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United States
Environmental Protection
Agency
Atmospheric Sciences
Research Laboratory
Research Triangle Park NC 27711
Research and Development
EPA/600/S3-87/002 Apr. 1 987
&EPA Project Summary
Further Studies of Parameterized
Air Quality Modeling Methods for
Materials Damage Assessment
L R. Dupuis, F. W. Lipfert, and J. W. Peters
/ I V
One of the components of the Na-
tional Acid Precipitation Assessment
Program (NAPAP) deals with damage
to materials in the environment. Such
an assessment requires detailed infor-
mation on deposition of corrosive
agents, namely SO2 and wet IT, on
spatial scales compatible with materials
distributions in urban areas. The objec-
tive was to provide sufficiently accurate
deposition estimates for materials
damage for over 100 cities, within very
limited time and cost constraints.
Since extant urban SO2 monitoring
data are inadequate to characterize the
distribution of air quality within cities
(i.e., monitors tend to be located only
to meet specific regulatory needs), a
modeling approach was necessary to
estimate detailed annual average SO2
concentrations. The basic approach
used was one of parameterization, in
which closed-form algorithms are de-
veloped for point and area sources which
mimic the performance of EPA's Cli-
matological Dispersion Model (COM),
and allow rapid assessment of a large
number of sources. The modeling sys-
tem, called PAQMAN (Parameterized
Air Quality Model AIMnual), was suc-
cessfully applied to over 100 urban
areas in the Northeastern U.S. in which
materials distributions have been
derived.
Sensitivity analyses of various model
components and assumptions were
performed and are described in this
report. The results indicate that model
calculations are most sensitive to emis-
sion grid cell size (particularly 1-2 km)
and to the treatment of a given source
as an area or point source depending on
stack height. Comparisons between
COM and PAQMAN calculations show
PAQMAN to overpredict or under-
predict point source impacts for in-
dividual MSA's suggesting that wind
direction effects should be accounted
for in lieu of directional averaging. The
parameterized approach developed for
point sources using the McElroy-Pooler
dispersion coefficients are supported
by the use of the Briggs curves as well.
Comparisons between PAQMAN values
and observed data (grid square aver-
ages) for several major cities indicate
acceptable agreement, generally within
a factor of 2.
When considering aggregated effects
across an extensive region involving
thousands of sources, PAQMAN is a
very suitable tool for estimating SO2
distributions in urban areas. Its auto-
mated source-receptor allocation proce-
dures allow for the rapid assessment of
impacts for many sources and receptors
with minimal user-imput requirements
and computer running times. Should
the scope of future accessments focus
on a more detailed study of a single city
or a few cities, more in-depth models
may be more suitable. Nevertheless,
some of the automated procedures
developed in PAQMAN would be useful
in alternative models as well.
This Project Summary was developed
by EPA's Atmospheric Sciences Re-
search Laboratory, Research Triangle
Park, NC, to announce key findings of
the research project that Is fully docu-
mented In a separate report of the same
title (see Project Report ordering In-
formation at back).
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Introduction
Assessment of damage to materials is
one of the components of the National
Acid Precipitation Assessment Program
(NAPAP) Damage can result from both
dry and wet deposition of corrosive agents
in the atmosphere, and therefore such
assessments require appropriate air
quality and deposition estimates. These
estimates can be calculated either from
extant monitoring data or by use of
mathematical models; mathematical
models are required to evaluate a priori
the potential benefits of candidate control
strategies
For assessment purposes, the linkages
between damage to specific materials
and the presence of various corrosive
agents in the atmosphere are made by
using mathematical damage functions
which have been derived from field and
laboratory tests. The atmospheric species
of interest for materials damage due to
acidic deposition include S02, HN03,
particulates and wet deposition of H*.
However, currently available test results
have limited the present damage func-
tions to gaseous SO2 and wet H+.
Objectives
This project is concerned with methods
of estimating annual average concentra-
tion levels of S02 in urban areas for use
with the damage functions in deriving
aggregate economic estimates for large
metropolitan areas. Previous estimates
(EPA/600/8-85/028) were based on S02
estimates resolved to 5x5 km grid-square
averages using the PAQMAN modeling
system. This grid size was selected as a
compromise between precision and com-
puting time requirements. Additional
studies performed subsequent to the
development of the PAQMAN algorithms
have involved examination of the sen-
sitivity of some of the modeling concepts.
