United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
September 1980
Air
Air Quality
Modeling
What It Is and
How It Is Used
-------
This publication was prepared for the U.S. Envi-
ronmental Protection Agency under contract by
Environmental Research & Technology, Inc.,
Concord, MA. Among many individuals who con-
tributed to the brochure in the review process,
the efforts of Carol Counihan and Dr. Bruce Egan
are especially appreciated.
Authors: David Strimaitis, Robert Bibbo
Robert McCann
-------
EPA is charged by Congress to protect the Nation's land, air
and water systems. Under a mandate of national environ-
mental laws focused on air and water quality, solid waste
management and the control of toxic substances, pesticides,
noise and radiation, the Agency strives to formulate and imple-
ment actions which lead to a compatible balance between
human activities and the ability of natural systems to support
and nurture life.
-------
Foreword
The purpose of this brochure is to acquaint the reader with the
basic concepts of air quality modeling and its application in air
quality management. It is directed to non-technical audiences to
explain what models are, how they are used, and what their limita-
tions are as a tool in the air pollution control process. Several
publications are listed for those who desire further information.
It should be understood that models are mathematically derived
tools. The reliability of predicted air quality estimates is directly
dependent upon the detail and quality of the information used in
applying the models. Their primary purpose is to serve as an aid
in arriving at sound regulatory decisions.
-------
Contents
iv Glossary of Terms
1 Air Quality Modeling in Decision-Making
What is an air quality model?
What are air quality models used for?
What are the air quality standards and PSD
increments?
When are models used to assess compliance
with the standards and increments?
What is the relationship between monitoring
and modeling?
6 Applying Air Quality Models
What is the general approach to modeling?
What is a screening analysis?
What is a refined model analysis?
What kinds of data are needed to apply a
model?
What source information is needed?
What air quality information is needed?
What meteorological information is needed?
What determines the selection of a particular
model?
What computer resources are required?
13 Available Air Quality Models
What are the general types of air quality
models?
What is the EPA UNAMAP series?
What models are included in UNAMAP?
When may other models be used?
17 Accuracy of Air Quality Modeling,
and Decision-Making
What determines the adequacy of a model?
How is a model validated?
What is the expected accuracy of models?
How should air quality data be used to verify
model-based decisions?
When are air quality data more acceptable
than models in decision-making?
-------
IV
Glossary of Terms
Area Source: a group of pollutant emitting facilities, with small
and variable emission rates, which are evenly dis-
tributed across a well-defined region. Emissions
from residential and commercial space heating
furnaces over several city blocks may be modeled
as one area source.
Background that portion of observed ambient pollutant concen-
Pollutant trations which is not directly attributable to major
Concentration: nearby pollutant sources.
Chemical a series of chemical reactions which changes the
Removal chemical composition of a pollutant. Such trans-
Process: formations reduce the amount of the original pol-
lutant in the ambient atmosphere.
Dispersion/ a mixing process in which air motions mix a pol-
Diffusion: lutant plume over an ever increasing volume, there-
by diluting the concentration of the pollutant in
the ambient air.
Line Source: a pollutant producing activity which is uniformly
spread out along a narrow band. Pollutant emis-
sions from moving vehicles on a major highway
may be modeled as a line source.
Long-Term: a period of time associated with annual air quality
standards. Long-term models usually address pol-
lutant concentrations over several seasons to one
year.
Meteorological a short period of time, varying between one hour
Episode or and a few days, over which a single class of weath-
Event: er conditions is dominant.
Physical a series of events which leads to the direct deple-
Removal tion of an air pollutant in the ambient atmosphere
Process: without chemical transformation. Several physical
mechanisms include settling of heavy particles,
impaction on vegetation and structures, and rain-
out.
Point Source: a single activity that causes the release of a pol-
lutant plume from a stationary vent. Large smoke-
stack emissions are modeled as a single point
source.
Primary a substance which is produced by a source and
Pollutant: released directly into the atmosphere as a pol-
lutant.
Secondary a pollutant which forms in the atmosphere as a
Pollutant: result of chemical reactions between substances
released by a source, and other substances already
present in the atmosphere. Many of these reac-
tions depend on sunlight, and are called photo-
chemical reactions.
Short-Term: a period of time associated with air quality stan-
dards for pollutant exposures ranging between
one hour and 24 hours.
