the ultimate use of the results.
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TABLE 4-1
Preferred Models for Selected Applications in Simple Terrain
Short Term (i.e., 1-24 hours) Land Use Model'
Single Source Rural CRSTER
Urban RAM
Multiple Source Rural MPTER
Urban RAM
Complicated Sources2 Rural/Urban ISCST2
Buoyant Industrial Line Sources Rural BLP
Long Term (i.e., monthly, seasonal or annual)
Single Source Rural CRSTER
Urban RAM
Multiple Source Rural MPTER
Urban COM 2.0 or RAM3
Complicated Sources2 Rural/Urban ISCLT2
Buoyant Industrial Line Sources Rural BLP
'Several of these models contain options which allow them to be inter-
changed. For Example, ISCST2 can be substituted for CRSTER and equivalent, if
not identical, concentration estimates obtained. Similarly, for a point
source application, MPTER with urban option can be substituted for RAM. Where
a substitution is convenient to the user and equivalent estimates are assured,
it may be made. The models as listed here reflect the applications for which
they were originally intended.
Complicated sources are those with special problems such as aerodynamic
downwash, particle deposition, volume and area sources, etc.
3If only a few sources in an urban area are to be modeled, RAM should be
used.
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5.0 MODEL USE IN COMPLEX TERRAIN
5.1 Discussion
For the purpose of this guideline, complex terrain is defined as
terrain exceeding the height of the stack being modeled. Complex terrain
dispersion models are normally applied to stationary sources of pollutants
such as SO2 and particulates.
A major outcome from the EPA Complex Terrain Model Development
project has been the publication of a refined dispersion model (CTDM) suitable
for regulatory application to plume impaction assessments in complex terrain.21
Although CTDM as originally produced was only applicable to those hours
characterized as neutral or stable, a computer code for all stability
conditions, CTDMPLUS,19 together with a user's guide,22 and on-site meteorolog-
ical and terrain data processors,23'24 is now available. Moreover, CTSCREEN,'9>23
a version of CTDMPLUS that does not require on-site meteorological data
inputs, is also available as a screening technique.
The methods discussed in this section should be considered in two
categories: (1) screening techniques, and (2) the refined dispersion model,
CTDMPLUS, discussed below and listed in Appendix A.
Continued improvements in ability to accurately model plume disper-
sion in complex terrain situations can be expected, e.g., from research on lee
side effects due to terrain obstacles. New approaches to improve the ability
of models to realistically simulate atmospheric physics, e.g., hybrid models
which incorporate an accurate wind field analysis, will ultimately provide
more appropriate tools for analyses. Such hybrid modeling techniques are also
acceptable for regulatory applications after the appropriate demonstration and
evaluation. '5
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5.2 Recommendations
Recommendations in this Section apply primarily to those situations
where the impaction of plumes on terrain at elevations equal to or greater
than the plume centerline during stable atmospheric conditions are determined
to be the problem. If a violation of any NAAQS or the controlling increment
is indicated by using any of the preferred screening techniques, then a
refined complex terrain model may be used. Phenomena such as fumigation, wind
direction shear, lee-side effects, building wake- or terrain-induced downwash,
deposition, chemical transformation, variable plume trajectories, and long
range transport are not addressed by the recommendations in this section.
Where site-specific data are used for either screening or refined
complex terrain models, a data base of at least 1 full-year of meteorological
data is preferred. If more data are available, they should be used. Meteoro-
logical data used in the analysis should be reviewed for both spatial and
temporal representativeness.
Placement of receptors requires very careful attention when modeling
in complex terrain. Often the highest concentrations are predicted to occur
under very stable conditions, when the plume is near, or impinges on, the
terrain. The plume under such conditions may be quite narrow in the vertical,
so that even relatively small changes in a receptor's location may substan-
tially affect the predicted concentration. Receptors within about a kilometer
of the source may be even more sensitive to location. Thus, a dense array of
receptors may be required in some cases. In order to avoid excessively large
computer runs due to such a large array of receptors, it is often desirable to
model the area twice. The first model run would use a moderate number of
receptors carefully located over the area of interest. The second model run
would use a more dense array of receptors in areas showing potential for high
concentrations, as indicated by the results of the first model run.
When CTSCREEN or CTDMPLUS is used, digitized contour data must be
first processed by the CTDM Terrain Processor23 to provide hill shape parame-
ters in a format suitable for direct input to CTDMPLUS. Then the user
supplies receptors either through an interactive program that is part of the
model or directly, by using a text editor; using both methods to select
receptors will generally be necessary to assure that the maximum concentra-
tions are estimated by either model. In cases where a terrain feature may
"appear to the plume" as smaller, multiple hills, it may be necessary to model
the terrain both as a single feature and as multiple hills to determine design
concentrations.
The user is encouraged to confer with the Regional Office if any
unresolvable problems are encountered with any screening or refined analytical
procedures, e.g., meteorological data, receptor siting, or terrain contour
processing issues.
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5.2.1 Screening Techniques
Five preferred screening techniques are currently available
to aid in the evaluation of concentrations due to plume impaction during
stable conditions: (1) for 24-hour impacts, the Valley Screening Technique'9
as outlined in the Valley Model User's Guide;26 (2) CTSCREEN," as outlined in
the CTSCREEN User's Guide;25 (3) COMPLEX I;19 (4) SHORTZ/LONGZ ;19-27 and (5) Rough
Terrain Dispersion Model (RTDM) |9>9° in its prescribed mode described below. As
appropriate, any of these screening techniques may be used consistent with the
needs, resources, and available data of the user.
The Valley Model, COMPLEX I, SHORTZ/LONGZ, and RTDM should be
used only to estimate concentrations at receptors whose elevations are greater
than or equal to plume height. For receptors at or below stack height, a
simple terrain model should be used (see Chapter 4). Receptors between stack
height and plume height present a unique problem since none of the above
models were designed to handle receptors in this narrow regime, the definition
of which will vary hourly as meteorological conditions vary. CTSCREEN may be
used to estimate concentrations under all stability conditions at all recep-
tors located "on terrain" above stack top, but has limited applicability in
multi-source situations. As a result, the estimation of concentrations at
receptors between stack height and plume height should be considered on a
case-by-case basis after consultation with the EPA Regional Office; the most
appropriate technique may be a function of the actual source(s) and terrain
configuration unique to that application. One technique that will generally
be acceptable, but is not necessarily preferred for any specific application,
involves applying both a complex terrain model (except for the Valley Model)
and a simple terrain model. The Valley Model should not be used for any
intermediate terrain receptor. For each receptor between stack height and
plume height, an hour-by-hour comparison of the concentration estimates from
both models is made. The higher of the two modeled concentrations should be
chosen to represent-the impact at that receptor for that hour, and then used
to compute the concentration for the appropriate averaging time(s). For the
simple terrain models, terrain may have to be "chopped off" at stack height,
since these models are frequently limited to receptors no greater than stack
height.
5.2.1.1 Valley Screening Technique
The Valley Screening Technique may be used to
determine 24-hour averages. This technique uses the Valley Model with the
following worst-case assumptions for rural areas: (1) P-G stability "F";
(2) wind speed of 2.5 m/s; and (3) 6 hours of occurrence. For urban areas
the stability should be changed to "P-G stability E."
When using the Valley Screening Technique to obtain
24-hour average concentrations the following apply: (1) multiple sources
should be treated individually and the concentrations for each wind direction
summed; (2) only one wind direction should be used (see User's Guide,26 page 2-
15) even if individual runs are made for each" source; (3) for buoyant sources,
the BID option may be used, and the option to use the 2.6 stable plume rise
factor should be selected; (4) if plume impaction is likely on any elevated
terrain closer to the source than the distance from the source to the final
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plume rise, then the transitional (or gradual) plume rise option for stable
conditions should be selected.
The standard polar receptor grid found in the Valley
Model User's Guide may not be sufficiently dense for all analyses if only one
geographical scale factor is used. The user should choose an additional set
of receptors at appropriate downwind distances whose elevations are equal to
plume height minus 10 meters. Alternatively, the user may exercise the
"Valley equivalent" option in COMPLEX I or SCREEN2 and note the comments above
on the placement of receptors in complex terrain models.
When using the "Valley equivalent" option in
COMPLEX I, set the wind profile exponents (PL) to 0.0, respectively, for all
six stability classes.
5.2.1.2 CTSCREEN
CTSCREEN may be used to obtain conservative, yet
realistic, worst-case estimates for receptors located on terrain above stack
height. CTSCREEN accounts for the three-dimensional nature of plume and
terrain interaction and requires detailed terrain data representative of the
modeling domain. The model description and user's instructions are contained
in the user's guide.25 The terrain data must be digitized in the same manner
as for CTDMPLUS and a terrain processor is available.23 A discussion of the
model's performance characteristics is provided in a technical paper.91
CTSCREEN is designed to execute a fixed matrix of meteorological values for
wind speed (u) , standard deviation of horizontal and vertical wind speeds (crv,
ffw), vertical potential temperature gradient (d6/dz), friction velocity (u.) ,
Monin-Obukhov length (L) , mixing height (z-,) as a function of terrain height,
and wind directions for both neutral/stable conditions and unstable convective
conditions. Table 5-1 contains the matrix of meteorological variables that is
used for each CTSCREEN analysis. There are 96 combinations, including
exceptions, for each wind direction for the neutral/stable case, and 108
combinations for the unstable case. The specification of wind direction,
however, is handled internally, based on the source and terrain geometry. The
matrix was developed from examination of the range of meteorological variables
associated with maximum monitored concentrations from the data bases used to
evaluate the performance of CTDMPLUS. Although CTSCREEN is designed to
address a single source scenario, there are a number of options that can be
selected on a case-by-case basis to address multi-source situations. However,
the Regional Office should be consulted, and concurrence obtained, on the
protocol for modeling multiple sources with CTSCREEN to ensure that the worst
case is identified and assessed. The maximum concentration output from
CTSCREEN represents a worst-case 1-hour concentration. Time-scaling factors
of 0.7 for 3-hour, 0.15 for 24-hour and 0.03 for annual concentration averages
are applied internally by CTSCREEN to the highest 1-hour concentration
calculated by the model.
5.2.1.3 COMPLEX I
If the area is rural, COMPLEX I may be used to
estimate concentrations for all averaging times. COMPLEX I is a modification
of the MPTER model that incorporates the plume impaction algorithm of the
Valley Model." It is a multiple-source screening technique that accepts
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hourly meteorological data as input. The output is the same as the normal
MPTER output. When using COMPLEX I the following options should be selected:
U) set terrain adjustment IOPT{1) = 1; (2) set buoyancy induced dispersion
IOPT (4) =1; (3) set IOPT (25) = 1; (4) set the terrain adjustment values to
0.5, 0.5, 0.5 0.5, 0.0, 0.0, (respectively for six stability classes); and
(5) set Z MIN = 10.
When using the "Valley equivalent" option (only) in
COMPLEX I, set the wind profile exponents (PL) to 0.0, respectively, for all
six stability classes. For all other regulatory uses of COMPLEX I, set the
wind profile exponents to the values used in the simple terrain models, i.e.,
0.07, 0.07, 0.10, 0.15, 0.35, and 0.55, respectively, for rural modeling.
Gradual plume rise should be used to estimate
concentrations at nearby elevated receptors, if plume impaction is likely on
any elevated terrain closer to the source than the distance from the source to
the final plume rise (see Section 8.2.5).
5.2.1.4 SHORTZ/LONGZ
If the source is located in an urbanized (Section
8.2.8) complex terrain valley, then the suggested screening technique is
SHORTZ for short-term averages or LONGZ for long-term averages. SHORTZ and
LONGZ may be used as screening techniques in these complex terrain applica-
tions without demonstration and evaluation. Application of these models in
other than urbanized valley situations will require the same evaluation and
demonstration procedures as are required for all Appendix B models.
Both SHORTZ and LONGZ have a number of options.
When using these models as screening techniques for urbanized valley applica-
tions, the options listed in Table 5-2 should be selected.
5.2.1.5 RTDM (Screening Mode)
RTDM with the options specified in Table 5-3 may be
used as a screening technique in rural complex terrain situations without
demonstration and evaluation.
The RTDM screening technique can provide a more
refined concentration estimate if on-site wind speed and direction character-
istic of plume dilution and transport are used as input to the model. In
complex terrain, these winds can seldom be estimated accurately from the
standard surface (10m level) measurements. Therefore, in order to increase
confidence in model estimates, EPA recommends that wind data input to RTDM
should be based on fixed measurements at stack top height. For stacks greater
than 100m, the measurement height may be limited to 100m in height relative to
stack base. However, for very tall stacks, see guidance in Section 9.3.3.2.
This recommendation is broadened to include wind data representative of plume
transport height where such data are derived from measurements taken with
remote sensing devices such as SODAR. The data from both fixed and remote
measurements should meet quality assurance and recovery rate requirements.
The user should also be aware that RTDM in the screening mode accepts the
input of measured wind speeds at only one height. The default values for the
wind speed profile exponents shown in Table 5-3 are used in the model to
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determine the wind speed at other heights. RTDM uses wind speed at stack top
to calculate the plume rise and the critical dividing streamline height, and
the wind speed at plume transport level to calculate dilution. RTDM treats
wind direction as constant with height.
RTDM makes use of the "critical dividing streamline"
concept and thus treats plume interactions with terrain quite differently from
other models such as SHORTZ and COMPLEX I. The plume height relative to the
critical dividing streamline determines whether the plume impacts the terrain,
or is lifted up and over the terrain. The receptor spacing to identify
maximum impact concentrations is quite critical depending on the location of
the plume in the vertical. Analysis of the expected plume height relative to
the height of the critical dividing streamline should be performed for
differing meteorological conditions in order to help develop an appropriate
array of receptors. Then it is advisable to model the area twice according to
the suggestions in Section 5.2.
5.2.1.6 Restrictions
For screening analyses using the Valley Screening
Technique, COMPLEX I or RTDM, a sector greater than 22%° should not be
allowed. Full ground reflection should always be used in the Valley Screening
Technique and COMPLEX I.
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5.2.2 Refined Analytical Techniques
When the results of the screening analysis demonstrate a
possible violation of NAAQS or the controlling PSD increments, a more refined
analysis may need to be conducted.
The Complex Terrain Dispersion Model PLus Algorithms for
Unstable Situations (CTDMPLUS) is a refined air quality model that is pre-
ferred for use in all stability conditions for complex terrain applications.
CTDMPLUS is a sequential model that requires five input files: (1) general
program specifications; (2) a terrain data file; (3) a receptor file; (4) a
surface meteorological data file; and (5) a user created meteorological
profile data file. Two optional input files consist of hourly emissions
parameters and a file containing upper air data from rawinsonde data files,
e.g., a National Climatic Data Center TD-6201 file, unless there are no hours
categorized as unstable in the record. The model description and user
instructions are contained in Volume 1 of the User's Guide.22 Separate
publications23'24 describe the terrain preprocessor system and the meteorologi-
cal preprocessor program. In Part I of a technical article92 is a discussion
of the model and its preprocessors; the model's performance characteristics
are discussed in Part II of the same article.93 The size of the CTDMPLUS
executable file on a personal computer is approximately 360K bytes. The model
produces hourly average concentrations of stable pollutants, i.e., chemical
transformation or decay of species and settling/deposition are not simulated.
To obtain concentration averages corresponding to the NAAQS, e.g., 3- or 24-
hour, or annual averages, the user must execute a postprocessor program such
as CHAVG." CTDMPLUS is applicable to all receptors on terrain elevations
above stack top. However, the model contains no algorithms for simulating
building downwash or the mixing or recirculation found in cavity zones in the
lee of a hill. The path taken by a plume through an array of hills cannot be
simulated. CTDMPLUS does not explicitly simulate calm meteorological periods,
and for those situations the user should follow the guidance in Section 9.3.4.
The user should follow the recommendations in the User's Guide under General
Program Specifications for: (1) selecting mixed layer heights, (2) setting
minimum scalar wind speed to 1 m/s, and (3) scaling wind direction with
height. Close coordination with the Regional Office is essential to insure a
consistent, technically sound application of this model.
The performance of CTDMPLUS is greatly improved by the use of
meteorological data from several levels up to plume height. However, due to
the vast range of source-plume-hill geometries possible in complex terrain,
detailed requirements for meteorological monitoring in support of refined
analyses using CTDMPLUS should be determined on a case-by-case basis. The
following general guidance should be considered in the development of a
meteorological monitoring protocol for regulatory applications of CTDMPLUS and
reviewed in detail by the Regional Office before initiating any monitoring.
As appropriate, the On-Site Meteorological Program Guidance document66 should
be consulted for specific guidance on siting requirements for meteorological
towers, selection and exposure of sensors, etc. As more experience is gained
with the model in a variety of circumstances, more specific guidance may be
developed.
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Site specific meteorological data are critical to dispersion
modeling in complex terrain and, consequently, the meteorological requirements
are more demanding than for simple terrain. Generally, three different
meteorological files (referred to as surface, profile, and rawin files) are
needed to run CTDMPLUS in a regulatory mode.
The surface file is created by the meteorological preprocess-
or (METPRO)24 based on on-site measurements or estimates of solar and/or net
radiation, cloud cover and ceiling, and the mixed layer height. These data
are used in METPRO to calculate the various surface layer scaling parameters
(roughness length, friction velocity, and Monin-Obukhov length) which are
needed to run the model. All of the user inputs required for the surface file
are based either on surface observations or on measurements at or below 10m.
The profile data file is prepared by the user with on-site
measurements (from at least three levels) of wind speed, wind direction,
turbulence, and potential temperature. These measurements should be obtained
up to the representative plume height(s) of interest (i.e., the plume
height(s) under those conditions important to the determination of the design
concentration). The representative plume height(s) of interest should be
determined using an appropriate complex terrain screening procedure (e.g.,
CTSCREEN) and should be documented in the monitoring/modeling protocol. The
necessary meteorological measurements should be obtained from an appropriately
sited meteorological tower augmented by SODAR if the representative plume
height(s) of interest exceed 100m. The meteorological tower need not exceed
the lesser of the representative plume height of interest (the highest plume
height if there is more than one plume height of interest) or 100m.
Locating towers on nearby terrain to obtain stack height or
plume height measurements for use in profiles by CTDMPLUS should be avoided
unless it can clearly be demonstrated that such measurements would be repre-
sentative of conditions affecting the plume.
The rawin file is created by a second meteorological prepro-
cessor (READ62)24 based on NWS (National Weather Service) upper air data. The
rawin file is used in CTDMPLUS to calculate vertical potential temperature
gradients for use in estimating plume penetration in unstable conditions. The
representativeness of the off-site NWS upper air data should be evaluated on a
case-by-case basis.
In the absence of an appropriate refined model, screening
results may need to be used to determine air quality impact and/or emission
limits.
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TABLE 5-la
NEUTRAL/STABLE METEOROLOGICAL MATRIX FOR CTSCREEN
Variable
U
*v
(m/£
(m/£
3)
3)
ffw (m/s)
AO/Az
WD
(K/m)
l
0
0
0
.0
.3
.08
.01
2
0
0
0
.0
.75
.15
.02
(Wind direction
meteorological
Specific Values
3.
0.
0.
0 4.0 5.0
30 0.75
035
optimized internally for each
combination)
Exceptions:
(1) If U s 2 m/s and av s 0.3 m/s, then include
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TABLE 5-2
Preferred Options for the SHORTZ/LONGZ Computer Codes When Used
in a Screening Mode
Option
I Switch 9
I Switch 17
GAMMA 1
GAMMA 2
XRY
NS, VS, FRQ (SHORTZ)—
NUS, VS, FRQ (LONGZ)—
ALPHA
SIGEPU-
-(particle size,
etc.)
SIGAPU-
- (dispersion parameters)
P (wind profile)
Selection
If using NWS data, set = 0
If using site-specific data,
check with the Regional Office
Set = 1 (urban option)
Use default values (0.6
entrainment coefficient)
Always default to "stable"
Set = 0 (50m rectilinear
expansion distance)
Do not use (applicable only
in flat terrain)
Select 0.9
Use Cramer curves (default); if
site-specific turbulence data
are available, see Regional
Office for advice.
Select default values given in
Table 2-2 of User's Instruc-
tions; if site-specific data
are available, see Regional
Office for advice.
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Revised 2/93
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TABLE 5-3
Preferred Options for the RTDM Computer Code When Used
in a Screening Mode
Parameter
PR001-003
PRO 04
PRO 05
PRO 06
PRO 09
PRO 10
PRO 11
PR012
PR013
PRO 14
PR015
PR020
PR022
PRO 2 3
PR016 to
019; 021;
and 024
Variable
SCALE
ZWIND1
ZWIND2
IDILUT
ZA
EXPON
ICOEF
IPPP
IBUOY
ALPHA
IDMX
ITRANS
TERCOR
RVPTG
ITIPD
I SHEAR
IREFL
IHORIZ
SECTOR
IY, IZ,
I RVPTG,
IHVPTG/IEPS,
IEMIS
Value
Wind measurement height
Not used
1
0 (default)
0.09, 0.11, 0.12,
0.14, 0.2, 0.3
(default)
3 (default)
0 (default)
1 (default)
3.162 (default)
1 (default)
1 (default)
6*0.5 (default)
0.02, 0.035
(default)
1
0 (default)
1 (default)
2 (default)
6*22.5 (default)
0
Remarks
Scale factors assuming horizontal
distance is in kilometers,
vertical distance is in feet, and
wind speed is in meters per second
See Section 5.2.1.4
Height of second anemometer
Dilution wind speed scaled to plume
height
Anemometer -terrain height above
stack base
Wind profile exponents
Briggs Rural/ASME (1979) dispersion
parameters
Partial plume penetration; not used
Buoyancy -enhanced dispersion is used
Buoyancy -enhanced dispersion
coefficient
Unlimited mixing height for
stable conditions
Transitional plume rise is used
Plume patch correction factors
Vertical potential temperature gra-
dient values for stabilities E and F
Stack- tip downwash is used
Wind shear; not used
Partial surface reflection is used
Sector averaging
Using 22.5° sectors
Hourly values of turbulence, vertical
potential temperature gradient, wind
speed profile exponents, and stack
emissions are not used
5-11
Revised 2/93
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6.0 MODELS FOR OZONE, CARBON MONOXIDE AND NITROGEN DIOXIDE
••••^fSV.-*' •
6.1 Discussion
Models discussed in this section are applicable to pollutants often
associated with mobile sources, e.g., ozone (O3) , carbon monoxide (CO) and
nitrogen dioxide (NO2) . Where stationary sources of CO and N02 are of concern,
the reader is referred to Sections 4 and 5.