Results of these studies are described in
this summary.
Technical Approach
The PAQMAN system is a param-
eterized scheme in which simplified
algorithms describing the dispersion of
both point and area sources were in-
tended to emulate EPA's Climatological
Dispersion Model (COM). The parametric
studies used to develop these algorithms
involved a range of stack heights and flue
gas exit conditions for point sources;
various geometric patterns and emission
densities were used for area sources.
McElroy-Pooler (M-P) dispersion coef-
ficients were used for point sources while
the Pasquill-Gifford (P-G) coefficients
were applied to area sources. Plume rise
was calculated according to the Briggs
method; removal processes were de-
scribed by an exponential decay. Wind
roses for New York City (JFK), Pittsburgh
(PIT) and Cincinnati (CVG) were used m
the parametric runs; the results were
then combined into two generic cate-
gories, coastal (JFK) and interior (a blend
of PIT and CVG), in order to eliminate
site-specific wind roses in favor of re-
gionally representative meteorology.
The point source calculation algorithms
were based on the use of the averaged
distance (rmax) from the source to the
location of the maximum annual average
ground-level concentration as a scaling
parameter. This distance was found to be
proportional to stack height The down-
wind ratio of concentration with respect
to the maximum concentration (x xma*)
was a function of the ratio downwind
distance to this scale length (r/rmax).
xmax was an inverse-squared function
of stack height. Such a parameterization
scheme combines all stack heights into
one generalized representation, and im-
plicitly averages all wind directions. The
scheme thus requires only source-
receptor separation distance to estimate
annual average impact which is a major
computational simplification These sim-
plifying assumptions and methods also
limit the application of the parameterized
model to cases where there are many
point sources of varying heights and
locations, and to estimating annual im-
pacts only
Emission density (Q/A) and scale length
(grid size) were the controlling factors for
the area source calculation algorithms.
The underlying assumption is that con-
centration patterns tend to "flow" from
areas of high emission density into ad-
jacent areas of lower emission density,
but not vice-versa.
A rectangular grid (5-km spacing) was
overlaid encompassing census tract cen-
troids within each /Metropolitan Statistical
Area (MSA). Sources inside this grid with
stack heights less than or equal to 200 ft.
were grouped and treated as area sources;
those with stack heights greater than
200 ft. were treated as point sources in
the model. All sources within 50 km
outside the grid boundaries were treated
as point sources. Source emissions data
were obtained from the NAPAP emissions
inventory (Version 2.0) for 1980. Back-
ground S02 estimates (due to sources >
50 km from the MSA boundary) were
supplied by exogenous calculations based
on Shannon's ASTRAP Model.
Results/Discussion
Earlier studies in which the PAQMAN
algorithms were exercised for over 100
MSA's throughout the Northeastern U.S.
indicated reasonable agreement between
model predictions and observed values
on an overall, aggregate basis. Further
examination of various model components
and assumptions was performed, and the
results indicate that model predictions
are sensitive to some of these factors as
described below.
Sensitivity of PAQMAN
Predictions to Grid Cell Size
Since area sources within each model
grid square are aggregated and the pre-
dicted contribution (grid square average)
based on emission density is assigned to
the grid centroid, the area source calcula-
tions are dependent on the grid cell size.
The optimal grid size with which to model
is an interesting but complex problem.
Smaller grid spacing allows for more
detail, but such detail may not be so
important if the effects are to be aggre-
gated over large areas such as MSA's.
The effect of applying different grid
size options in PAQMAN was analyzed in
terms of S02 concentrations for some of
the larger urban areas Results indicate
that MSA-averaged values decrease with
decreasing grid cell size (relative to 5 km),
but show little change for larger cell
sizes. This is likely due to the increase in
the number of individual grids with pre-
dicted values at the lower levels when
the grid cell size is decreased, and may
indicate that the area source algorithm is
underestimating at the lower gridscale
levels.