"Worst-Case" a specific combination of wind speed, wind direc-
Meteorology: tion, and other weather variables which fosters
the highest expected pollutant concentrations due
to emissions from a particular group of air pol-
lution sources.
-------
Air Quality Modeling in Decision-Making
What is an air quality model?
An air quality model is a set of mathematical
equations relating the release of air pollutants to
the corresponding concentrations of pollutants
in the ambient atmosphere. Ambient air is the
outdoor air to which people, structures, plants,
and animals are exposed. Such mathematical
APPLICATION
Link Ambient
Concentrations to
Pollutant Emissions
\
p^aM Changes
n Air Quality
A
Supplement Air
, Quality Data
\
AIR QUALITY MODEL
relationships provide a technique for predicting
the consequences of changing the amount of
pollutants released into the air from either new
or existing sources of air pollutants.
What are air quality models used for?
Air quality models are used to identify and
evaluate the level of controls required to solve
industrial and urban air pollution problems. They
are applied in an engineering or analytical way
to identify the causes of existing problems, and
in a planning or predictive way to project and
avoid future problems. Air quality models are
used to:
• develop air pollution control plans for attain-
ment and maintenance of acceptable air
quality,
• assess environmental impacts expected from
industrial expansion and urban development,
and
• project the future air quality trends and pat-
terns associated with regional planning op-
tions.
-------
Each of these model applications is illustrated
by an example.
• Unacceptably high ambient pollutant con-
centrations are measured in a residential
area near an industrial zone containing many
large pollutant sources. Modeling must be
used to identify which sources are contribut-
ing to the excessive concentrations. Once
the problem sources are identified, air quality
engineers can take appropriate action to
solve the problem. By administrative action
the state agency can then incorporate this
solution into the state air pollution control
plan.
• An industry wants to construct a major new
facility in an industrial park near a large
urban area and submits an application to
the state for a permit to construct. Modeling
must be used by the state agency or indus-
trial consultants to predict how emissions
from the new facility will affect ambient air
quality. The state and federal air pollution
authorities will issue a permit to construct
only if the modeling indicates that accept-
able air quality will be maintained after the
facility is in operation.
• A regional planning agency has several dif-
ferent options for industrial expansion in a
rural county. Based on typical source charac-
teristics and projected emissions, the impact
of each option can be assessed with an
appropriate air quality model. The model
results can be used in conjunction with other
information to rank each option. In this way
environmental and economic factors can be
clearly assessed and integrated in the plan-
ning process.
In each case, modeling provides a quantitative
link between sources of air pollutants and ambient
air quality. Such a link is necessary when regu-
latory decisitns must be made within the frame-
work of the air quality standards and Prevention
of Significant Deterioration (PSD) increments.
What are the air quality standards and PSD
increments?
National Ambient Air Quality Standards
(NAAQS) are maximum pollutant concentration
-------
limits for ambient air in the United States. The
U.S. Environmental Protection Agency (EPA) and
state air pollution agencies must ensure that
NAAQS are attained and maintained throughout
the country.
Primary NAAQS protect the public health and
are based on known health effects. Secondary
NAAQS are generally more restrictive than primary
standards. They are based on vegetative and
material effects and are intended to protect public
welfare.
The PSD program was established to maintain
the ambient air quality existing on a specific
baseline date. The program applies, on a pol-
lutant-specific basis, to areas of the country where
existing air pollutant concentrations are below
the limits specified by NAAQS.
PSD increments are ambient pollutant concen-
tration limits which legally define how much
pollutant concentrations in an area can increase
from a set baseline level for all future time. As
new pollutant sources come on-line and each
increases ambient pollutant concentrations slight-
ly, they are said to "consume available incre-
ment." The full increment is available to these
NAAQS
-------
sources if the difference between the NAAQS
and the baseline level is greater than the incre-
ment.
When are models used to assess compliance
with the standards and PSD increments?
Compliance with the ambient air quality stan-
dards is primarily assessed with ambient air
quality monitoring data, when that data exist.
However, the geographical coverage and samp-
ling frequency achievable in most monitoring
systems limits the ability of the system to docu-
ment all possible occurrences of high pollutant
concentrations. Consequently, supplemental
modeling analyses are frequently performed to
determine if the standards are being attained
and maintained in areas where it is suspected
that air quality data do not include maximum
possible concentrations.