A control agency with jurisdiction over areas with significant ozone
problems and which has sufficient resources and data to use a photochemical
dispersion model is encouraged to do so. Experience with and evaluations of
the Urban Airshed Model show it to be an acceptable, refined approach, and
better data bases are becoming available that support the more sophisticated
analytical procedures. However, empirical models (e.g., EKMA) fill the gap
between more sophisticated photochemical dispersion models and proportional
(rollback) modeling techniques and may be the only applicable procedure if the
available data bases are insufficient for refined dispersion modeling.
Models for assessing the impact of carbon monoxide emissions are
needed for a number of different purposes, e.g., to evaluate the effects of
point sources, congested intersections and highways, as well as the cumulative
effect on ambient CO concentrations of all sources of CO in an urban area.94-95
Nitrogen oxides are reactive and also an important contribution to
the photochemical ozone problem. They are usually of most concern in areas of
high ozone concentrations. Unless suitable photochemical dispersion models
are used, assumptions regarding the conversion of NO to NO2 are
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6.2 Recommendations
6.2.1 Models for Ozone
The Urban Airshed Model (UAM)19>28 is recommended for photo-
chemical or reactive pollutant modeling applications involving entire urban
areas. To ensure proper execution of this numerical model, users must satisfy
the extensive input data requirements for the model as listed in Appendix A
and the users guide. Users are also referred to the "Guideline for Regulatory
Application of the Urban Airshed Model"29 for additional data requirements and
procedures for operating this model.
The empirical model, City-specific EKMA,19>30"33 has limited
applicability for urban ozone analyses. Model users should consult the
appropriate Regional Office on a case-by-case basis concerning acceptability
of this modeling technique.
Appendix B contains some additional models that may be
applied on a case-by-case basis for photochemical or reactive pollutant
modeling. Other photochemical models, including multi-layered trajectory-
models, that are available may be used if shown to be appropriate. Most
photochemical dispersion models require emission data on individual hydrocar-
bon species and may require three dimensional meteorological information on an
hourly basis. Reasonably sophisticated computer facilities are also often
required. Because the input data are not universally available and studies to
collect such data are very resource intensive, there are only limited evalua-
tions of those models.
For those cases which involve estimating the impact on ozone
concentrations due to stationary sources of VOC and NO,, whether for permit-
ting or other regulatory cases, the model user should consult the appropriate
Regional Office on the acceptability of the modeling technique.
Proportional (rollback/forward) modeling is not an acceptable
procedure for evaluating ozone control strategies.
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6.2.2 Models for Carbon Monoxide
For analyzing CO impacts at roadway intersections, users
should follow the procedures in the "Guideline for Modeling Carbon Monoxide
from Roadway Intersections".34 The recommended model for such analyses is
CAL3QHC.33 This model combines CALINE3 (already in Appendix A) with a traffic
model to calculate delays and queues that occur at signalized intersections.
In areas where the use of either TEXIN2 or CALINE4 has previously been
established, its use may continue. The capability exists for these intersec-
tion models to be used in either a screening or refined mode. The screening
approach is described in reference 34; a refined approach may be considered on
a case-by-case basis. The latest version of the MOBILE (mobile source
emission factor) model should be used for emissions input to intersection
models.
For analyses of highways characterized by uninterrupted
traffic flows, CALINE3 is recommended, with emissions input from the latest
version of the MOBILE model.
The recommended model for urban areawide CO analyses is RAM
or Urban Airshed Model (UAM); see Appendix A. Information on SIP development
and requirements for using these models can be found in references 34, 96, 97
and 9 8.
Where point sources of CO are of concern, they should be
treated using the screening and refined techniques described in Section 4 or 5
of the Guideline.
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6.2.3 Models for Nitrogen Dioxide (Annual Average)
A three-tiered screening approach is recommended to obtain
annual average estimates of NO2 from point sources for New Source Review
analysis, including PSD, and for SIP planning purposes:
a. Initial screen: Use an appropriate Gaussian model from
Appendix A to estimate the maximum annual average concentration and assume a
total conversion of NO to NO2. If the concentration exceeds the NAAQS and/or
PSD increments for N02, proceed to the 2nd level screen.
b. 2nd level screen: Apply the Ozone Limiting Method3* to
the annual NO, estimate obtained in (a) above using a representative average
annual ozone concentration. If the result is still greater than the NAAQS,
and/or PSD increments, the more refined Ozone Limiting Method in the 3rd level
screen should be applied.
c. 3rd level screen: Apply the Ozone Limiting Method
separately for each hour of the year or multi-year period. Use representative
hourly NO2 background and ozone levels in the calculations.
In urban areas, a proportional model may be used as a
preliminary assessment to evaluate control strategies to meet the NAAQS for
multiple minor sources, i.e., minor point, area and mobile sources of NOX;
concentrations resulting from major point sources should be estimated sepa-
rately as discussed above, then added to the impact of the minor sources. An
acceptable screening technique for urban complexes is to assume that all NOX
is emitted in the form of NO2 and to use a model from Appendix A for nonreac-
tive pollutants to estimate N02 concentrations. A more accurate estimate can
be obtained by (1) calculating the annual average concentrations of NO, with
an urban model, and (2) converting these estimates to NO2 concentrations based
on a spatially averaged NO2/NOX annual ratio determined from an existing air
quality monitoring network.
To demonstrate compliance with N02 PSD increments in urban
areas, emissions from major and minor sources should be included in the
modeling analysis. Point and area source emissions should be modeled as
discussed above. If mobile source emissions do not contribute to localized
areas of high ambient NO2 concentrations, they should be modeled as area
sources. When modeled as area sources, mobile source emissions should be
assumed uniform over the entire highway link and allocated to each area source
grid square based on the portion of highway link within each grid square. If
localized areas of high concentrations are likely, then mobile sources should
be modeled as line sources with the preferred model ISCLT2.
In situations where there are sufficient hydrocarbons
available to significantly enhance the rate of NO to N02 conversion, the
assumptions implicit in the Ozone Limiting Procedure may not be appropriate.
More refined techniques should be considered on a case-by-case basis and
agreement with the reviewing authority should be obtained. Such techniques
should consider individual quantities of NO and N02 emissions, atmospheric
transport and dispersion, and atmospheric transformation of NO to N02. Where
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it is available site-specific data on the conversion of NO to NO2 may be used.
Photochemical dispersion models, if used for other pollutants in the area, may
also be applied to the NOX problem.
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transport distances are limited in detail. This limitation is a result of the
expense to perform the field studies required to verify and improve mesoscale
and long range transport models. Particularly important and sparse are
meteorological data adequate for generating three dimensional wind fields.
Application of models to complicated terrain compounds the difficulty. EPA
has completed limited evaluation of several long range transport (LRT) models
against two sets of field data. The evaluation results are discussed in the
document, "Evaluation of Short-Term Long-Range Transport Models."99-100 For the
time being, long range and mesoscale transport models must be evaluated for
regulatory use on a case-by-case basis.
There are several regulatory programs for which air pathway analysis
procedures and modeling techniques have been developed. For continuous
emission releases, ISC2 forms the basis of many analytical techniques. EPA is
continuing to evaluate the performance of a number of proprietary and public
domain models for intermittent and non-stack emission releases. Until EPA
completes its evaluation, it is premature to recommend specific models for air
pathway analyses of intermittent and non-stack releases in this guideline.
Regional scale models are used by EPA to develop and evaluate national
policy and assist State and local control agencies. Two such models are the
Regional Oxidant Model (ROM)101-102-103 and the Regional Acid Deposition Model
(RADM) .104 Due to the level of resources required to apply these models, it is
not envisioned that regional scale models will be used directly in most model
applications.
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7.2.2 Particulate Matter
The new particulate matter NAAQS, promulgated on July 1, 1987
(52 FR 24634), includes only particles with an aerodynamic diameter less than
or equal to a nominal 10 micrometers (PM-10). EPA has also proposed regula-
tions for PSD increments measured as PM-10 in a notice published on October 5,
1989 (54 FR 41218).
Screening techniques like those identified in Section 4 are
also applicable to PM-10 and to large particles. It is recommended that
subjectively determined values for "half-life" or pollutant decay not be used
as a surrogate for particle removal. Conservative assumptions which do not
allow removal or transformation are suggested for screening. Proportional
models (rollback/forward) may not be applied for screening analysis, unless
such techniques are used in conjunction with receptor modeling.
Refined models such as those in Section 4 are recommended for
PM-10 and large particles. However, where possible, particle size, gas-to-
particle formation, and their effect on ambient concentrations may be consid-
ered. For urban-wide refined analyses COM 2.0 or RAM should be used. CRSTER
and MPTER are recommended for point sources of small particles. For source-
specific analyses of complicated sources, the ISC2 model is preferred. No
model recommended for general use at this time accounts for secondary particu-
late formation or other transformations in a manner suitable for
SIP control strategy demonstrations. Where possible, the use of receptor
models38-39'105'106'107 in conjunction with dispersion models is encouraged to more
precisely characterize the emissions inventory and to validate source specific
impacts calculated by the dispersion model. A SIP development guideline,108
model reconciliation guidance,106 and an example model application109 are avail-
able to assist in PM-10 analyses and control strategy development.
Under certain conditions, recommended dispersion models are
not available or applicable. In such circumstances, the modeling approach
should be approved by the appropriate Regional Office on a case-by-case basis.
For example, where there is no recommended air quality model and area sources
are a predominant component of PM-10, an attainment demonstration may be based
on rollback of the apportionment derived from two reconciled receptor models,
if the strategy provides a conservative demonstration of attainment. At this
time, analyses involving model calculations for distances beyond 50km and
under stagnation conditions should also be justified on a case-by-case basis
(see Sections 7.2.6 and 8.2.10).
As an aid to assessing the impact on ambient air quality of
particulate matter generated from prescribed burning activities, reference 110
is available.
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7.2.4 Visibility
The visibility regulations as promulgated in December 1980
require consideration of the effect of new sources on the visibility values of
Federal Class I areas. The state of scientific knowledge concerning identify-
ing, monitoring, modeling, and controlling visibility impairment is contained
in an EPA report "Protecting Visibility: An EPA Report to Congress".42 In
1985, EPA promulgated Federal Implementation Plans (FIPs) for states without
approved visibility provisions in their SIPs. A monitoring plan was estab-
lished as part of the FIPs.b
Guidance and a screening model, VISCREEN, is contained in the
EPA document "Workbook for Plume Visual Impact Screening and Analysis
(Revised)."43 VISCREEN can be used to calculate the potential impact of a
plume of specified emissions for specific transport and dispersion conditions.
If a more comprehensive analysis is required, any refined model should be
selected in consultation with the EPA Regional Office and the appropriate
Federal Land Manager who is responsible for determining whether there is an
adverse effect by a plume on a Class I area.
PLUVUE II, listed in Appendix B, may be applied on a case-by-
case basis when refined plume visibility evaluations are needed. Plume
visibility models have been evaluated against several data sets.*4'45
b40 CFR 51.300-307
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7.2.5 Good Engineering Practice Stack Height
The use of stack height credit in excess of Good Engineering
Practice (GEP) stack height or credit resulting from any other dispersion
technique is prohibited in the development of emission limitations by 40 CFR
51.118 and 40 CFR 51.164. The definitions of GEP stack height and dispersion
technique are contained in 40 CFR 51.100. Methods and procedures for making
the appropriate stack height calculations, determining stack height credits
and an example of applying those techniques are found in references 46, 47,
48, and 49.
If stacks for new or existing major sources are found to be
less than the height defined by EPA's refined formula for determining GEP
height,0 then air quality impacts associated with cavity or wake effects due
to the nearby building structures should be determined. Detailed downwash
screening procedures18 for both the cavity and wake regions should be followed.
If more refined concentration estimates are required, the Industrial Source
Complex (ISC2) model contains algorithms for building wake calculations and
should be used. Fluid modeling can provide a great deal of additional
information for evaluating and describing the cavity and wake effects.
The EPA refined formula height is defined as H + 1.5L (see Reference 46).
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7.2.6 Long Range Transport (LRT) (i.e., beyond 50km)
Section 165(e) of the Clean Air Act requires that suspected
significant impacts on PSD Class I areas be determined. However, 50km is the
useful distance to which most Gaussian models are considered accurate for
setting emission limits. Since in many cases PSD analyses may show that
Class I areas may be threatened at distances greater than 50km from new
sources, some procedure is needed to (1) determine if a significant impact
will occur, and (2) identify the model to be used in setting an emission limit
if the Class I increments are threatened (models for this purpose should be
approved for use on a case-by-case basis as required in Section 3.2) . This
procedure and the models selected for use should be determined in consultation
with the EPA Regional Office and the appropriate Federal Land Manager (FLM).
While the ultimate decision on whether a Class I area is adversely affected is
the responsibility of the permitting authority, the FLM has an affirmative
responsibility to protect air quality related values that may be affected.
If LRT is determined to be important, then estimates utiliz-
ing an appropriate refined model for receptors at distances greater than 50 km
should be obtained. MESOPUFF II, listed in Appendix B, may be applied on a
case-by-case basis when LRT estimates are needed. Additional information on
applying this model is contained in the EPA document "A Modeling Protocol For
Applying MESOPUFF II to Long Range Transport Problems".111
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7.2.7 Modeling Guidance for Other Governmental Programs
When using the models recommended or discussed in this
guideline in support of programmatic requirements not specifically covered by
EPA regulations, the model user should consult the appropriate Federal or
State agency to ensure the proper application and use of that model. For
modeling associated with PSD permit applications that involve a Class I area,
the appropriate Federal Land Manager should be consulted on all modeling
questions.
The Offshore and Coastal Dispersion (OCD) model"2 was devel-
oped by the Minerals Management Service and is recommended for estimating air
quality impact from offshore sources on onshore flat terrain areas. The OCD
model is not recommended for use in air quality impact assessments for onshore
sources. Sources located on or just inland of a shoreline where fumigation is
expected should be treated in accordance with Section 8.2.9.
The Emissions and Dispersion Modeling System (EDMS)"3 was
developed by the Federal Aviation Administration and the United States Air
Force and is recommended for air quality assessment of primary pollutant
impacts at airports or air bases. Regulatory application of EDMS is intended
for estimating the cumulative effect of changes in aircraft operations, point
source, and mobile source emissions on pollutant concentrations. It is not
intended for PSD, SIP, or other regulatory air quality analyses of point or
mobile sources at or peripheral to airport property that are independent of
changes in aircraft operations. If changes in other than aircraft operations
are associated with analyses, a model recommended in Chapter 4, 5, or 6 should
be used.
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7.2.8 Air Pathway Analyses (Air Toxics and Hazardous Waste)
Modeling is becoming an increasingly important tool for
regulatory control agencies to assess the air quality impact of releases of
toxics and hazardous waste materials. Appropriate screening techniques114-"5
for calculating ambient concentrations due to various well-defined neutrally
buoyant toxic/hazardous pollutant releases are available.
Several regulatory programs within EPA have developed
modeling techniques and guidance for conducting air pathway analyses as noted
in references 116-129. ISC2 forms the basis of the modeling procedures for
air pathway analyses of many of these regulatory programs and, where identi-
fied, is appropriate for obtaining refined ambient concentration estimates of
neutrally buoyant continuous air toxic releases from traditional sources.
Appendix A to this Guideline contains additional models appropriate for
obtaining refined estimates of continuous air toxic releases from traditional
sources. Appendix B contains models that may be used on a case-by-case basis
for obtaining refined estimates of denser-than-air intermittent gaseous
releases, e.g., DEGADIS;130 guidance for the use of such models is also
available.131
.Many air toxics models require input of chemical properties
and/or chemical engineering variables in order to appropriately characterize
the source emissions prior to dispersion in the atmosphere; reference 132 is
one source of helpful data. In addition, EPA has numerous programs to
determine emission factors and other estimates of air toxic emissions. The
Regional Office should be consulted for guidance on appropriate emission
estimating procedures and any uncertainties that may be associated with them.
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8.2 Recommendations
8.2.1 Design Concentrations
8.2.1.1 Design Concentrations for Criteria Pollutants with
Deterministic Standards
An air quality analysis for S02, CO, Pb, and NO2 is
required to determine if the source will (1) cause a violation of the NAAQS,
or (2) cause or contribute to air quality deterioration greater than the
specified allowable PSD increment. For the former, background concentration
(see Section 9.2) should be added to the estimated impact of the source to
determine the design concentration. For the latter, the design concentration
includes impact from all increment consuming sources.
If the air quality analyses are conducted using the
period of meteorological input data recommended in Section 9.3.1.2 (e.g., 5
years of NWS data or 1 year of site-specific data), then the design concentra-
tion based on the highest, second-highest short term concentration or long
term average, whichever is controlling, should be used to determine emission
limitations to assess compliance with the NAAQS and to determine PSD incre-
ments .
When sufficient and representative data exist for
less than a 5-year period from a nearby NWS site, or when on-site data have
been collected for less than a full continuous year, or when it has been
determined that the on-site data may not be temporally representative, then
the highest concentration estimate should be considered the design value.
This is because the length of the data record may be too short to assure that
the conditions producing worst-case estimates have been adequately sampled.
The highest value is then a surrogate for the concentration that is not to be
exceeded more than once per year (the wording of the deterministic standards).
Also, the highest concentration should be used whenever selected worst-case
conditions are input to a screening technique. This specifically applies to
the use of techniques such as outlined in "Screening Procedures for Estimating
the Air Quality Impact of Stationary Sources, Revised".18 Specific guidance
for CO may be found in the "Guideline for Modeling Carbon Monoxide from
Roadway Intersections".34
If the controlling concentration is an annual
average value and multiple years of data (on-site or NWS) are used, then the
design value is the highest of the annual averages calculated for the individ-
ual years. If the controlling concentration is a quarterly average and
multiple years are used, then the highest individual quarterly average should
be considered the design value.
As long a period of record as possible should be
used in making estimates to determine design values and PSD increments. If
more than 1 year of site-specific data is available, it should be used.
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8.2.1.2 Design Concentrations for Criteria Pollutants with
Expected Exceedance Standards
Specific instructions for the determination of
design concentrations for criteria pollutants with expected exceedance
standards, ozone and PM-10, are contained in special guidance documents for
the preparation of SIPs for those pollutants.86'108 For all SIP revisions the
user should check with the Regional Office to obtain the most recent guidance
documents and policy memoranda concerning the pollutant in question.
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8.2.5 Plume Rise
The plume rise methods of Briggs56'57 are incorporated in the
preferred models and are recommended for use in all modeling applications. No
provisions in these models are made for fumigation or multistack plume rise
enhancement or the handling of such special plumes as flares; these problems
should be considered on a case-by-case basis.
Since there is insufficient information to identify and
quantify dispersion during the transitional plume rise period, gradual plume
rise is not generally recommended for use. There are two exceptions where the
use of gradual plume rise is appropriate: (1) in complex terrain screening
procedures to determine close-in impacts; (2) when calculating the effects of
building wakes. The building wake algorithm in the ISC2 model incorporates
and automatically (i.e., internally) exercises the gradual plume rise calcula-
tions. If the building wake is calculated to affect the plume for any hour,
gradual plume rise is also used in downwind dispersion calculations to the
distance of final plume rise, after which final plume rise is used.
Stack tip downwash generally occurs with poorly constructed
stacks and when the ratio of the stack exit velocity to wind speed is small.
An algorithm developed by Briggs (Hanna, et al.)57 is the recommended technique
for this situation and is found in the point source preferred models.
Where aerodynamic downwash occurs due to the adverse in-
fluence of nearby structures, the algorithms included in the ISC2 model58
should be used.
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8.2.9 Fumigation
Fumigation occurs when a plume (or multiple plumes) is
emitted into a stable layer of air and that layer is subsequently mixed to the
ground either through convective transfer of heat from the surface or because
of advection to less stable surroundings. Fumigation may cause excessively
high concentrations but is usually rather short-lived at a given receptor.
There are no recommended refined techniques to model this phenomenon. There
are, however, screening procedures (see "Screening Procedures for Estimating
the Air Quality Impact of Stationary Sources"18) that may be used to approxi-
mate the concentrations. Considerable care should be exercised in using the
results obtained from the screening techniques.
Fumigation is also an important phenomenon on and near the
shoreline of bodies of water. This can affect both individual plumes and
area-wide emissions. When fumigation conditions are expected to occur from a
source or sources with tall stacks located on or just inland of a shoreline,
this should be addressed in the air quality modeling analysis. The Shoreline
Dispersion Model (SDM) listed in Appendix B may be applied on a case-by-case
basis when air quality estimates under shoreline fumigation conditions are
needed.133 Information on the results of EPA's evaluation of this model
together with other coastal fumigation models may be found in reference 134.
