EPA-450/3-77-003b
January 1977
IMPROVEMENTS
TO SINGLE-SOURCE MODEL
VOLUME 2:
TESTING AND EVALUATION
OF MODEL IMPROVEMENTS
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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EPA-450/3-77-003b
IMPROVEMENTS
TO SINGLE-SOURCE MODEL
VOLUME 2: TESTING AND EVALUATION
OF MODEL IMPROVEMENTS
by
Michael T. Mills and Roger W. Stern
GCA Corporation
GCA/Technology Division
Bedford, Massachusetts 01730
Contract No. 68-02-1376, Task Order 23
EPA Project Officer: Russell F. Lee
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
January 1977
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This report is issued by the Environmental Protection Agency to report
technical data of interest to a limited number of readers. Copies are
available free of charge to Federal employees, current contractors and
grantees, and nonprofit organizations - in limited quantities - from the
Library Services Office (MD-35) , Research Triangle Park, North Carolina
27711; or, for a fee, from the National Technical Information Service,
5285 Port Royal Road, Springfield, Virginia 22161.
This report was furnished to the Environmental Protection Agency by GCA
Corporation, GCA/Technology Division, Bedford, Massachusetts 01730, in
fulfillment of Contract No. 68-02-1376, Task Order 23. The contents of this
report are reproduced herein as received from GCA Corporation. The
opinions, findings, and conclusions expressed are those of the author
and not necessarily those of the Environmental Protection Agency. Mention
of company or product names is not to be considered as an endorsement
by the Environmental Protection Agency.
Publication No. EPA-450/3-77-003b
11
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CONTENTS
Page
List of Figures iv
List of Tables x
Acknowledgments xi
Sections
I Introduction 1
II Survey of Dispersion Calculation Methods 5
III Site and Data Base Descriptions for Model Improvement
Study 44
IV Model Validation Results 54
V Conclusions and Recommendations 89
VI References 91
Appendixes
A Turner Scheme for Stability Classification 93
B Listings of the Fractional Stability Preprocessor Pro-
gram and Corresponding Version of the Single Source
Model 97
C Concentration Profiles for the Canal and Muskingum
Plants for Different Sets of Dispersion Curves 116
iii
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LIST OF FIGURES
No. Page
1 Vertical Dispersion Coefficient as a Function of
Distance According to Gifford 7
2 Horizontal Dispersion Coefficient as a Function of
Distance According to Gifford 8
3 Vertical Dispersion Coefficient as a Function of
Downwind Distance From the Source as Currently Employed
in the Single Source Model 10
4 Determination of Hourly Mixing Heights 12
5 Wind Direction Trace Types Used to Determine Atmospheric
Stability by the Smith-Singer Method 17
6 Variation of ay With Distance for the Smith-Singer
Stability Classes 19
7 Variation of oz With Distance for Each of the Smith-Singer
Stability Classes 20
8 F.B. Smith Scheme for Assignment of Fractional Stability
Classes 24
2
9 Incoming Solar Radiation (mW/cm ) Measured at Cambridge,
England on a Cloudless Day 25
10 Solar Radiation Intensity as a Function of Zenith Angle 27
11 Variation With Distance of the Vertical Dispersion Param-
eter az (Normalized With Respect to the Neutral Stability
Value) for Different Values of P 29
12 Variation cf oz With Distance for Stability D 30
13 Contours of the Vertical Dispersion Coefficient Correction
Factor F(zQ,x) 32
IV
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LIST OF FIGURES (continued)
No.
14a Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class A According to Briggs,
F.B. Smith and Pasquill-Turner 34
14b Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class B According to Briggs,
F.B. Smith and Pasquill-Turner 34
14c Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class C According to Briggs,
F.B. Smith and Pasquill-Turner 35
14d Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class D According to Briggs,
F.B. Smith and Pasquill-Turner 35
14e Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class E According to Briggs,
F.B. Smith and Pasquill-Turner 36
14f Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class F According to Briggs,
F.B. Smith and Pasquill-Turner 36
15a Horizontal Dispersion Coefficient as a Function of Downwind
Distance for Stability Class A According to Briggs and
Pasquill-Turner 37
15b Horizontal Dispersion Coefficient as a Function of Downwind
Distance for Stability Class B According to Briggs and
Pasquill-Turner 37
15c Horizontal Dispersion Coefficient as a Function of Downwind
Distance for Stability Class C According to Briggs and
Pasquill-Turner 38
15d Horizontal Dispersion Coefficient as a Function of Downwind
Distance for Stability Class D According to Briggs and
Pasquill-Turner 38
15e Horizontal Dispersion Coefficient as a Function of Downwind
Distance for Stability Class E According to Briggs and
Pasquill-Turner 39
15f Horizontal Dispersion Coefficient as a Function of Downwind
Distance for Stability Class F According to Briggs and
Pasquill-Turner 39
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LIST OF FIGURES (continued)
No. Page
16a Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class A and Surface Roughnesses of
10 cm and 100 cm According to F. B. Smith 40
16b Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class B and Surface Roughnesses of
10 cm and 100 cm According to F. B. Smith 40
16c Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class C and Surface Roughnesses of
10 cm and 100 cm According to F. B. Smith 41
16d Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class D and Surface Roughnesses of
10 cm and 100 cm According to F. B. Smith 41
16e Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class E and Surface Roughnesses of
10 cm and 100 cm According to F. B. Smith 42
16f Vertical Dispersion Coefficient as a Function of Downwind
Distance for Stability Class F and Surface Roughnesses of
10 cm and 100 cm According to F. B. Smith 42
17 Map of Eastern Massachusetts and Rhode Island Showing
Locations of the Canal Plant 45
18 Sketch of the Canal Plant Area Showing the Locations of
the Four Automatic S02 Stations by the Symbol 48
19 Sketch of the Muskingum Plant Area Showing Locations of
Four Automatic SO,, Monitoring Stations 51
20a Model Validation Run No. 1 61
20b Model Validation Run No. 1 61
20c Model Validation Run No. 2 62
20d Model Validation Run No. 1 62
20e Model Validation Run No. 1 63
21a Model Validation Run No. 2 63
21b Model Validation Run No. 2 64
vi
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LIST OF FIGURES (continued)
No. Page
21c Model Validation Run No. 2 64
21d Model Validation Run No. 2 65
21e Model Validation Run No. 2 65
22a Model Validation Run No. 3 66
22b Model Validation Run No. 3 66
22c Model Validation Run No. 3 67
22d Model Validation Run No. 3 67
22e Model Validation Run No. 3 68
23a Model Validation Run No. 4 68
23b Model Validation Run No. 4 69
23c Model Validation Run No. 4 69
23d Model Validation Run No. 4 70
23e Model Validation Run No. 4 70
24a Model Validation Run No. 5 71
24b Model Validation Run No. 5 71
24c Model Validation Run No. 5 72
24d Model Validation Run No. 5 72
24e Model Validation Run No. 5 73
25a Model Validation Run No. 6 73
25b Model Validation Run No. 6 74
25c Model Validation Run No. 6 74
25d Model Validation Run No. 6 75
25e Model Validation Run No. 6 75
vii
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LIST OF FIGURES (continued)
No. Page
26a Model Validation Run No. 7 76
26b Model Validation Run No. 7 76
26c Model Validation Run No. 7 77
26d Model Validation Run No. 7 77
26e Model Validation Run No. 7 78
27a Model Validation Run No. 8 78
27b Model Validation Run No. 8 79
27c Model Validation Run No. 8 79
27d Model Validation Run No. 8 80
27e Model Validation Run No. 8 80
28a Model Validation Run No. 9 81
28b Model Validation Run No. 9 81
28c Model Validation Run No. 9 82
28d Model Validation Run No. 9 82
28e Model Validation Run No. 9 83
29a Model Validation Run No. 10 83
29b Model Validation Run No. 10 84
29c Model Validation Run No. 10 84
29d Model Validation Run No. 10 85
29e Model Validation Run No. 10 85
30a Model Validation Run No. 11 86
30b Model Validation Run No. 11 86
30c Model Validation Run No. 11 '87
viii
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LIST OF FIGURES (continued)
No. Page
30d Model Validation Run No. 11 87
30e Model Validation Run No. 11 88
IX
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LIST OF TABLES
No. Page
9
1 Meteorological Categories According to Pasquill and 9
Meade10
2 Wind Profile Exponents (a) for Different Stabilities 13
3 Smith-Singer Power Law Parameters a,b for Horizontal 18
and Vertical Dispersion Parameters a = ax° Where
x is in Meters^ ^*
4 Variation of 0y and az with Distance x (Meters) for 22
Rural Areas
5 Multiplication Factors for Incoming Solar Radiation 23
Intensity for Different Amounts of Cloud Cover
6 Fit Parameters for Dispersion Coefficients 28
7 Coefficients of the Roughness Correction Factor Used 31
in Calculating oz(x) for Various Roughness Lengths
(x is given in Meters)
8 Plant Characteristics 46
9 Monthly Percent Sulfur Content of Fuel 47
10 Sulfur Dioxide Monitoring Stations for the Canal and 49
Muskingum Plants
11 Description of Model Validation Runs and Results 58
12 Comparison of Pasquill-Turner (P-T) and F. B. Smith 60
(F.B.S.) Stability Assignments for Three Days of
Huntington, W. Va. 1973 Surface Meteorological Data
x
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ACKNOWLEDGMENTS
The key data used in carrying out this study were made available to
GCA/Technology Division by the New England Gas and Electric System and
the Ohio Power Company. Project direction and guidance were given by
Mr. Russell Lee of the Source-Receptor Analysis Branch, Monitoring and
Data Analysis Division, EPA, Durham, North Carolina, who served as
project officer.
xi
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SECTION I
INTRODUCTION
The purpose of this study is to test a number of suggested improvements
to the EPA Single Source Model (CRSTER). In particular three alternate
methods for the parameterization of vertical and horizontal dispersion
coefficients with distance will be evaluated along with two additional
stability class selection algorithms. The predictions of each modified
version of the Single Source Model will be compared with actual con-
centration measurements so that these potential model improvements can
be evaluated. Another objective of this study was to determine whether
the use of a variable buoyancy flux in the plume rise equation in the
model would yield better predictions.
1 2
During two previous EPA sponsored projects ' GCA carried out validation
studies for the Single Source 24-Hour Model at four separate power plant
sites. Model predictions of 1-hour and 24-hour S0» concentration fre-
quency distributions were carried out based upon emission parameters and
hourly meteorological data and compared with the corresponding frequency
distributions of S0_ concentration measurements corrected for background
contributions.
In the first validation exercise, which was performed for the Canal
Power Plant in southeastern Massachusetts, concentration predictions
were made for a variety of emissions and meteorological data bases rang-
ing in degree of resolution from monthly average emission rates taken
from FPC Form-67 and hourly meteorological data from the nearest weather
station to actual hourly emissions and on-site wind speed and direction
1
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data in conjunction with hourly stabilities and mixing heights extracted
from the weather station observations. Regardless of the choice of input
data sets the model was found to underpredict both 1-hour and 24-hour S0«
concentrations. With the exception of one receptor location, the ratios
of measured minus background to predict second highest yearly S09 con-
centrations fell between 1.0 and 2.0. The corresponding ratios for the
24-hour concentrations, again neglecting one receptor location, ranged
from 1.2 to 6.4 with an arithmetic mean of 3.2.