Air quality modeling becomes essential when
compliance with standards must be assessed
during permit review for new major sources. The
analysis must evaluate whether or not allowed
emissions from the new source will cause or
contribute to a violation of a NAAQS.
The consumption and allocation of PSD incre-
ments is also calculated with modeling. This is
because PSD permit conditions demand that
increment consumption expected from new major
sources and major modifications of existing
sources be predicted in advance of granting the
permit.
What is the relationship between monitoring
and modeling?
Collection and analysis of air quality data is
useful in (1) providing model validation data,
(2) monitoring for NAAQS attainment and main-
tenance, and (3) establishing background pollutant
concentrations due to minor or distant sources
not included in dispersion calculations. In cases
where there are few existing sources in the area
of a proposed new source or modification, moni-
toring may also provide a check on the main-
tenance of applicable PSD increments. Each of
these functions is directly related to the use of
models.
Ambient air quality monitoring ultimately deter-
mines the validity of modeling assumptions. The
most valuable interaction between monitoring and
-------
modeling occurs when modeling is used to iden-
tify areas of highest expected pollutant concen-
trations, and subsequent monitoring near these
locations is used to evaluate model predictions,
and to ensure that air quality standards are main-
tained. A second type of interaction frequently
occurs when monitors record excursions of the
standards. Such excursions usually trigger model-
ing analyses to develop a control strategy aimed
at correcting the causes of the violations. In
both cases, modeling is used as a predictive
tool in identifying which sources have an impor-
tant air quality impact and where these impacts
occur, while monitoring provides a basis for
assessing the accuracy of those predictions.
-------
Applying Air Quality Models
What is the general approach to modeling?
Generally accepted practice calls for a two
step modeling procedure. The first step provides
for a screening of potential air quality problems
with the use of a simple model. The second step
is a detailed assessment of an air quality prob-
lem identified in the screening analysis, using a
more refined model. The second step is initiated
if potential air quality problems, such as viola-
tions of NAAQS, are singled out in the first step.
What is a screening analysis?
The purpose of a screening analysis is to elim-
inate, with minimum effort, those sources that
clearly will not cause or contribute to ambient
concentrations in excess of any air quality stan-
dard. When properly applied, screening models
can eliminate unnecessary expenditures of re-
sources associated with more refined modeling
assessments.
The screening procedure is most useful for
point sources when the short-term standards are
more limiting than long-term standards. The first
Presence of Secondary Pollutant Due to
Complex Chemical Reaction
-------
phase of the procedure consists of simple calcu-
lations for estimating concentrations under worst-
case meteorological situations not complicated
by terrain or other physical features. A second
phase includes more detailed screening proce-
dures for special cases including simple terrain
impingement, building downwash, and long range
transport.
What is a refined model analysis?
A refined model incorporates many of the same
assumptions found in the more complex screen-
ing models. However, the refined model retains
much more of the detail present in source data
and meteorological data. While screening model
predictions consider worst-case meteorological
conditions and simplified physical assumptions,
the refined model incorporates more complex
physical assumptions, and uses the actual dis-
tribution of meteorological episodes and source
characteristics to assess the potential for ambient
air quality violations.
What kinds of data are needed to apply a
model?
Data needed to apply a model fall into three
categories:
• source data
• air quality data
• meteorological data
Source data describe where pollutants are
released, and determine initial pollutant concen-
trations. Air quality data provide information on
background pollutant concentrations that either
add to or react with pollutants included in the
source data. Meteorological data describe the
potential for pollutant transport, diffusion, and
transformation in the atmosphere before reaching
the ground.
What source information is needed?
All simulation models require at least the fol-
lowing source information:
• location of air pollution sources
-------
• estimates of the amount of pollutant that
each can emit
• description of how pollutants are released
to the atmosphere
• description of nearby structures
The location of a source of air pollutionjs usually
referenced to a conventional map coordinate
system. This enables a model to specify the
individual locations of each source relative to
significant terrain features, populated areas, other
sources, and air quality monitors. A description
of the pollutant-producing process at each source
is used to estimate the amount of pollutants
emitted to the atmosphere, and a description of
how the pollutants are emitted determines what
atmospheric processes are important in estimating
ambient concentrations resulting from these
emissions.
All of this information is generally obtained
from engineering, process, and fuel use data.