Sensitivity to Designation of
Sources as Area vs. Point
Sources
The choice of 200 ft as the source-
type criterion in PAQMAN is not purely
arbitrary. Comparison of point and area
source calculations for a source assuming
a range of stack heights (for the point
source algorithms) revealed that a source
with a stack height of 200 ft. would
produce a maximum groundlevel concen-
tration in the point-source mode equiva-
lent to the concentration that would be
predicted if it were assumed an area
source using 5-km emission grids. Similar
analysis assuming different emission grid
sizes for the area source calculations
suggests that the stack height criterion
should be adjusted relative to the grid
size chosen in the model.
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Sensitivity to Wind Direction
Effects
One of the major assumptions inherent
in the PAQMAN model is that local
meteorology over a long-term, annual
basis can be generalized into a regional
representation. It was thought that this
methodology would not introduce any
net bias for a large number of sources
scattered around an urban area. However,
test case studies comparing PAQMAN
calculations with COM results for in-
dividual MSA's reflected some bias, par-
ticularly at the lower S02 levels for cities
where major point sources were con-
centrated in a given area.
For New Haven, PAQMAN underpre-
dicted the higher point-source impacts
relative to COM. This is explained by the
fact that the major point sources affecting
New Haven are located to the southwest
of the city, and with prevailing winds out
of the southwest, the effect of these
sources is underestimated by the direc-
tional-averaging technique that was
applied in developing the PAQMAN point
source algorithms. The opposite effect
occurs for Pittsburgh since most of the
major point sources are situated to the
southeast of the city. Thus, the magnitude
and direction of bias will depend on the
orientation of the major point sources
with respect to a given MSA.
The errors induced by the directional
averaging in PAQMAN may very well
balance out in the overall aggregated
Assessment over the greater than 100
MSA's in the Northeast U.S. Nevertheless,
the tendency toward over- and under-
prediction of point source estimates (rela-
tive to COM) suggests that wind direction
effects are important and should be
considered.
Sensitivity to the Use of
Alternative Dispersion
Coefficients
Although the M-P coefficients have
been recommended by EPA for modeling
point sources in urban areas, it is im-
portant to examine whether the param-
eterization developed will be valid using
alternative dispersion coefficients. This
was accomplished using the Briggs dis-
persion coefficients, adjusted by one
stability class (toward more unstable
conditions) to account for increased
turbulence in urban areas, in the pa-
rametric COM runs. The results revealed
relationships very similar to those estab-
lished with the M-P dispersion algorithms.
However, the generalization of all stack
heights into a single representation was
not as apparent with the Briggs coef-
ficients, as shown in Figure 1.
Figure 1 suggests that perhaps separate
algorithms describing the decay of con-
centration downwind of the maximum be
developed for shorter vs. taller stacks.
However, when the effects are analyzed
across an entire MSA, the differences
described above do not appear to be
greatly significant. A comparison of
PAQMAN runs for various MSA's applying
both the M-P and Briggs algorithms in
the point source calculations revealed
only minor differences for the larger
MSA's. Greater differences were found
for smaller MSA's where individual point
source effects are likely to have a more
important effect, although SO2 levels are
generally quite low.
Comparison with Monitoring
Data
Comparisons were made between
PAQMAN predicted concentrations and
observed data for some of the larger
cities (where more monitoring data were
available). Monitoring data were acquired
from the U.S. EPA's Aerometric Data
Bank as quarterly averages, then averaged
Figure 1. Concentration ratio vs. distance ratio PIT wind rose - varying H, (m). Briggs' rural
P's (adjusted upward by one stability class).
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over the entire period in order to derive
the maximum possible number of annual
average estimates, compensating for
periods of missing data. In addition, since
PAQMAN predicts for grid centroids only,
comparisons for the same location (in
space) were seldom possible. Therefore,
observed data falling within the same
modeled grid square were averaged and
compared with the PAQMAN estimate.
Results showed acceptable agreement
between predicted and observed S02
values, and are summarized in Table 1. (A
sample comparison is presented for Cin-
cinnati, OH in Figure 2.) PAQMAN pre-
dictions are within a factor of ± 2 of
observed values with the exception of a
few outliers, and within a factor of ± 1.5
over 70% of the time for seven of the
nine cities analyzed. The mean ratio of
predicted to observed values over the
nine cities is 1.17; the median value is
1.03.
