United States Office of Air Quality EPA-450/2-78-028a
Environmental Protection Planning and Standards OAQPS No. 1.2-097
Agency Research Triangle Park NC 27711 May 1978 « .
_
v>EPA OAQPS Guideline
Series
Workbook for
Comparison of Air
Quality Models
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EPA-450/2-78-028a
OAQPS No. 1.2-097
Workbook for Comparison
of
Air Quality Models
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Monitoring and Data Analysis Division
Research Triangle Park, North Carolina 27711
*>- *
May 1978
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OAQPS GUIDELINE SERIES
The guideline series of reports is being issued by the Office of Air Quality Planning and Standards (OAQPS) to
provide information to state and local air pollution control agencies; for example, to provide guidance on the
acquisition and processing of air quality data and on the planning and analysis requisite for the maintenance of air
quality. Reports published in this series will be available - as supplies permit - from the Library Services Office
(MD-35), U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, or, for a nominal
fee, from the National Technical Information Service, 5285 Port Royal Road, Springfield, Virginia 22161.
Publication No. EPA-450/2-78-028a
(OAQPS Guideline No. 1.2-097)
11
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ACKNOWLEDGEMENT
This workbook was prepared by Argonne National Laboratory for the
Environmental Protection Agency under Interagency Agreement No. EPA-IAG-D6-
0013. The primary authors were Albert E. Smith, Kenneth L. Brubaker,
Richard R. Cirillo, and Donald M. Rote of the Energy and Environmental Systems
Division, ANL. Their contributions are gratefully acknowledged. Extensive
technical and editorial review was provided by staff of the Source Receptor
Analysis Branch, Monitoring and Data Analysis Division.
iii
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TABLE OF CONTENTS
1.
2.
3.
4.
5.
INTRODUCTION
PROCEDURE
2.1 GENERAL
2.2 OVERVIEW
2 . 3 STEP -BY-STEP INSTRUCTIONS
APPLICATION CLASSIFICATION
3.1 INTRODUCTION
3.2 INSTRUCTIONS
3. 3 CLASSIFICATION OF POLLUTANT CHARACTERISTICS
3.4 CLASSIFICATION OF AVERAGING TIMES
3.5 CLASSIFICATION OF SOURCE CHARACTERISTICS
3. 6 CLASSIFICATION OF TRANSPORT CHARACTERISTICS
PRELIMINARY ANALYSIS
4.1 INTRODUCTION
4.2 CHECK COMPATIBILITY OF STUDY MODEL WITH APPLICATION
4 . 3 CLASSIFICATION OF STUDY MODEL
4.4 IDENTIFICATION OF REFERENCE MODEL
4.5 REVIEW AND MODIFICATION OF IMPORTANCE RATINGS
TREATMENT OF APPLICATION ELEMENTS
5.1 INTRODUCTION
5.2 TREATMENT OF SOURCE-RECEPTOR RELATIONSHIP
5.3 TREATMENT OF EMISSION RATE
5.4 TREATMENT OF COMPOSITION OF EMISSIONS
5.5 TREATMENT OF PLUME BEHAVIOR
5.6 TREATMENT OF HORIZONTAL AND VERTICAL WIND FIELDS
5.7 TREATMENT OF HORIZONTAL AND VERTICAL DISPERSION
5.8 TREATMENT OF CHEMISTRY AND REACTION MECHANISM
5.9 TREATMENT OF PHYSICAL REMOVAL PROCESSES
5.10 TREATMENT OF BACKGROUND, BOUNDARY AND INITIAL CONDITIONS...
5. 11 TREATMENT OF TEMPORAL CORRELATIONS ,
Page
1
3
3
4
4
15
15
15
17
21
21
26
29
29
29
30
32
35
51
51
51
59
60
64
65
68
77
78
80
85
IV
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TABLE OF CONTENTS (Cont'd)
Pae
6. COMPARATIVE EVALUATION .......................................... 93
6.1 INTRODUCTION ............................................... 93
6.2 TECHNICAL COMPARISON ....................................... 93
6.2.1 Comparing Treatments of Individual Elements
6.2.2 Overall Technical Comparison
6.2.2.1 Comparison .Based on HIGH-Rated
Elements
6.2.2.2 Comparison Based on MEDIUM- and LOW-Rated
Elements , 98
6.2.2.3 Comparison with a CRITICAL Element "
7. ROLLBACK/STATISTICAL MODELS 101
7.1 GENERAL 101
7.2 ADVANTAGES AND DISADVANTAGES 102
7. 3 COMPARISON OF ROLLBACK/STATISTICAL MODELS 103
APPENDIX A, TECHNICAL SUPPORT MATERIAL, t,, A-1
APPENDIX B. BACKGROUND MATERIAL ON REFERENCE MODELS %_i
APPENDIX C. APPLICATIONS TO SPECIFIC MODELS ,«....,,.., C-l
APPENDIX D. APPLICATION CLASSIFICATION AND MODEL EVALUATION FORMS.. D_!
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LIST OF TABLES
Number Page
2.1 Workbook Section and Form for Each Step in Comparison 4
3 .1 Classification of Criteria Pollutants , 22
3.2 Classification of NAAQS Averaging Times 23
3.3 Classification of Common Source Categories 25
4.1 Suggested Reference Models for Indexed Applications , 33
4.2 Importance Ratings for Source-Receptor Relationship 39
4.3 Importance Ratings for Emission Rate 40
4.4 Importance Ratings for Chemical Composition of Emissions 41
4 .5 Importance Ratings for Plume Behavior 42
4.6 Importance Ratings for Horizontal Wind Field 43
4.7 Importance Ratings for Vertical Wind Field 44
4.8 Importance Ratings for Horizontal Dispersion 45
4.9 Importance Ratings for Vertical Dispersion 46
4.10 Importance Ratings for Chemistry and Reactor Mechanism 47
4.11 Importance Ratings for Physical Removal Processes 48
4.12 Importance Ratings for Background, Boundary and
Initial Conditions 49
4.13 Importance Ratings for Temporal Correlations 50
5.1 Treatment of Source-Receptor Relationship 52
5.2 Treatment of Emission Rate 61
5.3 Treatment of Composition of Emissions 63
5.4 Treatment of Plume Behavior 66
5.5 Treatment of Horizontal Wind Field 69
5.6 Treatment of Vertical Wind Field 70
5.7 General Treatment of Dispersion 71
5.8 Treatment of Atmospheric Stability 73
VI
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LIST OF TABLES (Cont'd)
Number Page
5.9 Treatment of Surface Roughness 73
5.10 Possible Bases for Estimating Dispersion Parameter Values 74
5.11 Spatial and/or Temporal Dependence of Eddy Diffusivities 76
5.12 Treatment of Chemistry and Reaction Mechanism 79
5.13 Treatment of Physical Removal Processes 81
5.14 Treatment of Background, Boundary and Initial Conditions 86
5.15 Treatment of Temporal Correlations 92
6.1 Effect of Numbers of Elements on Ratings 99
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LIST OF FIGURES
Number Page
2.1 Procedure for the Comparison of Air Quality
Simulation Models 5
2.2 Evaluation Form - Part A 8
2.3 Application Elements as Major Factors Affecting
Pollutant Concentrations 9
2 .4 Evaluation Form - Part B 10
2 .5 Evaluation Form - Part C 12
2 .6 Evaluat ion Form - Part D 14
3.1 Scheme for Classifying Model Applications 16
3.2 Sample Completed Application Classification Form 18
3.3 Decision Tree for Classifying Pollutant Characteristics 19
3.4 Decision Tree for Classifying Averaging Times 22
3.5 Decision Tree for Classifying Source Characteristics 23
3.6 Decision Tree for Classifying Transport Characteristics 26
viii
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1 INTRODUCTION
A wide variety of air quality dispersion models are used by regulatory
agencies, consulting firms and industry to estimate the air quality impacts of
pollutant sources. It is often desired to compare two or more models to
determine which is the most acceptable for a given application. It is particu-
larly useful to be able to compare a given model with those which, by virtue
of their extensive use, are familiar to most of the modeling community.
This workbook describes a technique for the qualitative comparison of
modeling approaches on technical grounds. The methodology is based upon an
applications approach. The results of the model comparison depend upon the
application for which the model is to be used as well as upon the model char-
acteristics. In each application of the technique, the model of interest
(the "study" model) is compared with a "reference" model. Any models may be
specified as study or reference models, as long as they are compatible with
the application of interest.
The approach taken in this workbook is restricted to models that
mathematically simulate the physical phenomena which determine atmospheric
pollutant concentrations. Simulation models may require locally measured
air quality data in order to fix the initial and boundary conditions or to
determine appropriate background pollutant levels. Models excluded from
that category are any that make use of locally measured air quality data to
optimize or determine adjustable parameters unrelated to the physical pro-
cesses being simulated. Thus, for example, calibration or averaging time
conversion procedures are not considered as part of a simulation model but
rather as statistical procedures which are applied to the calculations of a
simulation model. Rollback models are also excluded from the category of
simulation models. General considerations involved in the comparison of
rollback and statistical or empirical models are discussed briefly in Sec-
tion 7.
Although the amount and detail of the technical material, particularly
that in Appendix A, may appear rather formidable to the user, it has been
included for reference purposes and as an aid in dealing with unfamiliar
treatments or situations. The user should refer to the examples in Appendix c
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2
If examples of the application of the methodology are examined, it should
become clear that use of this workbook is not difficult.
It is important to understand that the methodology described in this
workbook does not enable the user to evaluate the results obtained using a
particular air quality model. That would require an evaluation of the
quality and suitability of the input data as well as of the model. The
methodology enables the user to determine only if the model used is as tech-
nically adequate as another model for the application of interest.
The workbook contains seven main sections and four appendices.
Section 2 contains an overall description of the methodology and general
instructions for its implementation. Sections 3-6 contain specific instruc-
tions and guidelines for carrying out various steps in the procedure. Sec-
tion 3 deals with the classification of the user's application. Section 4 is
concerned with the general suitability and compatibility of a model with the
given application. It also considers the importance of various aspects of
atmospheric dispersion in that application. Selected reference models for
the various applications are also suggested in Section 4. Section 5 provides
guidelines for identifying the treatments of various physical phenomena by a
given model. Section 6 contains instructions and guidelines for making the
comparative evaluation. Finally, Section 7 contains a discussion of some of
the considerations involved in comparing rollback/statistical models.
The appendices contain general reference material useful in imple-
menting the methodology. Appendix A contains technical discussions of the
physical phenomena that determine atmospheric pollutant concentrations. It
also contains a discussion of the importance of each phenomenon in different
types of applications. Appendix B contains information on the treatments of
these phenomena by selected reference models, including the working equations.
Appendix C provides several examples of the use of the methodology in various
common applications. Finally, copies of each of the various forms used in
the methodology are provided for the user's convenience in Appendix D.
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2 PROCEDURE
2.1 GENERAL
This section provides a general overview of the methodology, outlines
the steps involved, and explains the types of information and decisions re-
quired at each step. The user is required to exercise judgment and to make
qualitative decisions at each step, since model comparison is not, and cannot
be made routine. Information and guidelines are provided for each step in
the procedure. Prior to the initial use of the methodology, the user should
read and understand the guidelines in this section. The experienced user
can proceed directly to the comparison with occasional consultation of the
reference materials.
The procedure is application-specific; that is, the results depend
upon the specific situation to be modeled. Initially, the user identifies
both the application of interest and an associated "reference model." This
reference model serves as a standard of comparison against which the user
gages the "study model" being evaluated. The way in which the study model
treats twelve aspects of atmospheric dispersion called "application elements,"
or simply "elements" is determined. These application elements represent
physical and chemical phenomena that govern atmospheric pollutant concen-
trations and include such aspects as horizontal and vertical dispersion,
emission rate, and chemical reactions. The importance of each element to the
application is defined in terms of an "importance rating." Tables giving the
importance ratings for each element are provided, although the user
may modify them under some circumstances. The heart of the procedure
involves an element-by-element comparison of the way in which each element
is treated by the two models. These individual comparisons, together with
the importance ratings for each element in the given application, form the
basis upon which the final comparative evaluation of the two models is made.
It is especially important that the user understand the physical
phenomena involved, because the comparison of two models with respect to the
way that they treat these phenomena is basic to the procedure. Sufficient
information is provided in the text to permit these comparisons to be made
and the availability of expert advice in the event of difficulties is
assumed.
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2.2 OVERVIEW
Comparison of a study model to a reference model is carried out in
nine steps. Table 2.1 lists the section and tables to be used for each step
in the comparison. Figure 2.1 illustrates schematically the steps in the
comparison and their relation to each other. Greater detail, specific guide-
lines, and tables are given in Sections 3-6 and Appendices A and B. Forms
for organizing and documenting a comparison are provided in Appendix D,
Table 2.1. Workbook Section and Form for Each Step in Comparison
Step
Number
Action
Workbook
Sections
Form in
Appendix D
1 Classify application
Record study model information
2 Document study model equations
3 Check study model compatibility
o
4 Classify study model type
5 Identify reference model
6 Review importance ratings
7 Determine treatments of elements
8 Compare treatments on element-by-
element basis
9 Synthesize individual comparisons
into overall comparison
3 Application Classi-
fication Form
2.3 Evaluation Form A
2.3 Reverse side of
Evaluation Form A
4.2 Evaluation Form A
4.3 Evaluation Form A
4.4 Evaluation Form A
4.5 Evaluation Form B
5 Evaluation Form C
6.2.1 Evaluation Form C
6.2.2 Evaluation Form D
If the study model has been classified as
user should proceed directly to Section 7
a rollback/statistical model, the
wherein such models are discussed.
2.3 STEP-BY-STEP INSTRUCTIONS
Step 1 - Classify Application; Record Basic Information
The user first classifies the application of interest. Specifically,
the user considers each of the following four aspects of the application:
Pollutant characteristics,
Averaging time,
Source characteristics, and
Transport characteristics.
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2. DOCUMENT STUDY
MODEL EQUATIONS
3. CHECK COMPATIBILITY
OF STUDY MODEL
WITH APPLICATION
4. CLASSIFY STUDY
MODEL
1. CLASSIFY APPLICATION
5. IDENTIFY
REFERENCE MODEL
7. DETERMINE TREATMENTS
OF ELEMENTS
BY BOTH MODELS
8. COMPARE TREATMENTS OF
EACH ELEMENT BASED ON
RELATIVE LEVEL OF DETAIL
6. REVIEW AND MODIFY
IMPORTANCE RATINGS
IF NECESSARY
9. COMBINE TREATMENT COMPARISONS
WITH IMPORTANCE RATINGS
RESULT:
COMPARATIVE EVALUATION
Note: Numbers in the boxes refer to the steps in the comparison procedure
as given in Table 2.1.