Selection of the appropriate model for applications where shoreline fumigation
is of concern should be determined in consultation with the Regional Office.
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8.2.10 Stagnation
Stagnation conditions are characterized by calm or very low
wind speeds, and variable wind directions. These stagnant meteorological
conditions may persist for several hours to several days. During stagnation
conditions, the dispersion of air pollutants, especially those from low-level
emissions sources, tends to be minimized, potentially leading to relatively
high ground-level concentrations.
When stagnation periods such as these are found to occur,
they should be addressed in the air quality modeling analysis. WYNDvalley,
listed in Appendix B, may be applied on a case-by-case basis for stagnation
periods of 24 hours or longer in valley-type situations. Caution should be
exercised when applying the model to elevated point sources. Users should
consult with the appropriate Regional Office prior to regulatory application
of WYNDvalley.
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9.1.2 Recommendations
For point source applications the load or operating condition
that causes maximum ground-level concentrations should be established. As a
minimum, the source should be modeled using the design capacity (100 percent
load). If a source operates at greater than design capacity for periods that
could result in violations of the standards or PSD increments, this load*1
should be modeled. Where the source operates at substantially less than
design capacity, and the changes in the stack parameters associated with the
operating conditions could lead to higher ground level concentrations, loads
such as 50 percent and 75 percent of capacity should also be modeled. A range
of operating conditions should be considered in screening analyses; the load
causing the highest concentration, in addition to the design load, should be
included in refined modeling. The following example for a power plant is
typical of the kind of data on source characteristics and operating conditions
that may be needed. Generally, input data requirements for air quality models
necessitate the use of metric units; where English units are common for
engineering usage, a conversion to metric is required.
a. Plant layout. The connection scheme between boilers and
stacks, and the distance and direction between stacks, building parameters
(length, width, height, location and orientation relative to stacks) for plant
structures which house boilers, control equipment, and surrounding buildings
within a distance of approximately five stack heights.
b. Stack parameters. For all stacks, the stack height and
inside diameter (meters), and the temperature (K) and volume flow rate (actual
cubic meters per second) or exit gas velocity (meters per second) for
operation at 100 percent, 75 percent and 50 percent load.
c. Boiler size. For all boilers, the associated megawatts,
106 BTU/hr, and pounds of steam per hour, and the design and/or actual fuel
consumption rate for 100 percent load for coal (tons/hour), oil
(barrels/hour), and natural gas (thousand cubic feet/hour).
d. Boiler parameters. For all boilers, the percent excess
air used, the boiler type (e.g., wet bottom, cyclone, etc.), and the type of
firing (e.g., pulverized coal, front firing, etc.).
e. Operating conditions. For all boilers, the type, amount
and pollutant contents of fuel, the total hours of boiler operation and the
boiler capacity factor during the year, and the percent load for peak
conditions.
Malfunctions which may result in excess emissions are not considered to
be a normal operating condition. They generally should not be considered in
determining allowable emissions. However, if the excess emissions are the
result of poor maintenance, careless operation, or other preventable
conditions, it may be necessary to consider them in determining source impact.
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f. Pollution control equipment parameters. For each boiler
served and each pollutant affected, the type of emission control equipment,
the year of its installation, its design efficiency and mass emission rate,
the data of the last test and the tested efficiency, the number of hours of
operation during the latest year, and the best engineering estimate of its
projected efficiency if used in conjunction with coal combustion; data for any
anticipated modifications or additions.
g. Data for new boilers or stacks. For all new boilers and
stacks under construction and for all planned modifications to existing
boilers or stacks, the scheduled date of completion, and the data or best
estimates available for items (a) through (f) above following completion of
construction or modification.
In stationary point source applications for compliance with
short term ambient standards, SIP control strategies should be tested using
the emission input shown on Table 9-1. When using a refined model, sources
should be modeled sequentially with these loads for every hour of the year.
To evaluate SIPs for compliance with quarterly and annual standards, emission
input data shown in Table 9-1 should again be used. Emissions from area
sources should generally be based on annual average conditions. The source
input information in each model user's guide should be carefully consulted and
the checklist in Appendix C should also be consulted for other possible
emission data that could be helpful. PSD NAAQS compliance demonstrations
should follow the emission input data shown in Table 9-2. For purposes of
emissions trading, new source review and demonstrations, refer to current EPA
policy and guidance to establish input data.
Line source modeling of streets and highways requires data
on the width of the roadway and the median strip, the types and amounts of
pollutant emissions, the number of lanes, the emissions from each lane and the
height of emissions. The location of the ends of the straight roadway
segments should be specified by appropriate grid coordinates. Detailed
information and data requirements for modeling mobile sources of pollution are
provided in the user's manuals for each of the models applicable to mobile
sources.
The impact of growth on emissions should be considered in
all modeling analyses covering existing sources. Increases in emissions due
to planned expansion or planned fuel switches should be identified. Increases
in emissions at individual sources that may be associated with a general
industrial/commercial/residential expansion in multi-source urban areas should
also be treated. For new sources the impact of growth on emissions should
generally be considered for the period prior to the start-up date for the
source. Such changes in emissions should treat increased area source emis-
sions, changes in existing point source emissions which were not subject to
preconstruction review, and emissions due to sources with permits to construct
that have not yet started operation.
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TABLE 9-1 MODEL EMISSION INPUT DATA FOR POINT SOURCES1
Averaging Time
Emission Limit
(#/MMBtu)2
Operating Level
(MMBtu/hr)z
Operating Factor
y\ (e.g., hr/yr, hr/day)
Stationary Point Source(s) Subject to SIP Emission Li*it(s) Evaluation for
Compliance with tabient Standards (Including Areawide Dewmst rat ions)
Annual & quarterly:
Short term:
Maximum allowable
emission limit or
federally enforceable
permit limit.
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Actual or design capacity
(whichever is greater),
or federally enforceable
permit condition.
Actual or design capacity
(whichever is greater),
or federally enforceable
permit condition.*
Actual operating
factor averaged over
most recent 2 years.3
Continuous opera-
tion, i.e., all hours
of each time period
under consideration
(for all hours of the
meteorological data
base).6
Nearby Background Source(s)
Same input requirements as for stationary point source(s) above.
Other Background Source(s)
If modeled (see Section 9.2.3), input data requirements are defined below.
Annual & quarterly:
Short term:
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Annual level when actu-
ally operating, averaged
over the most recent 2
years.3
Annual level when actu-
ally operating, averaged
over the most recent 2
years.3
Actual operating
factor averaged over
the most recent 2
years.3
Continuous opera-
tion, i.e., all hours
of each time period
under consideration
(for all hours of the
meteorological data
base).6
1 The model input data requirements shown on this table apply to stationary source control strategies for STATE
IMPLEMENTATION PLANS. For purposes of emissions trading, new source review, or prevention of significant
deterioration, other model input criteria may apply. Refer to the policy and guidance for these programs to
establish the input data.
2 Terminology applicable to fuel burning sources; analogous terminology (e.g., ^/throughput) may be used for
other types of sources.
3 Unless it is determined that this period is not representative.
* Operating levels such as 50 percent and 75 percent of capacity should also be modeled to determine the load
causing the highest concentration.
6 If operation does not occur for all hours of the time period of consideration (e.g., 3 or 24 hours) and the
source operation is constrained by a federally enforceable permit condition, an appropriate adjustment to the
modeled emission rate may be made (e.g., if operation is only 8:00 a.m. to 4:00 p.m. each day, only these
hours will be modeled with emissions from the source. Modeled emissions should not be averaged across non-
operating time periods.)
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Revised 2/93
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TABLE 9-2 POINT SOURCE MODEL INPUT DATA (EMISSIONS) FOR PSD HMDS COMPLIANCE DEMONSTRATIONS
Averaging Time
Emission Limit
(tf/MMBtu)1
Operating Level
(HMBtu/hr)1
Operating Factor
(e.g., hr/yr, hr/day)
Proposed Major New or Modified Source
Annual & quarterly:
Short term:
(< 24 hours)
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Design capacity or fed-
erally enforceable permit
condition.
Design capacity or fed-
erally enforceable permit
condition.3
Continuous operation
(i.e., 8760 hours).2
Continuous operation
(i.e., all hours of
each time period un-
der consideration)
(for all hours of the
meteorological data
base).2
Nearby Background Source(s)*
Annual & quarterly:
Short term:
(< 24 hours)
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Maximum allowable emis-
sion limit or federally
enforceable permit
Iimit.
Actual or design capacity
(whichever is greater),
or federally enforceable
permit condition.
Actual or design capacity
(whichever is greater),
or federally enforceable
permit condition.
Actual operating
factor averaged over
the most recent 2
years. '
Continuous operation
(i.e., all hours of
each time period un-
der consideration)
(for all hours of the
meteorological data
base).2
Other Background Source(s)6
Annual & quarterly:
Short term
(< 24 hours)
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Maximum allowable emis-
sion limit or federally
enforceable permit
limit.
Annual level when actu-
ally operating, averaged
over the most recent 2
years.6
Annual level when actu-
ally operating, averaged
over the most recent 2
years.
Actual operating
factor averaged over
the most recent 2
years.
Continuous operation
(i.e., all hours of
each time period un-
der consideration)
(for all hours of the
meteorological data
base).2
Terminology applicable to fuel burning sources; analogous terminology (e.g., ^/throughput) may be used for
other types of sources.
If operation does not occur for all hours of the time period of consideration (e.g., 3 or 24 hours) and the
source operation is constrained by a federally enforceable permit condition, an appropriate adjustment to the
modeled emission rate may be made (e.g., if operation is only 8:00 a.m. to 4:00 p.m. each day, only these
hours will be modeled with emissions from the source. Modeled emissions should not be averaged across non-
operating time periods.
Operating levels such as 50 percent and 75 percent of capacity should also be modeled to determine the load
causing the highest concentration.
Includes existing facility to which modification is proposed if the emissions from the existing facility will
not be affected by the modification. Otherwise use the same parameters as for major modification.
Unless it is determined that this period is not representative.
Generally, the ambient impacts from non-nearby background sources can be represented by air quality data
unless adequate data do not exist.
For those permitted sources not yet in operation or that have not established an appropriate factor,
continuous operation (i.e., 8760 hours) should be used.
9-6
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9.2.2 Recommendations (Isolated Single Source)
Two options are available to determine the background
concentration near isolated sources.
Option One: Use air quality data collected in the vicinity
of the source to determine the background concentration for the averaging
times of concern.6 Determine the mean background concentration at each
monitor by excluding values when the source in question is impacting the
monitor. The mean annual background is the average of the annual concentra-
tions so determined at each monitor. For shorter averaging periods, the
meteorological conditions accompanying the concentrations of concern should be
identified. Concentrations for meteorological conditions of concern, at
monitors not impacted by the source in question, should be averaged for each
separate averaging time to determine the average background value. Monitoring
sites inside a 90° sector downwind of the source may be used to determine the
area of impact. One hour concentrations may be added and averaged to deter-
mine longer averaging periods.
Option Two: If there are no monitors located in the vicin-
ity of the source, a "regional site" may be used to determine background. A
"regional site" is one that is located away from the area of interest but is
impacted by similar natural and distant man-made sources.
9.2.3 Recommendations (Multi-Source Areas)
In multi-source areas two components of background should be
determined.
Nearby Sources: All sources expected to cause a significant
concentration gradient in the vicinity of the source or sources under consid-
eration for emission limit(s) should be explicitly modeled. For evaluation
for compliance with the short term and annual ambient standards, the nearby
sources should be modeled using the emission input data shown in Table 9-1 or
9-2. The number of such sources is expected to be small except in unusual
situations. The nearby source inventory should be determined in consultation
with the reviewing authority. It is envisioned that the nearby sources and
the sources under consideration will be evaluated together using an appropri-
ate Appendix A model.
The impact of the nearby sources should be examined at
locations where interactions between the plume of the point source under
consideration and those of nearby sources (plus natural background) can occur.
Significant locations include: (1) the area of maximum impact of the point
source; (2) the area of maximum impact of nearby sources; and (3) the area
where all sources combine to cause maximum impact. These locations may be
identified through trial and error analyses.
eFor purposes of PSD, the location of monitors as well as data quality
assurance procedures must satisfy requirements listed in the PSD Monitoring
Guidelines.63
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Other Sources: That portion of the background attributable
to all other sources (e.g., natural sources, minor sources and distant major
sources) should be determined by the procedures found in Section 9.2.2 or by
application of a model using Table 9-1 or 9-2.
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9.3.3.2 Recommendations
Site-specific Data Collection
The document "On-Site Meteorological Program
Guidance for Regulatory Modeling Applications"66 provides recommendations on
the collection and use of on-site meteorological data. Recommendations on
characteristics, siting, and exposure of meteorological instruments and on
data recording, processing, completeness requirements, reporting, and archiv-
ing are also included. This publication should be used as a supplement to the
limited guidance on these subjects now found in the "Ambient Monitoring
Guidelines for Prevention of Significant Deterioration"63 and the "Quality
Assurance Handbook for Air Pollution Measurement Systems"67 contains such
information for meteorological measurements. As a minimum, site-specific
measurements of ambient air temperature, transport wind speed and direction,
and the parameters to determine Pasquill-Gifford stability categories should
be available in meteorological data sets to be used in modeling. Care should
be taken to ensure that monitors are located to represent the area of concern
and that they are not influenced by very localized effects. Site-specific
data for model applications should cover as long a period of measurement as is
possible to ensure adequate representation of "worst-case" meteorology. The
Regional Office will determine the appropriateness of the measurement loca-
tions .
All site-specific data should be reduced to hourly
averages. Table 9-3 lists the wind related parameters and the averaging time
requirements.
Temperature Measurements
Temperature measurements should be made at standard
shelter height (2m)-in accordance with the guidance in reference 66.
Wind Measurements
Wind speed and direction should be measured at or
near plume height for use in estimating transport and dilution. To approxi-
mate this, if a source has a stack below 100m, select the stack top height as
the transport wind measurement height. For sources with stacks extending
above 100m, a 100m tower is suggested unless the stack top is significantly
above 100 meters (200m or more). In cases with stacks 200m or above, the
Regional Office should determine the appropriate measurement height on a case-
by-case basis. Remote sensing may be a feasible alternative. The dilution
wind speed used in determining plume rise and also used in the Gaussian
dispersion equation is, by convention, defined as the wind speed at stack
top.
Multiple level (typically three or more) measure-
ments of wind temperature and turbulence (wind fluctuation statistics) are
required for refined modeling applications in complex terrain. Such measure-
ments should be obtained up to the representative plume height(s) of interest
(i.e., the plume height(s) under those conditions important to the determina-
tion of the design concentration). The representative plume height(s) of
interest should be determined using an appropriate complex terrain screening
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procedure (e.g., CTSCREEN) and should be documented in the monitoring/modeling
protocol. The necessary meteorological measurements should be obtained from
an appropriately sited meteorological tower augmented by SODAR if the repre-
sentative plume height(s) of interest exceed 100m. The meteorological tower
need not exceed the lesser of the representative plume height of interest (the
highest plume height if there is more than one plume height of interest) or
100m.
For routine tower and surface measurements, the
wind speed should be measured using an anemometer, and the wind direction
measured using a horizontal vane. Specifications for wind measuring instru-
ments and systems are contained in the "On-Site Meteorological Program
Guidance for Regulatory Modeling Applications".66
Stability Categories
The Pasquill-Gifford (P-G) stability categories, as
originally defined, couple near-surface measurements of wind speed with
subjectively determined insolation assessments based on hourly cloud cover and
ceiling observations. The wind speed measurements are made at or near 10m.
The insolation rate is typically assessed using observations of cloud cover
and ceiling based on criteria outlined by Turner.50 In the absence of site
specific observations of cloud cover and ceiling, alternative procedures using
wind fluctuation statistics (i.e., the aA and aE methods)66 and Turner's method
with off-site cloud cover and ceiling and on-site 10m wind speed are recom-
mended.
The two methods of stability classification which
use wind fluctuation statistics, the Qk and ffE methods, are described in
detail in EPA's "On-Site Meteorological Program Guidance for Regulatory-
Modeling Applications"66 (note applicable tables in Chapter 6). In the case of
the crA method it should be noted that wind meander may occasionally bias the
determination of 0A and thus lead to an erroneous determination of the P-G
stability category. To minimize wind direction meander contributions, aA may
be determined for each of four 15-minute periods in an hour. However, 360
samples are needed during each 15-minute period. If the aA method is being
used for stability determinations in these situations, take the square root of
one-quarter of the sum of the square of the four 15 minute ffA's, as illustrat-
ed in the footnote to Table 9-3. While this approach is an acceptable
alternative for determining stability, as qualified above, ffA's calculated in
this manner are not likely to be suitable for input to models under develop-
ment that are desigried to accept on-site hourly a's based on 60-minute
periods. For additional information on stability classification using wind
fluctuation statistics, see references 68-72.
In summary, when on-site data are being used, P-G
stability categories should be estimated based on:
9-17 Revised 2/93
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(1) Turner's method55 using site-specific data which
include cloud cover, ceiling height and surface
(~10m) wind speeds;
(2)
-------
TABLE 9-3
Averaging Times for Site-Specific Wind and Turbulence Measurements
Parameter Averaging Time
Surface wind speed 1-hr
(for use in stability
determinations)
Transport direction 1-hr
Dilution wind speed 1-hr
Turbulence measurements l-hr1
(crE and aA) for use
in stability determinations
1 To minimize meander effects in
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(THESE PAGES INTENTIONALLY DELETED)
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10.1.4 Evaluation of Models
A number of actions are being taken to ensure that the
best model is used correctly for each regulatory application and that a model
is not arbitrarily imposed. First, this guideline clearly recommends the most
appropriate model be used in each case. Preferred models, based on a number
of factors, are identified for many uses. General guidance on using alterna-
tives to the preferred models is also provided. Second, all the models in
eight categories (i.e., rural, urban, industrial complex, reactive pollutants,
mobile source, complex terrain, visibility and long range transport) that are
candidates for inclusion in this guideline are being subjected to a systematic
performance evaluation and a peer scientific review.83 The same data bases are
being used to evaluate all models within each of eight categories.
Statistical performance measures, including measures of difference (or
residuals) such as bias, variance of difference and gross variability of the
difference, and measures of correlation such as time, space, and time and
space combined as recommended by the AMS Woods Hole Workshop," are being
followed. The results of the scientific review are being incorporated in this
guideline and will be the basis for future revision.12-13 Third, more specific
information has been provided for justifying the site specific use of alterna-
tive models in the documents "Interim Procedures for Evaluating Air Quality
Models",15 and the "Protocol for Determining the Best Performing Model".17
Together these documents provide methods that allow a judgment to be made as
to what models are most appropriate for a specific application. For the
present, performance and the theoretical evaluation of models are being used
as an indirect means to quantify one element of uncertainty in air pollution
regulatory decisions.
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11.0 REGULATORY APPLICATION OF MODELS
11.1 Discussion
Procedures with respect to the review and analysis of air quality
modeling and data analyses in support of SIP revisions, PSD permitting or
other regulatory requirements need a certain amount of standardization to
ensure consistency in the depth and comprehensiveness of both the review and
the analysis itself. This section recommends procedures that permit some
degree of standardization while at the same time allowing the flexibility
needed to assure the technically best analysis for each regulatory applica-
tion.
Dispersion model estimates, especially with the support of
measured air quality data, are the preferred basis for air quality demonstra-
tions. Nevertheless, there are instances where the performance of recommended
dispersion modeling techniques, by comparison with observed air quality data,
may be shown to be less than acceptable. Also, there may be no recommended
modeling procedure suitable for the situation. In these instances, emission
limitations may be established solely on the basis of observed air quality
data as would be applied to a modeling analysis. The same care should be
given to the analyses of the air quality data as would be applied to a
modeling analysis.
The current NAAQS for SO2 and CO are both stated in terms
of a concentration not to be exceeded more than once a year. There
is only an annual standard for NO2 and a quarterly standard for Pb.
The PM-10 and ozone standards permit the exceedance of a concentration
on an average of not more than once a year; the convention is to
average over a 3-year period.5>86'103 This
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11.2 Recommendations
11.2.1 Analysis Requirements
Every effort should be made by the Regional Office to meet
with all parties involved in either a SIP revision or a PSD permit application
prior to the start of any work on such a project. During this meeting, a
protocol should be established between the preparing and reviewing parties to
define the procedures to be followed, the data to be collected, the model to
be used, and the analysis of the source and concentration data. An example of
requirements for such an effort is contained in the Air Quality Analysis
Checklist included here as Appendix C. This checklist suggests the level of
detail required to assess the air quality resulting from the proposed action.
Special cases may require additional data collection or analysis and this
should be determined and agreed upon at this preapplication meeting. The
protocol should be written and agreed upon by the parties concerned, although
a formal legal document is not intended. Changes in such a protocol are often
required as the data collection and analysis progresses. However, the
protocol establishes a common understanding of the requirements.
An air quality analysis should begin with a screening
model to determine the potential of the proposed source or control strategy to
violate the PSD increment or NAAQS. It is recommended that the screening
techniques found in "Screening Procedures for Estimating the Air Quality
Impact of Stationary Sources"18 be used for point source analyses. Screening
procedures for area source analysis are discussed in "Applying Atmospheric
Simulation Models to Air Quality Maintenance Areas".*7 For mobile source
impact assessments the "Guideline for Modeling Carbon Monoxide from Roadway
Intersections"34 is available.