To determine whether the underprediction found for the Canal Plant was due
to the coastal location of the plant site or some weakness in the model
itself, three power plant sites were chosen in Ohio for additional tests
of the model. Source characteristics and emission rates for the J. M.
Stuart, Muskingum and Philo power plants were used in conjunction with sur-
face and upper air meteorological data from nearby weather stations to
generate model estimates of S09 concentrations for the 1-hour and 24-hour
averaging times employed in the Canal plant study. With the exception of
the Philo plant the predicted 1-hour S0? concentrations were in much better
agreement with measurements than for the Canal plant study. The average
ratio of second highest measured to predicted 1-hour S02 concentrations
was 1.02 and 1.10 for the Stuart and Muskingum plants respectively. One-
hour S02 concentrations for the Philo plant were overpredicted by a factor
of 2, a circumstance due in large part to the inadequacy of the Single
Source Model to handle the dispersion effects associated with complex ter-
rain, particularly for those receptor locations with elevations comparable
to that of the stack top. The predicted second highest 24-hour S07 con-
centrations for the J. M. Stuart and Muskingum plants were in better agree-
ment with the measured values than in the case of the Canal plant with the
measured to predicted ratios of 1.5 and 2.0 for the J. M. Stuart and
Muskingum plants respectively.
Based upon these model validation studies two problems areas could be iden-
tified. The first concerned the underprediction of second highest 24-hour
concentrations at three of the four plants studied. To a large degree
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this tendency to underpredict 24-hour concentrations may be traced to the
method by which 24-hour predictions are obtained from 1-hour concentration
calculations. For the calculation of 1-hour concentrations the Single
Source Model requires that the wind flow vector remain constant for the
entire hour so that no mechanism exists for a smooth transition from one
hourly flow direction to the next. While this assumption does not seri-
ously affect the quality of the peak 1-hour concentration predictions, the
resulting deficiency in low and intermediate concentrations (i.e., large
number of zero concentration predictions) may lead to an underestimate in
the associated 24-hour concentrations. An alternate method for the esti-
mation of peak 24-hour concentrations is through the application of peak
to mean ratio distribution statistics. In each of the model validation
studies distributions of peak 1-hour to average 24-hour S02 concentration
ratios were constructed from actual hourly SQ~ concentration measurements
corrected for background. For the four plants studied the geometric means
of these distributions ranged from 7.3 to 7.9 and the standard geometric
deviations from 1.5 to 1.7- If the second highest predicted 1-hour S02
concentration were found to be accurate, then an estimated second highest
24-hour S02 concentration obtained by dividing the 1-hour value by the
geometric mean of the 1-hour to 24-hour peak to mean ratio should be accu-
rate to at least a factor of 2. Volume I of this study was devoted to a
further examination of these ratio distributions to determine their sensi-
tivity to the use of successively higher threshold values of peak 1-hour
S09 concentrations.
The second area of concern dealt with the theoretical bases for the model
predictions, namely, the plume rise formulation, stability class selection
procedure and the choice of parameters for the calculation of vertical and
horizontal plume dispersion coefficients. The basic question was whether
the use of alternate techniques would improve the agreement between pre-
dicted and measured 1-hour SCL concentrations, particularly at the Canal
3,4,5
plant. The Briggs ' ' plume rise estimates currently incorporated in
the Single Source Model represent the best fit to currently existing data.
For the Canal plant study, a modification was made to the plume rise
-------
computation in the model to include the effect of stack downwash but this
modification did not improve the quality of the predictions to a signifi-
cant degree. On the other hand, there are a number of techniques differ-
ent from the Pasquill-Turner method which is currently in use for the
classification of stabilities and the calculation of dispersion coeffi-
cients. In Section II we shall describe some of these techniques and
describe the manner in which they were included in the Single Source
Model. Section III will deal with the source and meteorological input
data bases to be used in the test of potential model improvements. In
Secion IV we shall present the model validation results for the alternate
dispersion calculation techniques and draw a conclusion as to the adequacy
of the existing model formulation. Also, in Section IV we shall investi-
gate the utility of incorporating a variable volume flux in the Single
Source Model.
4
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SECTION II
SURVEY OF DISPERSION CALCULATION METHODS
DESCRIPTION OF THE EXISTING MODEL
We shall begin our discussion of dispersion calculation methods with a
description of the EPA Single Source Model as it currently exists. The
program, which was developed by the EPA Meteorology and Assessment Division,
calculates hourly and daily concentrations for an array of receptor loca-
tions and maximum hourly and daily pollutant concentrations for a year along
with the meteorological conditions which can lead to these maxima. These
concentrations are written on magnetic tape for the 252 receptor positions
situated at each of 36 directions from the source and seven different
distance ranges. The normal version of the model has five distances and
180 receptors. The seven distances and 252 receptors occur only in the
special GCA adaptation. The model can handle from 1 to 19 sources but
treats all of them as if they were at the same physical location. The
expression used for evaluation of 1-hour pollutant concentrations downwind
of a point source is the Gaussian plume equation ' given by
Q exp
X(x,y,z)=
27r a (x) a (x) u
y z
exp
expl-
(1)
where x = distance along plume axis (m)
y = horizontal distance from plume axis (m)
z = distance above surface (m)
o
X(x,y,z) = concentration of pollutant (g/m )
Q = effective emission rate of pollutant distance x
(g/sec)
-------
a (x), a (x) = horizontal and vertical dispersion coefficients for
y a particular atmospheric stability (A,B,C,D,E,F) and
distance x
u = wind speed at source height (m/sec)
h(x) = effective emission height at distance x (m)
The variation of a and p with distance was first parameterized by
6 Z
Gifford as shown in Figures 1 and 2. These curves represent a
fit to a number of concentration field measurements including those made
Q
during the Prairie Grass study conducted during the summer of 1956.
Although these plume dispersion estimates were based largely upon ground
level releases they are also generally applied to elevated point
sources. Criteria for selection of a particular stability class were
9 10
first suggested by Pasquill and Meade and are listed in Table 1.
The measurements upon which these curves were based were taken within
1 km of the source, the shape of the
-------
z
UJ
u.
Ul
o
u
V)
DC
UJ
Q.
V)
QL
Ul
=EXTREMELY UNSTABLE
=MODERATELY UNSTABLE
= SLIGHTLY UNSTABLE
=NEUTRAL
= SLIGHTLY STABLE
-MODERATELY STABLE
5 |0° 2 5 |o" 2
DISTANCE FROM SOURCE,km
Figure 1. Vertical dispersion coefficient as a function of distance
according to Gifford^
-------
Ul
o
Ul
o
u
tO
IE
Ul
Q.
CO
O
N
o:
o
X
A = EXTREMELY UNSTABLE
B= MODERATELY UNSTABLE
C= SLIGHTLY UNSTABLE
D = NEUTRAL
E = SLIGHTLY STABLE
F = MODERATELY STABLE
10
10° 2 5 10' 2
DISTANCE FROM SOURCE, km
10
Figure 2. Horizontal dispersion coefficient as a function of distance
according to Gifford"
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Table 1. METEOROLOGICAL CATEGORIES ACCORDING TO
PASQUILL9 AND MEADE10
Surface wind
speed ,
m/sec
A
B
C
D
< 2
2
4
6
>6
Daytime insolation
Strong
A
A-B
B
C
C
Moderate
A-B
B
B-C
C-D
D
Slight
B
C
C
D
D
Thin overcast
or > 4/8 cloudi-
ness
E
D
D
D
> 3/8 cloudi-
ness
F
E
D
D
- Extremely unstable conditions
- Moderately unstable conditions
- Slightly unstable conditions
- Neutral conditions (Applicable to heavy overcast,
day or night)
E - Slightly stable conditions
F - Moderately stable conditions
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1,500
O.t
I 10
DISTANCE DOWNWIND , km
Figure 3. Vertical dispersion coefficient as a function of down-
wind distance from the source as currently employed in
the Single Source Model'
10
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vector (wind direction plus 180 ), and randomized flow vector. The
randomized flow vector is equal to the flow vector minus 4 degrees plus
a random number between 0 and 9 degrees. The preprocessor output tape
is then read by the Single Source Model which performs the actual concen-
tration calculations. The twice daily mixing height data can be obtained
from the National Climatic, Asheville, North Carolina. Missing data were
filled in through interpolation.
Two different sets of hourly mixing heights are calculated by the pre-
processor. One is for rural surroundings; the other is for urban loca-
tions. The way in which hourly mixing heights are determined from
maximum mixing heights (MXDP) for yesterday (i-1), today (i) and
tomorrow (i + 1) and minimum mixing heights (MNDP) for today (i) and
tomorrow (i + 1) is depicted in Figure 4. For urban mixing height
between midnight and sunrise the following procedure is used: if the
stability is neutral interpolate between MXDP. and MXDP. (T), if
!•• J. i ^^
stability is stable use MNDP. (2). For hours between sunrise and 1400,
if the hour before sunrise was neutral, interpolate between MXDP. - and
MXDP. (3). For sunrise to 1400, if the hour before sunrise was stable,
•1-
interpolate between MNDP. and MXDP. (4). For 1400 to sunset, use
i i ^~^
MXDP. (5). For hours between sunset and midnight, if stability is
.L
neutral interpolate between MXDP. and MXDP. - (?), if stability is
1 J. "t" i. _t*1^
stable interpolate between MXDP. and MNDP. (7).
For rural mixing height between midnight and sunrise, interpolate between
MXDP..- and MXDP. (s). For hours between sunrise and 1400, if the hour
before sunrise was neutral interpolate between MXDP. and MXDP . (?).
For sunrise to 1400, if the hour before sunrise was stable, interpolate
between 0 and MXDP. (iCJ) . For 1400 to sunset, use MXDP. (Jl) . For sun-
1 x--x !._ '
set to midnight, interpolate between MXDP. and MXDP.