Conclusions
A method of estimating annual average
S02 concentration levesl in urban areas
has been developed, to be used with
damage functions to derive aggregate
economic estimates of materials damage
for large metropolitan areas. Earlier
studies in which the model was exercised
for over 100 MSA's throughout the
Northeastern U.S., indicated agreement
generally within a factor 2 between model
predictions and observations on an over-
all, aggregate basis. Further sensitivity
analysis of various model components
and assumptions have indicated that
some improvements or modifications
should be made. These include:
1. The area source calculation scheme
should be further examined since
the model may be underpredicting
area source impacts at the lower
(1-2 km) emission grid scales. The
criterion used to estimate the effect
of neighboring emission grids may
require adjustment, particularly at
the lower grid-scale levels where
emission densities tend to be non-
homogeneous from one cell to
another.
2. The model may be underestimating
the impacts of individual point
sources. While area source impacts
are averaged over a grid square in
the model, point source effects are
distant-dependent. A similar concept
of averaging point source impacts
over a given area may be more ap-
propriate and should be investigated.
3. The concept of directional-averaging
for the point source algorithms can
result in over- or underestimation of
impacts for individual MSA's where
major point sources are concentrated
within a given area of the MSA. This
suggests that site-specific wind
direction effects should be accounted
for.
4. The relationships found between
stack height, maximum ground-level
concentration and distance to the
maximum concentration in the
original COM studies using the M-P
coefficients are supported using the
Briggs dispersion coefficients (rural
values adjusted to account for in-
creased turbulence in urban areas).
However, the concept of collapsing
all stack heights to a single repre-
sentation needs to be examined
further. Results using the Briggs
values suggest that separate point
source algorithms should be derived
for shorter vs. taller stacks.
In spite of these areas of uncertainty
comparison of PAQMAN predictions witf
monitored data for several large urbar
areas revealed acceptable agreement
Predictions were within a factor of ±2 fo
over 90% of the total number of com
parisons; within a factor of ±1.5 for bette
than 70% of the comparisons.
In the context of aggregated effect;
across a large region involving thousand:
of individual sources, PAQMAN is a ven
suitable tool for estimating S02 distri
butions in urban areas. If the scope o
future materials damage assessment:
narrows to a detailed analysis of a singl<
or a few cities, a more sophisticate)
model would be more appropriate. How
ever, many of the automated procedure;
developed in PAQMAN would be usefu
in other models as well and should bi
considered.
TaWe 1. PAQMAN vs. Monitored Data Comparisons
PAQMAN
City MSA-Average*
Baltimore
Boston
Chicago
Cincinn ati
Cleveland
New York City
Philadelphia
Pittsburgh
Washington, DC
28.3
22.8
38.0
33.0
46.0
26.0
34.7
55.5
26.5
Me asured
MS A- Aver ag
24.3
25.8
24.4
31. 1
37.0
35.8
36.7
57.6
24.6
PAQMAN/ Me asured
e Mean
1.27
1.01
1.55
1.14
1.14
0.83
1.10
1.05
1.19
Median %±2
1.04
0.84
1.26
1.14
1.03
0.76
1.02
0.97
0.85
97
95
87
100
95
88
97
100
95
%±1.5
71
68
62
86
82
73
76
85
85
Slope of
Line ar
Regression*'
1.30
0.97
1.52
1.06
1.18
0.73
1.01
0.93
1.28
Average
34.5
32.9
1.17 1.03
95
76
1.11
* Average for grid squ ares with monitored d at a (background included).
** Regression forced through origin. PAQMAN value as dependent variable.
Average over entire data set.
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700
0 25 5 75 10 125 75 775 20 225 25 27 5 30 32.5 35 375 40 42.5 45 47.5 50
Measured S02
Figure 2 Comparison of PAQMAN vs measuredSOz- Cincinnati, OH f/jg/m3}.
L. R. Dupuis, F W Lipfert, and J, W. Peters are with Brookhaven National
Laboratory, Upton, NY 11973.
Francis S. Binkowski is the EPA Project Officer (see below)
The complete report, entitled "Further Studies of Parameterized Air Quality
Modeling Methods for Materials Damage Assessment," (Order No. PB 87-
145 280/AS. Cost: $13.95, subject to change) will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Atmospheric Sciences Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
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