If the concentration estimates from screening techniques
indicate that the PSD increment or NAAQS may be approached or exceeded, then a
more refined modeling analysis is appropriate and the model user should select
a model according to recommendations in Sections 4-8. In some instances, no
refined technique may be specified in this guide for the situation. The model
user is then encouraged to submit a model developed specifically for the case
at hand. If that is not possible, a screening technique may supply the needed
results.
Regional Offices should require permit applicants to
incorporate the pollutant contributions of all sources into their analysis.
Where necessary this may include emissions associated with growth in the area
of impact of the new or modified source's impact. PSD air quality assessments
should consider the amount of the allowable air quality increment that has
already been granted to any other sources. Therefore, the most recent source
applicant should model the existing or permitted sources in addition to the
one currently under consideration. This would permit the use of newly
acquired data or improved modeling techniques if
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11.2.3 Emission Limits
11.2.3.1 Design Concentrations
Emission limits should be based on concentration
estimates for the averaging time that results in the most stringent control
requirements. The concentration used in specifying emission limits is called
the design value or design concentration and is a sum of the concentration
contributed by the source and the background concentration.
To determine the averaging time for the design
value, the most restrictive National Ambient Air Quality Standard (NAAQS)
should be identified by calculating, for each averaging time, the ratio of the
applicable NAAQS (S) minus background (B) to the predicted concentration (P)
(i.e., (S-B)/P). The averaging time with the lowest ratio identifies the most
restrictive standard. If the annual average is the most restrictive, the
highest estimated annual average concentration from one or a number of years
of data is the design value. When short term standards are most restrictive,
it may be necessary to consider a broader range of concentrations than the
highest value. For example, for pollutants such as SO2, the highest, second-
highest concentration is the design value. For pollutants with statistically
based NAAQS, the design value is found by determining the more restrictive of:
(1) the short-term concentration that is not expected to be exceeded more than
once per year over the period specified in the standard, or (2) the long-term
concentration that is not expected to exceed the long-term NAAQS. Determina-
tion of design values for PM-10 is presented in more detail in the "PM-10 SIP
Development Guideline".103
When the highest, second-highest concentration
is used in assessing potential violations of a short term NAAQS, criteria that
are identified in "Guideline for Interpretation of Air Quality Standards"88
should be followed.- This guideline specifies that a violation of a short term
standard occurs at a site when the standard is exceeded a second time. Thus,
emission limits that protect standards for averaging times of 24 hours or less
are appropriately based on the highest, second-highest estimated concentration
plus a background concentration which can reasonably be assumed to occur with
the concentration.
11.2.3.2 NAAQS Analyses for New or Modified Sources
For new or modified sources predicted to have a
significant ambient impact63 and to be located in areas designated attainment
or unclassifiable for the SO2, Pb, N02, or CO NAAQS, the demonstration as to
whether the source will cause or contribute to an air quality violation should
be based on: (1) the highest estimated annual average concentration deter-
mined from annual averages of individual years; or (2) the highest, second-
highest estimated concentration for averaging times of 24-hours or less; and
(3) the significance of the spatial and temporal contribution to any modeled
violation. For Pb, the highest estimated concentration based on an individual
calendar quarter averaging period should be used. Background concentrations
should be added to the estimated impact of the source. The most restrictive
standard should be used in all cases to assess the threat of an air quality
violation. For new or modified sources predicted to have a significant
ambient impact63 in areas designated attainment or unclassifiable for the
11-7 Revised 2/93
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PM-10 NAAQS, the demonstration of whether or not the source will cause or
contribute to an air quality violation should be based on sufficient data to
show whether: (1) the projected 24-hour average concentrations will exceed the
24-hour NAAQS more than once per year, on average; (2) the expected (i.e.,
average) annual mean concentration will exceed the annual NAAQS; and (3) the
source contributes significantly, in a temporal and spatial sense, to any
modeled violation.
11.2.3.3 PSD Air Quality Increments and Impacts
The allowable PSD increments for criteria
pollutants are established by regulation and cited in 40 CFR 51.166. These
maximum allowable increases in pollutant concentrations may be exceeded once
per year at each site, except for the annual increment that may not be
exceeded. The highest, second-highest increase in estimated concentrations
for the short term averages as determined by a model should be less than or
equal to the permitted increment. The modeled annual averages should not
exceed the increment.
Screening techniques defined in Sections 4 and 5
can sometimes be used to estimate short term incremental concentrations for
the first new source that triggers the baseline in a given area. However,
when multiple increment- consuming sources are involved in the calculation, the
use of a refined model with at least 1 year of on-site or 5 years of off-site
NWS data is normally required. In such cases, sequential modeling must
demonstrate that the allowable increments are not exceeded temporally and
spatially, i.e., for all receptors for each time period throughout the year(s)
(time period means the appropriate PSD averaging time, e.g., 3-hour, 24-hour,
etc.).
The PSD regulations require an estimation of the
S02, particulate matter, and N02 impact on any Class I area. Normally,
Gaussian models should not be applied at distances greater than can be
accommodated by the steady state assumptions inherent in such models. The
maximum distance for refined Gaussian model application for regulatory
purposes is generally considered to be 50km. Beyond the 50km range, screening
techniques may be used to determine if more refined modeling is needed. If
refined models are needed, long range transport models should be considered in
accordance with Section 7.2.6. As previously noted in Sections 3 and 7, the
need to involve the Federal Land Manager in decisions on potential air quality
impacts, particularly in relation to PSD Class I areas, cannot be overempha-
sized.
11.2.3.4 Emissions Trading Policy (Bubbles)
EPA's final Emissions Trading Policy, commonly
referred to as the "bubble policy," was published in the Federal Register in
1986.89 Principles contained in the policy should be used to evaluate ambient
impacts of emission trading activities.
Emission increases and decreases within the
bubble should result in ambient air quality equivalence. Two levels of
analysis are defined for establishing this equivalence. In a Level I analysis
the source configuration and setting must meet certain limitations (defined in
11-8 Revised 2/93
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the policy) that ensure ambient equivalence; no modeling is required. In a
Level II analysis a modeling demonstration of ambient equivalence is required
but only the sources involved in the emissions trade are modeled. The
resulting ambient estimates of net increases/decreases are compared to a set
of significance levels to determine if the bubble can be approved. A Level II
analysis requires the use of a refined model and the most recent readily
available full year of representative meteorological data. Sequential
modeling must demonstrate that the significance levels are met temporally and
spatially, i.e., for all receptors for each time period throughout the year
(time period means the appropriate NAAQS averaging time, e.g., 3-hour,
24-hour, etc.).
For those bubbles that cannot meet the Level I
or Level II requirements, the Emissions Trading Policy allows for a Level III
analysis. A Level III analysis, from a modeling standpoint, is generally
equivalent to the requirements for a standard SIP revision where all sources
(and background) are considered and the estimates are compared to the NAAQS as
in Section 11.2.3.2.
The Emissions Trading Policy allows States to
adopt generic regulations for processing bubbles. The modeling procedures
recommended in this guideline apply to such generic regulations. However, an
added requirement is that the modeling procedures contained in any generic
regulation must be replicable such that there is no doubt as to how each
individual bubble will be modeled. In general this means that the models, the
data bases and the procedures for applying the model must be defined in the
regulation. The consequences of the replicability requirement are that
bubbles for sources located in complex terrain and certain industrial sources
where judgments must be made on source characterization cannot be handled
generically.
11-9 Revised 2/93
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78. Bowne, N.E., 1981. Validation and Performance Criteria for Air Quality
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12-8 Revised 2/93
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89. Environmental Protection Agency, 1986. Emissions Trading Policy
Statement; General Principles for Creation, Banking, and Use of Emission
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90. Environmental Research and Technology, 1987. User's Guide to the Rough
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91. Burns, D.J., S.G. Perry and A.J. Cimorelli, 1991. An Advanced Screening
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92. Perry, S.G., 1992. CTDMPLUS: A Dispersion Model for Sources near Complex
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93. Paumier, J.O., S.G. Perry and D.J. Burns, 1992. CTDMPLUS: A Dispersion
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94. Environmental Protection Agency, 1986. Evaluation of Mobile Source Air
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95. Shannon, J.D., 1987. Mobile Source Modeling Review. A report prepared
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96. Environmental Protection Agency, 1991. Emission Inventory Requirements
for Carbon Monoxide State Implementation Plans. EPA Publication No.
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97. Environmental Protection Agency, 1992. Guideline for Regulatory
Application of the Urban Airshed Model for Areawide Carbon Monoxide. EPA
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98. Environmental Protection Agency, 1992. Technical Support Document to Aid
States with the Development of Carbon Monoxide State Implementation
Plans. EPA Publication No. EPA-452/R-92-003. U.S. Environmental
Protection Agency, Research Triangle Park, NC. (NTIS No. PB 92-233055)
99. Environmental Protection Agency, 1986. Evaluation of Short-Term Long-
Range Transport Models, Volumes I and II. EPA Publication Nos.
EPA-450/4-86-016a and b. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS Nos. PB 87-142337 and PB 87-142345)
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100. McNider, R.T., 1987. Review of Short-Term Long-Range Models. A report
prepared under a cooperative agreement with the Environmental Protection
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101. Lamb, R.G., 1983. A Regional Scale (1,000km) Model of Photochemical Air
Pollution, Part I-Theoretical Formulation, Part II-Input Processor
Network Design, and Part Ill-Tests of Numerical Algorithms. EPA
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EPA-600/3-85-037. U.S. Environmental Protection Agency, Research
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102. Young, J.O., M. Aissa, T.L. Boehm et al., 1989. Development of the
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103. Environmental Protection Agency, 1991. The Regional Oxidant Model (ROM)
User's Guide. Part 1: The ROM Preprocessors. EPA Publication No.
EPA-600/8-90-083a (NTIS No. PB 91-171926); Part 2: The ROM Processor
Network. EPA Publication No. EPA-600/8-90-083b (NTIS No. PB 91-171934);
Part 3: The Core Model. EPA Publication No. EPA-600/8-90-083c (NTIS No.
PB 91-171942). U.S. Environmental Protection Agency/ Research Triangle
Park, NC.
104. Chang, J.S., R.A. Brost, I.S.A. Isaksen, S. Madronich, P. Middleton, W.R.
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Deposition Model: Physical Concepts and Formulation. Journal of
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105. Environmental Protection Agency/ 1987. Protocol for Applying and
Validating the CMB. U.S. Environmental Protection Agency. EPA
Publication No. EPA-450/4-87-010. U.S. Environmental Protection Agency,
Research Triangle Park, NC. (NTIS No. PB 87-206496)
106. Environmental Protection Agency, 1987. Protocol for Reconciling
Differences Among Receptor and Dispersion Models. EPA Publication No.
EPA-450/4-87-008. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 87-206504)
107. Environmental Protection Agency, 1988. Chemical Mass Balance Model
Diagnostics. EPA Publication No. EPA-450/4-88-005. U.S. Environmental
Protection Agency, Research Triangle Park, NC. (NTIS No. PB 88-208319)
108. Environmental Protection Agency, 1987. PM-10 SIP Development Guideline.
EPA Publication No. EPA-450/2-86-001. U.S. Environmental Protection
Agency, Research Triangle Park, NC. (NTIS No. PB 87-206488)
109. Environmental Protection Agency, 1987. Example Modeling to Illustrate
SIP Development for The PM-10 NAAQS. EPA Publication No. EPA-450/4-87-012
U.S. Environmental Protection Agency, Research Triangle Park, NC. (NTIS
No. PB 87-205191)
12-10 Revised 2/93
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110. Sestak, M. L. and A. R. Riebau, 1988. SASEM Simple Approach Smoke
Estimation Model. U.S. Bureau of Land Management, Technical Note 382.
BLM/YA/PT-88/003 + 7000. Available from Printed Materials Distribution
Section, BLM Service Center (SC-658B), Denver, CO 80225-0047. (NTIS No.
PB 90-185653)
111. Environmental Protection Agency, 1992. A Modeling Protocol for Applying
Mesopuff II to Long Range Transport Problems. EPA Publication No.
EPA-454/R-92-021. U.S. Environmental Protection Agency, Research
Triangle Park, NC.
112. DiCristofaro, D.C. and S.R. Hanna, 1989. The Offshore and Coastal
Dispersion (OCD) Model, Volume I: User's Guide, Volume II: Appendices.
Version 4 Prepared for Minerals Management Services by Sigma Research
Corporation, Westford, MA. (Docket No. A-88-04, II-D-A-06)
113. Federal Aviation Administration, 1988. A Microcomputer Pollution Model
for Civilian Airports and Air Force Bases, Model Description, Model
Application and Background, and EDMS User's Guide (June 1991) . Federal
Aviation Administration Publication Nos. FAA-EE-88-4 and 5; FAA-EE-91-3,
respectively. United States Air Force Publication Nos. ESL-TR-88-53 and
55; ESL-TR-91-31, respectively. Federal Aviation Administration, Office
of Environment and Energy, Washington, D.C. (NTIS Nos. ADA 199003,
ADA 199794, and ADA 240528, respectively)
114. Environmental Protection Agency, 1992. Workbook of Screening Techniques
for Assessing Impacts of Toxic Air Pollutants (Revised). EPA Publication
No. EPA-454/R-92-024. U.S. Environmental Protection Agency, Research
Triangle Park, NC.
115. Environmental Protection Agency, 1990. User's Guide to TSCREEN: A Model
for Screening,Toxic Air Pollutant Concentrations. EPA Publication No.
EPA-450/4-90-013. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 91-141820)
116. Environmental Protection Agency, 1989. Hazardous Waste TSDF Fugitive
Particulate Matter Air Emissions Guidance Document. EPA Publication No.
EPA-450/3-89-019. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 90-103250)
117. Environmental Protection Agency/ 1989. Procedures for Conducting Air
Pathway Analyses for Superfund Applications, Volume I Applications of Air
Pathway Analyses for Superfund Activities and Volume IV Procedures for
Dispersion Modeling and Air Monitoring for Superfund Air Pathway
Analysis, EPA-450/1-89-001 and 004. U.S. Environmental Protection
Agency, Research Triangle Park, NC. (NTIS Nos. PB 89-113374 and
PB 89-113382)
118. Environmental Protection Agency, 1988. Air Dispersion Modeling as
Applied to Hazardous Waste Incinerator Evaluations, An Introduction For
the Permit Writer. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (Docket No. A-88-04, II-J-10)
12-11 Revised 2/93
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119. Environmental Protection Agency, 1989. U.S. EPA Office of Toxic
Substances Graphical Exposure Modeling System (GEMS) User's Guide and
GAMS Version 3.0 User's Guide (DRAFT). Prepared under Contract No.
68-02-0481 for the U.S. Environmental Protection Agency/ Washington, D.C.
(Docket No. A-88-04, II-J-5a and II-J-13)
120. Federal Emergency Management Agency, 1989. Handbook of Chemical Hazard
Analysis Procedures. Available on request by writing to: Federal
Emergency Management Agency, Publications Office, 500 C Street, S.W.,
Washington, D.C. 20472.
121. Environmental Protection Agency, 1987. Technical Guidance for Hazards
Analysis: Emergency Planning for Extremely Hazardous Substances.
Available on request by telephone: 1-(800)-535-0202.
122. Environmental Protection Agency, 1988. Superfund Exposure Assessment
Manual. EPA-540/1-88-001, OSWER Directive 9285.5-1. Office of Remedial
Response, Washington, D.C. 20460. (NTIS No. PB 89-135859)
123. Environmental Protection Agency, 1989. Incineration of Sewage Sludge;
Technical Support Document. Office of Water Regulations and Standards,
Washington, D.C. 20460. (NTIS No. PB 89-136592)
124. Environmental Protection Agency, 1989. Sludge Incineration Modeling
(SIM) System User's Guide (Draft). Office of Pesticides and Toxic
Substances, Exposure Evaluation Division, Washington, D.C. 20460.
(NTIS No. PB 89-138762)
125. Environmental Protection Agency, 1989. Risk Assessment Guidance for
Superfund. Volume I: Human Health Evaluation Manual Part A. (Interim
Final). OSWER Directive 9285.7-Ola. Office of Solid Waste and Emergency
Response, Washington, D.C. 20460.
126. Environmental Protection Agency, 1986. User's Manual for the Human
Exposure Model (HEM). EPA Publication No. EPA-450/5-86-001. Office of
Air Quality Planning and Standards, Research Triangle Park, NC. 27711.
127. Environmental Protection Agency, 1992. A Tiered Modeling Approach for
Assessing the Risks Due to Sources of Hazardous Air Pollutants. EPA
Publication No. EPA-450/4-92-001. Environmental Protection Agency,
Research Triangle Park, NC. (NTIS No. PB 92-164748)
128. Environmental Protection Agency, 1992. Toxic Modeling System Short-term
(TOXST) User's Guide. EPA Publication No. EPA-450/4-92-002.
Environmental Protection Agency, Research Triangle Park, NC.
129. Environmental Protection Agency, 1992. Toxic Modeling System Long-term
(TOXLT) User's Guide. EPA Publication No. EPA-450/4-92-003.
Environmental Protection Agency, Research Triangle Park, NC.
130. Environmental Protection Agency, 1989. User's Guide for the DEGADIS 2.1
Dense Gas Dispersion Model. EPA Publication No. EPA-450/4-89-019. U.S.
Environmental Protection Agency, Research Triangle Park, NC. (NTIS No.
PB 90-213893)
12-12 Revised 2/93
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131. Environmental Protection Agency, 1991. Guidance on the Application of
Refined Models for Air Toxics Releases. EPA Publication No.
EPA-450/4-91-007. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 91-190983)
132. Perry, R. H. and Chilton, C. H., 1973. Chemical Engineers' Handbook,
Fifth Edition, McGraw-Hill Book Company, New York, NY.
133. Environmental Protection Agency, 1988. User's Guide to SDM - A Shoreline
Dispersion Model. EPA Publication No. EPA-450/4-88-017. U.S. Environ-
mental Protection Agency, Research Triangle Park, NC. (NTIS No.
PB 89-164305)
134. Environmental Protection Agency, 1987. Analysis and Evaluation of
Statistical Coastal Fumigation Models. EPA Publication No.
EPA-450/4-87002. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 87-175519)
135. Irwin, J.S., J.O. Paumier and R.W. Erode, 1988. Meteorological Processor
for Regulatory Models (MPRM 1.2) User's Guide. EPA Publication No.
EPA-600/3-88-043R. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS No. PB 89-127526)
12-13 Revised 2/93
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13.0 BIBLIOGRAPHY"
American Meteorological Society, 1971-1985. Symposia on Turbulence,
Diffusion, and Air Pollution (1st - 7th). Boston, MA.
American Meteorological Society, 1977-1984. Joint Conferences on Applications
of Air Pollution Meteorology (1st - 4th). Sponsored by the American
Meteorological Society and the Air Pollution Control Association.
Boston, MA.
American Meteorological Society, 1978. Accuracy of Dispersion Models.
Bulletin of the American Meteorological Society, 59(8): 1025-1026.
American Meteorological Society, 1981. Air Quality Modeling and the Clean
Air Act: Recommendations to EPA on Dispersion Modeling for Regulatory
Applications. Boston, MA.
Briggs, G. A., 1969. Plume Rise. U.S. Atomic Energy Commission Critical
Review Series, Oak Ridge National Laboratory, Oak Ridge, TN.
Dickerson, W. H. and P. H. Gudiksen, 1980. ASCOT FY 79 Program Report.
Report UCRL - 52899, ASCOT 80-1. Lawrence Livermore National Laboratory,
Livermore, CA.
Drake, R. L. and S. M. Barrager, 1979. Mathematical Models for Atmospheric
Pollutants. EPRI EA-1131. Electric Power Research Institute, Palo Alto,
CA.
Environmental Protection Agency, 1978. Workbook for Comparison of Air
Quality Models. EPA Publication No. EPA-450/2-78-028a and b. U.S.
Environmental Protection Agency, Research Triangle Park, NC.
Fox, D. G., and J. E. Fairobent, 1981. NCAQ Panel Examines Uses and
Limitations of Air Quality Models. Bulletin of the American Meteo-
rological Society, 62(2): 218-221.
Gifford, F. A., 1976. Turbulent Diffusion Typing Schemes: A Review.
Nuclear Safety, 17(1): 68-86.
Gudiksen, P. H., and M. H. Dickerson, Eds., Executive Summary: Atmospheric
Studies in Complex Terrain Technical Progress Report FY-1979 Through FY-
1983. Lawrence Livermore National Laboratory, Livermore, CA. (Docket
Reference No. II-I-103).
Hales, J. M., 1976. Tall Stacks and the Atmospheric Environment. EPA
Publication No. EPA-450/3-76-007. U.S. Environmental Protection Agency,
Research Triangle Park, NC.
"The documents listed here are major sources of supplemental information
on the theory and application of mathematical air quality models.
13-1 Revised 2/93
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APPENDIX A TO APPENDIX W OF PART 51
Table of Contents
A.O INTRODUCTION AND AVAILABILITY A-l
A.I BUOYANT LINE AND POINT SOURCE DISPERSION MODEL (BLP) ... A-3
A. 2 CALINE3 A-7
A.3 CLIMATOLOGICAL DISPERSION MODEL (COM 2.0) A-ll
A.4 GAUSSIAN-PLUME MULTIPLE SOURCE AIR QUALITY
ALGORITHM (RAM) A-15
A.5 INDUSTRIAL SOURCE COMPLEX MODEL (ISC2) A-21
A.6 MULTIPLE POINT GAUSSIAN DISPERSION ALGORITHM
WITH TERRAIN ADJUSTMENT (MPTER) A-25
A. 7 SINGLE SOURCE (CRSTER) MODEL A-29
A. 8 URBAN AIRSHED MODEL (UAM) A-33
A.9 OFFSHORE AND COASTAL DISPERSION MODEL (OCD) A-39
A. 10 EMISSIONS AND DISPERSION MODEL SYSTEM (EDMS) A-43
A. 11 COMPLEX TERRAIN DISPERSION MODEL PLUS ALGORITHMS
FOR UNSTABLE SITUATIONS (CTDMPLUS) A-47
A.REF REFERENCES AR-1
A-i Revised 2/93
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A.O INTRODUCTION AND AVAILABILITY
This appendix summarizes key features of refined air quality models
preferred for specific regulatory applications. For each model, information is
provided on availability, approximate cost in 1990, regulatory use, data input,
output format and options, simulation of atmospheric physics, and accuracy.