Wind sppeds u measured at instrument height h (7 meters is common for
o o
weather stations) are adjusted by means of a stability dependent power
11
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YESTERDAY
TODAY
TOMORROW
URBAN
MXDPj-|
0
X
(£
UJ
X
MXDPj
©
MNOPj
MNDPj+i
1 1
RURAL
MXDPj-i
X
o
UJ
X
SR 14
MXDP
SR 14 SS
TIME
Figure 4. Determination of hourly mixing heights
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law (u = u (h/h
to correspond to values one would expect at the ac-
tual stack height h. The variation of the exponent a with stability is
shown in Table 2. Plume rise is calculated on an hourly basis using
3-5
the method of Briggs. The effective stack height h(x) will be greater
than the actual stack height h due to the buoyancy of the plume. The
s
expression for h(x) for stabilities A through D is given by
where Ah =
1.6F1/3 u-1 x
h(x)
2/3
h + Ah
s
(2)
for x < 3o5x
Ah = 1.6F1/3 u"1 (3.5x*)2/3 for x > 3.5x*
* 5/8 4. 3
x = 14F ' when F < 55 m/sec
* 2/5 U 3
x = 34F ' when F _> 55 m /sec
F = gwr
(T - T \
M
g = gravitational acceleration (m/sec )
w = stack gas exit velocity (m/sec)
Ts = stack gas temperature (°K)
T = ambient temperature (°K)
Table 2. WIND PROFILE EXPONENTS (a) FOR
DIFFERENT STABILITIES
Stability class
A
B
C
D
E
F
a
0.1
0.15
0.2
0.25
0.3
0.3
13
-------
For stability classes E and F the plume rise becomes
,1/3
Ah = 2.9lM (3)
• -fe)
g_ de
Q =s a — —
s T dz
e
6 = potential temperature ( K)
— = 0.02 °K/m for stability E
dz
t\fi
f = 0.035 °K/m for stability F
If the plume rise calculation indicates that the plume axis will rise
above the mixing layer, then a zero concentration contribution is specified,
If the final height plume is below the top of the mixing layer, the
presence of the mixing boundary is accounted for in the Single Source
Model by the incorporation of multiple image sources as was done to
satisfy the zero flux condition at ground level. With this assumption
Equation (1) is generalized to give
14
-------
Q exp
X(x,y,z)
(2ay2(x))
ay(x) az(x)
+ exp I-
(z + h(x))2
2 a/Cx)
n
£
exp
3 =
I_ (z - h(x) - 2JLV
2 a/Cx)
exp I-
exp I-
+ exp I-
2 o
(z + h(x) + 2jL)
2 a 2(x)
z
2 a/(x)
(4)
where L = depth of the mixing layer (m)
n = number of images considered
In practice only the first few image terms contribute significantly to
the overall ambient concentration. For distances greater than 2 x , where
x is given by a (x ) = 1.6, Equation (5) was approximated by
Q exp
X(x,y,z) =
2 o^(x)
/27T a (x) u L
y
x > 2 x7
(5)
15
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Source input to the Single Source Model may possess several degrees of
temporal resolution. In the seasonal version of the model an annual
average S02 source strength is specified along with monthly variation
factors. In addition to the seasonal factors, the diurnal version of the
model employs hourly emission variation factors for each month of the
year. A modification made to the model used in our validation studies
allowed actual hourly source strengths to be utilized. A second modifica-
tion made to the model allowed actual receptor elevations to be accounted
for. In Section IV of this report we shall present the results of a val-
idation of a version of the Single Source Model which allows the stack
exit velocity to vary with the fuel consumption rate.
DESCRIPTIONS OF OTHER DISPERSION COEFFICIENTS TO BE TESTED
The stability selection algorithm and the dispersion calculation technique
currently used within the Single Source Model will henceforth be referred
to as the Pasquill-Turner method. During the next three parts of this
section we shall discuss three other methods: (1) Smith-Singer, (2) Gifford
Briggs and (3) F. B. Smith and the manner in which they were included in
modified versions of the Single Source Model.
SMITH SINGER DISPERSION COEFFICIENTS
The Smith-Singer method for determining the horizontal and vertical disper-
sion coefficients is based upon a series of atmospheric diffusion experi-
ments conducted over a period of 15 years at the Brookhaven National Lab-
oratory. These included oil fog studies for an elevated source, monitoring
41
of reactor emissions by A and low level uranine dye releases. The choice
of a particular stability assignment (A, B2, Bl, C or D) for a given hour
is related to a subjective estimate of the lateral turbulence intensity
determined from analogue wind direction recordings (Figure 5). A more
quantitative explanation of the classification scheme shown in Figure 5 is
presented below:
16
-------
TYPE A
TYPE B
Figure 5. Wind direction trace types used to determine
atmospheric stability by the Smith-Singer
method1^
17
-------
A = fluctuations of the wind direction exceeding 90 ;
B2 = fluctuations ranging from 40 to 90 ;
Bl = similar to A and B2, with fluctuations confined to 15
and 45° limits;
C = distinguished by the unbroken solid core of the trace,
through which a straight line can be drawn for the
entire hour, without touching "open space"; and
D = the trace approximates a line - short-term fluctuations
do not exceed 15 .
Power law expressions describing the variation of a and a with distance
12 y z
from the source are specified in Table 3 for four of the five "gustiness
classes" (B2, Bl, C, and D).
Table 3. SMITH-SINGER POWER LAW PARAMETERS a,b FOR HORI-
ZONTAL AND VERTICAL DISPERSION PARAMETERS
a = axb WHERE x IS IN METERS13
Stability class
B2
a
0.40
0.41
b
0.91
0.91
Bl
a
0.36
0.33
b
0.86
0.86
C
a
0.32
0.22
b
0.78
0.78
D
a
0.31
0.06
b
0,71
0.71
y
The dispersion curves described by these parameters are shown in Figures
6 and 7.
18
-------
vo
STPBILITY CLPSS=&2,
STPBILITY CLPSS=fcl
STPBILITY CLPSS=3
STPBILITY CLPSS=4
3 U S 6 7
Z 3 4 S 6 7 8 9 "l tf
DOWNWIND DISTANCE (KM)
3 4
7TT\tf
Figure 6. Variation of o with distance for the Smith-Singer stability classes
-------
STRBILITY
STP31L1TY
STPB1UTY
STPBIUTY
CLPSS=B2
CLPSS=C
ClflSS=D
"o
N5
O
T T^ T T T-
DOWNWINO OISTPNCE (KM)
T
S 6 7 8
Figure 7. Variation of a with distance for each of the Smith-Singer stability classes
-------
No dispersion, parameters are given for stability A since this condition
is characterized by no organized horizontal wind flow so that the resul-
tant ground level concentrations may only be described in a qualitative
manner. Stability A cases were therefore not included in our validation
studies to be described later in this report. As in the case of the
Pasquill-Turner scheme the wind speed is assumed to increase with height
according to a power law with the exponent a assigned the values 0.16,
0.25, 0.32, and 0.50 for atmospheric stabilities B2 through D.13
In the application of these dispersion curves to the prediction of con-
centrations downwind of large elevated point sources M.E. Smith calcu-
lates the effective stack height by use of the following formula presented
in the ASME Guide Second Edition, 1973:
'F1/3 h 2/3\ (6)
h + 7.4 I —
s 1 u
Since we were primarily interested in the comparison of different dis-
persion calculation methods we continued to employ the Briggs formulae,
with Equation (2) used for stabilities B2, Bl and C and Equation (3)
used for stability D. For power plant diffusion modeling Smith mod-
ifies his estimate of a by 'adding a term to allow for the presence
of directional wind shear:
b
cr = ax + x tan 4> (7)
where <(> = wind direction change
Since no rule is given for the selection of <|> as a function of stability
or plume height, the term was not included in our analysis. Had the term
been included, it would have effectively lowered the predictions of
ground level air-concentrations especially for the more stable conditions
21
-------
GIFFORD-BRIGGS DISPERSION COEFFICIENTS
A method for the determination of plume standard deviations has recently
been developed by Briggs1" using a wide range of experimental data includ-
ing the TVA and Prairie Grass measurements mentioned earlier. The selec-
tion of an appropriate stability class is called out according to the
Pas quill-Turner method but the corresponding curves for a and o* are
y z
chosen to represent a wider range of source elevations and source-receptor
distances. Analytical expressions for
-------
roughness and provide for the fractional assignment of stability classes.
This latter development was especially significant since the variation of
ground level air concentration with stability class can be an order of
magnitude or more.
The scheme utilizes numerical solutions of the diffusion equation up to
100 km downwind with profiles of wind, u(z), and diffusivity, (K(z) , sug-
gested by actual measurements in unstable, neutral and stable conditions.
The horizontal dispersion coefficients are chosen to be the same as the
Pasquill-Turner. The reason for this is that F. B- Smith does not recom-
mend any specific a curve, but rather advises the use of wind fluctuation
data, with an adjustment for downwind distance. At larger distances, this
1/2
adjustment makes cr Ct x where x is downwind distance. Since the required
wind fluctuation data are not available, the Pasquill-Turner a data were
used. It should be pointed out, however, that the Pasquill-Turner curves
0.9
show a to be approximately proportional to x at all distances, and not
1/2 ^
x . The method for fractional stability assignment is illustrated in
Figure 8. F-B. Smith presented Figure 9 as a guide for choosing a value
for incoming solar radiation as a function of solar elevation angle. He
recommends that this value be multiplied by an appropriate factor to
account for the presence of cloud cover (see Table 5).
Table 5. MULTIPLICATION FACTORS FOR INCOMING
SOLAR RADIATION INTENSITY FOR DIF-
FERENT AMOUNTS OF CLOUD COVER
Cloud amount (eights)
0
1
2
3
4
5
6
7
8
Multiplier
1.07
0.89
0.81
0.76
0.72
0.67
0.59
0.45
0.23
23
-------
•Strong-
J — i
INCOMING SOLAR RADIATION mw/cm2
60 50 «0 30
20
-Moderate
WIND SPEED (of 10m.)
m/sec
•-Slight-
STABILITY P
P
f CLOUD AMOUNT
I0765*3210 (in eighths)
rrrv?»rj
0 /
•-' ' WIND
SPEED {Ot I0m.)
m/jec
4-]
3-1
2-
UNSTABLE
1-
t i t_
J L
UPWARD HEAT FLUX. H mw/cm2
I' t iii
ROUGHNESS
LENGTH =
stability
category
6 STABLE
: Normal mox.lHl
'...» '
2« 27 H 25 24 23 22 21 20 19 18 17 16 IS U 13 12 II 10 9 8 7 6 5 '4 3 2 I 0 -1 -2 -3 -4 -5 -6 -7 -8
Figure 8. F.B. Smith scheme for assignment of fractional stability classes
17
-------
5 6 7 8 9 10 II 12 13 14 15 16 17 18 19 20
DEC.
- NOV.
-I SOT
/ 7W OF DAY (GMT)
JAN.
Figure 9. Incoming solar radiation (mW/cm ) measured at
Cambridge, England on a cloudless
25
-------
To obtain a relationship between solar angle and incident solar radia-
tion, we sought to describe the data presented in Figure 9 for Cam-
no
bridge, England in terms of the following equation:
I - | asec9 cos 9 (8)
where I = solar radiation intensity
J =135.3 milliwatts/cm2
o
a = transmission factor
9 = solar zenith angle (90° - solar elevation angle)
r = "radius vector" of earths orbit (« 1)
For a specific latitude and longitude the angle 9 may be determined
based upon the time zone classification, hour of the day (standard time)
and day of the year. When the data were analyzed it was found that the
diurnal and seasonal variation of the radiation intensity, I, could not
be reproduced by use of a constant transmission factor a_. The best fit
was obtained for the following variation of the transmission factor, a,
with zenith angle 6.
a = 0.57 + 0.0045 9 (9)
where 9 is measured in degrees. The fitted solar radiation intensity
as a function of zenith angle is shown in Figure 10.
With the relationships given by Equations (8) and (9) the fractional sta-
bility index, P, may be determined from the curves shown in Figure 8
once the windspeed and cloud cover have been specified. In his article
F. B. Smith identifies a P value of 3.6 with a D stability index (i.e.,
stability 4) which would have been determined according to the Turner
scheme presented in Appendix A. The relationship between the fractional
stability P and the Turner stability S should then be given by
S = (P + 0.4) rounded (10)
26
-------
10
20
30 40 50
ZENITH ANGLE, dtgrett
60
70
80
90
Figure 10.