Figure 2.1. Procedure for the Comparison of Air Quality Simulation Models
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The classification is based on an application tree approach as described in
Section 3. An Application Classification Form (see Figure 3.2 or Appendix D)
is provided for carrying out this classification. Next, the four-digit "appli-
cation index" is determined. This index identifies the application throughout
the remainder of the comparison. The application must be classified with
respect to the physical situation being modeled. Some basic background infor-
mation about the study model is then recorded.
Step 2 - Document Study Model Equations
The element-by-element comparisons are facilitated by listing the (
major equations used by the study model on the back of the Evaluation Form -
Part A. The user must examine the study model documentation carefully to
determine the equations which are actually used. In some cases, when the
study model documentation is inadequate or inconsistent, it may be necessary
to examine the computer code itself to make the determination. The equations
used by selected reference models are documented in Appendix B.
Step 3 - Check Model Compatibility
In this step the general compatibility of the study model with the
application of interest is checked. Brief guidelines are given in Section 4.2
for determining whether
Treatments of elements essential to the application of
interest are incorporated in the study model and
Output from the study model meets the user's requirements.
The documentation for the study model should contain the information to make
the compatibility determination.
Step 4 - Classify Study Model Type
In this step, the study model is classified according to the general
modeling approach adopted. This model classification is useful in identifying
the way in which the model treats several application elements. Specific
guidelines can be found in Section 4.3.
If the model is classified as a rollback/statistical model, or if it is
found to involve both simulation and statistical estimation procedures, the
methodology described in this workbook does not apply. A general discussion
of some of the considerations involved in the comparison of such models may be
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found in Section 7. If the study model incorporates a calibration procedure
which empirically adjust the estimates made by a simulation model, the user
should consider only the simulation model and simply ignore the presence of the
calibration procedure when applying the methodology.
Step 5 - Identify Reference Model
Table 4.1, Section 4.4, identifies suggested reference models for some
of the indexed applications. This step only involves looking up the appro-
priate reference model for the application index determined in Step 1.
At this point, the Evaluation Form - Part A should be completely
filled out. This form is shown in Figure 2.2.
Step 6 - Review and Modify Importance Ratings
This is the first step in which the user must consider the twelve
application elements. Each element specifies a particular physical aspect
of the overall processes by which the emission of pollutants into the at-
mosphere affects the air quality at some point. Figure 2.3 depicts the re-
lationship between these application elements and the estimation of atmos-
pheric pollutant levels. In order to compare the study model to the re-
ference model, the user needs to know
The importance of each element to the application of
interest and
How the treatment used by the study model compares to
that used by the reference model.
An estimate of the importance of each element to each application can be
found from Tables 4.2-4.13 in Section 4.5. Each element has been rated as
being of HIGH, MEDIUM, or LOW importance to each application. The user
should review these importance ratings. In light of the specific appli-
cation, a particular rating may either be changed to another of the ratings
given above or be designated as CRITICAL or IRRELEVANT. Critical elements
are those to which it is desired to give extraordinary weight when the two
models are compared. Irrelevant elements describe processes that are in-
operative in the application of interest* Generally, with the exception of
irrelevant elements, the user should expect to make very few modifications
to the given ratings and, at most, one CRITICAL designation.
The Evaluation Form - Part B should now be completed by indicating
the importance rating for each application element and any changes (see
Figure 2.4).
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8
EVALUATION FORM
Part A; Abstract and References
Study Model;
References:
Abstract:
Classification:
Application Index: Reference Model:
Application Description;
Model Applicability: Applicable
Not Applicable
Note: The reverse side of this form for documenting the equations
is not shown.
Figure 2.2. Evaluation Form - Part A
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10
EVALUATION FORM
Part B; Importance Ratings
Application Index:
Application Importance Rating
Element Initial Modified3
Source-Receptor Relationship
Emission Rate
Composition of Emissions
Plume Behavior
Horizontal Wind Field
Vertical Wind Speed
Horizontal Dispersion
Vertical Dispersion
Chemistry and Reaction Mechanism
Physical Removal Processes
Background, Boundary, Initial Conditions
Temporal Correlations
the exception of the designation of IRRELEVANT elements, it is expected
that at most one CRITICAL designation and possibly one other modification
may be made.
Figure 2.4. Evaluation Form - Part B
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11
Step 7 - Determine Treatments of Application Elements
In this step the treatments of the application elements by both the
study model and the reference model are determined. The treatments for each
element should be described on the Evaluation Form - Part C. The user
should consult that part of Section 5 that corresponds to each element.
Section 5 gives guidelines, questions, and tables to aid the user in de-
termining the study model's treatment of each element. If additional guid-
ance is needed, Appendix A provides detailed discussions of various common
treatments of the application elements.
The treatment of each element by selected reference models can be
found in Tables B.2-B.13 in Appendix B.
It is strongly recommended that the sections of Appendix A appropriate
to each element be read. The general discussion in each section provides
information on the physical processes which are involved and hence builds a
foundation for making the comparisons required in Step 8.
Step 8 - Compare the Two Treatments of Each Element
Once the treatment of a particular element has been determined, the
next step is to determine whether the study model's treatment of that element
is
BETTER than,
COMPARABLE to, or
WORSE than
that of the reference model. Detailed guidance on making this comparison is
given in Section 6.2.1. The required comparison is qualitative. Occasionally,
the user may have some difficulty in deciding whether, for instance, the
study model's treatment is better than or comparable to the reference model's.
In such cases, it is suggested that the user enter the best estimate and
note the other rating in parentheses for later consideration. In general,
the user is urged to make a unique comparison whenever possible.
The Evaluation Form - Part C should be completed at this point (see
Figure 2.5). Note that the form in Figure 2.5 contains room for describing
the treatments of two elements only. Additional copies of this form up to a
maximum total of six will be required in order to handle all relevant elements.
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13
Step 9 - Synthesize the Final Technical Comparison
The information required for the final technical comparison can be
organized on the Evaluation Form - Part D (see Figure 2.6). As discussed in
Section 6.2.2, the user first summarizes the results of the element-by-element
comparisons. An initial evaluation is made by considering the relative treat-
ments of the most important elements, and this initial evaluation is then
modified or not according to the relative treatments of the elements of
lesser importance. Elements of low importance are considered only in am-
biguous cases. The final evaluation obtained in this way represents the
final result of applying the methodology and at this point the comparison
is complete.
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15
3 APPLICATION CLASSIFICATION
3.1 INTRODUCTION
The first step in the methodology is to suitably define the application
as discussed in Sections 3.2-3.6. This workbook cannot treat all possible
factors in detail. Thus, the user needs to consider the situation of interest
and to exercise judgment at all stages of the evaluation. It is necessary,
however, to classify the application in as much detail as practicable.
Four general aspects of air pollution simulation have been identified
as being suitable for this purpose. In this section, the user classifies the
application with respect to these four aspects. In the process, a four digit
number is generated. This number serves to identify the class of applica-
tions to be considered in the comparison. This number, the application index,
is used throughout the workbook for various purposes. The user should not
consider in any way the details of the operation of either the reference or
the study model in classifying the application. The classification should
reflect only the characteristics of the problem at hand without regard to
possible simulation techniques.
Note that meteorological concepts are not used in the classification
scheme. Relevant aspects of meteorology comprise several of the application
elements discussed in Section 5.
3.2 INSTRUCTIONS
The following procedure enables the user to classify the application
of interest and to construct the application index. Figure 3.1 shows the
classification process schematically. Decision trees and the accompanying
guidelines are used to classify the application in the following four
categories:
Pollutant characteristics
Averaging time,
Source characteristics, and
Transport characteristics.
The trees require definite decisions at each branch point. In cases of un-
certainty, the user may follow multiple branches and refer to the application
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16
( BEG
\
\
X METHOD OF
1M A PRODUCTION
/
PRIMARY ]/
1 K
/ v
POLLUTANT /
CHARACTERISTICS \
\ L
\ SECONDARY If
V\_
Y
LONG-TERM
AVERAGING S
TIME X SHORT-TERM
NUMBER
LIMITED /
SOURCE / \
REMOVAL
PROCESSES
NONE
CHEMICAL
PHYSICAL
CHEMICAL 8 PHYSICAL
NONE
CHEMICAL
PHYSICAL
CHEMICAL 8 PHYSICAL
GEOMETERY
POINT
AREA
LINE
CHARACTERISTICS \
\ MULTIPLE/COMBINATION
GEOGRAPHIC
FEATURES
COMPLEX /"
/ X.
TRANSPORT /
CHARACTERISTICS^
\ SIMPLE /~
X
APPLICATION
INDEX
TRANSPORT
DISTANCE
SHORT-RANGE
LONG-RANGE
SHORT-RANGE
LONG-RANGE
1
2
3
4
5
6
7
8
1
2
1
2
3
4
1
2
3
4
Figure 3.1. Scheme for Classifying Model Applications
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17
element descriptions in Appendix A. The information in these detailed des-
criptions may facilitate the identification of the most pertinent classifica-
tion. Each branch of each decision tree ends in a one-digit number that
classifies the given application within the category being considered. After
classifying the application in all four categories, the index numbers are
combined into the four-digit composite application index.
The steps in classifying the application are listed below:
1. Classify the application within each of the four categories
shown In Figure 3.1.
2. Determine the one-digit numbers corresponding to the
specific classification chosen within each of the four
categories.
3. Form the composite application index from these four
one-digit numbers.
In classifying the application, the user should consult the guidelines
for each descriptive category contained in Sections 3.3-3.6.
As an example, consider an application that involves estimating the
short-term concentrations of total suspended particulate (a primary pollutant)
due to a power plant (single point source) when (1) the interest is in the
area close to the plant; (2) particulate removal by fallout, deposition, etc.
can be ignored; and (3) the local geographic features are simple. The appli-
cation index would be 1213, corresponding to the index numbers of 1, 2, 1 and
3 for the categories "pollutant characteristics," "averaging time," "source
characteristics," and "transport characteristics" respectively. Figure 3.2
shows a completed sample Application Classification Form for this specific
example.
3.3 CLASSIFICATION OF POLLUTANT CHARACTERISTICS
The decision tree for classifying pollutant characteristics is shown
in Figure 3.3. The tree indicates processes by which pollutants are pro-
duced and/or removed from the atmosphere. The first step is to classify the
pollutant as either primary or secondary. Primary pollutants are defined as
those emitted directly into the atmosphere and secondary pollutants are de-
fined as those produced in the atmosphere by chemical reactions. For example,
if the application involves estimating the additional CO concentration caused
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19
METHOD OF
PRODUCTION
POLLUTANT
REMOVAL INDEX
PROCESSES NUMBER
PRIMARY
POLLUTANT
CHARACTERISTICS
SECONDARY
NONE
CHEMICAL
PHYSICAL
CHEMICAL 8
PHYSICAL
3
4
1
CHEMICAL
f
^ PHYSICAL
i CHEMICAL a
3
,, 7
a
Figure 3.3. Decision Tree for Classifying Pollutant Characteristics
by a new highway link, CO is classified as a primary pollutant because it
comes directly from the vehicular sources using the link. The most common
example of a secondary pollutant is ozone, which is produced by photo-
chemically initiated reactions involving reactive hydrocarbons and nitrogen
oxides.
When the application involves a secondary pollutant, it eventually
becomes necessary to determine the chemical identity of the primary pre-
cursors of that pollutant. Knowledge of the nature of the precursors and
their sources is required by the nature of the modeling process; namely, to
relate emissions from sources to atmospheric concentrations. Primary pre-
cursors are defined here as those substances that are emitted directly into
the atmosphere, undergo chemical reaction, and whose ultimate reaction pro-
ducts include the pollutant of interest. Determination of the precursors
often requires expert advice but is not required at this point in the
classification. Knowledge of sources of the precursors is necessary when
the source characteristics are classified.
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20
A particular pollutant can be both emitted directly into the atmosphere
and produced by atmospheric chemical reactions; hence it can be both primary
and secondary. For example, particulate sulfates are emitted directly from
catalytic converters on automobiles and result as well from atmospheric re-
actions involving S02. In applications involving the total concentration of
such a pollutant, it may be possible to choose a single classification. For
example, if primary sources are known to be dominant, the pollutant should
be classified primary. On the other hand, if secondary generation dominates,
the secondary classification should be used. In situations where neither
prevails, both branches should be explored. The model used must be able to
handle both primary and secondary production. In such cases, the comparison
will involve going through the evaluation process twice: identifying two
applications, two reference models, two sets of importance ratings and making
two independent evaluations. These evaluations can then be weighted by the
relative importance of primary and secondary production and combined to
arrive at the desired overall comparison.
In applications involving a specific source, the classification should
be made based upon whether the pollutant emitted from that source is the
pollutant of interest or a precursor.
After the method of production has been classified, the processes by
which the pollutant is removed from the atmosphere must be classified. This
second classification should be made by considering removal processes that
are important over the range of time and distance involved in the applica-
tion. In some situations, removal of the pollutant may be negligible and
the branch labeled "None" is chosen. The determining factor is the rela-
tionship between the pollutant's removal rate under the conditions being
studied and its residence time within the study area. Estimation of the
appropriate removal rates may require expert advice. If roughly more than
one-quarter to one-third of the pollutant could be removed within the study
area, removal processes should be accounted for within a simulation model.
If removal is important, a decision is required as to the type of re-
moval processes involved. Chemical removal processes are those in which the
pollutant reacts chemically in the atmosphere as, for example, when S02
reacts to form sulfates and ceases to exist as the chemical species of inter-
est. Physical removal processes produce a change in the amount of pollutant
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21
in the air without causing an immediate change in the chemical species of the
material removed. They include such processes as gravitational settling,
impaction, precipitation scavenging, and dry deposition. In cases where both
chemical and physical removal processes are significant, the branch labeled
"Chemical and Physical" should be chosen, even if the user is interested pri-
marily in only one type. Of course, if one type of removal process is clearly
predominant, that branch should be chosen.
Other terminology is frequently employed in discussing pollutant
characteristics. Reactive pollutants are those that react chemically in
the atmosphere. They thus belong on one of the four branches labelled
"chemical" or "chemical and physical" removal. Pollutants that are not
reactive are called stable even if physical processes remove them from
the atmosphere. Conservative pollutants are those for which no removal
process is significant enough to be considered.