These models may be used without a formal demonstration of applicability
provided they satisfy the recommendations for regulatory use; not all options
in the models are necessarily recommended for regulatory use.
Many of these models have been subjected to a performance evaluation
using comparisons with observed air quality data. A summary of such compari-
sons for models contained in this appendix is included in "A Survey of Statis-
tical Measures of Model Performance and Accuracy for Several Air Quality
Models," EPA-450/4-83-001. Where possible, several of the models contained
herein have been subjected to evaluation exercises, including (1) statistical
performance tests recommended by the American Meteorological Society and (2)
peer scientific reviews. The models in this appendix have been selected on the
basis of the results of the model evaluations, experience with previous use,
familiarity of the model to various air quality programs, and the costs and
resource requirements for use.
The Availability statement for models in this Appendix that refers to the
User's Network for Applied Modeling of Air Pollution (UNAMAP) should be ignored
since UNAMAP is no longer operational. However, all models and user's documen-
tation in this appendix are available from:
Computer Products
National Technical Information Service (NTIS)
U.S. Department of Commerce
Springfield, VA 22161
Phone: (703) 487-4650
In addition, model codes and selected, abridged user's guides are
available from the Support Center for Regulatory Air Models Bulletin Board
System19 (SCRAM BBS), telephone (919) 541-5742. The SCRAM BBS is an electronic
bulletin board system designed to be user friendly and accessible from anywhere
in the country. Model users with personal computers are encouraged to use the
SCRAM BBS to download current model codes and text files.
A-l Revised 2/93
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(THIS PAGE INTENTIONALLY BLANK)
A-2 Revised 2/93
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A.5 INDUSTRIAL SOURCE COMPLEX MODEL (ISC2)
Reference:
Environmental Protection Agency, 1992. User's Guide for the
Industrial Source Complex (ISC2) Dispersion Models, Volumes
1, 2, and 3. EPA Publication Nos. EPA-450/4-92-008a-c.
Environmental Protection Agency, Research Triangle Park, NC.
(NTIS Nos. PB 92-232461, PB 92-232453, and PB 92-232479,
respectively)
Availability:
The model code is available on the Support Center for Regu-
latory Air Models Bulletin Board System and also from the
National Technical Information Service (see page A-l).
Abstract:
The ISC2 model is a steady-state Gaussian plume model which
can be used to assess pollutant concentrations from a wide
variety of sources associated with an industrial source
complex. This model can account for the following: settling
and dry deposition of particles; downwash; area, line and
volume sources; plume rise as a function of downwind dis-
tance; separation of point sources; and limited terrain
adjustment. It operates in both long-term and short-term
modes.
a. Recommendations for Regulatory Use
ISC2 is appropriate for the following applications:
0 industrial source complexes;
0 rural or urban areas;
0 flat or rolling terrain;
0 transport distances less than 50 kilometers;
0 l-hour to annual averaging times; and
continuous toxic air emissions.
The following options should be selected for regulatory applications:
For short term or long term modeling, set the regulatory "default
option"; i.e., use the keyword DFAULT, which automatically selects
stack tip downwash, final plume rise, buoyancy induced dispersion
(BID), the vertical potential temperature gradient, a treatment for
calms, the appropriate wind profile exponents, the appropriate value
for pollutant half-life, and a revised building wake effects algo-
rithm; set the "rural option" (use the keyword RURAL) or "urban
option" (use the keyword URBAN); and set the "concentration option"
(use the keyword CONG .
A-21
Revised 2/93
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b. Input Requirements
Source data: location, emission rate, physical stack height, stack gas
exit velocity, stack inside diameter, and stack gas temperature. Option-
al inputs include source elevation, building dimensions, particle size
distribution with corresponding settling velocities, and surface reflec-
tion coefficients.
Meteorological data: ISCST2 requires hourly surface weather data from
the preprocessor program RAMMET, which provides hourly stability
class,wind direction, wind speed, temperature, and mixing height. For
ISCLT2, input includes stability wind rose (STAR deck), average afternoon
mixing height, average morning mixing height, and average air tempera-
ture.
Receptor data: coordinates and optional ground elevation for each
receptor.
c. Output
Printed output options include:
0 program control parameters, source data, and receptor data;
0 tables of hourly meteorological data for each specified day;
0 "N"-day average concentration or total deposition calculated at each
receptor for any desired source combinations;
0 concentration or deposition values calculated for any desired source
combinations at all receptors for any specified day or time period
within the day;
0 tables of highest and second highest concentration or deposition
values calculated at each receptor for each specified time period
during a(n) "N"-day period for any desired source combinations, and
tables of the maximum 50 concentration or deposition values calcu-
lated for any desired source combinations for each specified time
period.
d. Type of Model
ISC2 is a Gaussian plume model.
e. Pollutant Types
ISC2 may be used to model primary pollutants and continuous releases of
toxic and hazardous waste pollutants. Settling and deposition are
treated.
A-22 Revised 2/93
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f. Source-Receptor Relationships
ISC2 applies user-specified locations for point, line, area and volume
sources, and user-specified receptor locations or receptor rings.
User input topographic evaluation for each receptor is used. Elevations
above stack top are reduced to the stack top elevation, i.e., "terrain
chopping".
User input height above ground level may be used when necessary to
simulate impact at elevated or "flag pole" receptors, e.g., on buildings.
Actual separation between each source-receptor pair is used.
g. Plume Behavior
ISC2 uses Briggs (1969, 1971, 1975) plume rise equations for final rise.
Stack tip downwash equation from Briggs (1974) is used.
Revised building wake effects algorithm is used. For stacks higher than
building height plus one-half the lesser of the building height or
building width, the building wake algorithm of Huber and Snyder (1976) is
used. For lower stacks, the building wake algorithm of Schulman and
Scire (Schulman and Hanna, 1986) is used, but stack tip downwash and BID
are not used.
For rolling terrain (terrain not above stack height), plume centerline is
horizontal at height of final rise above source.
Fumigation is not treated.
h. Horizontal Winds
Constant, uniform (steady-state) wind is assumed for each hour.
Straight line plume transport is assumed to all downwind distances.
Separate wind speed profile exponents (EPA, 1980) for both rural and
urban cases are used.
An optional treatment for calm winds is included for short term modeling.
i. Vertical Wind Speed
Vertical wind speed is assumed equal to zero.
A-23 Revised 2/93
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j. Horizontal Dispersion
Rural dispersion coefficients from Turner (1969) are used, with no
adjustments for surface roughness or averaging time.
Urban dispersion coefficients from Briggs (Gifford, 1976) are used.
Buoyancy induced dispersion (Pasquill, 1976) is included.
Six stability classes are used.
k. Vertical Dispersion
Rural dispersion coefficients from Turner (1969) are used, with no
adjustments for surface roughness.
Urban dispersion coefficients from Briggs (Gifford, 1976) are used.
Buoyancy induced dispersion (Pasquill, 1976) is included.
Six stability classes are used.
Mixing height is accounted for with multiple reflections until the
vertical plume standard deviation equals 1.6 times the mixing height;
uniform vertical mixing is assumed beyond that point.
Perfect reflection is assumed at the ground.
1. Chemical Transformation
Chemical transformations are treated using exponential decay. Time
constant is input by the user.
m. Physical Removal
Settling and dry deposition of particulates are treated.
n. Evaluation Studies
Bowers, J. F., and A. J. Anderson, 1981. An Evaluation Study for the
Industrial Source Complex (ISC) Dispersion Model, EPA Publication No.
EPA-450/4-81-002. U.S. Environmental Protection Agency, Research
Triangle Park, NC.
Bowers, J. F., A. J. Anderson, and W. R. Margraves, 1982. Tests of the
Industrial Source Complex (ISC) Dispersion Model at the Armco Middle-
town, Ohio Steel Mill, EPA Publication No. EPA-450/4-82-006. U.S.
Environmental Protection Agency, Research Triangle Park, NC.
Scare, J. S., and L. L. Schulman, 1981. Evaluation of the BLP and ISC
Models with SF6 Tracer Data and SO2 Measurements at Aluminum Reduction
Plants. Air Pollution Control Association Specialty Conference on
Dispersion Modeling for Complex Sources, St. Louis, MO.
A-24 Revised 7/87
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A.8 URBAN AIRSHED MODEL (UAM)
References:
Environmental Protection Agency, 1990. User's Guide for the
Urban Airshed Model, Volume I-VIII. EPA Publication Nos.
EPA-450/4-90-007a-c, d(R), e-g, and EPA-454/B-93-004,
respectively. U.S. Environmental Protection Agency, Research
Triangle Park, NC (NTIS Nos. PB 91-131227, PB 91-131235,
PB 91-131243, PB 93-122380, PB 91-131268, PB 92-145382, and
PB 92-224849, respectively, for Vols. I-VII).
Availabilitv:
The model code is available on the Support Center for Regu-
latory Air Models Bulletin Board System and also from the
National Technical Information Service (see page A-l).
Abstract:
UAM is an urban scale, three dimensional, grid type numerical
simulation model. The model incorporates a condensed photo-
chemical kinetics mechanism for urban atmospheres. The UAM
is designed for computing ozone (03) concentrations under
short-term, episodic conditions lasting one or two days
resulting from emissions of oxides of nitrogen (NO,) , vola-
tile organic compounds (VOC), and carbon monoxide (CO). The
model treats urban VOC emissions as their carbon-bond surro-
gates .
a. Recommendations for Regulatory Use
UAM is appropriate for the following applications: urban areas having
significant ozone attainment problems and one hour averaging times.
UAM has many options but no specific recommendations can be made at this
time on all options. The reviewing agency should be consulted on selec-
tion of options to be used in regulatory applications.
b. Input Requirements
Source data: gridded, hourly emissions of PAR, OLE, ETH, XYL, TOL, ALD2,
FORM, ISOR, ETOTH, MEOH, CO, NO, and N02 for low-level sources. For
major elevated point sources, hourly emissions, stack height, stack
diameter, exit velocity, and exit temperature.
Meteorological data: hourly, gridded, divergence free, u and v wind
components for each vertical level; hourly gridded mixing heights and
surface temperatures; hourly exposure class; hourly vertical potential
temperature gradient above and below the mixing height; hourly surface
atmospheric pressure; hourly water mixing ratio; and gridded surface
roughness lengths.
A-33
Revised 2/93
-------
Air quality data: concentration of all carbon bond 4 species at the
beginning of the simulation for each grid cell; and hourly concentrations
of each pollutant at each level along the inflow boundaries and top
boundary of the modeling region.
Other data requirements are: hourly mixed layer average, NO2 photolysis
rates; and ozone surface uptake resistance along with associated gridded
vegetation (scaling) factors.
c. Output
Printed output includes:
0 gridded instantaneous concentration fields at user-specified time
intervals for user-specified pollutants and grid levels;
0 gridded time-average concentration fields for user-specified time
intervals, pollutants, and grid levels.
d. Type of Model
UAM is a three dimensional, numerical, photochemical grid model.
e. Pollutant Types
UAM may be used to model ozone (03) formation from oxides of nitrogen
(NOX) and volatile organic compound (VOC) emissions.
f. Source-Receptor Relationship
Low-level area and point source emissions are specified within each
surface grid cell. Emissions from major point sources are placed within
cells aloft in accordance with calculated effective plume heights.
Hourly average concentrations of each pollutant are calculated for all
grid cells at each vertical level.
g. Plume Behavior
Plume rise is calculated for major point sources using relationships
recommended by Briggs (1971) .
h. Horizontal Winds
See Input Requirements.
i. Vertical Wind Speed
Calculated at each vertical grid cell interface from the mass continuity
relationship using the input gridded horizontal wind field.
A-34 Revised 2/93
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j- Horizontal Dispersion
Horizontal eddy diffusivity is set to a user specified constant value
(nominally 50 m2/s) .
k. Vertical Dispersion
Vertical eddy diffusivities for unstable and neutral conditions calcu-
lated using relationships of Lamb et al. (1977) ,- for stable conditions,
the relationship of Businger and Arya (1974) is employed. Stability
class, friction velocity, and Monin-Obukhov length determined using
procedure of Liu et al. (1976) .
1. Chemical Transformation
HAM employs a simplified version of the Carbon-Bond IV Mechanism (CBM-IV)
developed by Gery et al. (1988) employing various steady state approxima-
tions .
m. Physical Removal
Dry deposition of ozone and other pollutant species are calculated.
Vegetation (scaling) factors are applied to the reference surface uptake
resistance of each species depending on land use type.
n. Evaluation Studies
Builtjes, P. J. H., K. D. van der Hurt, and S. D. Reynolds, 1982.
Evaluation of the Performance of a Photochemical Dispersion Model in
Practical Applications, 13th International Technical Meeting on Air
Pollution Modeling and Its Application, lie des Embiez, France.
Cole, H. S., D. E. Layland, G. K. Moss, and C. F. Newberry, 1983. The
St. Louis Ozone Modeling Project. EPA Publication No. EPA-450/4-83-
019. U.S. Environmental Protection Agency, Research Triangle Park, NC.
Dennis, R. L., M. W. Downton, and R. S. Keil, 1983. Evaluation of
Performance Measures for an Urban Photochemical Model. EPA Publica-
tion No. EPA-450/4-83-021. U.S. Environmental Protection Agency, Re-
search Triangle Park, NC.
Haney, J. L. and T. N. Braverman, 1985. Evaluation and Application of
the Urban Airshed Model in the Philadelphia Air Quality Control
Region. EPA Publication No. EPA-450/4-85-003. U.S. Environmental
Protection Agency, Research Triangle Park, NC.
Layland, D. E. and H. S. Cole, 1983. A Review of Recent Applications of
the SAI Urban Airshed Model. EPA Publication No. EPA-450/4-84-004.
U.S. Environmental Protection Agency, Research Triangle Park, NC.
Layland, D. E., S. D. Reynolds, H. Hogo and W. R. Oliver, 1983. Demon-
stration of Photochemical Grid Model Usage for Ozone Control Assess-
ment. 76th Annual Meeting of the Air Pollution Control Association,
Atlanta, GA.
A-35 Revised 2/93
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Morris, R. E. et al., 1990. Urban Airshed Model Study of Five Cities.
EPA Publication No. EPA-450/4-90-006a-g. U.S. Environmental Protec-
tion Agency, Research Triangle Park, NC.
Reynolds, S. D., H. Hogo, W. R. Oliver, L. E. Reid, 1982. Application of
the SAI Airshed Model to the Tulsa Metropolitan Area, SAI No. 82004.
Systems Applications, Inc., San Rafael, CA.
Schere, K. L. and J. H. Shreffler, 1982. Final Evaluation of Urban-Scale
Photochemical Air Quality Simulation Models. EPA Publication No.
EPA-600/3-82-094. U.S. Environmental Protection Agency, Research
Triangle Park, NC.
Seigneur C., T. W. Tesche, C. E. Reid, P. M. Roth, W. R. Oliver, and J.
C. Cassmassi, 1981. The Sensitivity of Complex Photochemical Model
Estimates to Detail In Input Information, Appendix A - A Compilation
of Simulation Results. EPA Publication No. EPA-450/4-81-031b. U.S.
Environmental Protection Agency, Research Triangle Park, NC.
South Coast Air Quality Management District, 1989. Air Quality Manage-
ment Plan--Appendix V-R (Urban Airshed Model Performance Evaluation).
El Monte, CA.
Stern, R. and B. Scherer, 1982. Simulation of a Photochemical Smog
Episode in the Rhine-Ruhr Area with a Three Dimensional Grid Model.
13th International Technical Meeting on Air Pollution Modeling and
Its Application, lie des Embiez, France.
Tesche, T. W., C. Seigneur, L. E. Reid, P. M. Roth, W. R. Oliver, and J.
C. Cassmassi, 1981. The Sensitivity of Complex Photochemical Model
Estimates to Detail in Input Information. EPA Publication No.
EPA-450/4-81-031a. U.S. Environmental Protection Agency, Research
Triangle Park, NC.
Tesche, T. W., W. R. Oliver, H. Hogo, P. Saxeena and J. L. Haney, 1983.
Volume IV- -Assessment of NOX Emission Control Requirements in the
South Coast Air Basin--Appendix A. Performance Evaluation of the
Systems Applications Airshed Model for the 26-27 June 1974 O3 Episode
in the South Coast Air Basin, SYSAPP 83/037. Systems Applications,
Inc., San Rafael, CA.
Tesche, T. W., W. R. Oliver, H. Hogo, P. Saxeena and J. L. Haney, 1983.
Volume IV--Assessment of NO, Emission Control Requirements in the
South Coast Air Basin--Appendix B. Performance Evaluation of the
Systems Applications Airshed Model for the 7-8 November 1978 NO,
Episode in the South Coast Air Basin, SYSAPP 83/038. Systems
Applications, Inc., San Rafael, CA.
Tesche, T. W, 1988. Accuracy of Ozone Air Quality Models. Journal of
Environmental Engineering, 114(4): 739-752.
A-36 Revised 2/93
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A-37 Revised 2/93
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A-38 Revised 2/93
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A.9 OFFSHORE AND COASTAL DISPERSION MODEL (OCD)
Reference: DiCristofaro, D. C. and S. R. Hanna, 1989. OCD: The Offshore
and Coastal Dispersion Model, Version 4. Volume I: User's
Guide, and Volume II: Appendices. Sigma Research Corpora-
tion, Westford, MA. (NTIS Nos. PB 93-144384 and PB 93-144392)
Availability: This model code is available on the Support Center for Regu-
latory Air Models Bulletin Board System and also from the
National Technical Information Service (see page A-l).
Technical
Contact: Minerals Management Service
Attn: Mr. Dirk Herkoff
Parkway Atrium Building,
381 Elden Street, Herndon, VA 22070-4817
Phone: (703) 787-1735
Abstract: OCD is a straight-line Gaussian model developed to determine
the impact of offshore emissions from point, area or line
sources on the air quality of coastal regions. OCD incorpo-
rates 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. These include water surface temperature,
overwater air temperature, mixing height, and relative
humidity.
Some of the key features include platform building downwash,
partial plume penetration into elevated inversions, direct
use of turbulence intensities for plume dispersion, inter-
action with the overland internal boundary layer, and con-
tinuous shoreline fumigation.
a. Recommendations for Regulatory Use
OCD has been recommended for use by the Minerals Management Service for
emissions located on the Outer Continental Shelf (50 FR 12248; 28 March
1985). OCD is applicable for overwater sources where onshore receptors
are below the lowest source height. Where onshore receptors are above
the lowest source height, offshore plume transport and dispersion may be
modeled on a case-by-case basis in consultation with the EPA Regional
Office.
b. Input Requirements
Source data: point, area or line source location, pollutant emission
rate, building height, stack height, stack gas temperature, stack inside
diameter, stack gas exit velocity, stack angle from vertical, elevation
A-39 Revised 2/93
-------
of stack base above water surface and gridded specification of the
land/water surfaces. As an option, emission rate, stack gas exit veloci-
ty and temperature can be varied hourly.
Meteorological data (over water): wind direction, wind speed, mixing
height, relative humidity, air temperature, water surface temperature,
vertical wind direction shear (optional), vertical temperature gradient
(optional), turbulence intensities (optional).
Meteorological data (over land): wind direction, wind speed, tempera-
ture, stability class, mixing height.
Receptor data: location, height above local ground-level, ground-level
elevation above the water surface.
c. Output
All input options, specification of sources, receptors and land/water map
including locations of sources and receptors.
Summary tables of five highest concentrations at each receptor for each
averaging period, and average concentration for entire run period at each
receptor.
Optional case study printout with hourly plume and receptor characteris-
tics . Optional table of annual impact assessment from non-permanent
activities.
Concentration files written to disk or tape can be used by ANALYSIS
postprocessor to produce the highest concentrations for each receptor,
the cumulative frequency distributions for each receptor, the tabulation
of all concentrations exceeding a given threshold, and the manipulation
of hourly concentration files.
d. Type of Model
OCD is a Gaussian plume model constructed on the framework of the MPTER
model.
e. Pollutant Types
OCD may be used to model primary pollutants. Settling and deposition are
not treated.
f. Source-Receptor Relationship
Up to 250 point sources, 5 area sources, or 1 line source and 180 recep-
tors may be used.
Receptors and sources are allowed at any location.
The coastal configuration is determined .by a grid of up to 3600 rectan-
gles . Each element of the grid is designated as either land or water to
identify the coastline.
A-40 Revised 2/93
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g. Plume Behavior
As in MPTER, the basic plume rise algorithms are based on Briggs' recom-
mendations .
Momentum rise includes consideration of the stack angle from the verti-
cal.
The effect of drilling platforms, ships, or any overwater obstructions
near the source are used to decrease plume rise using a revised platform
downwash algorithm based on laboratory experiments.
Partial plume penetration of elevated inversions is included using the
suggestions of Briggs (1975) and Weil and Brower (1984) .