Solar radiation intensity as a function of zenith angle.
Relationship based upon data presented in Figure 9
27
-------
To determine the validity of this assumption we carried out a polynomial
fit to the curves given in Figure 8 so that, based upon the solar ele-
vation angle, cloud cover and wind speed, a comparison between the
F. B. Smith and Turner assignment schemes could be made for a wide range
of meteorological configurations. Based upon this comparison we found
that the Turner stability class assignment was higher during the middle
part of the day, especially during the summer months when the difference
could be greater than an entire stability class. The polynomial fits
used for this comparison formed the basis of the fractional stability of
the Single Source Model Preprocessor Program which is presented in
Appendix B.
Once the stability parameter P has been selected the corresponding ver-
tical dispersion coefficient a is determined for a particular downwind
z
distance x by use of the curves presented in Figures 11 and 12. These
19
results have been fitted by R. P. Hosker to analytical expressions
of the form
oz(x) =
alx
(ID
x
A list of the numerical values of the parameters used in Equation (11) is
given in Table 6.
Table 6. FIT PARAMETERS FOR DISPERSION COEFFICIENTS
Stability
A (P =
B (P =
C (P =
D (P =
E (P =
F (P =
category
0.6)
1.6)
2.6)
3.6)
4.6)
5.6)
al
0.112
0.130
0.112
0.098
0.0609
0.0638
»i
1.06
0.950
0.920
0.889
0.895
0.783
a2
5.38 x 10~4
6.52 x 10~4
9.05 x 10"4
1.35 x 10~3
1.96 x 10~3
1.36 x 10~3
b2
0.815
0.750
0.718
0.688
0.684
0.672
28
-------
or
LJ
»-
UJ
1 4
m
or
__I I I I I
CONTOURS OF RATIO OF «rz ( x; P)/
-------
1000
4OO
NEUTRAL STABILITY:p = 3.6
ROUGHNESS LENGTH: Z0 =10 cm
100
40
10
I
100 m
400 I km 4 10 km 4O
X, DISTANCE DOWNWIND FROM SOURCE
100 km
Figure 12. Variation of az with distance for
stability D (P = 3.6)17
30
-------
According to the F.B. Smith method the dispersion curves may be modified
to account for the effect of surface roughness z0. These correction fac-
tors are shown in Figure 13. As parameterized by Hosker, this cor-
rection factor F(zQ, x) takes the following forms:
F(ZQ,X) = An < c,x
= Jin < c,x
1 +
(,'f
1 +
C0X
-1
, z > 10 cm
, z < 10 cm
o
(12)
(13)
The corrected dispersion coefficient a (z , x) may be written as
a (z ,x) = F(z ,x) a(10 cm, x)
z o o
(14)
where the a(10 cm, x) are the a values given by the curves in Figures
Z
11 and 12. The parameters required to evaluate Equations (12a) and
(12b) are presented in Table 7.
Table 7. COEFFICIENTS OF THE ROUGHNESS CORRECTION FACTOR USED IN
CALCULATING az(x) FOR VARIOUS ROUGHNESS LENGTHS (x IS
GIVEN IN METERS)
Roughness length
1 cm
4 cm
40 cm
100 cm
400 cm
cl
1.56
2.02
5.16
7.37
11.7
dl
0.0480
0.0269
-0.098
-0.0957
-0.128
C2
6.25 x 10 ~4
7.76 x 10~4
18.6
4.29 x 103
4.59 x 104
d2
0.45
.0.37
-0.225
-0.60
-0.78
In Section IV of this report we will describe three types of model vali-
dation studies based upon the F.B. Smith dispersion coefficients. The
first test will combine the Turner stability class assignment scheme with
the F.B. Smith dispersion curves for the point stabilities (A, B, C, D, E
and F). The second test will involve the calculation and use of fractional
31
-------
I Om
1.8
Im
10 cm
I cm
Inrm
0.5
1.0
i
lOOm 400 I km 4 10km
X, DISTANCE FROM SOURCE
CITIES
FORESTS
LOW
MOUNTAINS
PLAINS
(mixed rural)
STEPPES
NORMAL SEA
40
1 00 km
Figure 13. Contours of the vertical dispersion coefficient
correction factor F(z ,x)
32
-------
stabilities. Finally the effect of incorporating surface roughness will
be investigated.
COMPARISON OF THE DISPERSION COEFFICIENTS
A comparison of the dispersion curves we have just discussed will prove
useful in our analysis of the model validation results which will be
presented in Section IV. In Figures 14(a) through (f), vertical disper-
sion coefficients according to Briggs, F.B. Smith, and Pasquill-Turner
are plotted as a function of downwind distance for stabilities A through F.
The following observations may be made based upon an examination of these
curves:
1. The Briggs and Pasquill-Turner curves are quite
close to one another except in the case of
stability A.
2. The F.B. Smith vertical dispersion curve falls
below the other two curves for stabilities A, B
and C and above the other curves for stabilities
D, E and F.
3. The worst agreement between all three of the curves
is seen for stability A with the best agreement for
stabilities D, E and F.
In Figures 15(a) through (f) we have plotted the horizontal dispersion
curves according to Briggs and Pasquill-Turner by stability class. The
Pasquill-Turner horizontal dispersion curves are used in conjunction with
the F.B. Smith vertical dispersion curves, so that no F.B. Smith horizontal
curves have been presented. An obvious feature of these plots is that the
Briggs and Pasquill curves are virtually identical. The horizontal and
vertical dispersion curves according to Smith-Singer were presented in
Figures 6 and 7 for the four Smith-Singer stability classes B2, Bl, C and
D. The most striking feature of these plots is the identical slope for
oz and ay curves for the same stability. Finally the effect of surface
roughness upon the F. B. Smith vertical dispersion curves is illustrated
in Figures 16(a) through (f).
33
-------
i « i i 7 ii1
DOHNHINO OISTfMCE CKHI
Figure 14a. Vertical dispersion coefficient as a function of down-
wind distance for Stability Class A according to
Briggs, F-B. Smith and Pasquill-Turner
1 — r~rTTTTTto
1 — i ; i M
DOUNUINO DISTANCE (KH)
Figure 14b.
Vertical dispersion coefficient as a function of down-
wind distance for Stability Class B according to
Briggs, F.B. Smith and Pasquill-Turner
34
-------
t i « i t t i i
-------
t i t i i
i «**» »*ltf
OOUMttlNO 01STRHCE IKH)
MflP
Figure 14e. Vertical dispersion coefficient as a function of down-
wind distance for Stability Class E accordings to
Briggs, F.B. Smith and Pasquill-Turner
MCf
DOMMUIMO DISTANCE CKW
Figure 14f
Vertical dispersion coefficient as a function of down-
wind distance for Stability Class F according to
Briggs, F.B. Smith and Pasquill-Turner
36
-------
Iff* *
* i *^ I t i i itf
OOUNM1MO DISTANCE WK>
*i TtTTTTitf
Figure 15a. Horizontal dispersion coefficient as a function of
downwind distance for Stability Class A according
to Briggs and Pasquill-Turner
Iff' t * * t *
i i « i t * i i
OOHNUIHO DISTANCE (KH1
i 1 « t i *
Figure 15b.
Horizontal dispersion coefficient as a function of
downwind distance for Stability Class B according to
Briggs and Pasquill-Turner
37
-------
* i i *.» * i \tf I T * i * t *T
DOHMUNO DISTANCE UWl
i i TrTTiT\(f
Figure 15c. Horizontal dispersion coefficient as a function of
downwind distance for Stability Class C according
to Briggs and Pasquill-Turner
<£
o
APfl50UlLL
i » is *TT*iff
DOHNUINO OtSTflNCE (KH)
» f * ) i i
Figure 15d
Horizontal dispersion coefficient as a function of down-
wind distance for Stability Class D according to Briggs
and Pasquill-Turner
38
-------
J — i i i t
DOtOiMINO OISTflNCE (KHl
1 — rnrTTTTT\cf
Figure 15e. Horizontal dispersion coefficient as a function of
downwind distance for Stability Class E according to
Briggs and Pasquill-Turner
rfRIGGS
1 1 i i ft t ft 4 ttf i r~TTTTTT\tf
OOKHMINO 01 STANCE (KHl
1 1 t
Figure 15f.
Horizontal dispersion coefficient as a function of
downwind distance for Stability Class F according to
Briggs and Pasquill-Turner
39
-------
ZO'10.0 CH
K>*100.0 CH
ff* t J* t* *»Mtf « » « ** * *Mtf
OOUNUINO DISTANCE (KH)
* J «TTTTT\(f
Figure 16a. Vertical dispersion coefficient as a function of down-
wind distance for Stability Class A and surface rough-
ness of 10 cm and 100 cm according to F-B. Smith
zo-io.o CH
ZtMOO.O CH
\cr *
i * \tf t i « i t
OOHNMINO DISTANCE (KH)
I J 4 i t 11
Figure 16b.
Vertical dispersion coefficient as a function of down-
wind distance for Stability Class B and surface rough-
ness of 10 cm and 100 cm according to F-B. Smith
40
-------
10"IO.O CN
10*100.0 CH
* 444*445? i — i 4 i 4 4 u
j — r—n-T-rnr\tf
Figure 16c. Vertical dispersion coefficient as a function of down-
wind distance for Stability Class C and surface rough-
ness of 10 cm and 100 cm according to F-B. Smith
zo-io.o CH
ZO'100.0 CH
1 i i * 4 U4ltf
OOHNHINO DISTANCE (KH)
Figure 16d.
Vertical dispersion coefficient as a function of down-
wind distance for Stability Class C and surface rough-
nesses of 10 cm and 100 cm according to F.B. Smith
41
-------
ZO-10.0 CM
ZO-100.0 CH
Figure 16e
i i i 44 i i \tf J * A i J UMtf J T-TTTrrntf
OOUMUINO OlSTflNCE CKH)
Vertical dispersion coefficient as a function of down-
wind distance for Stability Class E and surface rough-
nesses of 10 cm and 100 cm according to F.B. Smith
o
A
zo'io.o en
ZO'100.0 CM
; i
1 — i ; i * u
OOHNHINO OISTBMCE CKfl)
Figure I6f.
Vertical dispersion coefficient as a function of down-
wind distance for Stability Class F and surface rough-
nesses of 10 cm and 100 cm according to F.B. Smith
42
-------
PIS CUSS ION OF THE PROCEDURE FOR VARYING THE PLUME RISE
Another objective of this study was to determine whether the requirement
of a constant stack gas exit velocity was adversely affecting the model
predictions. To study the effect of a variable stack tas exit velocity,
the hourly velocity was calculated according to the following expression:
v - w T
h a f
a
where w = stack gas exit velocity obtained from form FPC-67
a
f = hourly fuel consumption for all boilers feeding
into the stack
f = average hourly fuel consumption for all boilers
Q
feeding into the stack
43
-------
SECTION III
SITE AND DATA BASE DESCRIPTIONS
FOR MODEL IMPROVEMENT STUDY
In this section we shall describe the site characteristics, SO,, monitor-
ing program and meteorological data base for the two power plants included!
in the model improvement study. Each topic will be covered on a plant-
by-plant basis. Much of this material has already been covered in three
previous EPA reports but is presented again for the sake of completeness.