The specific quantities derived from this data
and used to model each source include:
• source coordinates,
• pollutant emission rate
• height of the pollutant release such as stack
or vent height
• shape and dimensions of release points such
as the stack diameter of a point source, or
the width and length of an area source
• temperature of the plume upon release to
the atmosphere
• velocity of plume at the point of atmospheric
release
• dimensions and locations of nearby buildings
and structures
Source information is generally obtained from
local and state air pollution agencies, and the
EPA. Each EPA regional office collects and main-
tains emissions data, and makes it available to
the general public. State agencies submit de-
tailed source data to these offices annually. There-
fore, local and state agencies often provide de-
tailed source data directly from their own emis-
sions inventory system. Regional emissions over
the entire country can be found in the National
-------
Emissions Data System (NEDS), which is main-
tained by the EPA.
What air quality information is needed?
Air quality data from existing monitoring sta-
tions is needed to provide information on ambient
pollutant concentrations. When obtained from
appropriate monitors, these data are used to
determine if an area is in compliance with NAAQS,
and are also used to adjust air quality model
estimates for background pollutant concentra-
tions. These data can be obtained from state
and local air pollution control agencies, or through
the Storage And Retrieval Of Aerometric Data
(SAROAD) system at regional EPA offices. The
SAROAD system is the national air data bank.
These sources may be supplemented with data
from industrial monitoring networks. Most meas-
urements are processed into short-term and an-
nual averages for convenient comparison with
NAAQS.
What meteorological information is needed?
Meteorological variables that describe pollutant
transport and dispersion in the atmosphere are
wind direction, wind speed, atmospheric stability,
and mixing height. Wind direction determines
the general direction of pollutant transport. Wind
speed determines the amount of initial dilution
of the pollutants and also the height to which
the plume rises. Atmospheric stability is a
measure of turbulence, which in turn determines
the rate at which the effluent is dispersed as
it is transported by the wind. Mixing height is
the vertical depth of the atmosphere through
which pollutants can be dispersed.
Estimates of each variable are usually obtained
from meteorological observations made by the
National Weather Service (NWS) at numerous
observing stations throughout the country. They
are available as hour-by-hour weather observa-
tions and in summarized forms from the National
Climatic Center (NCC) in Asheville, North Carolina.
The variables can also be obtained from similar
information recorded by industrial site-specific
meteorological measurement programs.
Other variables, such as relative humidity and
solar radiation, may be required for sophisticated
-------
10
air quality models that simulate chemical reac-
tions and transformations in the atmosphere.
These variables can be inferred through appro-
priate analysis of NWS data and site-specific
measurements.
What determines the selection of a particular
model?
The choice of a model depends primarily on
the level of detail required to fulfill the objectives
of the analysis, on the availability of input data,
and on the physical nature of the system to be
analyzed.
Analysis objectives can include siting air quality
monitors, or assessing compliance with air quality
standards, for example. In siting monitors, zones
of high, frequently occurring concentrations must
be identified. When compliance modeling is
performed, only the highest, or second highest
predicted concentrations are of interest. Modeling
approaches in those two cases may not be the
same.
The availability of input data can influence
the selection of an air quality model. The more
complex models generally require more detailed
data bases. However, the availability of this
information alone does not control the choice of
model. In some cases, limited use of representa-
tive data to augment existing data required for
a more complex model will produce considerably
more useful and accurate concentration estimates
than those produced by a less complex model
that happens to fit the existing data.
The physical nature of the system depends on
(1) the characteristics of the pollutants, (2) the
averaging time for determining pollutant concen-
trations, (3) the characteristics of the sources
of those pollutants, and (4) the characteristics
of transport and diffusion between those sources
and points selected for air quality evaluation.
Elements of these four factors are listed in Table 1.
What computer resources are required?
The simplest screening calculations can be
done with n<5 more than a scientific pocket cal-
culator. However, more complicated analyses
are performed with a small computer.
-------
11
Table 1
Factors Important in Selecting a Model
Pollutant Characteristics
Production Process Removal Process
1. Primary
2. Secondary
Short-term
1. Hours
2. Days
Number
1. Few/Isolated
2. Multiple
1. None
2. Chemical
3. Physical
Averaging Time
Long-term
1. Months
2. Seasons
Source Characteristics
Geometry
1. Point
2. Area
3. Line
4. Volume
Transport and Diffusion Characteristics
Geographic Features Distance
1. Simple
2. Complex
1. Short-range (< 50 km)
2. Long-range (>50 km)
All refined models require a large computer.