Common characteristics of the criteria pollutants are given in
Table 3.1. The indicated classifications are illustrative only and are not
intended as an exhaustive list of all possibilities. In other circumstances,
the classification might be different from those shown in the table.
3.4 CLASSIFICATION OF AVERAGING TIMES
The decision tree for classifying averaging times is shown in Figure
3.4. The time of interest is that over which the estimated concentrations
are to be averaged. For a particular pollutant, averaging times from several
minutes to a year may be of interest. Applications involving concentrations
averaged for 24 hours or less should be considered as distinct from those in
which seasonal or annual averages are estimated. The former are classified
as short-term. Longer averaging times like a month, season, or year are
classified as long-term. Table 3.2 classifies the averaging times specified
in the NAAQS.
3.5 CLASSIFICATION OF SOURCE CHARACTERISTICS
In order to classify source characteristics, the number and the geometry
of the sources involved in the application must be determined. The decision
tree for classifying source characteristics is shown in Figure 3.5. The
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22
Table 3.1 Classification of Criteria Pollutants'
Pollutant
Conditions
Method of
Production
Removal
Processes
Pollutant
Index Number
TSP
S02
Particles smaller
than about 30pm.
Particles larger
than about 30ym.
Residence time,
under 5-8 hrs.
Primary None 1
Primary Physical 3
(gravitational
settling)
CO
NO 2
Oxidants
Non-methane
Hydrocarbons
Residence time
over 5-8 hrs.
Most conditions.
Most sources emit
mainly NO which
reacts to form N02
Primary sources
are generally
negligible.
-
Primary Chemical and
Physical
Primary None
Secondary Chemical
Secondary Chemical
Primary Chemical
4
1
6
6
2
a
These characteristics are for short-range urban situations without pre-
cipitation and could change under other circumstances.
"Residence time" is approximated by the time taken to traverse the
region of interest at a characteristic wind speed.
LONG-TERM
AVERAGING
TIME INDEX
NUMBER
AVERAGING
TIME
SHORT-TERM
Figure 3.4. Decision Tree for Classifying Averaging Times
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23
Table 3.2 Classification of NAAQS Averaging Times
Pollutant
TSPa
so2a
CO
Oxidants
Hydrocarbons
N02
Averaging Time
Annual
2 4 -hour
Annual
2 4 -hour
3 -hour
8 -hour
1-hour
1-hour
3 -hour
Annual
Classification
Long-term
Short-term
Long-term
Short-term
Short-term
Short-term
Short-term
Short-term
Short-term
Long-term
Averaging
Time
Index No.
1
2
1
2
2
2
2
2
2
1
o
These averaging times are also specified for the Prevention of Significant
Deterioration (PSD) increments.
SOURCE
CHARACTERISTICS
NUMBER GEOMETRY INDEX NUMBER
POINT
LIMITED f AREA 2
LINE ,
SOURCE
CHARACTERISTICS
\
MULTIPLE/COMBINATION
Figure 3.5. Decision Tree for Classifying Source Characteristics
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24
proper branch of the tree is chosen by considering both the number and the
geometry together. The user should choose the branch appropriate to the
physical characteristics of the sources as inventoried for use in the model.
Whenever the dimensions of a stationary source are small compared to
the distance at which concentrations are to be estimated, the source can be
treated as a geometric point. Generally, sources are treated as points if
they emit a substantial amount of any criteria pollutant, e.g. 100 tons per
year. Some control agencies treat sources with as little as 1 ton per year
of emissions as points.
Sources that emit small amounts of pollutant are usually aggregated
and treated as uniform area sources. Their large number and highly variable
emission rates preclude treating them as individual sources. In addition,
some sources, such as open quarries or windblown fields, are "true" area
sources due to their geometry. They are not aggregates of many point or
line sources.
The line source designation is usually reserved for special problems
involving aircraft or microscale analyses of vehicular impacts. As is the
case with multiple point sources, closely packed line sources such as streets
in downtown areas are frequently treated as uniform area sources. If indivi-
dual line source data exists, the more appropriate line classification should
be made; if the data base aggregates the lines to areas, the area classifica-
tion should be made.
A small number of sources (generally less than 10-20) having the same
geometry should be classified "limited" in number. Thus, if the impact of a
power plant with five stacks were being estimated, the "limited" branch should
be chosen. The same choice should also be made if five spatially separated
sources are involved. However, in the latter case, the user should be aware
that some models for treating a limited number of sources assume that these
sources are coincident in space or equivalently that the separations between
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25
sources are small compared to the transport distances. The choice between the
"limited" or the "multiple" branch should be based on the number of sources to
be modeled, not the number of actual sources. Thus, if several hundred small
incinerators have been inventoried as six area sources, the sources would be
characterized as limited in number (six area sources), not multiple.
If either multiple sources or several source geometries are to be
modeled, the "Multiple/Combination" branch is chosen. If a limited number of
sources of a single geometry are to be modeled, the appropriate branch along
the "Limited" path is chosen.
The source characteristics of some common source categories are given
in Table 3.3. In particular applications, these general guidelines may be
modified. For example, if the impact of a small number of industrial process
sources is being investigated, the source characteristics should be classified
as a limited number of point sources and not as part of an aggregated area
source.
Table 3.3. Classification of Common Source Categories
Source Category
Industrial
Process
Fuel Combustion
(Internal and
External)
Transpor tat ion
Electricity
Generation
Incineration
Urban Area
Number
Limited
Multiple
Limited
Multiple
Limited
Multiple
Limited
Multiple
Limited
Multiple
Multiple
Source
Size3
Large
Small
Large
Small
Various
Geometric
Description
Point
Area
Point
Area
Line
Line or Area
Point
Point
Point
Area
Combination
Source Characteristics
Index Number
1
4
1
4
3
4
1
4
1
4
4
a
Source size is measured relative to the point source size specified in the
emission inventory. For example, major (large) sources are generally consid-
ered to be those that emit more than 100 tons per year.
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26
3.6 CLASSIFICATION OF TRANSPORT CHARACTERISTICS
The decision tree for classifying transport characteristics is shown in
Figure 3.6. This tree classifies the application with respect to geographic
features and the transport distance from sources to receptors. One important
general factor affecting transport has been omitted from the tree: meteorology.
Meteorology has been omitted so that the application can be defined by rela-
tively fixed or invariant characteristics of the application rather than by the
variable factors which affect transport and dispersion.
The application is defined by specific pollutant characteristics,
specific averaging times, well-defined source characteristics, well-defined
geography, and a specific region. However, a wide range of meteorological
conditions frequently must be analyzed. The relevant meteorological con-
siderations and transport under certain specific adverse meteorological
conditions are discussed in Appendices A.2 and A.4.
TRANSPORT
GEOGRAPHIC TRANSPORT CHARACTERISTICS
FEATURES DISTANCE INDEX NUMBER
SHORT-RANGE
COMPLEX
LONG-RANGE
TRANSPORT
CHARACTERISTICS
SHORT-RANGE
SIMPLE
LONG-RANGE
Figure 3.6. Decision Tree for Classifying Transport Characteristics
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27
Geographic features should be classified as complex if their presence
requires the consideration of point-to-point variations in the speed or
direction of transport winds. Applications involving areas with rough
terrain, areas containing or close to a large body of water, or areas in
valleys or street canyons should generally be classified as having "complex"
geographic features. Areas with level or gently rolling terrain should
generally be classified as having "simple" geographic features. Determining
the appropriate classification may require the advice of an expert air
pollution meteorologist. The determination may also depend upon other
features of the specific application. For example, variations in terrain that
are significant when short-range transport is being considered might be in-
significant when long-range transport is of interest. In coastal areas or
near the Great Lakes, the potential effects of sea or lake breezes may
require the complex classification. The precise distance inland over which
the complex classification must be maintained cannot be specified without
knowing the details of the application. If in doubt, the user should consult
the technical material in Appendices A.3 and A.4 or obtain expert advice on
the particular situation.
A different set of applications arises when the effects of sources are
estimated over long rather than short distances. As a general rule-of-thumb,
distances between sources and receptors that exceed 60-100 km (40-60 mi)
should be classified long-range. The transport distance is also related to
the residence time considered when the pollutant characteristics were
classified. Care should be taken to see that the two choices are made on a
consistent basis.
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29
4 PRELIMINARY ANALYSIS
4.1 INTRODUCTION
In this section, guidelines and instructions are provided to enable
the user to carry out steps 3-6 as given in Table 2.1 and shown in Figure 2.1.
These steps involve a check to see that the study model is compatible with
the application in certain essential respects, the classification of the
study model, the identification of the reference model to be used in the
comparison, and the review and possible modification of the importance ratings.
These steps are considered in Sections 4.2-4.5, respectively. Sufficient
guidelines for carrying out Step 2, the documentation of the study model
equations, may be found in Section 2.3.
4.2 CHECK COMPATIBILITY OF STUDY MODEL WITH APPLICATION
It is desirable, before proceeding further, to determine that the study
model meets two specific requirements of the application of interest and is
therefore compatible with it. Generally, reference models can be used as
standards for comparison even when they are not strictly compatible with the
application of interest.
The first requirement is that the study model should contain treatments
of all elements in which the user has a specific interest or which are required
by the nature of the application. For example, if the user has determined that
some specific physical removal process is important for the application of
interest, and has as a result chosen the appropriate branch in the Application
Tree, the study model should incorporate a treatment, however simplified, of
that process. If the pollutant of interest is subject to chemical removal
processes, and/or if it is a secondary pollutant, the study model should incor-
porate a treatment of the effects of the relevant chemical reactions. This
may be extended to processes not covered in this workbook. If the user is
interested in the effects of any process whatever, the study model must incor-
porate a treatment of that process.
The second requirement is that the study model should provide the user
with the desired results. No attempt is made to list the various possibi-
lities here. It is assumed that the user knows what estimates are desired
and can determine whether or not the study model provides them. For example,
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30
the application might involve calculating the frequency distribution of
twenty-four hour averages at some location. In this case, a model which
gives only the maximum twenty-four hour average is not compatible with the
user's application, because the desired information is not available as an
output from the model.
4.3 CLASSIFICATION OF STUDY MODEL
The possible treatments of several application elements depend upon the
general type of model being considered. It is, therefore, useful to classify
the study model with regard to certain general characteristics. Guidelines
are provided in this section to enable the user to carry out this classifica-
tion; further discussion may be found in Appendix A.4.2.
The study model should first be categorized as either a simulation
model or as a rollback/statistical model. The distinctions between these two
broad categories are based upon
The extent to which the model in question attempts to
simulate the relevant physical and chemical processes
which significantly affect atmospheric pollution levels
and
The degree to which locally measured air quality data are
required for model usage or for the adjustment of model
parameters.
A simulation model should attempt to describe mathematically the effects of
all relevant physical phenomena expected to have a significant effect on air
quality in the application of interest. It should not absolutely require the
existence and use of locally measured air quality data except possibly to fix
initial and boundary conditions. For example, a model which incorporates a
model calibration procedure involving a statistical adjustment of concentration
estimates should still be classified as a simulation model.
Rollback/statistical models are also formulated mathematically and may
require many of the same input variables, such as wind speed or mixing height,
as do simulation models. They do not, however, attempt to describe the physi-
cal processes involved in the transport and dispersion of pollutants from
source to receptor in order to estimate pollutant concentrations. Instead,
the relationship between concentrations and the model input variables is deter-
mined empirically. This is usually done by assuming some simple functional
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31
relationship containing one or more adjustable parameters and then determining
the values of these parameters that produce the best agreement with air
quality data.
If the study model is classified as a rollback/statistical model, or
if statistical conversion of averaging times is used by the model, the
methodology described in this workbook does not apply. General guidelines
regarding the comparison of rollback/statistical models may be found in
Section 7 but the user should consult with an expert to determine the proper
way to perform the evaluation in such cases.
If the study model is a simulation model, it may be categorized
according to the following two additional features:
1. General modeling approach adopted
Numerical, involving the solution by numerical pro-
cedures of equations based upon the conservation of
mass (K-theory), or
Semiempirical, involving the assumption of a particular
functional form for the pollutant distribution; and
2. Treatment of the time dependence of pollutant concentrations
Steady-state, involving no time dependence; only a
single constant set of conditions is used,
Dynamic, involving the estimation of pollutant con-
centrations as functions of time or as functions of
position along a dynamic trajectory; evolution of the
system in time is described in a causal manner,
Sequential, in which a sequence of conditions is con-
sidered; a separate independent calculation is done for
each, or
Climatological, in which a number of different conditions
are considered, each weighted by its frequency of
occurrence; a separate calculation is done for each.
The user should be able to categorize the study model according to the general
modeling approach from the definitions given and the study model documentation.
If further discussion is needed, Appendix A.4.2 may be consulted. It should
be pointed out that the first categorization relates to the treatment of
dispersion by the study model and that different classifications may be needed
for the treatments of horizontal and vertical dispersion.
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32
The treatment of the time dependence of pollutant concentrations must
be determined in order to carry out the second classification, and the user
should be able to make this determination from the definitions provided
together with the study model documentation. Again, further discussion is
given in Appendix A.4.2.
Two points need to be made here regarding the classification of time
dependence. The first relates to the difference between a dynamic model and
a sequential model. Dynamic models often divide the total simulated time
interval into a series of time steps and treat the pollutant distribution at
the end of one step as the initial distribution for the next, thereby handling
the time dependence in a causal manner. Sequential models also consider a
series of time periods, but ignore the causal relation between pollutant dis-
tributions at each time step and do independent calculations for each.
The second point is that for sequential and climatological models,
the individual calculations made for each of the conditions considered may
be carried out using either dynamic or steady-state methods; a steady-state
model is almost always used. This classification should also be indicated.
Thus combinations like "climatological (steady-state)" or "sequential
(steady-state)" arise.
Table B.I in Appendix B gives the classification for selected reference
models suggested for use in this workbook.
4.4 IDENTIFICATION OF REFERENCE MODEL
Table 4.1 suggests reference models that may be associated with some of
the indexed applications. Each suggested reference model is briefly described
in Appendix B. In the table, many applications do not have an associated
reference model. In these cases, the user is encouraged to compare his model
with some other applicable simulation model. If no such model is available,
there is no reference model and no comparison can be made. Since not all
aspects of an application have been classified by the foregoing procedure,
footnotes have been provided where additional information is required in deter-
mining the appropriate reference model.