Also the description of the meteorological data base is somewhat different
for this study since for a large number of cases local wind speed and wind
direction data were used for model input as well as for background
subtraction.
At the outset of this study we planned to include the J.M. Stuart Plant
in our test of the Smith-Singer Dispersion Coefficients, but we sub-
sequently found that the angular resolution of the local wind direction
data did not permit a meaningful comparison between measurements and model
predictions. The Philo Power Plant was also excluded from our analysis
of model improvements due to the complications of terrain mentioned in
Section I. The tests of different dispersion calculation methods were,
therefore, carried out for the Canal and Muskingum River Plants.
CANAL PLANT
Site Description
The Canal Plant is located on the south side of the Cape Cod Canal about
1.6 kilometers from the entrance on Cape Cod Bay (Figure 17) The
44
-------
10 20
MASSACHUSETTS
Figure 17.
Map of eastern Massachusetts and Rhode Island showing locations
of the Canal Plant. Meteorological observations were used from
Quonset Point Naval Air Station and Chatham
-------
surrounding terrain is gently rolling with elevations generally below
60 meters above mean sea level. The highest elevations in the area are
about 90 meters above sea level in the western end of the Cape. Most of
the area is covered with scrub pine forests and low vegetation.
Data for the study were collected in 1971. During that year, the plant
consisted of a single oil-fired unit with a generating capacity of
560 megawatts. The top of the stack was about 91 meters above grade
and 5.6 meters in diameter. The main power plant structure to the north
of the stack totally enclosed the turbine generator and boiler. The
roofs of the turbine and boiler rooms were about 30 meters and 59 meters
above grade respectively. Stack and boiler data are given in Table 8.
The 1971 monthly percent sulfur content of the fuel used at the Canal
Plant is given in Table 9.
Table 8. PLANT CHARACTERISTICS
Characteristic
Stack height, m
Diameter, m
Velocity, m/sec
o
Temperature, F
Number of boilers
per stack
Maximum generating
capacity per
stack, MW
Average per stack,
MW
Plant total, MW
Plant average, MW
Plant
Canal
Stack
1
91
5.6
-
-
1
560
—
560
-
Muskingum
Stack
1
251
7.6
28.5
430
4
876
748
N^^^^^^fc^.
Stack
2
251
6.7
24.8
425
1
591
487
—I.
1467
1235
46
-------
Table 9.
MONTHLY PERCENT
SULFUR CONTENT
OF FUEL
Month
January
February
March
April
May
June
July
August
September
October
November
December
Canal
2.0
1.9
2.1
1.9
2.1
2.1
2.1
2.0
1.9
0.9
1.0
0.9
Muskingum
4.9
4.8
4.8
4.5
4.7
5.0
4.7
4.7
4.3
4.6
4.5
4.4
Overview of Canal Plant Monitoring Program
SO- concentrations are measured at four locations on a continuous basis
with Ultragas S02 Analyzers manufactured in Germany by H. Wosthoff.
These instruments measure sulfur dioxide by the increase in conductivity
of an acidified hydrogen peroxide solution and have a full scale reading
of 0.4 ppm. The instruments do not conform to the reference method for
sulfur dioxide or to any of the specified equivalent methods. They have,
however, been extensively studied and one comparison noted a correlation
coefficient of 0.99 with the West-Gaeke method. The instruments used
provide a continuous real-time chart trace and a tape printout giving
date, time, and average concentration over consecutive 30 minutes. The
sensitivity of the instrument in combination with the chart recorder is
approximately 0.005 ppm. The locations of the S0? monitors with respect
to the Canal Plant are given in Figure 18 and Table 10.
47
-------
•O-
00
\0~4 (AFTER
RTE 3 O 10/30/73)
\
SAGAMORE
BEACH
\
\
\
CAPE COO BAY
O4 (PRIOR TO
10/30/73)
N
Q5 I
km
SANDWICH
HARBOR
EAST
SANDWICH
Figure 18. Sketch of the Canal Plant area showing the locations of the four automatic
SO,., stations by the symbol ©
-------
Table 10. SULFUR DIOXIDE MONITORING STATIONS FOR THE CANAL
AND MUSKINGUM PLANTS
Plant
Canal
Musk in gum
Station
No.
1
2
3
4
1
2
3
4
-
Name
Beverly
Hackney
Rich Valley
Caldwell
Top of stacks
Distance,
km
4.7
2.3
1.4
2.0
5.3
4.3
8.3
19.6
-
Heading,
degrees
119
138
224
312
140
40
35
35
-
Elevation above
stack base, m
10
4
40
20
64
82
101
128
251
Meteorological Data for Canal Plant
Bendix-Friez Aeorovanes are used to provide local wind speed and direction
data. Through July 1971, the principal source of wind data was the
Aerovane mounted on a 12.2 meter mast located on the 58.8 meter boiler-
room roof. Since July 1971, wind data are obtained from a second Aerovane
installed on a 44 meter tower near the top of Telegraph Hill approximately
5 kilometers south-southeast of the Canal Plant. This hourly wind data
was used to define upwind receptor locations for calculation of hourly
background concentrations. A station was considered to be a background
receptor if it were located outside the boundaries of a 90 degree sector
centered about the wind flow vector. The concentrations for these back-
ground stations are then averaged and subtracted from the hourly concen-
tratios at all stations. Any resultant negative concentrations were set
equal to zero. The on-site wind speed, wind direction and ambient tem-
perature data were also input to the Single Source Model after proper
conversion to a wind measurement height of 7 meters. These stability
dependent wind speed corrections, which were discussed in Section II,
were based upon hourly atmospheric stabilities derived from a Single
49
-------
Source Model Preprocessor run using surface meteorological data for 1971
collected at Quonset Point Naval Air Station. Hourly mixing heights for
1971 were based upon surface data from Quonset Point, Rhode Island and
upper air observations taken at Chatham, Massachusetts. In this way
a "hybrid" Preprocessor output file was generated containing on-site
wind speed, wind direction and temperature measurements and nonlocal
stability and mixing height assignments.
MUSKINGUM PLANT
Site Description
The Muskingum Plant is located in southeastern Ohio on the Muskingum
River about 6 kilometers northwest of the town of Beverly. Figure 19
indicates the location of the plant, the SO- monitoring sites, and the
surrounding towns. The plant is in the river valley about 500 meters froi
the valley walls which rise about 75 meters above the valley floor. The
two 251 meter stacks are 640 meters apart and extend about 185 meters
above the surrounding terrain. During 1973 the plant consisted of five
coal-fired units with a total capacity of 1467 megawatts (Table 8).
Percent sulfur content of the fuel for 1973 is given in Table 9.
Overview of the Muskingum Monitoring Program
Four sulfur dioxide monitoring stations make up the monitoring network
(Figure 19 and Table 10). Data were available from all stations
for January 1 to November 21, 1973. During the entire year of 1973,
Station 1 missed 57 days and the other three stations missed approximately
41 days. Instruments at Muskingum were Leeds & Northrup Company, Catalog
No. 7860-SW, Aeroscan Air Quality Monitors. The sample was obtained by
passing ambient air taken from 5 feet above ground level, through an ab-
sorption column along with an absorption solution. The sample analysis
method was by electrolytic conductivity. Data were taken continuously
and listed every hour. Each instrument was automatically zeroed once a da)
50
-------
RT 77
0
RICH VALLEY 1*3
>CENTERVILLE
HACKNEY #2
RT 76
MUSKINGUM PLANT
N
KILOMETERS
2345
J 1 1 1
Figure 19. Sketch of the Muskingum Plant area showing locations of
four automatic SO,., monitoring stations
51
-------
The manufacturer's performance accuracy specifications for this instru-
ment are as follows. In a typical ambient atmosphere which includes
the normal interfering gases, this instrument has:
• Zero drift = 2 percent of full scale per week
• Sensitivity drift < 1 percent of full scale per week
• Reproductibility <1 percent of full scale
• Sensitivity = 0.01 ppm
• Recorder error < 0.5 percent of full scale
• Range = approximately 0-1 ppm
Meteorological Data for Muskingum Plant
There were two wind monitoring stations at the Muskingum Plant consisting
of Bendix-Friez Aerovane wind speed and direction devices. One station
was located 24 meters above ground at Beverly, and the other at the
Hackney S09 monitoring station, where the wind monitors were also located
24 meters above ground. The data from Hackney was used in this study,
as it was higher and common to more stations, but Beverly data was used
when the Hackney system was not recording. On-site hourly wind direction
data were used for the assignment of upwind receptor locations whose
concentrations were then used in a background subtraction procedure iden-
tical to the one described for the Canal plant. Wind speeds at these
two meteorological stations were adjusted to the 7 meter height by means
of the stability dependent power law currently used in the Single Source
Model and hourly stabilities based upon Huntington, West Virginia sur-
face observations for 1973. A hybrid Preprocessor output file was then
constructed using local wind direction and adjusted windspeed data in
conjunction with ambient temperature and stability assignments from
Huntington. Hourly mixing heights were based upon surface and upper air
data both collected at Huntington. This particular combination of on-
site and nonlocal meteorological data were used to test the Pasquill-
Turner, Gifford-Briggs and F« B. Smith dispersion parameters at the
Muskingum Plant. In our test of the F. B. Smith fractional stabilities,
the Preprocessor program was modified to include a two-digit stability
class.
52
-------
For the test of the Smith-Singer dispersion coefficients, local values
for wind direction, wind speed (uncorrected) and Smith-Singer stability
class (1 - 4) were used with nonlocal values for ambient temperature
and mixing height as input to the Single Source Model modified to in-
clude Smith-Singer dispersion coefficients and wind speed profile
parameters.
53
-------
SECTION IV
MODEL VALIDATION RESULTS
Our test of the different sets of dispersion coefficients described in
Section II was based upon a comparison of cumulative frequency distri-
butions of measured and predicted 1-hour SO- concentrations at the Canal
and Muskingum Power Plants. The combinations of power plant sites,
stability assignment algorithms, dispersion coefficients and meteorolog-
ical data bases are presented in Table 11 along with the results of
each model validation test and the numbers of the figures illustrating
each test. The results of the variable plume rise test are also included
in Table 11.
The overall conclusion which may be reached based upon the examination
of results presented in Table 11 is that the Pasquill-Turner dispersion
coefficients and stability assignment algorithm yield the best agreement
of the methods tested with the possible exception of the Gifford-Briggs
dispersion coefficients. Although in the case of the Canal Plant the
Gifford-Briggs coefficients gave slightly better agreement with measure-
ments than the Pasquill-Turner curves, the two schemes worked equally
well for the Muskingum Plant. This outcome is reasonable in light of the
close agreement between the a curves, except for stability A, for the
z
two different methods (see Figures 15a through 15f).
The most surprising result of the study was the failure of the Smith-
Singer dispersion coefficients and stability assignment scheme to predict
the upper percentile or even the shape of the 1-hour concentration fre-
quency distribution (see Figures 24a through 24e). One would expect these
54
-------
coefficients to be better suited to the prediction of short-term S02 levels
in the vicinity of power plants since they were based upon experiments in-
volving the release of tracers from elevated sources. Since the criteria
for selection of a given curve is somewhat qualitative, this may be a
factor in their not giving a proper frequency distribution shape.