The capabilities of a large computer are needed
since many meteorological conditions must be
simulated, and concentrations at many receptor
locations must be calculated for each meteoro-
logical condition.
-------
12
Background Pollutants
Photochemistry
\ Chemical
/ Removal
Secondary
Pollutant
Physical Removal
Ramout
Settling
Impaction
Pollutant characteristics and transport characteristics are important factors in selecting a model. Some pollutants
(primary) are nearly inert over short-range downwind distances, and their concentration in the atmosphere only
changes through diffusion. Over long-range downwind distances, these pollutants eventually leave the atmosphere
mainly through physical removal processes. Other primary pollutants are chemically reactive. They can be removed
through chemical transformations. Pollutants created by these chemical reactions are called secondary pollutants.
-------
13
Available Air Quality Models
What are the general types of air quality
models?
There are a number of different types of models
ranging from quite simple to complex. The sim-
plest type of air quality model is the proportional
"rollback" technique which is useful if very little
information is known, and crude estimates of
needed emissions reductions are desired. The
technique assumes that changes in the highest
concentrations of a particular pollutant are direct-
ly related to the changes in the areawide emis-
sions of that pollutant. Using this technique,
a required 50% reduction in ambient concentra-
tions needs a 50% reduction (or .rollback) in re-
gional emissions. In contrast, one of the most
complicated forms of an air quality model is a
photochemical model for reactive pollutants. This
type of model can contain many complicated
chemical reaction relationships which require a
vast number of computations. Extensive and
detailed emissions, air quality, and meteorological
data must be available in order to apply this type
of model.
Between these two extremes lies a variety of
statistical and simulation models. Statistical
models are similar to the rollback techniques,
relying on observed relationships between air
quality data, emission rates, and selected mete-
orological variables. These models are site-spe-
cific. Simulation models, on the other hand,
explicitly incorporate the effects of physical and
chemical processes through mathematical expres-
sions derived from fundamental scientific princi-
ples. As a result, the same simulation model
can be conveniently and correctly applied in many
different regions as long as the basic model
assumptions are not violated. This is not true of
statistical models. Therefore, most air quality
modeling is performed with simulation models.
The most frequently used screening and refined
simulation models for evaluating the dispersion
of atmospheric contaminants are those based on
the well-known Gaussian plume description of the
dispersion process. Gaussian plume models simu-
late transport and diffusion of air pollutants by
means of simple algebraic expressions that are
easily programmed for a computer. These models
have been used for more than two decades, and
-------
14
Rollback Technique
Gaussian Plume (Simulation Model)
Data and Assumptions Computations Predictions
Photochemical Model
Data and Assumptions
Computations
underlie much of the current and proposed regu-
latory modeling practice. They will continue to
be widely used in the future. Nearly all available
atmospheric dispersion models are based on the
Gaussian description.
What is the EPA UNAMAP series?
The User's Network for Applied Models of Air
Pollution (UNAMAP), instituted in 1973 by the EPA,
is a system consisting of a library of air quality
simulation models. EPA stores the models for
readily available access, updates the models and
model inventory, and provides a service that noti-
fies users of any changes to the models. The
UNAMAP series includes both screening models
and refined models and is available on magnetic
tape from the National Technical Information
Service (NTIS).
What models are included in UNAMAP?
The UNAMAP models, listed in Table 2, are
all Gaussian-based dispersion models. Gaussian
models have been used extensively in atmospheric
dispersion modeling and form the basis for much
of the current regulatory procedures.
-------
15
Table 2
Summary of Models in UNAMAP
APRAC, a short-term model for vehicle-generated pollutants located within and around an urban area.
HIWAY, a short-term model for vehicle-generated pollutants for calculating concentrations downwind of roadways.
PTMAX, PTDIS, short-term screening models for a single source in rural areas. These models determine distances of
maximum concentrations for specific meteorological conditions.
PTMTP, a short-term screening model for multiple sources in rural areas.
PAL, a point, area, and line source screening model for calculating short-term concentrations in rural areas.
COM, Climatological Dispersion Model, an annual or seasonal urban model.
CDMQC, version of COM capable of identifying individual source contributions to the predicted pollutant concentrations.
RAM, a series of models for calculating short-term and annual concentrations during a one-year period in flat urban areas
with point and area sources in multiple locations.