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Table 4.1. (Contd.)
Index Reference
Number Model
5211 SAI, DIFKIN (f)
5212
5213 SAI, DIFKIN (f)
5214
5221 SAI, DIFKIN (f)
5222
5223 SAI, DIFKIN (f)
5224
5231
5232
5233
5234
5241 SAI, DIFKIN (f)
5242
5243 SAI, DIFKIN (f)
5244
6111
6112
6113
6114
6121
6122
6123
6124
6131
6132
6133
6134
6141
6142
6143
6144
6211 SAI, DIFKIN (f)
6212
6213 STRAM, SAI, DIFKIN (f,g)
6214 STRAM
6221 SAI, DIFKIN (f)
6222
Index Reference
Number Model
6223 SAI, DIFKIN (f)
6224
6231
6232
6233
6234
6241 SAI, DIFKIN (f)
6242
6243 SAI, DIFKIN (f)
6244
7111
7112
7113
7114
7121
7122
7123
7124
7131
7132
7133
7134
7141
7142
7143
7144
7211
7212
7213 STRAM
7214 STRAM
7221
7222
7223
7224
7231
7232
7233
Index
Number
7234
7241
7242
7243
7244
8111
8112
8113
8114
8121
8122
8123
8124
8131
8132
8133
8134
8141
8142
8143
8144
8211
8212
8213
8214
8221
8222
8223
8224
8231
8232
8233
8234
8241
8242
8243
8244
Reference
Model
STRAM
STRAM
Note: References to users' guides for each suggested reference model can be
found in Appendix B.
«a
For applications for which no reference is listed, the user should compare
his model with another applicable simulation model.
Valley should be used when the receptor height exceeds the stack height
(plume impaction case) .
Q
CRSTER should be used only when receptor is below stack height.
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35
Table 4.1 (Contd.)
HIWAY is used for analysis of single highway link, APRAC for urban highway
systems.
g
Choose RAM for a combination of source types, APRAC for multiple line sources
(highway systems).
SAI is a regional grid model; DIFKIN is a trajectory model. Which to choose
as a reference model depends upon aspects of the user's application not
classified in the tree. SAI treats only photochemical smog. DIFKIN is also
designed to treat photochemical smog, but provision is made for user-speci-
fication of an arbitrary chemical mechanism involving arbitrary, user-defined
chemical species. Area sources may require other than emission data for pre-
processor or preprocessing by user in both models.
gSTRAM allows treatments of other than photochemical reactions. If the interest
is in photochemistry choose SAI or DIFKIN.
CRSTER assumes all sources are located at the same point. For a single source
with multiple stacks, where this is a reasonable approximation, choose CRSTER
rather than COM as the reference model.
CRSTER assumes all sources are located at the same point. For a single source
with multiple stacks, where this is a reasonable approximation, choose CRSTER
rather than RAM as the reference model.
4.5 REVIEW AND MODIFICATION OF IMPORTANCE RATINGS
As indicated in Section 2.1, the importance rating of an element is a
measure of the importance of that element as a factor in determining atmos-
pheric pollutant concentrations in the application of interest. The importance
ratings are used as weighting factors in combining the individual element-by-
element comparisons of the study and reference models into a final comparative
evaluation.
Tables 4.2-4.13 at the end of this section give the importance rating
of each element in each of the indexed applications. Brief discussions of
these ratings may be found in Appendix A.9. At this point in the methodology,
the user should review the importance ratings corresponding to the application
index previously constructed and determine the need for modification of these
ratings in the specific situation of interest.
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36
Three types of situations arise that may justify modifying the impor-
tance ratings given in the tables at the end of this section:
When the particular circumstances being modeled, or the
particular interests of the user indicate that an element
is either more or less important than the tabulated entry,
When a particular element is of such overwhelming interest
or importance that its treatment is critical to the appli-
cation, and
When a particular element has no bearing on the application
and hence is irrelevant.
In the first situation, the decision to change a rating depends very
much on the particular situation involved and the particular interests of the
user. The user should review these ratings considering those aspects of the
specific application not considered in the Application Tree. If necessary,
the user should modify these ratings. Such changes should be made only after
thoughtful reflection and consultation with an expert. For example, the user
may be interested in estimating the amount of S02 removed by deposition in a
region where deposition would usually be small and hence rated as of LOW
importance. Given this particular interest, the importance rating for
physical removal might be changed from LOW to MEDIUM or HIGH with the con-
currence of an expert. The choice between MEDIUM and HIGH must be left to the
user's discretion and depends upon how much weight it is felt that deposition
deserves relative to the other application elements.
It may also be desirable to give one element exceptional weight in the
technical evaluation. In this case, the element is designated CRITICAL to the
overall technical evaluation. The comparison of the way that element is
treated is weighted even more heavily than that of an element of HIGH impor-
tance. The CRITICAL designation should be used sparingly and then only when
the user has a very strong interest in an effect associated specifically with
that element. As an example, if it is desired to pick one of several alter-
native sites for a new source so as to give the "best" resulting air pollution
estimates, source-receptor relationship might be treated as a CRITICAL element.
In this example, the user needs to determine the differences in pollutant
concentrations as the horizontal location of the source changes, perhaps by
only relatively small amounts. Only models that handle horizontal location in
a detailed manner would be acceptable. However, horizontal location is only
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37
one aspect of the application element "source-receptor relationship." In
such situations, the user must identify clearly which aspect is critical in
making the comparison between two models.
Lastly, some elements may be IRRELEVANT in the application of interest
and should be so designated. These elements are not considered at all in the
technical comparison. Examples of irrelevant elements include chemistry and
reaction mechanism for primary conservative pollutants and physical removal
in situations for which dry deposition and precipitation scavenging are unim-
portant. Although it may appear a rather simple matter to decide whether a
given element is irrelevant, the user must be cautioned against the indis-
criminate designation of irrelevant elements. Except in clear-cut instances
such as the examples given above, most elements will have at least some LOW
importance to the application and may need to be considered in cases where
ambiguity exists. Irrelevant elements, however, are never considered in the
comparison under any circumstances.
It bears repeating that changes in the importance ratings and especially
the designation of an application element as CRITICAL should be undertaken only
with expert advice and a firm conviction that the specific situation to be
simulated clearly dictates such changes. Otherwise, the uniformity of evalua-
tion that this workbook can provide is nullified. At most, no more than one
or two changes in the tabulated importance ratings or a single critical desig-
nation, if any, should be made.
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TABLES 4.2-4.13 - IMPORTANCE RATINGS
These ratings are based on the relative importance of
each element to each class of applications as defined
by the branches of the Application Tree.
For an interpretation of the Application Index as it
applies to each table, see Fig. 3.1.
Brief discussions of these ratings are contained in
Append ix A.9.
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5 TREATMENT OF APPLICATION ELEMENTS
5.1 INTRODUCTION
This section gives specific guidelines for determining, for each
application element, the treatment used by a given model. In making these
determinations, reference to the dispersion equation and the other working
equations documented on Evaluation Form-Part A is useful. The user must be
careful in determining the treatments used by the study model. Model docu-
mentation is often inadequate and occasionally inconsistent, and in some
cases it may be necessary to examine the computer code itself to determine
what the real treatment of some element is. The list of input variables
should be examined and checked for consistency with the working equations
and general formulation to insure that sufficient information is input and
that no seemingly irrelevant data are required. If these general guidelines
are followed, the effort involved in determining the treatments of the appli-
cation elements will be minimized.
5.2 TREATMENT OF SOURCE-RECEPTOR RELATIONSHIP
There are six factors to be considered:
Horizontal location of sources,
Release heights,
Downwind and crosswind distances,
Orientation of area and line sources,
Horizontal location of receptors, and
Height of receptors.
Guidance to aid the user in determining the treatment of these factors is given
below.* This guidance and Table 5.1 listing the various treatments assume a
multiple source application. In the context of source location, receptor loca-
tion, release height, and receptor height, the user should not compare treat-
ments solely on their respective levels of detail. Consideration should also
be given to whether the level of detail employed is required for the applica-
tion of interest. For example, if a single source-receptor pair is of interest,
*Refer to Appendix A.1.2 for detailed discussion of the treatment of the
source-receptor relationship.
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52
Table 5.1. Treatment of Source-Receptor Relationship'
Source Type
Point
a. Horizontal Source Location
Method of Treatment
1. Sources located at specific, arbitrary points.
2. Sources aggregated onto many subareas.
3. Sources aggregated onto only a few subareas.
4. Sources aggregated on a basis other than location.
No information on location.
5. Not treated explicitly; all sources treated alike
regardless of location.
Area
1. Sources located at arbitrary locations; not
located as blocks on a grid network.
2. Sources located as blocks on grid network. User
can change scale of grid.
3. Sources located as blocks on a grid network. User
cannot change scale of grid.
4. Sources aggregated on a basis other than location.
No information on location.
5. Not treated explicitly.
Line
3,
4,
5,
Line located at any desired position; line treated
as volume source with width and height as well as
length.
Lines treated as one-dimensional (i.e., no width
or height) with arbitrary location.
Sources aggregated onto many subareas.
Sources aggregated onto only a few subareas.
Sources aggregated on a basis other than location.
No information on location.
6. Not treated explicitly.
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53
Table 5.1. (Contd.)
b. Release Height
Source Type
Point
Area
Method of Treatment
1. Accounts for both elevation of stack base and
physical stack height.
2. Assumes flat terrain; no elevation corrections.
Release at any physical stack height.
3. Several representative release heights can be
specified for each grid cell or category when
sources have been aggregated.
4. Model assumes all releases take place at same
user-defined height.
5. Model assumes all releases take place at same
height which user cannot change.
6. Not treated explicitly.
1. Accounts for both average elevation of area and
allows several arbitrary release heights.
2. Assumes flat terrain; no elevation corrections.
Several arbitrary release heights for each area.
3. Assumes flat terrain. Only one release height
for each area.
4. Only one release height may be specified for all
areas.
5. Model assumes all releases take place at same
height which user cannot change.
6. Not treated explicitly.
Line
1. Release height and elevation may both be specified,
2. Flat terrain assumed, arbitrary release height for
each source.
3. Several representative release heights can be spec-
ified for each grid square when sources have been
aggregated.
4. Assumes all releases at same height which user can-
not change.
5. Not treated explicitly.
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Table 5.1. (Contd.)
c. Downwind/Crosswind Distances
Source Type
Point
Area
Method of Treatment
1. Precise downwind and crosswind distances calculated
for each source-receptor pair.
2. Single representative or average value used for
aggregate of several point sources.
3. Not treated explicitly.
1. Calculated for various points within each area
source.
2. Single representative or average value used for
each area source.
3. Not treated explicitly.
Line
1. Single value calculated for each segment along line.
2. Single representative or average value used for en-
tire line.
3. Single representative or average value used for
aggregate of several line sources.
4. Not treated explicitly.
d. Source Orientation
Source Type
Point
Area
Method of Treatment
1. Not applicable.
1. Areas can assume any orientation; sides not restric-
ted to lie along specific directions.
2. Sides of areas restricted to be along specific grid
directions.
3. Not treated explicitly.
Line
1. Line can assume any orientation with respect to
receptor and may be inclined.
2. Line assumed to be horizontal; orientation arbitrary,
3. Applies to only a restricted range of orientations.
4. Not treated explicitly.
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Table 5.1. (Contd.)
e. Receptor Location
Method of Treatment
1. Receptor located at specific, arbitrary location.
2. Receptor located at specific, arbitrary location within some spe-
cific area, commonly an area source emission grid.
3. Receptors located at points on a separate user-defined grid.
4. Receptors located only at points defined within the model.
5. Receptor locations defined only as being within certain boundaries
smaller than the entire region of interest, e.g., within a given
grid cell.
6. Receptor location not treated explicitly. Concentration estimate
independent of receptor location within region of interest.
f. Receptor Height
Method of Treatment
I. Receptor located at specific, arbitrary height above ground.
2. Receptor located at specific, arbitrary height above ground sub-
ject to upper limit constraint, e.g., effective stack height.
3. Receptor located at one of several discrete user-defined heights.
4. Receptor located at one of several model-defined heights.
5. Receptor heights defined only as being within certain ranges.
6. Receptors constrained to be all at the same height.
7. Receptors constrained to be all at gound level.
8. Not treated explicitly.
Within each source type, treatments are listed in order of decreasing
level of detail. Various combinations of the treatments for each as-
pect of the source-receptor may be used; the user can arrive at an
overall comparison by determining how the models compare in their
treatment of each aspect.
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a model need not be able to locate many sources and receptors as long as a
single pair can be treated in its true relationship.
Horizontal Location
The treatment of the horizontal location of point sources can be found
by determining:
Whether each source can be located arbitrarily at its
true location.
If not, the level of aggregation imposed by the model
as distinct from that imposed by the emission inventory.
The basis for this aggregation.
The key consideration is the level or degree of aggregation required. Little
or none implies a relatively detailed treatment in contrast to treatments that
require a lot. Some treatments aggregate on the basis of a parameter such as
source type and hence convey little information on source location.
For area sources, the considerations are similar:
Whether each source can be located arbritarily or must be
blocks in a fixed grid network.
Whether the user can change the scale of the grid to suit
the detail available in the inventory.
Whether the model imposes aggregation in addition to any
imposed by the inventory in developing the area sources.
The basis for the model's aggregation.
The major difference between the point and area sources comes from the two-
dimensional nature of the area sources. They must be located as blocks rather
than as points; otherwise the progression from the most to the least detailed
treatments is the same for both types.
For line sources, the situation is similar except that the line may be
treated as an elongated volume source having length, width, and height. For
the location of a line the user should determine:
Whether the line can have width and/or height or is truly
considered a one-dimensional source.
If the receptor height is arbitrary or if only one height
(usually ground level) is assumed.
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57
Whether the line can be uniquely located, usually by the
location of its endpoints.
If not, the degree of aggregation imposed by the model.
The basis for that aggregation.
Release Height
As used here, release height means the height above ground level at
which emissions are physically released into the atmosphere and does not in-
clude any considerations of plume rise or other types of plume behavior, which
are dealt with in Section 5.5. The user should be aware, however, that some
effective plume rise may frequently be included in the user-specified release
height supplied as input to models that do not treat plume rise explicitly.
This approach is discussed in Section 5.5; the comparison of treatments of
release height should proceed as if the release heights were the heights at
which emissions actually enter the atmosphere. There are three considerations
in determining the level of detail with which release height is treated for
point, area, and line sources:
Whether the model treats elevation differences due to
terrain.