Since a major portion of our validation efforts involved the testing of the
fractional stability scheme of F.B- Smith, we shall examine a number of
reasons behind the resulting poor agreement with measured 1-hour S0« con-
centrations. Our first test of the F.B. Smith method involved point sta-
bility assignments according to Pasquill-Turner and the corresponding
F-B. Smith Dispersion curves for stabilities A through F. Again it should
be pointed out that only the F.B. Smith a estimates were used in this
z
model validation test. The Pasquill-Turner a curves (see Figure 2), were
used in conjunction with the F-B. Smith a 's. The results of this first
2
validation exercise (Run Nos. 6 and 8) indicated a strong tendency for the
F.B. Smith point stability dispersion curves to underpredict 1-hour SCL
concentrations both for the Canal and Muskingum Plants. The only exception
to this finding was the result for Muskingum Station 4 which showed slightly
improved agreement over the Pasquill-Turner results (Run No. 2). The rea-
son that this station did not follow the trend toward underprediction may
have been its location 19.6 km from the plant. At this distance the largest
concentrations should be observed during the more stable conditions (D, E
and F)• For these stability classes the F.B Smith a curves do not
z
differ radically from the Pasquill-Turner curves (see Figures 14c through
14e). When a surface roughness of 100 cm, rather than the standard value
of 10 cm, was used for calculation of the F.B. Smith a curves the agree-
o
ment between predicted and measured 1-hour SO^ concentrations was somewhat
better for the Canal Plant (Run No. 7), although the assumption of 100 cm
surface roughness for this site is clearly unrealistic.
To determine, whether the F. B. Smith vertical dispersion curves would
yield better results when used in conjunction with the F. B. Smith
stabilities described in Section II, we rewrote the Single Source Model
55
-------
Preprocessor Program to include the fractional stability calculation
techniques discussed in Section II. Minor modifications to the Single
Source Model itself were made to provide for the interpolation of o
and a values based upon the fractional stability assignment. A com-
z
parison of the Pasquill-Turner and F. B. Smith stabilities for three
days in 1973 based upon Huntington, West Virginia surface meteorological
data is presented in Table 12. Local windspeed and wind direction data
for the Muskingum River Plant were not used in this calculation since
the windspeed measurements were obtained at 24.2 m above the ground
and not the 10 m height required for use in the F. B. Smith calculation.
A stability dependent power law correction could have been used to con-
vert the windspeed to the 10 m height except that the purpose of the
exercise was to actually determine the fractional stability. Although
the 7 m measurement height assumed for Huntington, W. Va. was not equal
to the required 10 m height, the resulting error is negligible.
When the fractional stability versions of the Preprocessor Program and
the Single Source Model were run for the Muskingum Plant, an overpredic-
tion occurred for stations 2, 3 and 4, compared to the substantial under-
prediction which resulted when the F. B. Smith dispersion coefficients
were used in conjunction with the Pasquill-Turner point stability assign-
ments. The generally lower stability index assignments based upon the
F. B. Smith method have overcompensated for the smaller F. B. Smith a
£*
values for the A, B and C stability classes. An example of the generally
lower stability indices calculated by the F. B. Smith method is shown in
Table 12. For the midday hours during the summer months the F. B. Smith
stability indices can be more than one stability class lower than the
corresponding Pasquill-Turner values.
The final objective of the model improvement study was to determine
whether the incorporation of an hourly variation of a stack gas exit
velocity, which is directly proportional to the fuel consumption rate,
would improve model agreement with measured 1-hour SO^ concentrations.
The procedure for calculating hourly exit velocities was described in
56
-------
Section II. Although the tests for the Canal and Muskingum River Plants
showed no such improvement, the inclusion of a variable buoyancy flux in
the model Still may be desirable in the case of highly variable fuel
consumption.
57
-------
Table 11. DESCRIPTION OF MODEL VALIDATION RUNS AND RESULTS
Run
number
I
2
3
4
5
6
7
Site
Canal
Stability
assignment
method
Pa squill -Turner
i
Musktngum
Canal
Muskingum
Muskingum
Canal
Canal
Pasquill-Turner
Pa squill -Turner
Pasquill-Turner
Smith-Singer
Pasquill-Turner
Pasquill-Turner
Dispersion
calculation
method
Pasquill-Turner
Pasquill-Turner
Gifford-Briggs
Gifford-Briggs
Smith-Singer
F. B. Smith
F. B. Smith
Meteorological
data base
Local wind speed ,
wind direction and
ambient temperature.
Stabilities based upon
surface data from
Quonset Point, R.I.
raining heights from
Chatham, Mass .
Local wind speed and
wind direction. Am-
bient temperature and
stability from
Huntington, W. Va.
surface data. Mixing
heights from Hunting-
ton, W- Va.
Same as Run No. 1
Same as Run No. 2
Local wind speed, wind
direction and atmo-
spheric stability.
Ambient temperature
and mixing height from
Huntington, W. Va.
Same as Run No. 1
Same as Run No. 1
Special modifications
Validation results
All stations under predicted
for the entire distribution,
especially stations 2 and 4.
Closest agreement for station
3, which had the highest ele-
vation above the stack base.
Except for station 3, the
calculated distribution shapes
are also in error.
Good agreement for the higher
I end of the distributions ex-
Smith-Singer windspeed
profile incorporated.
For stabilities B2 , Bl
and C, plume rise is
calculated according
to Equation (2) in
Section II. For
stability D, Equation
(3) is used.
Surface roughness of
10 cm.
Surface roughness of
100 cm.
cept for station 2 which is
overpredicted .
In comparison with Run No. 1
slightly better agreement for
all stations was obtained, but
the entire frequency distribu-
tion is still underpredicted.
Slightly better agreement for
stations 2 and 4 when compared
with Run No. 1.
Considerable overprediction
for stations 1, 2 and 3 even
at the lower end of the dis-
tributions. Calculated dis-
tribution shapes are un-
realistic.
All stations underpredicted for
the entire distribution. For
stations 2, 3 and 4 agreement
considerably worse than for
Run No. 1.
Improved agreement over
Run No. 6.
Figure
numbers
20
21
22
23
24
25
26
CO
-------
Table 11 (continued). DESCRIPTION OF MODEL VALIDATION RUNS AND RESULTS
Run
number
8
9
10
11
j Site
Muskingum
Mu skingum
Muskingum
Canal
Stability
assignment
method
Pasquil 1-Turner
F. B. Smith
(fractional
stabilities)
Same as Run
No. 2
Same as Run
No. 1
Dispersion
calculation
method
F. B. Smith
F. B. Smith
(values for o and
o interpolated based
upon fractional sta-
bility assignment) .
Same as Run No. 2
Same as Run No. 1
Meteorological
data base
Same as Run No. 2
1973 Hunting ton,
W. Va. surface and
upper air data.
Same as Run No . 2
Same as Run No. 1
Special modifications
Preprocessor and single
Source Model modified
to include a two-digit
stability index and
provide for the inter-
polation of dispersion
coefficients .
Variable buoyancy flux.
Variable buoyancy flux.
Validation results
Only station 4 at 19.6 km
from the plant showed better
agreement than for Run No. 2
Figure
numbers
27
All other stations were con- '
siderably underpredicted for t
the entire distribution. j
All stations except 1 were
overpredicted at the high
end of the distributions.
No improvement over Run
No. 2.
No improvement over Run
No. 2
28
29
30
Ui
-------
Table 12. COMPARISON OF PASQUILL-TURNER
(P-T) AND F. B. SMITH (F.B.S.)
STABILITY ASSIGNMENTS FOR THREE
DAYS OF HUNTINGTON, W. VA. 1973
SURFACE METEOROLOGICAL DATAa
Day No. 64
P-T
6
5
5
6
5
5
6
4
4
4
3
3
4
4
4
4
4
3
4
5
7
7
7
7
F.B.S.
4.1
4.1
4.1
4.1
4.1
4.1
4.1
4.1
4.1
3.8
2.6
2.8
3.4
2.4
2.4
2.5
2.6
3.3
6.2
5.0
7.0
7.0
7.0
7.0
Day No. 134
P-T
4
4
7
4
4
6
4
3
3
2
2
3
3
4
4
4
3
3
3
4
6
6
6
4
F.B.S.
4.1
4.1
4.1
4.1
4.1
4.8
4.1
3.1
2.2
1.7
1.4
1.5
1.8
2.7
2.9
2.4
3.0
.
2.5
3.3
7.0
7.0
7.0
7.0
4.3
Day No. 323
P-T
4
4
4
4
4
4
5
4
4
4
4
4
4
4
4
4
4
3
6
6
7
7
6
7
F.B.S.
4.1
4.0
4.1
4.1
4.1
4.1
4.5
4.1
4.1
4.1
3.6
3.4
3.4
3.3
3.4
3.8
4.3
7.0
6.9
7.0
7.0
7.0
7.0
7.0
A value of 0.4 has been added
Smith stabilities so that they
pared with the Pasquill-Turner
to the F.B.
could be corn-
values .