Continuous shoreline fumigation is parameterized using the Turner method
where complete vertical mixing through the thermal internal boundary
layer (TIBL) occurs as soon as the plume intercepts the TIBL.
h. Horizontal Winds
Constant, uniform wind is assumed for each hour.
Overwater wind speed can be estimated from overland wind speed using
relationship of Hsu (1981).
Wind speed profiles are estimated using similarity theory (Businger
1973). Surface layer fluxes for these formulas are calculated from bulk
aerodynamic methods.
i• Vertical Wind Speed
Vertical wind speed is assumed equal to zero.
j . Horizontal Dispersion
Lateral turbulence intensity is recommended as a direct estimate of
horizontal dispersion. If lateral turbulence intensity is not available,
it is estimated from boundary layer theory. For wind speeds less than
8 m/s, lateral turbulence intensity is assumed inversely proportional to
wind speed.
Horizontal dispersion may be enhanced because of obstructions near the
source. A virtual source technique is used to simulate the initial plume
dilution due to downwash.
Formulas recommended by Pasquill (1976) are used to calculate buoyant
plume enhancement and wind direction shear enhancement.
At the water/land interface, the change to overland dispersion rates is
modeled using a virtual source. The overland dispersion rates can be
calculated from either lateral turbulence intensity or Pasquill-Gifford
curves. The change is implemented where the plume intercepts the rising
internal boundary layer.
A-41 Revised 2/93
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k. Vertical Dispersion
Observed vertical turbulence intensity is not recommended as a direct
estimate of vertical dispersion. Turbulence intensity should be estimat-
ed from boundary layer theory as default in the model. For very stable
conditions, vertical dispersion is also a function of lapse rate.
Vertical dispersion may be enhanced because of obstructions near the
source. A virtual source technique is used to simulate the initial plume
dilution due to downwash.
Formulas recommended by Pasquill (1976) are used to calculate buoyant
plume enhancement.
At the water/land interface, the change to overland dispersion rates is
modeled using a virtual source. The overland dispersion rates
can be calculated from either vertical turbulence intensity or the
Pasquill-Gifford coefficients. The change is implemented where the plume
intercepts the rising internal boundary layer.
1. Chemical Transformation
Chemical transformations are treated using exponential decay. Different
rates can be specified by month and by day or night.
m. Physical Removal
Physical removal is also treated using exponential decay.
n. Evaluation Studies
DiCristofaro, D. C. and S. R. Hanna, 1989. OCD: The Offshore and Coastal
Dispersion Model. Volume I: User's Guide. Sigma. Research
Corporation, Westford, MA.
Hanna, S. R. and D. C. DiCristofaro, 1988. Development and Evaluation of
the OCD/API Model. Final Report, API Pub. 4461, American Petroleum
Institute, Washington, D.C.
Hanna, S. R., L. L. Schulman, R. J. Paine and J. E. Pleim, 1984. The
Offshore and Coastal Dispersion (OCD) Model User's Guide, Revised.
DCS Study, MMS 84-0069. Environmental Research & Technology, Inc.,
Concord, MA. (NTIS No. PB 86-159803)
Hanna, S. R., L. L. Schulman, R. J. Paine, J. E. Pleim and M. Baer, 1985.
Development and Evaluation of the Offshore and Coastal Dispersion
(OCD) Model. Journal of the Air Pollution Control Association,
35: 1039-1047.
A-42 Revised 2/93
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A. 10 EMISSIONS AND DISPERSION MODELING SYSTEM (EDMS)
Reference:
Segal, H. M., 1991. "EDMS - Microcomputer Pollution Model
for Civilian Airports and Air Force Bases: User's Guide." FAA
Report No. FAA-EE-91-3; USAF Report No. ESL-TR-91-31, Federal
Aviation Administration, 800 Independence Avenue, S.W.,
Washington, D.C. 20591. (NTIS No. ADA 240528)
Segal, H. M., and Hamilton, P. L., 1988. "A Microcomputer
Pollution Model for Civilian Airports and Air Force Bases -
Model Description." FAA Report No. FAA-EE-88-4; USAF Report
No.ESL-TR-88-53, Federal Aviation Administration, 800 Inde-
pendence Avenue, S.H., Washington, D.C. 20591. (NTIS No.
ADA 199003)
Segal, H. M., 1988. "A Microcomputer Pollution Model for
Civilian Airports and Air Force Bases - Model Application and
Background." FAA Report No. FAA-EE-88-5; USAF Report No.
ESL-TR-88-55, Federal Aviation Administration, 800 Indepen-
dence Avenue, S.W., Washington, D.C. 20591. (NTIS No.
ADA 199794)
Availability:
EDMS is available for $40 from the address listed below:
Federal Aviation Administration
Attn: Mr. Howard Segal, ABE-120
800 Independence Avenue, S.W.
Washington, D.C. 20591
Phone: (202) 267-3494
Abstract:
EDMS is a combined emissions/dispersion model for assessing
pollution at civilian airports and military air bases. This
model, which was jointly developed by the Federal Aviation
Administration (FAA) and the United States Air Force (USAF),
produces an emission inventory of all airport sources and
calculates concentrations produced by these sources at speci-
fied receptors. The system stores emission factors for fixed
sources such as fuel storage tanks and incinerators and also
for mobile sources such as automobiles or aircraft. EDMS
incorporates an emissions model to calculate an emission
inventory for each airport source and a dispersion model, the
Graphical Input Microcomputer Model (GIMM), (Segal, 1983) to
calculate pollutant concentrations produced by these sources
at specified receptors. The GIMM, which processes point,
area, and line sources, also incorporates a special meteoro-
logical preprocessor for processing up to one year of Nation-
al Climatic Data Center (NCDC) hourly data. The model oper-
ates in both a screening and refined mode, accepting up to
170 sources and 10 receptors.
A-43
Revised 2/93
-------
a. Recommendations for Regulatory Use
EDMS is appropriate for the following applications:
0 cumulative effect of changes in aircraft operations, point source
and mobile source emissions at airports or air bases;
0 simple terrain;
0 transport distances less than 50 kilometers; and
0 1-hour to annual averaging times.
b. Input Requirements
All data are entered through a "runtime" version of the Condor data base
which is an integral part of EDMS. Typical entry items are source and
receptor coordinates, percent cold starts, vehicles per hour, etc. Some
point sources, such as heating plants, require stack height, stack
diameter, and effluent temperature inputs.
Wind speed, wind direction, hourly temperature, and Fasquill-Gifford
stability category (P-G) are the meteorological inputs. They can be
entered manually through the EDMS data entry screens or automatically
through the processing of previously loaded NCDC hourly data.
c. Output
Printed outputs consist of:
0 a monthly and yearly emission inventory report for each source
entered; and
0 a concentration summing report for up to 8760 hours (one year) of
data.
d. Type of Model
For its emissions inventory calculations, EDMS uses algorithms consistent
with the EPA Compilation of Air Pollutant Emission Factors, AP-42. For
its dispersion calculations, EDMS uses the GIMM model which is described
in reports FAA-EE-88-4 and FAA-EE-88-5, referenced above. GIMM uses a
Gaussian plume algorithm.
e. Pollutant Types
EDMS inventories and calculates the dispersion of carbon monoxide,
nitrogen oxides, sulphur oxides, hydrocarbons, and suspended particles.
f. Source-Receptor Relationship
Up to 170 sources and 10 receptors can be treated simultaneously.
Area sources are treated as a series of lines that are positioned perpen-
dicular to the wind.
A-44 Revised 2/93
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Line sources (roadways, runways) are modeled as a series of points.
Terrain elevation differences between sources and receptors are neglec-
ted.
Receptors are assumed to be at ground level.
g. Plume Behavior
Plume rise is calculated for all point sources (heating plants, incinera-
tors, etc.) using Briggs plume rise equations (Catalano, 1986; Briggs,
1969; Briggs, 1971; Briggs, 1972).
Building and stack tip downwash effects are not treated.
Roadway dispersion employs a modification to the Gaussian plume algo-
rithms as suggested by Rao and Keenan (1980) to account for close-in
vehi cle-induced turbulence.
h. Horizontal Winds
Steady state winds are assumed for each hour. Winds are assumed to be
constant with altitude.
Winds are entered manually by the user or automatically by reading
previously loaded NCC annual data files.
i. Vertical Wind Speed
Vertical wind speed is assumed to be zero.
j. Horizontal Dispersion
Four stability classes are used (P-G classes B through E).
Horizontal dispersion coefficients are computed using a table lookup and
linear interpolation scheme. Coefficients are based on Pasquill (1976)
as adapted by Petersen (1980).
A modified coefficient table is used to account for traffic-enhanced
turbulence near roadways. Coefficients are based upon data included in
Rao and Keenan (1980) .
k. Vertical Dispersion
Four stability classes are used (P-G classes B through E).
Vertical dispersion coefficients are computed using a table lookup and
linear interpolation scheme. Coefficients are based on Pasquill (1976)
as adapted by Petersen (1980) .
A modified coefficient table is used to account for traffic-enhanced
turbulence near roadways. Coefficients are based upon data from Rao and
Keenan (1980).
A-45 Revised 2/93
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1. Chemical Transformation
Chemical transformations are not accounted for.
m. Physical Removal
Deposition is not treated.
n. Evaluation Studies
Segal, H. M. and P. L. Hamilton, 1988. A Microcomputer Pollution Model
for Civilian Airports and Air Force Bases - Model Description. FAA
Report No. FAA-EE-88-4; DSAF Report No. ESL-TR-88-53, Federal Avia-
tion Administration, 800 Independence Avenue, S.W., Washington, D.C.
20591.
Segal, H. M., 1988. A Microcomputer Pollution Model for Civilian
Airports and Air Force Bases - Model Application and Background. FAA
Report No. FAA-EE-88-5; USAF Report No. ESL-TR-88-55, Federal Avia-
tion Administration, 800 Independence Avenue, S.W., Washington, D.C.
20591.
A-46 Revised 2/93
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A.11 Complex Terrain Dispersion Model Plus Algorithms for Unstable Situations
(CTDMPLUS)
Reference:
Perry, S. G., D. J. Burns, L. H. Adams, R. J. Paine, M. G.
Dennis, M. T. Mills, D. G. Strimaitis, R. J. Yamartino and E.
M. Insley, 1989. User's Guide to the Complex Terrain Disper-
sion Model Plus Algorithms for Unstable Situations (CTDMPLUS)
Volume 1: Model Descriptions and User Instructions. EPA
Publication No. EPA-600/8-89-041. Environmental Protection
Agency, Research Triangle Park, NC. (NTIS No. PB 89-181424)
Paine, R. J., D. G. Strimaitis, M. G. Dennis, R. J.
Yamartino, M. T. Mills and E. M. Insley, 1987. User's Guide
to the Complex Terrain Dispersion Model, Volume 1. EPA Publi-
cation No. EPA-600/8-87-058a. U.S. Environmental Protection
Agency, Research Triangle Park, NC. (NTIS No. PB 88-162169)
Availability:
This model code is available on the Support Center for Regu-
latory Air Models Bulletin Board System and also from the
National Technical Information Service (See page A-l).
Abstract:
CTDMPLUS is a refined point source Gaussian air quality model
for use in all stability conditions for complex terrain
applications. It contains, in its entirety, the technology
of CTDM for stable and neutral conditions. However, CTDMPLUS
can also simulate daytime, unstable conditions, and has a
number of additional capabilities for improved user friendli-
ness . Its use of meteorological data and terrain information
is different from other EPA models; considerable detail for
both types of input data is required and is supplied by
preprocessors specifically designed for CTDMPLUS. CTDMPLUS
requires the parameterization of individual hill shapes using
the terrain preprocessor and the association of each model
receptor with a particular hill.
a. Recommendation for Regulatory Use
CTDMPLUS is appropriate for the following applications:
elevated point sources;
" terrain elevations above stack top;
" rural or urban areas;
0 transport distances less than 50 kilometers; and
0 one hour to annual averaging times when used with a post-processor
program such as CHAVG.
A-47
Revised 2/93
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b. Input Requirements
Source data: For each source, user supplies source location, height,
stack diameter, stack exit velocity, stack exit temperature, and emission
rate; if variable emissions are appropriate, the user supplies hourly
values for emission rate, stack exit velocity, and stack exit tempera-
ture.
Meteorological data: the user must supply hourly averaged values of wind,
temperature and turbulence data for creation of the basic meteorological
data file ("PROFILE"). Meteorological preprocessors then create a
SURFACE data file (hourly values of mixed layer heights, surface friction
velocity, Monin-Obukhov length and surface roughness length) and a
RAWINsonde data file (upper air measurements of pressure, temperature,
wind direction, and wind speed).
Receptor data: receptor names (up to 400) and coordinates, and hill
number (each receptor must have a hill number assigned).
Terrain data: user inputs digitized contour information to the terrain
preprocessor which creates the TERRAIN data file (for up to 25 hills).
c. Output
When CTDMPLUS is run, it produces a concentration file, in either binary
or text format (user's choice), and a list file containing a verification
of model inputs, i.e.,
0 input meteorological data from "SURFACE" and "PROFILE"
0 stack data for each source
0 terrain information
0 receptor information
0 source-receptor location (line printer map).
In addition, if the case-study option is selected, the listing includes:
meteorological variables at plume height
geometrical relationships between the source and the hill
0 plume characteristics at each receptor, i.e.,
-> distance in along-flow and cross flow direction
-> effective plume-receptor height difference
-> effective <7y & aI values, both flat terrain and hill induced (the
difference shows the effect of the hill)
-> concentration components due to WRAP, LIFT and FLAT.
A-48 Revised 2/93
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If the user selects the TOPN option, a summary table of the top 4 con-
centrations at each receptor is given, if the ISOR option is selected, a
source contribution table for every hour will be printed.
A separate disk file of predicted (1-hour only) concentrations ("CONC")
is written if the user chooses this option. Three forms of output are
possible:
1) a binary file of concentrations, one value for each receptor in the
hourly sequence as run;
2) a text file of concentrations, one value for each receptor in the
hourly sequence as run; or
3) a text file as described above, but with a listing of receptor
information (names, positions, hill number) at the beginning of the
file.
Hourly information provided to these files besides the concentrations
themselves includes the year, month, day, and hour information as
well as the receptor number with the highest concentration.
d. Type of Model
CTDMPLUS is a refined steady-state, point source plume model for use in
all stability conditions for complex terrain applications.
e. Pollutant Types
CTDMPLUS may be used to model non-reactive, primary pollutants.
f. Source-Receptor Relationship
Up to 40 point sources, 400 receptors and 25 hills may be used. Receptors
and sources are allowed at any location. Hill slopes are assumed not to
exceed 15°, so that the linearized equation of motion for Bouissinesq flow
are applicable. Receptors upwind of the impingement point, or those
associated with any of the hills in the modeling domain, require separate
treatment.
g. Plume Behavior
As in CTDM, the basic plume rise algorithms are based on Briggs' (1975)
recommendations.
A central feature of CTDMPLUS for neutral/stable conditions is its use of
a critical dividing-streamline height (Hc) to separate the flow in the
vicinity of a hill into two separate layers. The plume component in the
upper layer has sufficient kinetic energy to pass over the top of the
hill while streamlines in the lower portion are constrained to flow in a
horizontal plane around the hill. Two separate components of CTDMPLUS
compute ground-level concentrations resulting from plume material in each
of these flows.
A-49 Revised 2/93
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The model calculates on an hourly (or appropriate steady averaging
period) basis how the plume trajectory (and, in stable/neutral condi-
tions, the shape) is deformed by each hill. Hourly profiles of wind and
temperature measurements are used by CTDMPLUS to compute plume rise,
plume penetration (a formulation is included to handle penetration into
elevated stable layers, based on Briggs (1984)), convective scaling
parameters, the value of H,,, and the Froude number above H,,.
h. Horizontal Winds
CTDMPLUS does not simulate calm meteorological conditions. Both scalar
and vector wind speed observations can be read by the model. If vector
wind speed is unavailable, it is calculated from the scalar wind speed.
The assignment of wind speed (either vector or scalar) at plume height is
done by either:
0 interpolating between observations above and below the plume height,
or
0 extrapolating (within the surface layer) from the nearest measurement
height to the plume height.
i. Vertical Wind Speed
Vertical flow is treated for the plume component above the critical
dividing streamline height (HJ ; see "Plume Behavior".
j. Horizontal Dispersion
Horizontal dispersion for stable/neutral conditions is related to the
turbulence velocity scale for lateral fluctuations, ffv, for which a
minimum value of 0.2 m/s is used. Convective scaling formulations are
used to estimate horizontal dispersion for unstable conditions.
k. Vertical Dispersion
Direct estimates of vertical dispersion for stable/neutral conditions are
based on observed vertical turbulence intensity, e.g.,
-------
n. Evaluation Studies
Burns, D. J., L. H. Adams and S. G. Perry, 1990. Testing and Evaluation
of the CTDMPLUS Dispersion Model: Daytime Convective Conditions.
Environmental Protection Agency, Research Triangle Park, NC.
Paumier, J. O., S. G. Perry and D. J. Burns, 1990. An Analysis of
CTDMPLUS Model Predictions with the Lovett Power Plant Data Base.
Environmental Protection Agency/ Research Triangle Park, NC.
Paumier, J. O., S. G. Perry and D. J. Burns, 1992. CTDMPLUS: A Dispersion
Model for Sources near Complex Topography. Part II: Performance
Characteristics. Journal of Applied Meteorology, 31(7): 646-660.
A-51 Revised 2/93
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Catalano, J. A., 1986. Addendum to the User's Manual for the Single Source
(CRSTER) Model. EPA Publication No. EPA-600/8-86-041. U.S. Environmental
Protection Agency, Research Triangle Park, NC. (NTIS No. PB 87-145843) .
Gery, M. W., G. Z. Whitten and J. P. Killus, 1988. Development and Testing of
CBM-IV for Urban and Regional Modeling. EPA Publication No. EPA-600/3-88-012.
U.S. Environmental Protection Agency, Research Triangle Park, NC. (NTIS No.
PB 88-180039)
Petersen, W. B., 1980. User's Guide for HIWAY-2 A Highway Air Pollution Model.
EPA Publication No. EPA-600/8-80-018. U.S. Environmental Protection Agency,
Research Triangle Park, NC. (NTIS PB 80-227556) .
Rao, T. R. and M. T. Keenan, 1980. Suggestions for Improvement of the EPA-
HIWAY Model. Journal of the Air Pollution Control Association, 30: 247-256
(and reprinted as Appendix C in Petersen, 1980).
Segal, H. M., 1983. Microcomputer Graphics in Atmospheric Dispersion Modeling.
Journal of the Air Pollution Control Association, 23: 598-600.
AR-3 Revised 2/93
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APPENDIX B TO APPENDIX W OF PART 51
Table of Contents
B.O INTRODUCTION AND AVAILABILITY B-l
B.I AIR QUALITY DISPLAY MODEL (AQDM) B-3
B.2 AIR RESOURCES REGIONAL POLLUTION ASSESSMENT (ARRPA) MODEL . B-7
B.3 APRAC-3 B-ll
B.4 COMPTER B-15
B.5 ERT AIR QUALITY MODEL (ERTAQ) Deleted
B.6 ERT VISIBILITY MODEL B-23
B.7 HIWAY-2 B-27
B.8 INTEGRATED MODEL FOR PLUMES AND ATMOSPHERIC CHEMISTRY
IN COMPLEX TERRAIN (IMPACT) B-31
B.9 LONGZ B-35
B.10 MARYLAND POWER PLANT SITING PROGRAM (PPSP) MODEL B-39
B.ll MESOSCALE PUFF MODEL (MESOPUFF II) B-43
B.12 MESOSCALE TRANSPORT DIFFUSION AND DEPOSITION MODEL
FOR INDUSTRIAL SOURCES (MTDDIS) B-47
B.13 MODELS' 3141 AND 4141 B-51
B.14 MULTIMAX B-55
B.15 MULTIPLE POINT SOURCE DIFFUSION MODEL (MPSDM) Deleted
B.16 MULTI-SOURCE (SCSTER) MODEL B-63
B.17 PACIFIC GAS AND ELECTRIC PLUMES MODEL B-67
B.18 PLMSTAR AIR QUALITY SIMULATION MODEL B-71
B.19 PLUME VISIBILITY MODEL (PLUVUE II) B-75
B.20 POINT, AREA, LINE SOURCE ALGORITHM (PAL-DS) B-79
B.21 RANDOM WALK ADVECTION AND DISPERSION MODEL (RADM) B-83
B.22 REACTIVE PLUME MODEL (RPM-II) B-87
B-i Revised 2/93
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B.23 REGIONAL TRANSPORT MODEL (RTM-II) B-91
B.24 SHORTZ B-95
B.25 SIMPLE LINE-SOURCE MODEL (GMLINE) B-99
B.26 TEXAS CLIMATOLOGICAL MODEL (TCM) B-103
B.27 TEXAS EPISODIC MODEL (TEM) B-107
B.28 AVACTA II MODEL B-lll
B.29 SHORELINE DISPERSION MODEL (SDM) B-115
B.30 WYNDvalley MODEL B-119
B.31 DENSE GAS DISPERSION MODEL (DEGADIS) B-123
B.REF REFERENCES BR-1
B-ii Revised 2/93
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B.O INTRODUCTION AND AVAILABILITY
This appendix summarizes key features of refined air quality models that
may be considered on a case-by-case basis for individual regulatory applica-
tions. For each model, information is provided on availability, approximate
cost in 1990, regulatory use, data input, output format and options, simulation
of atmospheric physics and accuracy. The models are listed by name in alpha-
betical order.