Whether the model allows the physical stack height (or
height of release above ground level for area and line
sources) to vary between different sources or source
categories.
Whether release heights can be specified arbitrarily by
the user or whether specific values or sets of values are
imposed by the model.
Receptor Location and Receptor Height
Since receptors are generally taken to be points, the user should be
able to describe the treatment of receptor location and height by making the
same considerations as outlined above. Specifically, the user should deter-
mine:
Whether the receptors can be located arbitrarily or are
limited to specific points within the given area.
If the receptor height is arbitrary or if only one height
(usually ground level) is assumed.
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With these considerations and the entries in Table 5.1, the user should be
able to describe and compare treatments of receptor location and receptor
height.
Downwind/Crosswind Distances
Some models contain parameters whose values depend explicitly on down-
wind or crosswind distances between source-receptor pairs. In such cases,
these treatments must be described and compared. In other cases, it should
simply be noted on the technical evaluation form that this aspect of the
source-receptor relationship is "not applicable." The key consideration for
all source types is whether the treatment causes a loss in the precision with
which the downwind and crosswind distances can be specified. Aspects for the
user to consider are:
Whether precise downwind/crosswind distances are calcu-
lated for each point source-receptor pair or for various
points within area sources or along line sources.
Whether, for area and line sources, single representative
or average distances are used.
It should be noted that when the model aggregates sources, the values of
downwind/crosswind distance are representative of the grid blocks used in
the aggregation and not of the sources themselves.
Orientation
Orientation does not apply to point sources. For area sources, the
user needs to consider:
Whether the sides of the area sources can be arbitrarily
oriented, or
Whether they are restricted to lie along specific directions
specified by a grid.
For line sources, the situation is slightly more complex, because a line
presents a significantly different appearance depending upon the angle from
which it is viewed. The considerations are:
Whether the line can be inclined or must be horizontal.
Whether the line can be arbitrarily oriented with respect
to the wind direction; some models can treat only a re-
stricted range of orientations.
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59
When these considerations have been made, the user should have
little trouble in locating the study model's treatment of each aspect of
the source-receptor relationship in Table 5.1 and in briefly describing that
treatment on the Evaluation Form-Part C. In applications involving several
source types, an overall evaluation must be reached based upon the comparative
treatment of each source type individually. Each treatment must be weighted
by the expected importance of that source type in the application of interest.
Table 5.1 gives the treatment of the source-receptor relationship by
models in general. Table B.2 gives the treatment of the source-receptor
relationship by selected reference models.
5.3 TREATMENT OF EMISSION RATE
The degree of spatial and temporal resolution must both be assessed
in determining the treatment of emission rate.* Regardless of the aspect
or type of source, the user is basically interested in determining:
Whether an emission rate and emission pattern unique to
each source can be specified, or
Whether average emission rates and general patterns must
be used.
For the spatial aspect of point sources, the user need only determine
whether each source can have an arbitrary emission rate or whether all sources
must have identical rates.
For area sources, there are several methods for treating the emission
rate, depending on how the concentration estimates are made. The user must
determine:
Whether variation in the emission rate is allowed within
a single source or whether each area is assumed to emit
uniformly.
If the areas must be uniform, whether the emission rates
are arbitrary or whether they must be the same or selected
from a specific set of values.
Whether concentration estimates are obtained by numerical
integration over the area or by replacing the area by a
small number of effective point sources.
*Refer to Appendix A.1.3 for detailed discussion of the treatment of emission
rate.
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60
Whether contributions from all individual area sources are estimated,
Whether a single estimate of the total area source contribution is
made.
Similarly, for line sources the considerations are:
Whether the emission rate can vary along the line or
whether the line is assumed to be a uniform source.
If the line must be uniform, whether the emission rate
is arbitrary.
Whether concentration estimates are obtained by inte-
gration or by replacing the line by a small number of
effective point sources.
For the temporal aspect, the considerations are the same for all types
of sources:
Whether the emissions can vary with time, or
Whether constant emission rates are assumed.
If the emissions can vary with time, whether the model
uses
- An actual time sequence of emission rates,
- A sampled set of emission rates, or
- A set of rates partially arranged in
sequence or correlated with other variables.
With these considerations, the user should be able to determine a
model's treatment of emission rate and to describe it on the evaluation Form-
Part C.
Table 5.2 gives the general treatment of emission rate. Table B.3
gives the treatment of emission rate by the reference models.
5.4 TREATMENT OF COMPOSITION OF EMISSIONS
The user must deal with two aspects of the composition of emissions.
For all types of emissions, the chemical composition must be treated except
when dealing with primary, stable pollutants. In addition, for particulate
matter, the size distribution may need to be considered.*
*Refer to Appendix A.1.4 for detailed discussion of the treatment of compo-
sition of emissions.
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Table 5.2. Treatment of Emission Rate
Variation
Source Type
Method of Treatment
Spatial
Temporal
Point 1. Allows arbitrary emission rate for each source.
2, All sources assumed to have identical emission rates.
Area 1. Allows variation over each area source.
Total contribution estimated by summing all individual contributions.
Individual contributions estimated by integration.
2. Assumes uniform area sources with arbitrary emission rates.
Total contribution estimated by summing all individual contributions.
Individual contributions estimated by integration.
3. Assumes uniform area sources with arbitrary emission rates.
Total contribution estimated by integration without estimating indi-
vidual source contributions.
4. Assumes uniform area sources with arbitrary emission rates.
Total contribution estimated by summing all individual contributions.
Individual contributions estimated by replacing each area source by a
small number of effective point sources.
5. Assumes uniform area sources, all with the same emission rate.
Total contribution estimated by replacing entire area source distri-
bution by a small number of effective point sources.
Line 1. Allows variation along the line.
Integrates to obtain concentration.
2. Assumes arbitrary emission rate is uniform along the line.
Integrates to obtain concentration.
3. Allows variation along the line.
Replaces line by a small number of effective point sources with
emission rates dependent upon position along line.
4. Assumes uniform lines with arbitrary emission rates.
Replaces line by small number of effective point sources.
5. Assumes all lines have the same uniform emission rate.
Replaces line by small number of effective point sources.
All 1. Treats an actual time sequence of emission rates averaged over a
short interval (typically one hour).
2.a. Treats a sampled set of the possible emission rates appropriate
to a short interval.
b. Treats time sequence of short-term emission rates derived by model
from input emission rates appropriate to longer term.
3. Treats a time sequence of emission rates averaged over a long
interval (e.g., one day).
4. Uses a set of emission rates which are at most partially arranged
in sequence.
5. Treats only constant emission rates.
Within each source type, the treatments are listed in order of decreasing level of detail.
In addition to the level of detail, the suitability of the technique of treating the variations
must be assessed as discussed in Appendix A.1.3 whenever the treatment allows temporal variations
to be specified.
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62
If treatment of chemical composition of emissions is required by the
application, the user should consider:
Whether all relevant compounds are treated individually
or whether certain compounds are lumped into classes with
each class treated by a representative or hypothetical
compound. The specific compounds or classes treated
should be listed or described on the Evaluation Form-Part C.
If lumping is used, the number of classes considered and
whether these classes are appropriate to the application
of interest.
Whether the model determines emissions of certain compounds
as fixed fractions of input emissions regardless of source
type.
Whether further assumptions are made regarding the compo-
sition of user-input emissions.
Whether the model treats only one of many compounds known to
interact.
In making these determinations, expert advice may be required.
When fallout, deposition, or precipitation scavenging (rainout or wash-
out) are involved, the size distribution of particulate matter is important.
The treatment used may be found by determining:
Whether a size distribution is used and if so, whether it
is continuous or discrete.
- If continuous, whether the functional form can
be specified or whether parameters are input
for a fixed distribution.
- If discrete, whether there are many narrow size
ranges or a few broad ranges.
If a size distribution is not used, whether some given
fraction of the emissions is affected by the size-dependent
mechanism.
If so, whether the fraction is arbitrary.
These considerations should enable the user to determine the treatment of com-
position of emissions.
Table 5.3 gives the general treatments of the composition of emissions.
Table B.4 gives the treatments used by the selected reference models.
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5.5 TREATMENT OF PLUME BEHAVIOR
By considering the following, the user should be able to determine the
study model's treatment of plume behavior:*
Whether a plume rise formula is used by the model.
If so, whether the formula has been extensively vali-
dated for the specific application of interest or for
similar applications.
Whether the formula is one of the common ones: Briggs'
2/3, Holland, CONCAWE, CONCAWE simplified, or the ASME
formula.
If the formula has not been validated and is not one of
the four common formulae:
- To what power of the inverse wind speed
the plume rise is proportional.
- Whether there is a buoyancy term and the
power to which it is raised.
- Whether there is a momentum term.
- Whether the formula accounts for differences
in atmospheric stability.
- Whether plume rise is a function of downwind
distance.
If no plume rise formula used, whether the product of wind
speed and plume rise is assumed constant.
If so, whether the constant can be changed from source to
source.
Upon what other parameters, like stability, the constant can
depend.
Whether downwash and/or fumigation are treated.
In comparing treatments of plume rise, the main consideration should be vali-
dation in either the application of interest or similar applications. A
properly validated formula should always be considered better than an unvali-
dated formula.
*Refer to Appendix A.2.2 for detailed discussion of the treatment of plume
behavior.
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As pointed out in Section 5.2, some effective plume rise may be included
in the values of the stack or release height specified by the user as input to
a model. If this approach is adopted, the treatment of plume rise must be
determined from the algorithm or formulae by which the effective plume rise is
estimated prior to its inclusion as part of the release height. Otherwise,
the treatment implemented in the computer program should be determined.
When the "tilted plume" approximation has been used to treat deposi-
tion from particulate plumes, this treatment should be included under dry
deposition (Table 5.13).
Table 5.4 gives the general treatments of plume behavior, and Table B.5
gives the treatments used by the selected reference models.
5.6 TREATMENT OF HORIZONTAL AND VERTICAL WIND FIELDS
The treatment of the horizontal wind field by the study model may be
determined from the following considerations:*
Whether the horizontal components of the wind velocity
may depend on horizontal location.
If not, whether both wind speed and direction are treated
explicitly or whether one or both are not treated explicitly.
If the horizontal components depend on position, whether
the dependence is arbitrary or assumed a priori.
If arbitrary, whether the components are specified at
discrete points or as continuous functions of position.
Whether both the horizontal components may depend on
height above ground.
If so, whether they are specified at discrete heights or
as continuous functions of height.
If the wind direction is constant with height, whether
the wind speed can depend upon height.
If so, whether the dependence is arbitrary.
If arbitrary, whether the wind speed is specified at dis-
crete intervals or given as a continuous function of height.
*Refer to Appendix A.3.2 for a discussion of the possible treatments of the
horizontal and vertical wind fields.
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Table 5.4. Treatment of Plume Behavior3
Method of Treatment
1. Plume rise formulation validated for the specific application of interest.
2. Plume rise formulation validated for applications similar to the one of
interest.
3. Fully detailed treatment with plume rise and dispersion treated simultan-
eously. Limited validation.13
4. Two-step treatments. Plume rise is calculated and then dispersion is cal-
culated from a virtual source at an effective stack height.
a. Analytical formulas, depending upon meteorology and stack parameters,
used to estimate plume rise:
Plume rise treated by one of the common formulas: Brigg's 2/3,
Holland, CONCAWE, CONCAWE simplified, or ASME.
Plume rise treated by unvalidated formula satisfying the general
guidelines and comparing favorably with common formulas.0 (See
Appendix A.2 and Table A.I for these guidelines.)
Plume rise treated by unvalidated formula satisfying some of the
general guidelines or comparing unfavorably with common formulas.0
(See Appendix A.2 and Table A.I for these guidelines.)
b. Product of plume rise and wind speed assumed constant. User can choose
value of constant for each source and use different constants for a
small number of meteorological or source parameters, e.g., stability.
c. Product of plume rise and wind speed assumed constant. User can choose
value of constant for each source. Constant is independent of other
source and meteorological parameters.
d. As in 4 (c), but one value of the constant used for all sources.
e. Single value of plume rise used for all sources. (Could be included
in release height.)
5. Not treated explicitly.
Treatments are listed in order of decreasing level of detail.
Not used in most models at this time; used only in special applications.
Special weight should be given to formulas treating plume rise as a function
of downwind distance. This consideration is more important for low-level
than for elevated releases.
b
c
Notes: 1. In addition to comparing the treatments of plume rise, the user
should consider whether the models treat downwash or fumigation.
Treatment of either or both by a model tends to make that model's
treatment of plume behavior better than the treatment by a model
that ignores these effects.
2. Where the "tilted plume" approximation has been used for particulate
plumes, the user should include this under the treatment of dry
deposition. (See Table 5.12.)
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67
Whether a specified dependence with height of either or
both wind speed and direction is assumed a priori.
If either or both wind speed and direction are constant
with height, whether different values are used for
different source heights.
Whether the horizontal components depend on time.
If so, whether they are specified continuously or at a
sequence of elapsed times.
If specified at a sequence of times, whether they are
assumed constant within each interval or interpolated
between times.
Whether the treatment is climatological.
These considerations should guide the user to an identification of the
treatment of the horizontal wind field. In addition, the following specific
information should be provided on the Evaluation Form-Part C:
The model classification as determined in Section 4.3.
A description of the nature of any constraints on the
allowable values of the wind speed and direction, e.g.,
the number of sectors and wind speed classes used in a
climatological model.
A description of the nature of any parameters, either
user-specified or built into the model, that govern the
dependence of wind speed and direction on position, height
above ground, or time, e.g., power law dependence of wind
speed on height with exponents dependent on atmospheric
stability.
A description of any dependence of the horizontal wind
components on position, height, or time that explicitly
or implicitly is assumed a priori by the study model.
The source of nature of any non-standard meteorological
data required in the model determination of the wind
field.
Any additional information relating to the treatment of
the horizontal wind field not covered in this discussion.
The treatment of the vertical component of the wind field may be deter-
mined in a similar manner from the following considerations:
Whether the vertical wind field is treated explicitly;
whether an implicit treatment is used; or whether the
vertical wind field is not considered in the study model
formulation.
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68
If treated explicitly, whether the vertical component
depends arbitrarily upon horizontal position and/or
height above ground.
If arbitrarily dependent on position and/or height,
whether the vertical component is a continuous function
of these variables or whether it is specified at dis-
crete points.
Whether there is any assumed a priori dependence of the
vertical component on position or height above ground.