60
-------
PERCENTAGE OF COMCENTIWTIONS
GHEBTER THflN JMOICflTED VHLUE
"QII •» » I H.S »» M If to M 70 >0 10 10 » M 10 I I
I—I 1 1 1 1 I 1 > ---{ 1 1 1 1 1 1 H-
.0,-fc,
ot-
to-
PLflNT HUN 1
CUMULflTlVE FREQUENCY DrsTniaUTTON
FOR 1 HOUR 303 COMCEMTflflTIOMS
fiT STflTION I
rUNUS BRCKGSOUNO
j.CflLCULfllfD
01 0» l.Z .3 I
Figure 20a
s 10 ?o )o HO co to 70 n to u MM
PEdCENTBBE OF CONCENTRflTIONS
LESS THflN INDICATED VflLOE
Model validation Run No. 1. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S0? concentrations for Canal Plant Station 1
Of
TMflN INDICATED VALUE
M n M u M so » 10 « t i .1 ; -i
CflNflL flflNT RUN 1
CUMULflTlVE FftEQUENCT DISTRIBUTION
FOR 1 HOUR 502 CONCENTnflTlONS
flT STflTtON
0NEflSUREO
AMEflSURED H1MUS BflCKGROUSO
I S 10 CO JO \t SO M TO »C tO
PCRCENTflGE OF COMCEMTMTIOII5
LESS THRU INDICATED VflLUE
Figure 20b.,
Model validation Run No. 1. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
hourly S00 concentrations for Canal Plant Station 2
61
-------
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VRLUE
•Q»I.M it t M c m u u »o 10 10 u » M jo a 10 < t i .t
CANAL PLANT RUN i
CURULATIVE FREQUENCY DISTRIBUTION
FOfl 1 HOUR SOZ CONCENTRATIONS
AT STATION 3
HINU3 BACKCnOUND
j.CALCULflTEQ
01 .OS .1.2 .S I t I 1O 20 90 to 80 H 10 tO fO n tt »t I
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
.ft n i tt 19
Figure 20c,
Model validation Run No. 2. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S07 concentrations for Canal Plant Station 3
PERCENTH6E Of CONCENTRATIONS
GREATER TMflN TNOICRTEO VALUE
» MM *o to »o so <*o so n to s f i 9 2
010
CowflL PLWWT RUM i
CUMULATIVE rflEOUEMCT D I STM I6UT10N
FOR 1 HOUrt SOZ CONCENTHflT 10MS
AT STATION il
^MEASURED HINDS BACKGROUND
c
^_)
"t:
cr
cc
V I IO 70 M 10 (O «) TO «O tO
PtRCENIASE OF CONCIN1RUT IONS
LESS TMftN INOICflTED VALUE
Figure 20d
Model validation Run No. 1. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S02 concentrations for Canal Plant Station 4
62
-------
PERCENTAGE OF CONCENTRATIONS
GRtATER T«AN INDICATED VALUE
II M IS 10 to ?o «0 CO W XO 20 10
CANAL PLANT BUN 1
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
AT STATION DLL
^MEASURED
AHEASUHED MINUS BACKGROUND
4.CALCULATEO
.01 .0* .I.t .511 5 10 to lo M M M 70 00 M M
PERCEMTASE OF CONCENTRATIONS
LESS THAN INOICflTEO
t> n.c ii.i ii.m
Figure 20e
Model validation Run No. 1. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S02 concentrations for Canal Plant for all
stations
Figure 21a
t>«»
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
,91 n.a M.S is fl» *s BO to TO 10 so no M eo to s ? i .s .f .1
^—i—I-
HU5KINGUH RUN 2
COMULHTIVE FREQUENCY DISTRIBUTION
F3R 1 HOUR 303 CQNCENTPIHTION3
pT STHTION 1
OHEHSUREO
AMEfl3UREO MINUS BACKGROUND
PERCESTPGE 8F CONCENTRATIONS
LESS THAN INDICATED VALUE
Model validation Run No. 2. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S09 concentrations for Muskingum Plant Station 1
63
-------
PFRCENTflGE OF CONCENTRRTJON3
GRERTEfl THRN INDICATED VRLUE
I *S.» M.S » »» IS fO H 10 iQ 50 1Q M N 10 S t
HU5K1NGUM RUN 2
CUHULRTIVE FREQUENCY DISTRIBUTION
FOR I HOUR 502 CONCENTRRTIONS
PT STPTION 2
(jHEHSUREO
AM£R3UHEO MINUS 8HCKGHOUNO
CRLCUIRIEO
f 5 10 fO JO HO SO 6tt TO 00 10
PERCENTflGE OF CONCENTRATIONS
LCS5 THflN INOICRTEO VHLUE
Figure 21b
Model validation Run No. 2. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour SOo concentrations for Muskingum Plant Station 3
TERCENTRGE OF CONCENTRPTIONS
GREATER THRN INOICATEO VRUUE
I.M n.i M.S n •• u to «o n to so «o 30 to 10 i t i .1 .f .1
0>-
tO~
r--
ta-
m-
Cn
O
=TD
(I ««-
OC m-
^ rr-
UJ
>_> m
^
O
•J cv.
RUSK INCUR RUN 2
CUMULRTIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR S02 CONCENTRRTION3
PT STflTION 3
QRERSUREO
4.MERSUREO MINUS 8RCKGHOUNO
4.CRLCULRTEO
00
Z
Z
O
a:
-in 1C
UJ
-
2:
O
-CM <->
.01 .OS .I.Z .SI
t S 10 (0 90 UO SO go 10 00 $0
rERCENTPGE OF CONCENTHRTIONS
LESS THRN INDICRTEO VRLUE
99.1 »».* 99.49
Figure 21c
Model validation Run No. 2. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S02 concentrations for Muskingum Plant Station 2
64
-------
Figure 2Id.
•b".
PERCENTRCE OF CONCENTRRTIONS
GRERTER TURN INDICRTEO VRLUE
M M.I SJ.S U •• IS »0 10 10 «0 U 10 3d SO 10 S Z I .5 .1 .•
•I 1—(-
MUSKINGUM RUN 2
CUMULATIVE FREQUENCY OISTHIaUTION
FOR 1 HOUR SOZ CONCENTRRTION3
BT 3TRTION
QMERSURED
&MEfl3UREO MINUS 8flCKGflOUND
+ CRLCULRTEO
.01 .os .i.t .sit s 10 to so «o so M 10 n M as MM 39. s a«.i 35.35
fERCENTWCE OF CONCENTRBTIONS
LESS THAN INDICATED VBLUE
Model validation Run No. 2. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S09 concentrations for Muskingum Plant Station 4
Figure 21e.
10-
U>-
o
cc ">
CC. in.
PERCENTflGE OF CONCEMTRflTION3
GREflTEfl THRM INDICATED VflLUE
i 93.S W.S 99 9t «5 »0 10 7Q CQ SO WO 90 (Q 10 & t I .5 ,e ,1 -01*O
MU5KIWGUM RUN 2
CUMULflTlVE FREOUENCr OI3TRI8UTION
FOfl I HOUR 382 CONCENTRflTION3
PT STflTION RLL
AMER3UflED MINUS BflCKGROUWO
^CflLCULRTEO
01 .05 .i.e .s i e s to co 30 no so 00 10 »o to
FERCENTHGE OF CONCENTRRTION3
LESS THflN INDICflT£0 VflLUE
'Model validation Run No. 2. Pasquill-Turner stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions of
1-hour S02 concentrations for Muskingum Plant for all
stations
65
-------
rcnccNTAcc OF CONCENTRATIONS
CHCRTCR THAN INOICRTCO VflLUE
> »n * M % M •# n M K> 10 «Q so «e M to 10 s
CflNRL TLANT RUN 3
CUHULRTIVE FREQUENCY OISTHIBUTIOM
FOR 1 HOUR 308 CQMCENTRRTIONS
fit STRTION I
&HEfl3URED MINUS BRCKGROUND
+CRLCULRTEO
10 to 90 HO 58 M TO 10 M 9S •• » MS W.I M.99
PERCENTflGE Of CONCENTHfllIONS
LESS THflN INOICRTEO VflLUE
Figure 22a.
Model validation Run No. 3. Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method. Measured and predicted cumulative frequency
distributions of 1-hour S02 concentrations for Canal
Plant Station 1
rEPlCENTflGE Or
TMSW INOICRTEO VflLUE
O»-M n ' "•* >s *• *5 *° *° )0 I0 so *° *° <°
C.ONPL PLSN' RUN 3
CUMULATIVE FREQUENC' OIS1BI8UTION
FOR 1 HOUR 302 CONCENTRRTIONS
PT STflTION 2
QMER3URED
AMERSURED MINUS BRCKGHOUNO
J.CRLCULBTEO
.01 .OS . l.< .5 t t S 10 CO 90 VO SO «Q 70 10 9D 95 M 99 19.S *9 9 t9.99
CERCENTSGE OF CONCENTRHTION3
LESS THAN INOICRTEO VflLUE
Figure 22b.
Model validation Run No. 3. Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method. Measured and predicted cumulative frequency
distributions of 1-hour SC>2 concentrations for Canal
Plant Station 2
66
-------
tc-
tn-
c>
z
\
o
PERCENTAGE or CONCENTRATIONS
GREATER THAN INDICATED VALUE
»•• H00 M TO fO » «0 M to 10
-t-
CANAL PLANT HUN 3
CUMULATIVE FREOUENCT DISTRIBUTION
FOR 1 HOUR 302 CONCEMTRATION3
AT STATION 3
^MEASURED
^MEASURED MINUS BACKGROUND
^CALCULATED
Figure 22c.
.01 .OS .I.C Sit S 10 (OH 10 » H to 10 M M M» M.S
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
Model validation Run No. 3. Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method. Measured and predicted cumulative frequency
distributions of 1-hour S0? concentrations for Canal
Plant Station 3
TERCENTACE OF CONCENTRATIONS
&REATER THAN INDICATED VALUE
CANAL PLANT HUN 3
CUMULATIVE FREQUENCY OtSTRIBUTION
FOR I HOUR 302 CONCENTRATIONS
AT STATION U
^MEASURED
^MEASURED MINUS BACKGROUND
^CALCULATED
t S 10 to M <0 M 10 70 >0 10
PERCENTAGE OF CONCtNTHATIONS
LESS THAN INDICATED VALUE
a* n M.S n.9 99.91
Figure 22d.
Model validation Run No. 3. Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method. Measured and predicted cumulative frequency
distributions of 1-hour SC^ concentrations for Canal
Plant Station 4
67
-------
PERCENTAGE OF CONCENTRATION]
GREATER THRU INDICATED VflLUE
tS.5 ».S » M MM «0 70 «0 So «0 » » <0
t i .1 .» .1 oi'o
o-
tA-
o
O m
Z
o
CflNflL PLANT HUN 3
CUMULATIVE FREQUENCY DISTRIBUTION
FOR I HOUR 302 CONCENTRATIONS
OT STATION ALL
^MEASURED
AMEASURED MINUS BACKGROUND
.(.CALCULATED
.01 .os .1.: -S
Figure 22e.
Z S 10 U M «0 SO §0 10 n 90 IS l» ^
PERCENTBtl Of CONCENTRATIONS
Lc.33 THAN INDICATED VOLJE
Model validation Run No. 3- Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method . Measured and predicted cumulative frequency
distributions of 1-hour SC>2 concentrations for Canal
Plant for all stations
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
so ro 10 M so » 90 n 10 s t
i 1 I I—i—(—I—i 1—i 1
MUSKINCUM RUN 4
CUMULATIVE FREQUENCY DISTRIBUTION
FOR i HOUR soz CONCENTRATIONS
AT STATION
(^MEASURED
^MEASURED MINUS BACKGROUND
^CALCULATED
.01 .os i.t .s i r s 10 eo 90 «o so to 10 «o to n o» <
PERCENTAGE OF CONCENTRflTIONS
LESS THAN INDICATED VALUE
II.S M.9 M.99
Figure 23a.
Model validation Run No. 4- Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method . Measured and predicted cumulative frequency
distributions of 1-hour S02 concentrations for Muskingum
Plant Station 1
68
-------
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VRLUE
Figure 23b.
tS M.I H.S MM MM
MU3KINGUM HUN
CUMULATIVE FREOUENCT 013Tni8UTI8N
FOR I HOUR 302 CONCENTRATIONS
AT STATION g
^MEASURED
4MEASURED MINUS BACKGROUND
...CALCULATED
,01 .at ,\.i .« i i s 10 to to u so «o re to w
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
» n 5J.I n.l n.M
Model validation Run No. 4. Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method. Measured and predicted cumulative frequency
distributions of 1-hour SC>2 concentrations for Muskingum
Plant Station 2
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
»0 TO id SO
.."o
MUSKINGUM RUN 4
CUMULATIVE FREOUENCT DISTRIBUTION
FOR I HOUR SOZ CONCENTRATIONS
AT STATION 3
OMEA3UREO
^MEASURED MINUS BACKGROUND
^CALCULATED
.01 .OS .l.t .Sit S 10 (0 90 110 SO >0 70 H 90
PERCENTAGE OF CONCENTRATIONS
LESS THBN INDICATED VALUE
» (9 99.1 M.9 99.99
Figure 23c.