There are three separate conditions under which these models will
normally be approved for use: first, if a demonstration can be made that the
model produces concentration estimates equivalent to the estimates obtained
using a preferred model (e.g., the maximum or high, second-high concentration
is within 2% of the estimate using the comparable preferred model); second, if
a statistical performance evaluation has been conducted using measured air
quality data and the results of that evaluation indicate the model in Appendix
B performs better for the application than a comparable model in Appendix A;
and third, if there is no preferred model for the specific application but a
refined model is needed to satisfy regulatory requirements. Any one of these
three separate conditions may warrant use of these models. See Section 3.2,
Use of Alternative Models, for additional details.
Hany of these models have been subject to a performance evaluation by
comparison with observed air quality data. A summary of such comparisons for
models contained in this appendix is included in "A Survey of Statistical
Measures of Model Performance and Accuracy for Several Air Quality Models",
EPA-450/4-83-001. Where possible, several of the models contained herein have
been subjected to rigorous evaluation exercises, including (1) statistical
performance measures recommended by the American Meteorological Society and (2)
peer scientific reviews.
Any availability statement for models in this appendix that refers to the
User's Network for Applied Modeling of Air Pollution (UNAMAP) should be ignored
since the UNAMAP is no longer operational. However, a source for some of these
models and user's documentation is:
Computer Products
National Technical Information Service (NTIS)
U.S. Department of Commerce
Springfield, VA 22161
Phone: (703) 487-4650
A number of the model codes and selected, abridged user's guides are also
available from the Support Center for Regulatory Air Models Bulletin Board
System1" (SCRAM BBS), Telephone (919) 541-5742. The SCRAM BBS is an electronic
bulletin board system designed to be user friendly and accessible from anywhere
in the country. Model users with personal computers are encouraged to use the
SCRAM BBS to download current model codes and text files.
B-l Revised 2/93
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B-2 Revised 2/93
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B-19 to B-22 Revised 2/93
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B.6 ERT VISIBILITY MODEL
Reference:
ENSR Consulting and Engineering, 1990. ERT Visibility Model:
Version 4; Technical Description and User's Guide. Document
M2020-003. ENSR Consulting and Engineering, 35 Nagog Park,
Acton, MA 01720.
Availability:
The user's guide and model code are available from the
National Technical Information Service (see page B-l).
Abstract:
The ERT Visibility Model is a Gaussian dispersion model de-
signed to estimate visibility impairment for arbitrary lines
of sight due to isolated point source emissions by simulating
gas-to-particle conversion, dry deposition, NO to NO2 conver-
sion and linear radiative transfer.
for Regulatory Use
There is no specific recommendation at the present time. The ERT Visi-
bility Model may be used on a case-by-case basis.
Input Requirements
Source data requirements are: stack height, stack temperature, emissions
of S02, NO,, TSP, fraction of NO, as N02, fraction of TSP which is carbo-
naceous, exit velocity, and exit radius.
Meteorological data requirements are: hourly ambient temperature, mixing
depth, wind speed at stack height, stability class, potential tempera-
ture gradient, and wind direction.
Receptor data requirements are: observer coordinates with respect to
source, latitude, longitude, time zone, date, time of day, elevation,
relative humidity, background visual range, line-of-sight azimuth and
elevation angle, inclination angle of the observed object, distance from
observer to object, object and surface reflectivity, number and spacing
of integral receptor points along line of sight.
Other data requirements are: ambient concentrations of O3 and NOX,
deposition velocity of TSP, sulfate, nitrate, SO2 and NO,, first-order
transformation rate for sulfate and nitrate.
B-23
Revised 2/93
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c. Output
Printed output includes both summary and detailed results as follows:
Summary output: page 1 - site, observer and object parameters; page 2 -
optical pollutants and associated extinction coefficients; page 3 - plume
model input parameters; page 4 - total calculated visual range reduction,
and each pollutant's contribution; page 5 - calculated plume contrast,
object contrast and object contrast degradation at the 550nm wavelength;
page 6 - calculated blue/red ratio and AE (U*V*W*) values for both sky
and object discoloration.
Detailed output: phase functions for each pollutant in four wavelengths
(400, 450, 550, 650nm), concentrations for each pollutant along sight
path, solar geometry, contrast parameters at all wavelengths,
intensities, tristimulus values and chromaticity coordinates for views of
the object, sun, background sky and plume.
d. Type of Model
ERT Visibility model is a Gaussian plume model for estimating visibility
impairment.
e. Pollutant Types
Optical activity of sulfate, nitrate (derived from SO2 and NOX emissions),
primary TSP and NO2 is simulated.
f. Source Receptor Relationship
Single source and hour is simulated. Unlimited number of lines-of-sight
(receptors) is permitted per model run.
g. Plume Behavior
Briggs (1971) plume rise equations for final rise are used.
h. Horizontal Wind Field
A single wind speed and direction is specified for each case study. The
wind is assumed to be spatially uniform.
i. Vertical Wind Speed
Vertical wind speed is assumed equal to zero.
j. Horizontal Dispersion
Rural dispersion coefficients from Turner (1969) are used.
B-24
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B.ll MESOSCALE PUFF MODEL (MESOPDFF II)
Reference:
Scire, J. S., F. W. Lunnann, A. Bass, S. R. Hanna, 1984.
User's Guide to the Mesopuff II Model and Related Processor
Programs. EPA Publication No. EPA-600/8-84-013. U.S. Envi-
ronmental Protection Agency, Research Triangle Park, NC.
(NTIS No. PB 84-181775)
A Modeling Protocol for Applying MESOPUFF II to Long Range
Transport Problems, 1992. EPA Publication No. EPA-454/R-92-021.
U.S. Environmental Protection Agency, Research Triangle Park, NC.
Availability;
This model code is available on the Support Center for Regu-
latory Air Models Bulletin Board System and also from the
National Technical Information Service (see page B-l).
Abstract:
MESOPUFF II is a short term, regional scale puff model de-
signed to calculate concentrations of up to 5 pollutant
species (SO2, S04, NOx, HNOs, NO3) . Transport, puff growth,
chemical transformation, and wet and dry deposition are
accounted for in the model.
Recommendations for Regulatory Use
There is no specific recommendation at the present time. The model may
be used on a case-by-case basis.
Input Requirements
Required input data include four types: 1) input control parameters and
selected technical options, 2) hourly surface meteorological data and
twice daily upper air measurements, hourly precipitation data are option-
al, 3) surface land use classification information, 4) source and emis-
sions data.
Data from up to 25 surface National Weather Service stations and up to 10
upper air stations may be considered. Spatially variable fields at hour
intervals of winds, mixing height, stability class, and relevant turbu-
lence parameters are derived by MESOPAC II, the meteorological prepro-
cessor program described in the User Guide.
Source and emission data for up to 25 point sources and/or up to 5 area
sources can be included. Required information are: location in grid
coordinates, stack height, exit velocity and temperature, and emission
rates for the pollutant to me modeled.
Receptor data requirements: up to a 40 X 40 grid may be used and non-
gridded receptor locations may be considered.
B-43
Revised 2/93
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c. Output
Line printer output includes: all input parameters, optionally selected
arrays of ground-level concentrations of pollutant species at specified
time intervals.
Line printer contour plots output from MESOFILE II post-processor
program. Computer readable output of concentration array to disk/tape for
each hour.
d. Type of Model
MESOPUFF II is a Gaussian puff superposition model.
e. Pollutant types modeled
Up to five pollutant species may be modeled simultaneously and include:
S02, S04, NO,, HN03, N03.
f. Source-Receptor Relationship
Up. to 25 point sources and/or up to 5 area sources are permitted.
g. Plume Behavior
Briggs (1975) plume rise equations are used, including plume penetration
with bouyancy flux computed in the model.
Fumigation of puffs is considered and may produce immediate mixing or
multiple reflection calculations at user option.
h. Horizontal Winds
Gridded wind fields are computed for 2 layers; boundary layer and above
the mixed layer. Upper air rawinsonde data and hourly surface winds are
used to obtain spatially variable u,v component fields at hourly
intervals. The gridded fields are computed by interpolation between
stations in the MESOPAC II preprocessor.
i. Vertical Wind Speed
Vertical winds are assumed to be zero.
j. Horizontal Dispersion
Incremental puff growth is computed over discrete time steps with
horizontal growth parameters determined from power law equations fit to
sigma y curves of Turner out to 100km. At distances greater than 100km,
puff growth is determined by the rate given by Heffter (1965) .
Puff growth is a function of stability class and changes in stability are
treated. Optionally, user input plume growth coefficients may be
considered.
B-44
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B-59 to B-62 Revised 2/93
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B.19 PLDME VISIBILITY MODEL (PLDVDE II)
Reference: Environmental Protection Agency, 1992. User's Manual for the
Plume Visibility Model, PLUVOE II (Revised). EPA Publication
No. EPA-454/B-92-008. U.S. Environmental Protection Agency,
Research Triangle Park, NC.
Availability; This model code is available on the Support Center for Regu-
latory Air Models Bulletin Board System and also from the
National Technical Information Service (see page B-l).
Abstract: The Plume Visibility Model (PLUVUE II) is a computerized
model used for estimating visual range reduction and atmo-
spheric discoloration caused by plumes resulting from the
emissions of particles, nitrogen oxides and sulfur oxides
from a single emission source. PLUVUE II predicts the trans-
port, dispersion, chemical reactions, optical effects and
surface deposition of point or area source emissions. Adden-
da to the User's Manual were prepared in February 1985 to
allow execution of PLUVUE II and the test cases on the UNIVAC
computer.
a. Recommendations for Regulatory Use
The Plume Visibility Model {PLUVUE II) may be used on a case-by-case
basis. When applying PLUVUE II to assess the visual impact of a plume,
the following precautions should be taken to avoid the possibility of
error:
1. Treat the optical effects of N02 and particles separately as well as
together to avoid cancellation of N02 absorption with particle scat-
tering.
2. Examine the visual impact of the plume in 0.1 (or 0), 0.5, and 1.0
times the expected level of particulate matter in the background air.
3. Examine the visual impact of the plume over the full range of obser-
ver - plume - sun angles.
b. Input Requirements
Source data requirements are: location and elevation; emission rates of
SO,, NO,, and particulates; flue gas flow rate, exit velocity, and exit
temperature; flue gas oxygen content; properties (including density, mass
median and standard geometric deviation of radius) of the emitted aero-
sols in the accumulation (0.1-1.0/im) and coarse (1.0-10./an) size modes;
and deposition velocities for S02, NOX, coarse mode aerosol, and accumula-
tions mode aerosol.
Meteorological data requirements are: stability class, wind direction
(for an observer-based run), wind speed, lapse rate, air temperature,
relative humidity, and mixing height.
B-75 Revised 2/93
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Other data requirements are: ambient background concentrations of NOX,
NOj? Oj, and S02r background visual range or sulfate and nitrate
concentrations.
Receptor (observer) data requirements are: location, elevation, terrain
which will be observed through the plume (for observer based run with
white, gray, and black viewing backgrounds).
c. Output
Printed output includes:
plume concentrations and visual effects at specified downwind
distances for calculated or specified lines of sight.
d. Type of Model
PLUVUE is a Gaussian plume model.
e. Pollutant Types
PLUVUE II treats NO, N02, SO2, H2S04, HNO3, 03, primary and secondary
particles to calculate effects on visibility.
f. Source Receptor Relationship
PLUVUE treats a single point or area source.
Predicted concentrations and visual effects are obtained
at user specified downwind distances.
g. Plume Behavior
PLUVUE uses Briggs (1969, 1971, 1972) final plume rise equations.
h. Horizontal Winds
User-specified wind speed (and direction for an observer-based run) are
assumed constant for the calculation.
i. Vertical Wind Speed
Vertical wind speed is assumed equal to zero.
j. Horizontal Dispersion
User specified plume widths, or widths computed from either Pasquill-
Gifford-Turner curves (Turner, 1969) or TVA curves (Carpenter, et al.,
1971) are used in PLUVUE.
B-76
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B.29 SHORELINE DISPERSION MODEL (SDM)
Reference; PEI Associates, 1988. User's Guide to SDM - A Shoreline
Dispersion Model. EPA Publication No. EPA-450/4-88-017. U.S.
Environmental Protection Agency, Research Triangle Park, NC.
(NTIS No. PB 89-164305)
Availability; The user's guide is available from the National Technical
Information Service. The model code is available on the
Support Center for Regulatory Air Models Bulletin Board
System (see page B-l).
Abstract; SDM is a hybrid multipoint Gaussian dispersion model that
calculates source impact for those hours during the year when
fumigation events are expected using a special fumigation
algorithm and the MPTER regulatory model for the remaining
hours (see Appendix A).
a. Recommendations for Regulatory Use
SDM may be used on a case-by-case basis for the following applications:
0 tall stationary point sources located at a shoreline of any large
body of water;
0 rural or urban areas;
0 flat terrain;
0 transport distances less than 50 km;
0 1-hour to 1-year averaging times.
b. Input Requirements
Source data: location, emission rate, physical stack height, stack gas
exit velocity, stack inside diameter, stack gas temperature and shoreline
coordinates.
Meteorological data: hourly values of mean wind speed within the Thermal
Internal Boundary Layer (TIBL) and at stack height; mean potential
temperature over land and over water; over water lapse rate; and surface
sensible heat flux. In addition to these meteorological data, SDM access
standard NWS surface and upper air meteorological data through the RAMMET
preprocessor.
Receptor data: coordinates for each receptor.
B-115 Revised 2/93
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c. Outnut
Printed output includes the MPTER model output as well as: special
shoreline fumigation applicability report for each day and source; high-
five tables on the standard output with "F" designation next to the
concentration if that averaging period includes a fumigation event.
d. Type of Model
SDM is hybrid Gaussian model.
e. Pollutant Types
SDM may be used to model primary pollutants. Settling and deposition are
not treated.
f. Source-Receptor Relationships
SDM applies user-specified locations of stationary point sources and
receptors. User input stack height, shoreline orientation and source
characteris'tics for each source. No topographic elevation is input; flat
terrain is assumed.
g. Plume Behavior
SDM uses Briggs (1975) plume rise for final rise. SDM does not treat
stack tip or building downwash.
h. Horizontal Winds
Constant, uniform (steady-state) wind is assumed for an hour. Straight
line plume transport is assumed to all downwind distances. Separate wind
speed profile exponents (EPA, 1980) for both rural and urban cases are
assumed.
i. Vertical Wind Speed
Vertical wind speed is assumed equal to zero.
j. Horizontal Dispersion
For the fumigation algorithm coefficients based on Misra (1980) and Misra
and McMillan (1980) are used for plume transport in stable air above TIBL
and based on Lamb (1978) for transport in the unstable air below the
TIBL. An effective horizontal dispersion coefficient based on Misra and
Onlock (1982) is used. For nonfumigation periods, algorithms contained
in the MPTER model are used (see Appendix A).
k. Vertical Dispersion
For the fumigation algorithm, coefficients based on Misra (1980) and
Misra and McMillan (1980) are used.
B-116 Revised 2/93
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1. Chemical Transformation
Chemical transformation is not included in the fumigation algorithm.
m. Physical Removal
Physical removal is not explicitly treated.
n. Evaluation Studies
Environmental Protection Agency, 1987. Analysis and Evaluation of
Statistical Coastal Fumigation Models. EPA Publication No.
EPA-450/4-87-002. U.S. Environmental Protection Agency, Research
Triangle Park, NC. (NTIS PB 87-175519)
B-117 Revised 2/93
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B-118 Revised 2/93
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B.30 WYNDvalley Model
Reference:
Harrison, Halstead, 1992. "A User's Guide to WYNDvalley
3.11, an Eulerian-Grid Air-Quality Dispersion Model with
Versatile Boundaries, Sources, and Winds," WYNDsoft Inc.,
Mercer Island, WA.
Availability;
Copies of the user's guide and the executable model computer
codes are available at a cost of $295.00 from:
WYNDsoft, Incorporated
6333 77th Avenue SE
Mercer Island, WA 98040
Phone: (206) 232-1819
Abstract:
WYNDvalley 3.11 is a multi-layer (up to five vertical layers)
Eulerian grid dispersion model that permits users flexibility
in defining borders around the areas to be modeled, the
boundary conditions at these borders, the intensities and
locations of emissions sources, and the winds and diffusivi-
ties that affect the dispersion of atmospheric pollutants.
The model's output includes gridded contour plots of pollut-
ant concentrations for the highest brief episodes (during any
single time step), the highest and second-highest 24-hour
averages, averaged dry and wet deposition fluxes, and a
colored 'movie' showing evolving dispersal of pollutant
concentrations, together with temporal plots of the concen-
trations at specified receptor sites and statistical infer-
ence of the probabilities that standards will be exceeded at
those sites. WYNDvalley is implemented on IBM* compatible
microcomputers, with interactive data input and color graph-
ics display.
a. Recommendations for Regulatory Use
WYNDvalley may be used on a case-by-case basis to estimate concentrations
during valley stagnation periods of 24 hours or longer. Recommended
inputs are listed below.
Variable
Horizontal cell dimension
Vertical layers
Layer depth
Background (internal to model)
Lateral meander velocity
Diffusivities
Ventilation parameter (upper
boundary condition)
Dry deposition velocity
Washout ratio
Recommended Value
250 to 500 meters
3 to 5
50 to 100 meters
zero (background should be added
externally to model estimates)
default
default
default
zero (site-specific)
zero (site-specific)
B-119
Revised 2/93
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b. Input Requirements
Input data, including model options, modeling domain boundaries, boundary
conditions, receptor locations, source locations, and emission rates, may
be entered interactively, or through existing template files from a
previous run. Meteorological data, including wind speeds, wind direc-
tions, rain rates (optionally, for wet deposition calculations), and time
of day and year, may be of arbitrary time increment (usually an hour) and
are entered into the model through an external meteorological data file.
Optionally, users may specify diffusivities and upper boundary conditions
for each time increment. Source emission rates may be constant or
modulated on a daily, weekly, and/or seasonal basis.
c. Output
Output from WYNDvalley includes gridded contour maps of the highest
pollutant concentrations at each time step and the highest and second-
highest 24-hour average concentrations. Output also includes the deposi-
tion patterns for wet, dry, and total fluxes of the pollutants to the
surface, integrated over the simulation period. A running "movie" of the
concentration patterns is displayed on the screen (with optional print-
out) as they evolve during the simulation. Output files include tables
of daily-averaged pollutant concentrations at every modeled grid cell,
and of hourly concentrations at up to eight specified receptors. Statis-
tical analyses are performed on the hourly and daily data to estimate the
probabilities that specified levels will be exceeded more than once
during an arbitrary number of days with similar weather.
d. Type of Model
WYNDvalley is a three dimensional Eulerian grid model.
e. Pollutant Types
WYNDvalley may be used to model any inert pollutant.
f. Source-Receptor Relationships
Source and receptors may be located anywhere within the user-defined
modeling domain. All point and area sources, or portions of an area
source, within a given grid cell are summed to define a representative
emission rate for that cell. Concentrations are calculated for each and
every grid cell in the modeling domain. Up to eight grid cells may be
selected as receptors, for which time histories of concentration and
deposition fluxes are determined, and probabilities of exceedance are
calculated.
g. Plume Behavior
Emissions for buoyant point sources are placed by the user in a grid cell
which best reflects the expected effective plume height during stagnation
conditions. Five vertical layers are available to the user.
B-120 Revised 2/93
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h. Horizontal Winds
During each time step in the model, the winds are assumed to be uniform
throughout the modeling domain. Numerical diffusion is minimized in the
advection algorithm. To account for terrain effects on winds and disper-
sion, an ad hoc algorithm is employed in the model to distribute concen-
trations near boundaries.
i. Vertical Wind Speed
Winds are assumed to be constant with height.
j. Horizontal Dispersion
Horizontal eddy diffusion coefficients may be entered explicitly by the
user at every time step. Alternatively, a default algorithm may be
invoked to estimate these coefficients from the wind velocities and their
variances.
k. Vertical Dispersion
Vertical eddy diffusion coefficients and a top-of-model boundary condi-
tion may be entered explicitly by the user at every time step. Alterna-
tively, a default algorithm may be invoked to estimate these coefficients
from the horizontal wind velocities and their variances, and from an
empirical time-of-day correction derived from temperature gradient
measurements and Monin-Obukhov similarities.
1. Chemical Transformation
Chemical transformation is not explicitly treated by WYNDvalley.
m. Physical Removal
WYNDvalley optionally simulates both wet and dry deposition. Dry deposi-
tion is proportional to concentration in the lowest layer, while wet
deposition is proportional to rain rate and concentration in each layer.
Appropriate coefficients (deposition velocities and washout ratios) are
input by the user.
n. Evaluation Studies
Harrison, H., G. Fade, C. Bowman and R. Wilson, 1990. Air Quality
During Stagnations: A Comparison of RAM and WYNDvalley with PM-10
Measurements at Five Sites. Journal of the Air & Waste Management
Association, 40: 47-52.
Yoshida, C., 1990. A Comparison of WYNDvalley Versions 2.12 and 3.0 with
PM-10 Measurements in Six Cities in the Pacific Northwest, Lane
Regional Air Pollution Authority, Springfield, OR.
Maykut, N. et al., 1990. Evaluation of. the Atmospheric Deposition of
Toxic Contaminants to Puget Sound, State of Washington, Puget Sound
Water Quality Authority, Seattle, WA.