Whether the vertical component depends on time.
If so, whether it is specified continuously or at a
sequence of elapsed times.
If specified at a sequence of times, whether it is assumed
constant within each interval or whether its value is
interpolated.
Although these questions will enable the user to identify the study
model's treatment of vertical wind field, additional information should be
provided. This additional information is the same as required above for the
horizontal wind field. If the study model uses an implicit treatment of the
vertical wind field, the treatment should be described in sufficient detail
to make clear the assumptions involved.
Tables 5.5 and 5.6, respectively, give the treatments of the horizontal
wind field and the vertical wind field by models in general. Tables B.6 and
B.7 give the treatments used by selected reference models.
5.7 TREATMENT OF HORIZONTAL AND VERTICAL DISPERSION
The treatment of both horizontal and vertical dispersion by the study
model may represent different modeling approaches.* For example, horizontal
dispersion may be described with a semiempirical method and vertical dispersion
may be described with a numerical method. On the other hand, the two treat-
ments may be closely related. In either case, separate descriptions of the
treatments of these two elements are required on the Evaluation Form-Part C.
General treatments of dispersion corresponding to the different types of models
identified in the classification procedure outlined in Section 4.3 are given
in Table 5.7. Certain information is required to adequately specify the par-
ticular treatment used by the study model. Regardless of the model type, the
*Refer to Appendix A.4.2 for a detailed discussion of the treatment of hori-
zontal and vertical dispersion.
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72
following information should be provided:
The model classification as determined in Section 4.3.
The treatment or parameterization of atmospheric
stability used in estimating the values of eddy
diffusivities or standard deviations (see Table 5.8).
The name (or names) of any parameter or turbulence
classification scheme used to specify the stability
of the atmosphere or the level of turbulence should be
noted. If a classification scheme is used, the number
of classes used should be noted. Limits or other
constraints to allowable parameter values should be
indicated.
The treatment or parameterization of surface roughness
effects used in estimating the values of eddy diffusi-
vities or standard deviations (see Table 5.9). Infor-
mation similar to that required for the treatment of
atmospheric stability should be provided.
The origin or basis for choosing the specific model
parameter values (see Table 5.10). If the specific
parameters are widely used or have been published in
the scientific literature, it is sufficient to identify
them (for example, the Pasquill-Gifford dispersion
coefficients for the Gaussian plume model) and provide
an appropriate reference; if they are not widely used
and not publicly available, the basis for using them
should be noted.
The averaging time for meteorological variables.
This information may be omitted in certain cases in which dispersion is des-
cribed implicitly, rather than explicitly. This is the case in the narrow
plume or sector averaging approximations for horizontal dispersion or in the
uniform mixing approximation for vertical dispersion, for example.
Additional information is also required, depending on the treatment
classification.
SemiempiricaiL. The functional form assumed for the pollutant distri-
bution should be identified if commonly used (e.g., Gaussian plume, narrow
plume approximation, sector averaging, uniform mixing), or described briefly
if not widely used, including some indication of its origin. Dependences of
model parameters on position, height, time, meteorological, or other variables
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73
Table 5.8. Treatment of Atmospheric Stability3
1. Atmospheric stability characterized by the numerical value of a
stability parameter (see for example Table A. 3) that may take
on any value within the range for which the model is designed.
2. Atmospheric stability divided into discrete classes within which
no variation is recognized.
a. Many classes, including time of day or other para-
meters.
b. Many classes, not including other factors, or
Few classes, but including additional factors.
c. Few classes, no additional factors included.
3. Atmospheric stability not explicitly treated.
Treatments given in order of decreasing level of detail.
Table 5.9. Treatment of Surface Roughness
a
1. Surface roughness characterized by the numerical value of a
roughness parameter (such as the roughness length) which can
take on any value within some appropriate range.
2. Surface roughness characterized in terms of discrete classes
or types of surface.
a. Many classes.
b. Few classes.
3. Surface roughness not treated explicitly.
Q
Treatments given in order of decreasing level of detail.
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75
should be indicated if not adequately described under the general information
above.
Numerical. The dependence of the eddy diffusivity on position, height,
time, meteorological, or other variables should be indicated, in addition to
the basis for the values or for the specific parameterization that is used by
the study model (see Table 5.11) . The general name or type of numerical
method used to solve the diffusion equation should be mentioned, although
comparison based on the details of the numerical techniques is beyond the
scope of this methodology.
Steady-State. The averaging time, or the period of time over which
a steady-state condition is assumed to hold, should be indicated.
Sequential or Climatological. No specific additional information is
required if the study model has been classified as sequential or climatologi-
cal.
Dynamic. The time dependence should be described to a sufficient ex-
tent to indicate its general nature. For example, a model that has been
classified dynamic because it involves the determination of a trajectory, but
in which the time dependence of the pollutant concentration is not explicit,
should be distinguished from a model in which it is. In cases involving
explicit time dependence, the method of describing the temporal variation,
either continuously or in a sequence of time steps, should be indicated
along with the size of the time step used.
Finally, any additional information relevant to the treatment of dis-
persion that may affect the evaluation or clarify the operation of the study
model should be given. This information may include:
Different modes of operation under different meteorolo-
gical circumstances,
Different treatments for different source geometries, and
Any additional or different assumptions made in the for-
mulation of the study model not covered in the discussion
in this workbook.
Table 5.7 gives the general treatments of dispersion. Tables 5.8 and
5.9, respectively, give the treatments of atmospheric stability and surface
roughness used in estimating the values of the dispersion parameters (the
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77
eddy diffusivities or standard deviations). Table 5.10 gives possible bases
for comparing different choices of dispersion parameter values. Table 5.11
gives possible treatments of the spatial and temporal dependence of eddy
diffusivities. Treatments of horizontal and vertical dispersion by selected
reference models are given in Tables B.8 and B.9.
5.8 TREATMENT OF CHEMISTRY AND REACTION MECHANISM
The treatment of chemistry and reaction mechanism used by the study
model may be determined from the following considerations (expert advice may
be required in some cases):
Whether all relevant reactions and chemical species
are handled.
Whether similar compounds are treated together in one
or more classes (lumping approximation) or whether only
some of the relevant compounds are treated.
Whether the equilibrium approximation is applied to the
system of reactions.
Whether all reactions are truly first-order (linear).
Whether the appearance and disappearance of pollutants
of interest are approximated by one or more first-order
processes.
In addition to these considerations, the user must also determine:
Whether any adjustment is made for the effects of in-
complete turbulent mixing.
Finally, the following additional information should also be provided;
A two-or three-word description of the general chemical
system being treated (e.g., photochemical smog system).
The number of distinct chemical reactions considered.
The number and an explicit list of the chemical species,
real or "lumped," treated in the mechanism.
If the lumping approximation is used, a list of those
species treated in the mechanism that are representative
compounds for the classes being used.
*Refer to Appendix A.5.2 for a discussion of the possible treatments of
chemistry and reaction mechanism.
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78
If the steady-state approximation is used, a list of those
species to which it is applied.
A description, including the extent of any user input,
of any spatial or temporal variation attributed to any
chemical reaction rate constant.
A description of any optional modes of operation, such
as user-specification of an arbitrary reaction mechanism.
Table 5.12 gives the general treatments of chemistry and reaction mech-
anism. The treatments used by selected reference models are given in Table B..10.
5.9 TREATMENT OF PHYSICAL REMOVAL PROCESSES
Two physical removal processes are considered in this workbook: dry
deposition and precipitation scavenging. The guidelines in this section
enable the user to identify the treatment of each used by the study model.*
Dry Deposition
The treatment of dry deposition may be determined from the following
considerations:
Whether both the effect on the vertical concentration
profile and the effect of pollutant removal are treated.
If so, whether the deposition velocity is assumed constant
and/or independent of position.
Whether only the effect of pollutant removal is treated.
(Effective source-strength treatment.)
If so, how the effective source strength is determined.
- Integration of mass removal rate proportional
to ground level concentration, or
- Assumed exponential decay.
Whether the deposition velocity is a function of meteorolo-
gical variables.
Whether the tilted plume approximation is used to treat
gravitational settling.
Additional information relating to assumed deposition velocity values
or assumed dependences on meteorological or other parameters should be
*Refer to Appendix A.6.2 and A.6.3 for discussions of possible treatments of
dry deposition and precipitation scavenging.
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79
a
Table 5.12. Treatment of Chemistry and Reaction Mechanism
1. Complete mechanism used:
a. System of truly first-order reactions - exact treatment
possible independent of dispersion.
b. More general system of reactions -
Includes all known relevant reactions except those
definitely known to be insignificant and
Treats all chemical species explicitly.
2. Simplified mechanism used, incorporating the steady-state
approximation for highly reactive intermediates but not the
lumping approximation for similar species.
3. Simplified mechanism used, involving the lumping of similar
chemical species into classes and/or treatment of only some
of the relevant compounds but not the steady-state approxi-
mation.
4. Simplified mechanism used, involving both steady-state and
either the lumping approximation and/or the treatment of only
some of the relevant compounds.
5. Equilibrium approximation used, with or without the lumping
approximation.
6. Approximates the disappearance and/or appearance of a pollu-
tant of interest and/or the appearance of its reaction pro-
ducts as first-order reactions and uses exact treatment for
the first-order (exponential) processes.
7. Not treated explicitly.
o
Treatments given in order of decreasing level of detail.
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80
included in the description on the Evaluation Form-Part C.
Precipitation Scavenging
The treatment of precipitation scavenging may be determined from the
following considerations:
Whether the study model allows the washout coefficient
to be an arbitrary function of time.
Whether the washout coefficient is obtained from a
user-supplied time-dependent rainfall rate.
Whether the washout coefficient is assumed to be con-
stant over the period during which precipitation occurs.
Whether each occurrence of rainfall is assumed to remove
the same fraction of pollutant.
Whether the user may specify the frequency of rainfall.
As before, additional information relating to any model assumptions
such as washout coefficient values, rainfall frequencies, etc. should be
provided. Precipitation scavenging should be assumed to occur only during
precipitation. If a study model always applies an exponential decay factor,
that treatment should not^ be considered as a treatment of precipitation
scavenging.
Table 5.13 gives the general treatments of these two removal processes
and Table B.ll gives the treatments of physical removal processes by selected
reference models.
5.10 TREATMENT OF BACKGROUND, BOUNDARY AND INITIAL CONDITIONS
There are five aspects of the element to be considered:
Background,
Upper boundary condition at the mixing height,
Lower boundary condition at the earth's surface,
Boundary condition at the vertical sides of the region
of interest, and
Initial conditions in the region of interest.
The treatments of each of these aspects depends upon the classification of the
------- An error occurred while trying to OCR this image.
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82
study model as numerical/dynamic, numerical/steady-state, semiempirical/dyna-
mic, or semiempirical/steady-state.* The treatment used by a climatological
model depends upon the treatment employed by the model used to do the basic
dispersion calculations. Sequential steady-state treatments may account for
variations by using different values for each time interval involved and
hence provide more detail than treatments that treat only a single steady-
state.
Background
Numerical models treat upwind pollutant levels in terms of the
boundary condition at the upwind vertical side; hence background does not
need to be considered for them.
For semiempirical/dynamic models the user must determine whether
spatial and temporal variations in background are treated:
Whether the background is time-dependent or constant.
Whether the background can change arbitrarily from re-
ceptor to receptor, or whether it must be uniform across
the region of interest.
For semiempirical/steady-state models, only the second consideration
need be made, because there can be no time dependence.
Upper Boundary Condition
The upper boundary condition refers to the way in which dispersion
is treated at the mixing height. The user should focus on the variations
in mixing height which can be accommodated by the model and whether the
top of the mixing layer is treated as an absolute or partial barrier to
pollutants.
For numerical/dynamic models, the user should determine:
Whether pollutants dispersing upward are allowed to
be only partially reflected at the mixing height, or
whether perfect reflection is specified.
Whether pollutants can be entrained into the region of
interest from above as the mixing height increases.
Whether the mixing height can vary with location.
*Refer to Appendix A.7.2 for a detailed discussion of treatments of background,
boundary and initial conditions.
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83
For a numerical/steady-state model only the first three considerations
apply.
For semiempirical/dynamic models, the user must determine:
Whether the mixing height can be a function of time.
Which method of treatment is used:
- Perfect reflection simulated by multiple image
sources and evaluation of the resulting infinite sum, or
- Perfect reflection with interpolation used between the region
where the mixing height has no effect and the region of uni-
form mixing.
Whether a functional form has been chosen that implicity assumes
the mixing height is large enough so as not to affect pollutant
concentrations.
Whether an implicit treatment has been used.
Implicit treatments simulate the effect of the mixing height by limiting the
appropriate parameters of the semiempirical dispersion function. For example,
the vertical dispersion coefficient in a Gaussian plume formulation may be lim-
ited to simulate the limited upward spread of a plume.
Only the last three considerations apply to a semiempirical/steady-state
model.
Lower Boundary Condition
The lower boundary condition refers to the way in which dispersion is
treated at the earth's surface.
For a numerical/dynamic model the following considerations should be
made:
Whether partial reflection treated, or whether perfect reflection
must be used.
If partial reflection is treated, a numerical model will generally
do so in terms of a dry deposition velocity. In this case the user
must determine:
- Whether the dry deposition velocity can vary with location within
the region of interest.
- Whether the dry deposition velocity can vary with time.
For numerical/steady-state models, the consideration of time dependence
is irrelevant.
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84
The considerations (and treatments) are the same for both semiempirical/
dynamic and semiempirical/steady-state models. The user should consider:
Whether partial reflection is treated, or whether only perfect
reflection is treated.
If only perfect reflection is treated:
- Whether multiple image sources or a single image source is used.
- Whether the infinite sum giving the concentration estimate is
evaluated or whether interpolation is used between the region
where the mixing height has no effect and the region of uni-
form mixing.
Note also that some semiempirical models use only a single image source to
treat perfect reflection at the earth's surface. In this case, no multiple
reflections can occur and the upper boundary is implicitly assumed to have
no effect on pollutant concentrations. If partial reflection is treated by
a semiempirical model, the functional form used is normally a solution to
the diffusion equation appropriate to the partial reflection boundary con-
dition.
Vertical Sides
For a numerical/dynamic model, the following considerations should
enable the user to determine the model's treatment of the boundary condi-
tions at the vertical sides. The considerations are almost the same for
numerical/steady-state models, except that time dependence need not be
considered. The user should determine:
Whether the flux into the region can vary from point to point.