CRSTER, a model for calculating short-term and annual concentrations during a one-year period from a single plant in a
rural area with moderate terrain.
VALLEY, a screening model for calculating maximum 24-hour concentrations from a single source in rural rough terrain.
ISC, a model for estimating short-term and annual concentrations during a one-year period for complex industrial sources.
MPTER, a model for estimating short-term and annual concentrations during a one-year period from multiple sources in
a rural area with moderate terrain.
-------
16
UNAMAP models incorporate a wide variety
of features and capabilities. Most of the models
handle primary pollutants without any considera-
tion for physical or chemical removal processes.
None handle the secondary production process
directly, while several approximate physical and
chemical removal processes with a simple math-
ematical formulation. A majority of the models
can be applied to estimate short-term concen-
trations while about half can be used for longer
averaging periods.
When may other models be used?
When circumstances become sufficiently com-
plicated, other refined models may be required.
Such models, when available, should be applied
cautiously and only under the direction of experi-
enced air pollution engineers or scientists. They
can be used to assess:
• emission releases from sources located in
areas with rough or complex terrain
• emission releases from sources near large
bodies of water
• the formation of secondary pollutants through
complex chemical reactions
• the long-range transport of both passive and
reactive pollutants
• emissions from moving sources such as jet
aircraft
• complicated downwashing situations which
are beyond the limitations of the ISC UNAMAP
model
-------
Accuracy of Air Quality Modeling,
and Decision-Making
17
What determines the adequacy of a model?
A model is considered adequate if it predicts
observed pollutant concentrations well. This usu-
ally occurs when the model incorporates all of
the important physical processes which deter-
mine maximum pollutant concentrations.
For example, plumes from short, stubby stacks
close to large buildings are known to downwash
at high wind speeds. (A plume caught in dis-
turbed air flow patterns in the wake of a struc-
ture reaches the ground quickly and is said to
"downwash.") If a model for such a plume does
not include this process, it will fail to produce
adequate predictions of pollutant concentrations
close to the stack.
Modeling adequacy is more difficult to assess
in complex situations. The physical processes
which are most important may not be clear. If
model adequacy is in doubt, validation or cali-
bration studies are required to test the ability
of the model to predict observed concentrations.
How is a model validated?
A model can be validated if its predictions are
directly comparable to detailed air quality observa-
tions. When comparisons are made, the follow-
ing conditions must be met:
• Terrain and meteorological conditions are
described adequately in the model.
• Source data are complete and any significant
variations are identified.
Limitations
-------
18
• Pollutant characteristics are well known,
including any important chemical reactions
or removal processes.
• The pollutants to be addressed must have
characteristics similar to those for which
the model was developed.
• Air quality data are representative of the area
and averaging times simulated, and are accu-
rate and complete.
When these conditions are satisfied, validation
of the model consists of the following steps:
• Simulated concentrations are compared with
measured data.
• The causes of any differences are identified.
• Data bases are corrected and improved.
• Inappropriate model assumptions are modi-
fied.
• The accuracy of predicted concentrations
is documented.
If a statistical evaluation of the results of com-
paring predicted and observed concentrations
indicates that predicted concentrations do not
compare well with measured concentrations, then
it is likely that one or both of the following prob-
lems exist: (1) the source data, meteorological
data, or air quality data are not appropriate, reli-
able, and complete or (2) the model itself is in-
adequate. Due to limitations in data bases, scien-
tific knowledge, time, and resources, a complete
validation is not always possible.
What is the expected accuracy of models?
Realistic assumptions used in air quality models
are in accordance with experience and scientific
theory, but they are at best only approximations.
When coupled with the inaccuracies inherent in
the source data and the meteorological data used
in the model, use of these approximations will
sometimes cause a model to either overpredict
or underpredict short-term concentrations. When
specific meteorological events are considered,
model predictions are generally within a factor
of 2 of the observed concentrations.
-------
19
How should air quality data be used to verify
model-based decisions?
Air quality data are used to verify model-based
decisions in a broad sense by indicating if the
NAAQS are maintained, or if further progress is
made toward attaining the standards in non-
attainment areas. In a more specific sense, air
quality data may also be used to test the applica-
bility of the modeling, and thereby either lend
support to the predictions of the model, or pro-
vide a basis for re-evaluating the modeling as-
sumptions employed.