B-121 Revised 2/93
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(THIS PAGE INTENTIONALLY BLANK)
B-122 Revised 2/93
-------
B.31 DENSE GAS DISPERSION MODEL (DEGADIS)
Reference:
Environmental Protection Agency, 1989. User's Guide for the
DEGADIS 2.1 - Dense Gas Dispersion Model. EPA Publication
No. EPA-450/4-89-019. U.S. Environmental Protection Agency,
Research Triangle Park, NC 27711. (NTIS No. PB 90-213893)
Availabilitv:
The model code is only available on the Support Center for
Regulatory Air Models Bulletin Board System (see page B-l).
Abstract:
DEGADIS 2.1 is a mathematical dispersion model that can be
used to model the transport of toxic chemical releases into
the atmosphere. Its range of applicability includes contin-
uous, instantaneous, finite duration, and time-variant re-
leases; negatively-buoyant and neutrally-buoyant releases;
ground-level, low-momentum area releases; ground-level or
elevated upwardly-directed stack releases of gases or aero-
sols . The model simulates only one set of meteorological
conditions, and therefore should not be considered applicable
over time periods much longer than 1 or 2 hours. The simula-
tions are carried out over flat, level, unobstructed terrain
for which the characteristic surface roughness is not a
significant fraction of the depth of the dispersion layer.
The model does not characterize the density of aerosol-type
releases; rather, the user must assess that independently
prior to the simulation.
Recommendations for Regulatory Use
DEGADIS can be used as a refined modeling approach to estimate short-term
ambient concentrations (1-hour or less averaging times) and the expected
area of exposure to concentrations above specified threshold values for
toxic chemical releases. It is especially useful in situations where
density effects are suspected to be important and where screening esti-
mates of ambient concentrations are above levels of concern.
Input Requirements
Data may be input directly from an external input file or via keyboard
using an interactive program module. The model is not set up to accept
real-time meteorological data or convert units of input values. Chemical
property data must be input by the user. Such data for a few selected
species are available within the model. Additional data may be added to
this data base by the user.
B-123
Revised 2/93
-------
Source data requirements are: emission rate and release duration; emis-
sion chemical and physical properties (molecular weight, density vs.
concentration profile in the case of aerosol releases, and contaminant
heat capacity in the case of a nonisothennal gas release; stack parame-
ters (i.e., diameter, elevation above ground level, temperature at
release point).
Meteorological data requirements are: wind speed at designated height
above ground, ambient temperature and pressure, surface roughness,
relative humidity, and ground surface temperature (which in most cases
can be adequately approximated by the ambient temperature).
Receptor data requirements are: averaging time of interest, above-ground
height of receptors, and maximum distance between receptors (since the
model computes downwind receptor distances to optimize model performance,
this parameter is used only for nominal control of the output listing,
and is of secondary importance). No indoor concentrations are calculated
by the model.
c. Output
Printed output includes in tabular form:
0 listing of model input data;
0 plume centerline elevation, mole fraction, concentration, density,
and temperature at each downwind distance;
0 cry and az values at each downwind distance;
0 off-centerline distances to 2 specified concentration values at a
specified receptor height at each downwind distance (these values can
be used to draw concentration isopleths after model execution);
0 concentration vs. time histories for finite-duration releases (if
specified by user).
The output print file is automatically saved and must be sent to the
appropriate printer by the user after program execution.
No graphical output is generated by the current version of this program.
d. Type of Model
DEGADIS estimates plume rise and dispersion for vertically-upward jet
releases using mass and momentum balances with air entrainment based on
laboratory and field-scale data. These balances assume Gaussian similar-
ity profiles for velocity, density, and concentration within the jet.
Ground-level denser-than-air phenomena is treated using a power law
concentration distribution profile in the vertical and a hybrid top hat-
Gaussian concentration distribution profile in the horizontal. A power
law specification is used for the vertical wind profile. Ground-level
cloud slumping phenomena and air entrainment are based on laboratory
measurements and field-scale observations.
B-124 Revised 2/93
-------
e. Pollutant Types
Neutrally- or negatively-buoyant gases and aerosols. Pollutants are
assumed to be non-reactive and non-depositing.
f. Source-Receptor Relationships
Only one source can be modeled at a time.
There is no limitation to the number of receptors; the downwind receptor
distances are internally-calculated by the model. The DEGADIS calcula-
tion is carried out until the plume centerline concentration is 50% below
the lowest concentration level specified by the user.
The model contains no modules for source calculations or release charac-
terization.
g. Plume Behavior
Jet/plume trajectory is estimated from mass and momentum balance equa-
tions. Surrounding terrain is assumed to be flat, and stack tip down-
wash, building wake effects, and fumigation are not treated.
h. Horizontal Winds
Constant logarithmic velocity profile which accounts for stability and
surface roughness is used.
The wind speed profile exponent, is determined from a least squares fit of
the logarithmic profile from ground level to the wind speed reference
height. Calm winds can be simulated for ground-level low-momentum
releases.
Along-wind dispersion of transient releases is treated using the methods
of Colenbrander (1980) and Seals (1971).
i. Vertical Wind Speed
Not treated.
j. Horizontal Dispersion
When the plume centerline is above ground level, horizontal dispersion
coefficients are based upon Turner (1969) and Slade (1968) with adjust-
ments made for averaging time and plume density.
When the plume centerline is at ground level, horizontal dispersion also
accounts for entrainment due to gravity currents as parameterized from
laboratory experiments.
B-125 Revised 2/93
-------
k. Vertical Dispersion
When the plume centerline is above ground level, vertical dispersion
coefficients are based upon Turner (1969) and Slade (1968) . Perfect
ground reflection is applied.
In the ground-level dense-gas regime, vertical dispersion is also based
upon results from laboratory experiments in density-stratified fluids.
1. Chemical Transformation
Not specifically treated.
m. Physical Removal
Not treated.
n. Evaluation Studies
Spicer, T. O. and J. A. Havens, 1986. Development of Vapor Dispersion
Models for Nonneutrally Buoyant Gas Mixtures - Analysis of USAF/N2O4
Test Data. USAF Engineering and Services Laboratory, Final Report
ESL-TR-86-24.
Spicer, T. O. and J. A. Havens, 1988. Development of Vapor Dispersion
Models for Nonneutrally Buoyant Gas Mixtures - Analysis of TFI/NH3
Test Data. USAF Engineering and Services Laboratory, Final Report.
o. Operating Information
The model requires either a VAX computer or an IBM* - compatible PC for
its execution.
The model currently does not require supporting software. A FORTRAN
compiler is required to generate program executables in the VAX computing
environment. PC executables are provided within the source code; how-
ever, a PC FORTRAN compiler may be used to tailor a PC executable to the
user's PC environment.
B-126 Revised 2/93
-------
McElroy, J. L. and F. Pooler, 1968. St. Louis Dispersion Study, Volume II-
Analyses. NAPCA Publication No. AP-53. National Air Pollution Control
Administration, Arlington, VA.
Mitchell, Jr., A. E. and K. O. Timbre, 1979. Atmospheric Stability Class from
Horizontal Wind Fluctuation. Presented at the 72nd Annual Meeting of the Air
Pollution Control Association, Cincinnati, OH.
Moore, G. E., T. E. Stoeckenius and D. A. Stewart, 1982. A Survey of
Statistical Measures of Model Performance and Accuracy for Several Air Quality
Models. EPA Publication No. EPA-450/4-83-001. U.S. Environmental Protection
Agency, Research Triangle Park, NC.
Mueller, S. F. and R. J. Valente, 1983. Meteorological Data Preprocessing
Manual for the Air Resources Regional Pollution Assessment Model (Generic
Version). TVA/ONR/AQB-83/13. Tennessee Valley Authority, Muscle Shoals, Al.
Mueller, S. F., R. J. Valente, T. L. Crawford, A. L. Sparks, and L. L. Gautney,
Jr., 1983. Description of the Air Resources Regional Pollution Assessment
(ARRPA) Model: September 1983. TVA/ONR/AQB-83/14. Tennessee Valley
Authority, Muscle Shoals, AL.
Myers, T. C., and J. E. Langstaff, 1981. Application of Meteorological and Air
Quality Modeling to the Las Vegas and Tampa Bay Areas. SAI Number 101-81EF81-
108. Systems Applications, Inc., San Rafael, CA.
Pasquill, F., 1976. Atmospheric Dispersion Parameters in Gaussian Plume
Modeling, Part II. EPA Publication No. EPA-600/4-76-030b. U.S. Environmental
Protection Agency, Research Triangle Park, NC.
Seigneur, C., T. W. Tesche, P. M. Roth and M. K. Liu, 1983. On the Treatment
of Point Source Emissions in Urban Air Quality Modeling. Atmospheric
Environment, 17: 1655-1676.
Schere, K. L., and K. L. Demerjian, 1977. Calculation of Selected Photolytic
Rate Constants over a Diurnal Range. EPA Publication No. EPA-600/477-015.
U.S. Environmental Protection Agency, Research Triangle Park, NC.
Turner, D. B., 1964. A Diffusion Model of An Urban Area. Journal of Applied
Meteorology, 3: 83-91.
Turner, D. B., 1969. Workbook of Atmospheric Dispersion Estimates.
PHS Publication No. 999-AP-26. U.S. Environmental Protection Agency, Research
Triangle Park, NC.
Venkatram, A., 1980. Dispersion From an Elevated Source in a Corrective
Boundary Layer. Atmospheric Environment, 14: 1-10.
Wesely, M. L., and B. B. Hicks, 1977. Some Factors That Affect the Deposition
Rates of Sulfur Dioxide and Similar Gases on Vegetation. Journal of the Air
Pollution Control Association, 27: 1110-1116.
BR-3
-------
Whitten, G. Z., J. p. Killus and H. Hogo, 1980. Modeling of Simulated Photo-
chemical Smog with Kinetic Mechanisms. Volume 1. Final Report. EPA
Publication No. EPA-600/3-80-028a. U.S. Environmental Protection Agency,
Research Triangle Park, NC.
Beals, G. A., 1971. A Guide to Local Dispersion of Air Pollutants. Air
Weather Service Technical Report #214 (April 1971) .
Colenbrander, G. H., 1980. A Mathematical Model for the Transient Behavior of
Dense Vapor Clouds, 3rd International Symposium on Loss Prevention and Safety
Promotion in the Process Industries, Basel, Switzerland.
Green, A. E., R. P. Singhal and R. Venkateswar, 1980. Analytical Extensions of
the Gaussian Plume Model. Journal of the Air Pollution Control Association,
30: 773-776.
Lamb, R. G., 1978. Numerical Simulation of Dispersion from an Elevated Point
Source in the Convective Boundary Layer. Atmospheric Environment,
12: 1297-1304.
MacCready, P. B., L. B. Baboolal and P. B. Lissaman, 1974. Diffusion and
Turbulence Aloft Over Complex Terrain. Preprint Volume, AMS Symposium on
Atmospheric Diffusion and Air Pollution, Santa Barbara, CA. American Meteoro-
logical Society, Boston, MA.
Misra, P. K., 1980. Dispersion from Tall Stacks into a Shoreline Environment.
Atmospheric Environment, 14: 397-400.
Misra, P. K. and A. C. McMillan, 1980. On the Dispersion Parameters of Plumes
from Tall Stacks in a Shoreline Environment. Boundary Layer Meteorology,
19: 175-185.
Misra, P. K. and S. Onlock, 1982. Modeling Continuous Fumigation of the
Nanticoke Generating Station. Atmospheric Environment, 16: 479-489.
Slade, D. H., 1968, Meteorology and Atomic Energy. U.S. Atomic Energy Commis-
sion; 445 pp. (NTIS NO. TID-24190)
BR-4 Revised 2/93
-------
1. Source location map(s) showing location with respect to:
0 Urban areas2
0 PSD Class I areas
0 Nonattainment areas2
0 Topographic features (terrain, lakes, river valleys, etc.)2
0 Other major existing sources2
0 Other major sources subject to PSD requirements
0 NWS meteorological observations (surface and upper air)
0 On-site/local meteorological observations (surface and upper air)
0 State/local/on-site air quality monitoring locations2
0 Plant layout on a topographic map covering a 1km radius of the source
with information sufficient to determine GEP stack heights
2. Information on urban/rural characteristics:
0 Land use within 3km of source classified according to Auer (1978):
Correlation of land use and cover with meteorological anomalies.
Journal of Applied Meteorology, 17: 636-643.
0 Population
- > total
-> density
0 Based on current guidance determination of whether the area should be
addressed using urban or rural modeling methodology
'The "Screening Procedures for Estimating the Air Quality Impact of
Stationary Sources, Revised", October 1992 (EPA-450/R-92-019), should be used
as a screening tool to determine whether modeling analyses are required.
Screening procedures should be refined by the user to be site/problem specific.
2Within 50km or distance to which source has a significant impact,
whichever is less.
C-3 Revised 2/93
-------
3. Emission inventory and operating/design parameters for major sources
within region of significant impact of proposed site (same as required for
applicant)
0 Actual and allowable annual emission rates (g/s) and operating rates3
0 Maximum design load short-term emission rate (g/s)3
0 Associated emissions/stack characteristics as a function of load for
maximum, average, and nominal operating conditions if stack height is
less than 6EP or located in complex terrain. Screening analyses as
footnoted on page 1 or detailed analyses, if necessary, must be
employed to determine the constraining load condition (e.g., 50%,
75%, or 100% load) to be relied upon in the short-term modeling
analysis.
- location (DTM's)
- height of stack (m) and grade level above MSL
- stack exit diameter (m)
- exit velocity (m/s)
- exit temperature (°K)
0 Area source emissions (rates, size of area, height of area source)3
0 Location and dimensions of buildings (plant layout drawing)
- to determine GEP stack height
- to determine potential building downwash considerations for stack
heights less than GEP
0 Associated parameters
- boiler size (megawatts, pounds/hr. steam, fuel consumption, etc.)
- boiler parameters (% excess air, boiler type, type of firing, etc.)
- operating conditions (pollutant content in fuel, hours of
operation, capacity factor, % load for winter, summer, etc.)
- pollutant control equipment parameters (design efficiency,
operation record, e.g., can it be bypassed?, etc.)
0 Anticipated growth changes
3Particulate emissions should be specified as a function of particulate
diameter and density ranges.
C-4 Revised 2/93
-------
Air quality monitoring data:
0 Summary of existing observations for latest five years (including any
additional quality assured measured data which can be obtained from
any state or local agency or company)4
0 Comparison with standards
0 Discussion of background due to uninventoried sources and
contributions from outside the inventoried area and description of
the method used for determination of background (should be consistent
with the Guideline on Air Quality Models)
Meteorological data:
0 Five consecutive years of the most recent representative sequential
hourly National Weather Service (NWS) data, or one or more years of
hourly sequential on-site data
0 Discussion of meteorological conditions observed (as applied or
modified for the site-specific area, i.e., identify possible
variations due to difference between the monitoring site and the
specific site of the source)
0 Discussion of topographic/land use influences
Air quality modeling analyses:
0 Model each individual year for which data are available with a
recommended model or model demonstrated to be acceptable on a case-
by-case basis
- urban dispersion coefficients for urban areas
- rural dispersion coefficients for rural areas
0 Evaluate downwash if stack height is less than GEP
° Define worst case meteorology
0 Determine background and document method
- long-term
- short-term
4See footnote 2 of this checklist.
C-5 Revised 2/93
-------
0 Provide topographic map(s) of receptor network with respect to
location of all sources
0 Follow current guidance on selection of receptor sites for refined
analyses
0 Include receptor terrain heights (if applicable) used in analyses
0 Compare model estimates with measurements considering the upper ends
of the frequency distribution
0 Determine extent of significant impact; provide maps
0 Define areas of maximum and highest, second-highest impacts due to
applicant source (refer to format suggested in Air Quality Summary
Tables)
-> long-term
-> short-term
Comparison with acceptable air quality levels:
0 NAAQS
0 PSD increments
0 Emission offset impacts if nonattainment
Documentation and guidelines for modeling methodology:
0 Follow guidance documents
-> "Guideline on Air Quality Models, Revised"
(EPA-450/2-78-027R)
-> "Screening Procedures for Estimating the Air Quality Impact
of Stationary Sources, Revised" (EPA-450/R-92-019), 1992
-> "Guideline for Determination of Good Engineering Practice
Stack Height (Technical Support Document for the Stack Height
Regulations)" (EPA-450/4-80-023R), 1985
-> "Ambient Monitoring Guidelines for PSD" (EPA-450/4-87-007),
1987
-> "Requirements for Preparation, Adoption and Submittal of
Implementation Plans: Approval and Promulgation of Imple-
mentation Plans", 40 CFR Parts 40 and 51 (Prevention of
Significant Deterioration), 1982
C-6 Revised 2/93
-------
Pollutant:
AIR QUALITY SOMMARY
For New Source Alone
Highest Highest Highest Highest
2nd High 2nd High
Annual
Concentration Due to
Modeled Source (/ig/m3)
Background Concentration
Total Concentration (/ig/m3)
Receptor Distance (km)
(or DTM Easting)
Receptor Direction (°)
(or UTM Northing)
Receptor Elevation (m)
Wind Speed (m/s)
Wind Direction (°)
Mixing Depth (m)
Temperature (°K)
Stability
Day/Month/Year of Occurrence
Surface Air Data From _
Surface Station Elevation (m)
Anemometer Height Above Local Ground Level (m)
Upper Air Data From
Period of Record Analyzed
Model Used
Recommended Model
'Use separate sheet for each pollutant (S02, TSP, CO, NO,, HC, Pb, Hg,
Asbestos, etc.)
2List all appropriate averaging periods (1-hr, 3-hr, 8-hr, 24-hr,
30-day, 90-day, etc.) for which an air quality standard exists
C-7
Revised 2/93
-------
Pollutant:
AIR OnaLITY SUMMARY
For All New Sources
Highest Highest Highest Highest
2nd High 2nd High
Annual
Concentration Due to
Modeled Source (/jg/m3)
Background Concentration
Total Concentration (/tg/m3)
Receptor Distance (km)
(or DTM Easting)
Receptor Direction (°)
(or DTM Northing) •
Receptor Elevation (m)
Wind Speed (m/s)
Wind Direction (°)
Mixing Depth (m)
Temperature (°K)
Stability
Day /Month/Year of Occurrence
Surface Air Data From _
Surface Station Elevation (m)
Anemometer Height Above Local Ground Level (m)
Upper Air Data From
Period of Record Analyzed
Model Used
Recommended Model
'Use separate sheet for each pollutant (S02, TSP, CO, NO,, HC, Pb, Hg,
Asbestos, etc.)
2List all appropriate averaging periods (1-hr, 3-hr, 8-hr, 24-hr,
30-day, 90-day, etc.) for which an air quality standard exists
C-8
Revised 2/93
-------
Pollutant:
AIR QUALITY STTMMaRY
For All Sources
Highest Highest Highest Highest
2nd High 2nd High
Annual
Concentration Due to
Modeled Source (/*g/m3)
Background Concentration
Total Concentration
Receptor Distance (km)
(or UTM Easting)
Receptor Direction (°)
(or UTM Northing)
Receptor Elevation (m)
Wind Speed (m/s)
Wind Direction (°)
Mixing Depth (m)
Temperature (°K)
Stability
Day /Month/Year of Occurrence
Surface Air Data From _
Surface Station Elevation (m)
Anemometer Height Above Local Ground Level (m)
Upper Air Data From
Period of Record Analyzed
Model Used
Recommended Model
'Use separate sheet for each pollutant (S02/ TSP, CO, NO,, HC, Pb, Hg,
Asbestos, etc.)
2List all appropriate averaging periods (1-hr, 3-hr, 8-hr, 24-hr,
30-day, 90-day, etc.) for which an air quality standard exists.
C-9
Revised 2/93
------- An error occurred while trying to OCR this image.
------- An error occurred while trying to OCR this image.
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TECHNICAL REPORT DATA
(Please read Instructions on reverse before completing)
1. REPORT NO.
EPA^50/2-78-027R (Supp. B)
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
Supplement B to the Guideline on Air Quality Models
(Revised)
5. REPORT DATE
February 1993
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Source Receptor Analysis Branch
Research Triangle Park, NC 27711
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME AND ADDRESS
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
The Guideline (published as Appendix W to 40 CFR Part 51) serves as the basis by which air quality
models are to be used for demonstrations associated with SIP (State Implementation Plan) revisions,
AQMA (Air Quality Maintenance Area) analyses, regional classifications for episode planning, new
source review, including that pertaining to PSD (Prevention of Significant Deterioration). It is intended
for use by EPA Regional Offices in judging the adequacy of modeling analyses performed by EPA, by
State and local agencies, and by industry and its consultants. It also identifies modeling techniques and
data bases that EPA considers acceptable. The Guideline makes specific recommendations concerning
air quality models, data bases, and general requirements for making concentration estimates.
This is Supplement B to the Guideline. Supplement B: (1) adds several models, including
CTDMPLUS (Complex Terrain Dispersion Model PLus Algorithms for Unstable Situations),
CTSCREEN, EDMS (Emissions and Dispersion Modeling System) for airports, SDM (Shoreline
Dispersion Model), WYNDvalley for valley stagnation, and DEGADIS (DEnse GAs DISpersion Model);
(2) updates several other models, i.e., OCD (Offshore and Coastal Dispersion Model), ISC and
SCREEN (now ISC2 and SCREEN2, resp.); (3) deletes several models (ERTAQ and MPSDM); and (4)
improves several existing techniques and clarifies the appropriate input data for various regulatory
compliance demonstrations. ___
17
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS
c COSAT1 Field/Group
Air Pollution
Atmospheric Dispersion Modeling
Atmospheric Diffusion
Meteorology
Dispersion Modeling
Gaussian Plume Models
Clean Air Act
18 DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (Report)
None
21. NO. OF PAGES
107
20. SECURITY CLASS (Page)
None
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION IS OBSOLETE
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