Whether the flux can differ at different elevations.
Whether the flux can vary with time, or whether it must be con-
stant .
The user should recall that numerical models treat background pollutant con-
centrations as a boundary condition at the vertical sides.
Semiempirical models treat this boundary condition at the vertical
sides as background. Hence, this condition need not be considered for
such models.
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85
Initial Conditions
Initial conditions need only be considered for dynamic models. For both
numerical/dynamic and semiempirical/dynamic models, the user should determine:
Whether the initial concentrations can vary from point to point, or
whether they must be uniform throughout the region.
In making this determination, both the dependence on horizontal location and
elevation should be considered.
After taking these considerations into account, the user should be able
to determine the study model's treatment of each relevant aspect of background,
boundary and initial conditions.
Any additional information which would clarify the study model's treat-
ment of a particular element should also be included with the description of
the treatment on the Evaluation Form-Part C. Examples of such information
include:
How background levels are determined at different locations or times.
For example, whether they are user-specified at each time interval or
are interpolated between one initial value and one final value.
How mixing height is determined and upon what parameters it depends.
The parameters limited and the limiting values or the method used in
an implicit treatment of an upper or lower boundary condition should
be noted.
How the flux through the vertical sides of the region of interest is
determined for different locations and times.
Any additional assumptions made in the study model's treatment that
are not covered by this workbook.
General treatments of background, boundary and initial conditions are
given in Table 5.14 and the treatments used by selected reference models are
given in Table B.12.
5.11 TREATMENT OF TEMPORAL CORRELATIONS
In dealing with temporal correlations, the quantities of primary interest
are emissions, meteorological variables, removal processes, background, and the
various boundary conditions.*
*Detailed discussions of treatments of temporal correlations can be found in
Appendix A.8.2.
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86
Table 5.14. Treatment of Background, Boundary
and Initial Conditions3
a. Background
Type of
Model
Numerical/
dynamic
Numerical/
steady-state
Semiempirical/
dynamic
Semiempirical/
steady-state0
Climatological
Method of Treatment
(Treated as a boundary condition at vertical boundaries.)
(Treated as a boundary condition at vertical boundaries.)
1. Time-dependent level added to calculated concentra-
tions; value can change at each receptor.
2. As in No. 1, but value is uniform throughout region of
interest at all times.
3. Single uniform, constant level added to calculated
concentrations.
4. No treated explicitly.
1. Background level can vary with location within region.
2. Single uniform level for entire region added to calcu-
lated concentrations.
3. Not treated explicitly.
Level of detail depends upon treatment employed by model
used to do basic dispersion calculations.
b. Upper Boundary Condition (at Mixing Height)
Type of
Model
Numerical/
dynamic
Method of Treatment
Treats both partial reflection and entrainment of pol-
lutants from above mixing layer.^
Mixing height depends upon location and time.
Treats either partial reflection or entrainment, but
not both.
Treats only perfect reflection.
Mixing height depends upon location and time.
Treats only perfect reflection.
Mixing height is a constant and uniform over region of
interest.
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87
Table 5.14 (Contd.)
b. Upper Boundary Condition (at Mixing Height)
Type of
Model
Numerical/
steady-state
Semiempirical/
dynamic
Semiempirical/
s teadystatec
Climatological
Method of Treatment
1. Treats both partial reflection and entrainment of pol-
lutants from above mixing layer."
Mixing height depends upon location only.
2. Treats either partial reflection or entrainment.
3. Treats only perfect reflection.
Mixing height depends upon location only.
4. Treats only perfect reflection.
Mixing height uniform over region of interest.
1. Uses perfect reflection boundary condition.
Mixing height is a function of time.
Uses method of multiple images and evaluates infinite sum.
2. Same as No. 1, but with constant mixing height.
3. Uses perfect reflection with interpolation between
region where mixing height has no effect and region of
uniform mixing.
4. Functional form implicitly assumes mixing height large
enough to have no effect.
5. Implicit treatment limits appropriate parameters, such
as vertical dispersion coefficient.
1. Uses perfect reflection with constant mixing height.
Uses method of multiple images and evaluates infinite sum.
2. Uses perfect reflection with interpolation between
region where mixing height has no effect and region of
uniform mixing.
3. Functional form implicitly assumes mixing height large
enough to have no effect.
4. Implicit treatment limits appropriate parameters, such
as vertical dispersion coefficient.
Level of detail depends upon treatment employed by model
used to do basic dispersion calculations.
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88
Table 5.14 (Contd.)
c. Lower Boundary Condition (at Earth's Surface)
Type of
Model
Numerical/
dynamic
Method of Treatment3
1. Allows for partial reflection in terms of a dry depo-
sition velocity, which can depend on location and time
2. Treats partial reflection usine constant drv denosi-
Numerical/
steady-state
Semiempirical/
dynamic
Semiempirical/
steady-state
tion velocity.
3. Treats perfect reflection only.
1. Allows for partial reflection in terms of a dry depo-
sition velocity, which can depend on location.
2. Treats partial reflection using constant dry deposi-
tion velocity.
3. Treats perfect reflection only.
1. Assumed form of vertical concentration profile based
on solution to diffusion equation which includes
boundary condition describing partial reflection.
2. Treats only perfect reflection by method of multiple
images; evaluates infinite sum.
3. Treats only perfect reflection; uses single image
source treatment and interpolates between region where
mixing height has no effect and region of uniform mix-
ing.
4. Treats only perfect reflection; uses single image
source treatment with an implicit treatment of upper
boundary condition (hence no multiple reflections).
1. Assumed form of vertical concentration profile based
on solution to diffusion equation which includes
boundary condition describing partial reflection.
2. Treats only perfect reflection by method of multipe
images; evaluates infinite sum.
3. Treats only perfect reflection; uses single image
source treatment and interpolates between region where
mixing height has no effect and region of uniform mixing,
4. Treats only perfect reflection; uses single image
source treatment with an implicit treatment of upper
boundary condition (hence no multiple reflections).
Climatological
Level of detail depends upon treatment employed by model
used to do basic dispersion calculations.
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89
Table 5.14 (Contd.)
d. Vertical Sides
Type of
Model
Numerical/
dynamic
Numerical/
steady-state
Semiempirical/
dynamic
Semiempirical/
steady-state
Climatological
Method of Treatment
1. Treats flux into region as function of location
(including elevation) and time.
2. a. Treats flux into region as function of horizontal
location (no elevation dependence) and time, or
b. Treats flux as a function of either location
(including elevation) or time, but not both.
3. Treats flux as a function of horizontal location only
(no elevation or time dependence).
4. Treats flux as a constant.
5. Not treated explicitly; assumes horizontal uniformity.
1. Treats flux into region as function of location
(including elevation).
2. Treats flux as a function of horizontal location only.
3. Treats flux as a constant.
4. Not treated explicitly; assumes horizontal uniformity.
(Treated as background.)
(Treated as background.)
Level of detail depends upon treatment employed by model
used to do basic dispersion calculations.
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90
Table 5.14 (Contd.)
Initial Conditions
Type of
Model
Numerical/
dynamic
Numerical/
steady-state
Semiempirical/
dynamic
Semiempirical/
steady-state
Climatological
Method of Treatment
1. Treated as a function of position (including elevation),
2. Specified as uniform, independent of position.
Not applicable.
1. Treated as a function of position (including elevation),
2. Treated as uniform, independent of position.
Not applicable.
Level of detail depends upon treatment employed by model
used to do basic dispersion calculations.
Treatments are listed in order of decreasing level of detail within each
type of model.
""Fumigation may also be treated by numerical models through an appropriate
choice of the upper boundary condition during the time of the fumigation.
"Sequential steady-state treatments can account for variations in parameters
like background and mixing height by assigning a different value to each of
the time intervals involved. Models providing this capability give more
detailed treatments of this element than those which do not.
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91
If the study model is dynamic or sequential, the temporal correlations
between these various quantities are usually accounted for automatically; in
other cases, the degree or correlation between the various time-dependent
quantities must be assessed by the user. For both sequential and non-sequential
treatments the user must determine:
»
The degree of temporal resolution available to describe the temporal
variations. The degree may be different for different parameters.
Whether these quantities are correlated to a high degree. In other
words, whether a concentration estimate for a particular time is
, made on the basis of values of the varying parameters that are appro-
priate to that particular time.
These considerations should enable the user to determine the study model's
treatment of temporal correlations.
In addition, when comparing treatments by two different models, the user
should consider:
Whether the magnitude of the variations in the specific application
of interest are sufficiently large to require detailed correlation.
Whether the quantities correlated by the model are important to the
specific application.
For example, if emission rates are truly constant, it is unnecessary to cor-
relate them with changes in meteorology. Or, it may be more important to
correlate two highly critical quantities than to correlate four quantities
of lesser importance to the application of interest.
When describing the treatment on Evaluation Form-Part C, the user should
list:
The quantities correlated,
The degree of temporal resolution; for example, day-night differences
or hourly differences in emission rates,
The method used to accomplish the correlations; for example, via a
stability wind rose or by hourly values input by the user,
Any scheme used to correlate variables; for example, adjusting input
mixing height by stability class,
Any correlations particularly important in the application of inter-
est, and
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92
Any correlations that are unimportant because certain variables are
constant in the particular application of interest.
General treatments of temporal correlations are given in Table 5.15 and
treatments by selected reference models are given in Table B.13.
a
Table 5.15. Treatment of Temporal Correlations
Method of Treatment
Q
1. Sequential treatments (correlations automatic).
a. High degree of temporal resolution (usually one hour) of all quanti-
ties.
b. High degree of temporal resolution of time-dependent quantities most
important to the application.
c. Either low degree of temporal resolution or failure to correlate some
important quantities.
2. Non-sequential treatments with limited correlation.
a. High degree of temporal resolution and correlation of time-dependent
quantities important to application.
b. Either low degree of temporal resolution or failure to correlate some
important quantities.
3. Correlations not treated explicitly.
£1
The quantities of interest here are those used to determine emissions, mete-
orology, removal processes, background, and boundary conditions.
Treatments are listed in order of decreasing level of detail.
s*
Found in dynamic and sequential models.
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6 COMPARATIVE EVALUATION
6.1 INTRODUCTION
This section provides detailed guidance on comparing two simulation
models. The comparison is made after the importance rating of each element
has been reviewed and the treatment of each element has been determined. The
comparative evaluation is technical in nature and consists of two steps
described in Sections 6.2.1 and 6.2.2, respectively. In the first step, the
models are compared on an element-by-element basis; in the second, these indi-
vidual comparisons and the importance ratings are combined into the technical
evaluation.
6.2 TECHNICAL COMPARISON
Before initially attempting to compare the treatments of an element by
two models, it is strongly recommended that the user be familiar with the
technical material presented in the appropriate section of Appendix A. Exper-
ienced users may have a lesser need for such reference material.
6.2.1 Comparing Treatments of Individual Elements
The study model's treatment of a particular element should be rated as
BETTER than, COMPARABLE to, or WORSE that the reference model's treatment.
This rating depends on the relative level of detail with which the two models
treat the element and the need for a detailed treatment. If the study model's
treatment is significantly more detailed than that used by the reference model
and considerable detail is needed in the application, the study model's treat-
ment is rated BETTER. If both treatments are essentially the same, the study
model is rated COMPARABLE. Finally, if the study model incorporates sub-
stantially less of the detail needed in the application, it is rated WORSE.
Guidance on determining the relative level of detail is available from three
sources:
The general tables in Section 5,
The discussions in Appendix A, and
The degree of flexibility the user has in defining input to
the model.
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94
The tables in Section 5 list various treatments of each element in
order of decreasing level of detail. These tables are the basic tools to
be used in determining the relative level of detail used in a given treat-
ment. Some elements have been further subdivided into several aspects,
each of which must be considered in making the comparison for those ele-
ments.
When there is only a single aspect, the user should locate the treatment
used by the study model and the treatment used by the reference model on the
appropriate table in Section 5. Tables B.2-B.13 in Appendix B give the treatments
used by selected reference models. Since not all possible treatments are listed
in the tables, the user may need to infer at what level a given treatment would
be located if it were explicitly included in the table. On the basis of the
relative level at which the two treatments occur, the user should decide upon a
comparative rating of the study model with respect to the reference model.
Judgment must be exercised at this stage; a treatment occurring at a slightly
higher level in the table than another is not necessarily a BETTER treatment.
COMPARABLE should be interpreted as meaning "near" or "approximately the same"
and should not be interpreted as meaning exact equality. A significant or
substantial difference makes the comparative rating BETTER or WORSE.
When the relative level of detail of two treatments is determined, the
relevance of that detail to the particular situation should also be considered.
The tables of treatments in Section 6 are general in nature and may indicate a
difference in the level of detail that is irrelevant in the application of
interest. For example, assume that the application involves level terrain,
that the study model accounts for physical stack height, and that the reference
model accounts for both the topographic elevation of the source as well as the
physical stack height. In this case, the study model would not be rated as
WORSE than the reference model, since elevation corrections are not required in
the specific situation being modeled.
The situation becomes more complicated for those elements for which
several aspects are discussed. The comparison is made for each aspect sepa-
rately and the results combined to give a comparative rating for the element
as a whole. The user should be guided by two things:
The likely importance of the various aspects in the particular
situation to be simulated, and
The expected sensitivity of model estimates to changes in each
aspect separately.
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95
The actual situation can be examined to determine which aspects might
require more detailed treatment. These would then weigh more heavily in the
evaluation of the element as a whole. Treatments of aspects to which the
concentration estimates are most sensitive would weigh more heavily than
treatments of aspects to which the estimates are least sensitive. A quali-
tative judgement on these matters is being sought; quantitative information
is not required. It may become necessary to consult an expert if questions
regarding sensitivity arise.
In difficult situations, the discussions in Appendix A may help resolve
the problem.
Specific guidance for all possible situations is clearly not feasible,
but the general principles discussed above should enable the user to compare
the treatments in most situations. If this guidance does not allow the user
to reach a decision, an expert should be consulted.
One final point needs to be made regarding the comparative rating of
treatments. For elements like dispersion for which the model itself must be
classified, the user must consider the appropriateness of the type of model
to the application at hand. Many factors could go into determing whether a
particular type of model is appropriate and no specific guidance can be given.