If a detailed emissions and meteorological
data base is collected in conjunction with moni-
tored air quality data, then a comparison of model
predictions, using actual emission rates, with the
observed pollutant concentrations is possible.
Such a comparison may lead to a recommenda-
tion for the use of an alternate model. When
it is evident that the model consistently under-
predicts the highest of the observed concentra-
tions, the decision to consider alternate model-
ing techniques is clear, provided the emissions
or meteorological data bases are not at fault.
When the comparison shows that the model con-
sistently overpredicts observed concentrations,
the decision to recommend a different model
may be considered.
Effective air quality decisions must be based
on realistic modeling estimates. At times, selec-
tion of the most appropriate, realistic modeling
technique is very difficult to make. Collection
and use of high quality monitoring data are essen-
tial in evaluating decisions based on modeling
data alone.
When are air quality data more acceptable
than models in decision-making?
Air quality modeling is a tool used to estimate
maximum expected pollutant concentrations over
a wide range of meteorological conditions with
the expectation that pollutant emission rates will
at times reach their maximum allowed limits.
Air quality data, on the other hand, represent
pollutant concentrations measured when emis-
sion rates are at their actual levels. These rates
could be below maximum allowed rates for much
of the time. If modeling shows that no violation
-------
20
For More Information
of the NAAQS is expected, but subsequent moni-
toring reveals excursions of the standards, then
the air quality data take precedence over the
modeling results.
Air quality data are also extremely important
in situations where either the data base needed
for modeling is inadequate, or the applicability
of modeling in general is questionable. Model-
based estimates of air quality and preliminary
decisions may still be made, but these will usually
be subject to review once additional monitoring
data are obtained.
Screening Procedures
Guidelines for Air Quality Maintenance Planning
and Analysis, Vol. 10 (Revised), Procedures for
Evaluating Air Quality Impact of New Stationary
Sources. OAQPS No. 1.2-029R, EPA-450/4-77-001,
October 1977.
Descriptions of Available Models
Guideline on Air Quality Models. OAQPS No.
1.2-080, EPA-450/2-78-027, April 1978.
Workbook for the Comparison of Air Quality
Models. OAQPS No. 1.2-097, EPA-450/2-78-028A,
May 1978.
Air Quality Monitoring Procedures
Ambient Air Monitoring Guidelines for PSD.
OAQPS No. 1.2-096, EPA-450/2-78-019, May 1978.
U.S. Oovcrnnent PrinUna Office: 1980- 735-000/3017 Reaion No. 3-II
-------
EPA Regional Offices
EPA Region 1 • JFK Federal Bldg. •
Boston, MA 02203 • Connecticut,
Maine, Massachusetts,
New Hampshire, Rhode Island,
Vermont •
617-223-7223
EPA Region 2 • 26 Federal Plaza •
New York, NY 10007 • New Jersey,
New York, Puerto Rico, Virgin
Islands •
212-264-2515
EPA Region 3 • 6th and Walnut
Streets • Philadelphia, PA 19106 •
Delaware, Maryland, Pennsylvania,
Virginia, West Virginia, District of
Columbia •
215-597-4081
EPA Region 4 • 345 Courtland Street
NE • Atlanta, GA 30308 • Alabama,
Georgia, Florida, Mississippi, North
Carolina, South Carolina, Tennessee,
Kentucky •
404-881-3004
EPA Region 5 • 230 S. Dearborn •
Chicago, IL 60604 • Illinois, Indiana,
Ohio, Michigan, Wisconsin,
Minnesota •
312-353-2072
EPA Region 6 • 1201 Elm Street
Dallas, TX 75270 • Arkansas,
Louisiana, Oklahoma, Texas,
New Mexico •
214-767-2630
EPA Region 7 • 324 East 11th Street
Kansas City, MO 64106 • Iowa,
Kansas, Missouri, Nebraska •
816-374-6201
EPA Region 8 • 1860 Lincoln Street <
Denver, CO 80295 • Colorado, Utah,
Wyoming, Montana, North Dakota,
South Dakota •
303-837-3878
EPA Region 9 • 215 Fremont Street
San Francisco, CA 94105 • Arizona,
California, Hawaii, Nevada, Pacific
Islands •
415-556-1840
EPA Region 10 • 1200 Sixth Avenue •
Seattle, WA 98101 • Alaska, Idaho,
Oregon, Washington •
206-442-1203
------- |