The user must make a decision based on specific needs of the problem. For
example, the tables for dispersion in Section 5 list numerical/dynamic treat-
ments above the semiempirical/steady-state treatments. However, as discussed
in Appendix A, if certain conditions are satisfied, a semiempirical/steady-
state treatment may be just as good as a numerical/dynamic treatment. In
fact, if a high degree of spatial resolution is required, the semiempirical
approach may be more applicable. Thus, the user would be warned that a highly
detailed approach may be inapplicable given the user's specific needs. This
example illustrates the need for the user to be familiar with the material
in Appendix A.
6.2.2 Overall Technical Comparison
This section describes the procedure for synthesizing the comparisons of
the individual elements into the TECHNICAL EVALUATION.
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96
When there have been no designations of CRITICAL elements, the user
should proceed as follows:
1. Examine the distribution of the treatments of the HIGH-rated ele-
ments among the categories BETTER, COMPARABLE, and WORSE. Based
on the type of distribution and the guidance below, formulate a
tentative evaluation.
2. Based on the distribution and number of the MEDIUM-rated elements,
determine the need to modify the tentative rating assigned in step
1. Modify as required.
3. The modified rating obtained in Step 2 will normally be the TECH-
NICAL EVALUATION. In ambiguous situations, the LOW-rated elements
may need to be considered.
If the user is unable to complete the TECHNICAL EVALUATION given the
following guidelines, an expert should be consulted.
It is also strongly suggested that the user document the reasons for
the decisions made, particularly in ambiguous cases.
6.2.2.1 Comparison Based on HIGH-Rated Elements (Step 1)
In step 1, only the high-rated elements are considered. The user should
take the following points into consideration:
The relative numbers of treatments in each category (the distribution),
The specific application elements in each category,
The relative importance of these elements in the application of
interest,
Factors unique to the application of interest, and
Possible ambiguous ratings in parentheses.
Five types of distributions can arise. Each is described below along with the
manner in which the other considerations affect the evaluation. It is not
always necessary for the user to identify the particular distribution as long
as the application of the general ideas is understood.
Case 1 - All Treatments of High-Rated Elements in Same Category (BETTER,
COMPARABLE, WORSE)
In this case, the comparison is obvious. For example, if there are three
highly important elements and the treatment of each by the study model is rated
better, BETTER is the unambiguous entry in the "Comparative Rating" column.
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97
Case - 2 Equal Numbers of Treatments in Each Category
With equal numbers of treatments in each category, the user cannot simply
assume that one better treatment balances out one worse treatment. Rather, the
user should identify those elements whose treatments are being considered in the
three categories. The importance of these elements to the specific situation to
be modeled should then be reassessed and any factors unique to that situation
should be considered. This process should not be interpreted as a reassignment
of the importance ratings but rather as a means to "fine tune" the HIGH ratings
in order to resolve an otherwise ambiguous situation. Although all these ele-
ments are of generally high importance in the application, the HIGH category
itself covers a rather broad range and some of these elements may be more
important than others. If such a determination can be made, a basis may exist
for making a comparison other then COMPARABLE.
Other information may be gained by looking at any ambiguous element-by-
element comparisons. For example, if one of the COMPARABLE ratings is ambigu-
ous and is indicated as perhaps belonging in the BETTER category, the judgement
would lean toward BETTER as the Comparative Rating. This judgment is made only
after the relative importances of the elements rated as better and worse have
been considered.
Case 3 - A Large Number of Treatments in One Category and a Smaller
Number in the Other Two
The considerations here are similar to those described above. The compar-
ative rating is that category with the largest number of elements. The confi-
dence in this rating increases as the relative number of treatments in this
category increases. For example, a rating of COMPARABLE based on three compar-
able treatments and two worse ones is much more tenuous than a COMPARABLE rat-
ing based on four comparable treatments and one worse one. Some additional
insight may also be gained by examining any ambiguous ratings. Since these
ratings are second guesses, their major use should be in cases where they tend
to remove ambiguity from the situation, that is, if they support the initial
comparison. In any case, no final assignment of the Comparative Rating should
be made until the elements whose treatments are listed in each column are identi-
fied and their relative importance reevaluated. It may be possible, for instance,
for a single WORSE treatment of a highly rated element to justify a Comparative
Rating of WORSE even if the treatments of several other high-rated elements are
COMPARABLE.
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98
Case 4 - Large Numbers of Treatments in COMPARABLE and
One Other Category and a Small Number in the Third
The same considerations apply here as enumerated in Case 3. Here,
however, any change in rating from the category with the largest number of
treatments would generally be to that associated with the next larger number
of elements.
Case 5 - A Large Number of Treatments in the BETTER and
WORSE Categories and a Small Number in COMPARABLE
This type of distribution should be considered anomalous and the user
should review the individual comparisons and importance ratings before pro-
ceeding. If the anomaly cannot be resolved, an expert should be consulted for
aid in the comparison.
6.2.2.2. Comparison Based on MEDIUM- and LOW-RATED ELEMENTS
(S-teps 2 and 3)
In step 2, the MEDIUM-rated elements are considered and the user must
decide whether or not to change the Comparative Evaluation reached at the end
of step 1. Keeping in mind that the MEDIUM-rated elements are by definition
less important individually than the HIGH-rated elements, the user should
consider the following:
The same considerations as involved in step 1, and
The relative numbers of HIGH- and MEDIUM-rated elements.
The consideration of the distribution of the MEDIUM-rated elements and
factors unique to the application follow lines parallel to those discussed in
Section 6.2.2.1. If the distribution of high and medium elements are similar,
no change is made in the rating. If the distributions are different, the
desirability of a change becomes stronger as the relative number of medium
elements increases. When the numbers of high and medium elements are considered,
the user must think about which elements are involved and their relative impor-
tance in the specific situation of interest. For example, consider the two
cases outlined in Table 6.1. In case A, the user would be much more likely to
change the initial Comparative Rating from BETTER to COMPARABLE than in case B,
because of the relatively larger number of MEDIUM-rated elements in case A.
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Table 6.1.
99
Effect of Numbers of
Elements on Ratings
Case
A
B
Importance
Rating
HIGH
MEDIUM
HIGH
MEDIUM
Better
1
0
3
0
Comparable
1
6
1
4
Worse
0
0
0
0
Comparative
Rating
BETTER
COMPARABLE
BETTER
BETTER
In most cases, step 3 simply involves writing down the Comparative
Rating reached at the end of step 2 as the TECHNICAL EVALUATION. The LOW-
rated elements are usually not considered. In cases in which the user
considers that a contemplated change based on the MEDIUM-rated elements is
ambiguous, it may be necessary to look at the LOW-rated elements in an
attempt to resolve the ambiguity. The rules for the comparison are essentially
the same as in step 2, except that in this case the user is examining the dis-
tribution, number of elements, and importance to the application to see if the
indicated direction of change is the same as that being contemplated. If it is,
the ambiguity may be removed. If not, the change should probably not be made.
If problems still remain, an expert should be consulted.
At this point, the TECHNICAL EVALUATION is complete.
6.2.2.3 Comparison with a CRITICAL Element
If a CRITICAL element has been designated, the procedure is almost the
same, except that the initial rating is based upon consideration of that element
alone. Possible subsequent modifications are then based first upon consideration
of the treatments of the HIGH-rated elements and then upon those of the MEDIUM-
rated elements. However, if a critical element is treated worse, the user may
consider making this single comparison the basis of the entire TECHNICAL
EVALUATION. For comparable and better treatments of the critical element, the
entire procedure should be applied. Since there will generally be only a
single critical element and several HIGH-rated elements, the user must decide
how many high elements would be required to override an initial Comparative
Rating based on the critical element alone. Again, the user must reach a
qualitative judgment based on the considerations discussed above and must not
base an entire comparison on a single critical element.
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7 ROLLBACK/STATISTICAL MODELS
7.1 GENERAL
The emphasis in this workbook is on the comparison of simulation
models. By definition, these models simulate mathematically the effects of
physical and chemical processes that affect air quality. Furthermore, the
relevant phenomena are considered and described in terms of fundamental
physical principles of general applicability. As a result, a simulation model
has the property of being transferable from one location to another as long as
the limitations imposed by assumptions made in the basic formulation of the
model are not violated. Air quality data taken within the region of interest
is not required except to fix boundary and/or initial conditions.
Models which do not satisfy these criteria may be encountered by the
user. This section provides general guidelines for their evaluation and
comparison. Such models are termed rollback/statistical models throughout
this workbook and are characterized by one or both of the following proper-
ties:
Only a very few of the factors relating to emissions,
meteorological, transformation, and removal processes
are explicitly considered in the formulation of the model.
Locally measured air quality data is required in order to
determine empirically the values of various coefficients
or parameters in the model.
Included in this classification is the simple rollback model and
various extensions of it. The simple rollback model assumes a linear relation
between total pollutant emissions within some region and pollutant concentra-
tions within that region. It does not explicitly consider the spatial distri-
bution of emissions, the location of the receptors of interest, nor any meteoro-
logical factors.
Also included in the rollback/statistical category are those models that
require the use of actual atmospheric monitoring data, including both air
quality and meteorological variables, for the empirical adjustment of model
parameters. The relationship between air quality and selected meteorological
parameters is determined empirically in these models, commonly through the
use of regression or other statistical techniques.
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102
7.2 ADVANTAGES AND DISADVANTAGES
The major technical advantage enjoyed by statistical models
is the close relationship between concentration estimates and values actually
measured under more or less similar circumstances. The effects of all those
factors that determine atmospheric pollutant concentrations are implicitly
accounted for in the air quality data used to develop and optimize the model.
The same may be said about rollback, since an air quality measurement is used
to estimate the ratio of emissions to atmospheric concentrations. Due to the
nature of the procedures used in developing a statistical model, information
is often available regarding the statistical significance of the variables
that are taken into account and the magnitude of the statistical error made
by the model; no such information is available for rollback. Other advan-
tages of rollback/statistical models, such as their low development cost and
low resource requirements, are primarily pragmatic in nature.
The major disadvantage of rollback/statistical models also arises from
their dependence on air quality data. A statistical model is not, in general,
applicable under conditions that are outside the range of conditions included
within the data used in its development and optimization. The range of condi-
tions commonly includes variations in meteorological variables, but for practi-
cal reasons very little variation in the spatial distribution of emissions can
be investigated. Consequently, statistical models are not generally suited for
applications that involve the consideration of significant changes in the dis-
tribution of emissions and, as a result, are not transferable without re-
evaluation of their specific empirical parameters or coefficients. Rollback
considers only one set of conditions, specifically that set of meteorological
conditions and emission rates which existed over that period of time in which
the air quality measurement used in the model was made. Therefore, it is also
unsuited for the consideration of changes in the emission distribution.
The applicability of rollback/statistical models is more limited than
that of a simulation model for other reasons as well. For example, only
rather general concentration estimates may be obtained. The dependence of
pollutant concentrations on position cannot normally be predicted, nor can
individual source contributions at any given position of interest.
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103
If a model that falls into the rollback/statistical category is to be
evaluated, the user should consider the applicability of the particular model
to the application of interest, keeping in mind the generally limited appli-
cability of such models. Statistical models are often formulated for a very
specific purpose. If that purpose coincides with the requirements of the
user, and if the range of conditions of interest to the user are included
within those used to develop the model, the model is applicable and may give
better results than a simulation model. Otherwise, the model may not be
appropriate.
7.3 COMPARISON OF ROLLBACK/STATISTICAL MODELS
The only basis that may exist for the comparison of a given statistical
model with a given simulation model is the observed performance of each in
previous practical applications. In general, the philosophies and goals of
these two approaches to estimating atmospheric pollutant levels are sufficiently
different as to preclude any systematic, objective, a priori technical comparison.
If, however, estimates of the errors made by the simulation model in applications
similar to the one of interest are available, they may be compared directly with
the expected error for the statistical model, thereby allowing a comparative
evaluation to be made. Unfortunately, even this basis does not exist for roll-
back, since the emission-concentration relationship is an assumed one, rather
than one obtained using accepted statistical procedures.
It may be possible in some cases to make a comparison of a rollback/
statistical model with a simulation model by determining the approximations that
must be made to reduce the working equations to a linear relation with constant
coefficients between the pollutant concentration and the total emission rate.
The degree of validity of the necessary approximations in the situation to be
modeled is a measure of the degree of comparability of the simulation model and
the rollback/statistical model. If this approach is adopted, the Evaluation
Form provides a convenient format for recording the necessary information.
Furthermore, if the element-by-element comparisons are interpreted as a measure
of the validity of the relevant approximations in going from the simulation
model treatment to the rollback or statistical model treatment, the information
can be summarized easily on Part D of the form. The technical comparison can
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104
in this case be made following the same guidelines as are used for the
comparison of two simulation models as described in the other sections of this
workbook.
It may not always be possible to make a comparison in this manner. A
statistical model may still be evaluated on its past performance. However,
since rollback is: (1) not really based upon consideration of the application
elements discussed in this workbook; (2) not obtained by statistical analysis
of appropriate air quality data; and (3) as yet unverified, no basis exists
for objectively evaluating the performance of a rollback model.
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TECHNICAL REPORT DATA
(Please read Imtructions on the reverse before completing)
REPORT NO.
EPA-450/2-78-028a
3. RECIPIENT'
OAQPS No. 1.2-097
TITLE AND SUBTITLE
Workbook for the Comparison of Air Quality Models
5. REPORT DATE
May 1 978
6. PERFORMING ORGANIZATION CODE
ACCESSION-NO.
AUTHOR(S)
8. PERFORM!
OAQPS No. 1.2-097
. PERFORMING ORGANIZATION NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
2. SPONSORING AGENCY NAME AND ADDRESS
13. TYPE OF REPORT AND PERIOD COVERED
EPA/OAQPS Guideline
14. SPONSORING AGENCY CODE
200/04
5. SUPPLEMENTARY NOTES
6. ABSTRACT
The workbook describes a technique for the qualitative comparison of modeling
approaches on technical grounds. The methodology is based upon an applications
approach. The results of the model comparison depend upon the application for which
the model is to be used as well as upon the model characteristics. In each
application of the technique, the model of interest is compared with a reference
model. Any model may be specified as the reference model, as long as it is compati-
ble with the application of interest.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Atmospheric Models
Air Pollution Abatement
Mathematical Models
Atmospheric Diffusion
b.IDENTIFIERS/OPEN ENDED TERMS
Implementation Air
Pollution Planning
Gaussian Plume Models
Diffusion Modeling
c. COSATI Field/Group
13B
13. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (This Report}
None
21. NO. OF PAGES
no
20. SECURITY CLASS (This page)
None
22. PRICE
EPA Form 2220-1 (9-73)
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