Model validation Run No. 4. Pasquill-Turner stability
assignment method and Gifford-Briggs dispersion calcula-
tion method . Measured and predicted cumulative frequency
distributions of 1-hour SC>2 concentrations for Muskingum
Plant Station 3
-------
03-
2 concentrations for Muskingum
Plant for all stations
70
-------
TERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
•t.f MM M to 80 TO 90 SO 10 X
Figure 24a.
MU3KINGUM RUN 5
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
AT STATION 1
0HEA5UREa
^MEASURED MINUS BACKGROUND
...CALCULATED
.912 s to n w «o H go TO M H « HII a.i u.i «.«•
rERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
Model validation Run No. 5. Smith-Singer stability
assignment and dispersion calculation method. Measured
and predicted cumulative frequency distributions
of 1-hour SOo concentrations for Muskingum Plant
Station 1
rERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
i m.i n.t » M «s «o to TO « u «o so to 10 t i i .s .c
n-
(n
3C
X
O
=)
i^1
^ °»'
i- r-
cr •»•
CC in
MUSKINGUM RUN 5
CUMULATIVE FREQUENCY DISTRIBUTION
tOfl 1 HOUR 30S CONCENTRATIONS
AT STATION £
^MEASURED
^MEASURED MINUS BACKGROUND
^CALCULATED
CO 9O to SO 00 TO
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
Figure 24b.
Model validation Run No. 5. Smith-Singer stability
assignment and dispersion calculation method. Mea-
sured and predicted cumulative frequency distributions
of 1-hour S02 concentrations for Muskingum Plant
Station 2
71
-------
rERCEMTRGE OF CONCENTRATIONS
GRERTER THRN INDICRTEO VflLUE
I M.t M.I MM MM M 10 M M W 90 to lal
• I—I-
I 1 .S .t .1
..•b
**^
•O>
Figure 24c.
MUSKINCUH RUN 3
CUHULRTIVE FREQUENCY DISTRIBUTION
FOR i HOUR 308 CONCENTRRTIONS
PT 3TRTION 3
QNERSURED
&HER3UREO MINUS BACKGROUND
J.CRLCULRTEO
i i 10 n «a >g M n TO
rERCENTHGE 8F C8MCENTRRTIOM3
LESS THRH INOICRTEO VRLUE
w •_•'«/ inrin inw
-------
PERCENTAGE OF CONCENTRATIONS
GREATER THRN INDICATED VALUE
I M.9 M.I MM MM M 10 M 10 tO M It 10
HUSKINGUH RUN 5
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
FIT 3THTION ALL
gMERSUREO
^MEASURED MINUS BRCKGROUNO
.•.CALCULATED
.01 .as .i.e .sic s 10 n *o u u «Q TQ M M tc
PERCENTRGE OF CONCENTRRTION?
LESS THRN INDICATED VALUE
M n n.s n.i n.»
Figure 24e.
Model validation Run No. 5. Smith-Singer stability
assignment and dispersion calculation method. Mea-
sured and predicted cumulative frequency distributions
of 1-hour SOo concentrations for Muskingum Plant for
all stations
PERCENTAGE QF CONCENTRATIONS
GREATER THRN INDICATED VALUE
i M.I M.I MM UN to rq « ia 10 to ni to i
CRMAL PLANT RUN 6
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR SOS CONCENTRATIONS
AT STATION I
^MEASURED
AMEASURED MINUS BACKGROUND
^CALCULATED
.& I 2 t 10 to 30 HO So SO 70 0Q M 9S n n M.C
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
Figure 25a.
Model validation Run No. 6. Pasquill-Turner stability
assignment method and F-B- Smith dispersion calculation
method. Surface roughness equal to 10 cm. Measured
and predicted cumulative frequency distributions of
1-hour SC>2 concentrations for Canal Plant Station 1
73
-------
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
i n.» m.l n n MM M it) ig to HO a n to
Figure 25b.
CANAL PLANT RUN e
CUMULATIVE FREOUENCY DISTRIBUTION
FOR 1 HOUR 502 CONCENTRATIONS
AT STATION 2
^MEASURED
^MEASURED MINUS BACKGROUND
+CALCULATED
.01 .<* .1.1
s 10 TO » vo so n TO to TC
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
Model validation Run No. 6. Pasquill-Turner stability
assignment method and F.B. Smith dispersion calculation
method. Surface roughness equal to 10 cm. Measured
and predicted cumulative frequency distributions of
1-hour S02 concentrations for Canal Plant Station 2
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
.» n.» n.i n » M N M n n lo no >o n |o i
.«fc
CANAL PLANT RUN 6
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR SOZ CONCENTflATIONS
AT STATION 3
OMEASUREO
&MEflSUHED MINUS BACKGROUND
^CALCULATED
zo vt «o so 00 10 00 to as
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
99. s n.t «t.M
Figure 25c.
Model validation Run No. 6. Pasquill-Turner stability
assignment method and F.B. Smith dispersion calculation
method. Surface roughness equal to 10 cm. Measured
and predicted cumulative frequency distributions of
1-hour S00 concentrations for Canal Plant Station 3
74
-------
PERCENTAGE OF CONCENTRATIONS
GREATER THAU INDICATED VALUE
ti.t n.t MM
10 70 M 50 W 30 CO 10
o 10 K n K w N ».t ».
PERCENTAGE OF CONCENTRATIONS
LESS THAk INDICATED VALUE
Model validation Run No. 6. Pasquill-Turner stability
assignment method and F.B. Smith dispersion calculation
method. Surface roughness equal to 10 cm. Measured
and predicted cumulative frequency distributions of
1-hour S02 concentrations for Canal Plant for all
stations
75
-------
OF CONCENTRATIONS
GREATER THRN INQICRTEO VALUE
t>l».«l **.! M.I M M
CANAL rLRNT RUN 7
CUHULRTIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR 30Z CONCENTRATIONS
fiT STATION 1
^MEASURED
^MEASURED MINUS BACKGROUND
.•.CALCULATED
f I la n 90 u M
rERCENTRGE OF CQNCENTRRTION9
LE33 THRN INDICRTEO VALUE
• n.i •».• n.M
Figure 26a
Model validation Run No. 7. Pasquill-Turner stability
assignment method and F.B. Smith dispersion calculation
method. Surface roughness equal to 100 cm. Measured
and predicted cumulative frequency distributions of
1-hour S(>2 concentrations for Canal Plant Station 1
o
="lb
o:
i—
z
UJ
o
o
<.)
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
«.i H.I MM nw wnianiofgn »
i i i—i—i 1 1——i—< ) •> H i i )
i i .s .( .1
CRNRL PLRNT RUN 7
CUHULRTIVE FREUUENCT DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
(IT STATION 2
OMER5UREO
AMERSURED MINUS BACKGROUNO
+ CAi_CULBtEQ
.01 .K .i.t .1 i
i * 10 n 90 »o so M TO H to
CERCENTHGE OF CONCENTRRT10NS
LESS THAN INDICRTEO VALUE
W •> H.S M.i M.M
Figure 26b
Model validation Run No. 7. Pasquill-Turner stability
assignment method and F-B* Smith dispersion calculation
method. Surface roughness equal to 100 cm. Measured
and predicted cumulative frequency distributions of
1-hour S0? concentrations for Canal Plant Station 2
76
-------
PERCENTAGE OF CONCENTRATIONS
GRERTER THAN 1NQICRTEO VALUE
M.I nw aw n TQ M H w w to 10 «
t i .s .e .1 .'"Ij
CRNHL PLRNT RUN 7
FREQUENCY DISTRIBUTION
FOR t HOUR see CONCENTRATIONS
AT STATION 3
^MEASURED
4MERSURCD MINUS BRCKGRQUNO
...CALCULATED
5 I < I 10 10 M U M 10 70 10 M
rERCENTRGE OF CONCENTRATIONS
LESS THRN INDICATED VRLUE
w » n.s n.i n.-n
Figure 26c
Model validation Run No. 7. Pasquill-Turner stability
assignment method and F-B. Smith dispersion calculation
method. Surface roughness equal to 100 cm. Measured
and predicted cumulative frequency distributions of
1-hour S00 concentrations for Canal Plant Station 3
PERCENTRGE OF CONCENTRRTIONS
GREATER THRN INDICATED VALUE
M.I MM MM M TO M M I
H I* t
tD-
in-
CflNPL PLRNT RUN 7
CUnULRTIVE FREOUENCT OISTniBUTION
FOR 1 HOUR 303 CONCENTRRTIONS
AT 3TRTI8N U
^MEASURED MINUS BACKGROUND
^.CALCULATED
a n.t H.I n.i
Figure 26d
.l.t .tit S 10 tOMUMMTOn 10 «
PERCENTAGE OF CQNCENTnRTIQNS
LESS THRH INDICATED VALUE
Model validation Run No. 7. Pasquill-Turner stability
assignment method and F.B. Smith dispersion calculation
method. Surface roughness equal to 100 cm. Measured
and predicted cumulative frequency distributions of
1-hour SOo concentrations for Canal Plant Station 4
77
-------
PERCENTRQC OF
GREATER THAN INOICRTEO VRLUE
i u.< M.I MM MM M TO M M •• • M n •
i i .1 .1.1
...•b
CHNRL PLRNT RUN 7
CUHULHT1VE FREOUENCT DISTRIBUTION
FQR 1 HOUR 302 CQNCENTRRT10N3
BT 3THTION RLL
QHER3UREO
4HERSURED MINUS 8RCKGROUND
4.CRLCULRTED
i > ID n w ID u M TO to w
rERCENTRCE OF CQNCENTRRTION3
LESS THRU INOICRTEO VRLUE
M M M.S M.I U.M
Figure 26e.
Model validation Run No. 7. Pasquill-Turner stability
assignment method and F.B. Smith dispersion calculation
method. Surface roughness equal to 100 cm. Measured
and predicted cumulative frequency distributions of
1-hour S02 concentrations for Canal Plant for all stations
PERCENTRGE 8F CONCENTRBTION3
GflEflTEn THRM INOICRTEO VRLUE
M.I U.I n U MM
10 «o IQ jo n 10 t i i .• .: .1
MU3K1NGUM RUN 8
CUMULRTIVE FHEOUENCT OI3TRI8UTICN
FOR 1 HOUR 502 CQNCENTRRTION3
PT STRTION 1
4HER3UREO HINU3 BRCKGRQUNO
+ CRLCULRTEO
Figure 27a
to jo to to to TO M w «
PEHCENTflGE OF CONCEMTRRTION3
LE33 THRH INOlCflTEO VRLUE
Model validation Run No. 8. Pasquill-Turner stability
assignment method and F.B. Smith dispersion calculation
method. Measured and predicted cumulative frequency
distributions of 1-hour S02 concentrations for Muskingum
Plant Station 1
78
-------
10-
\n-
.I it.c it n u n
rERCENTRGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
10 TO. n M w M to |0
H—lilt—I—I 1—
MUSKINGUM RUN 6
CUMULATIVE FREQUENCY OlSTfllBUTION
FQn 1 HOUR 302 CONCENTRATIONS
AT STATION Z
^MEASURED
^MEASURED MINUS BACKGROUND
^CALCULATED
.3 1 Z i 10 n 9Q «Q 50 00 10 BQ H
CERCENTBCE OF CONCENTRATIONS
n st as.s n.t
Figure 27b,
LESS THAN INOICATEO VALUE
Model validation Run No. 8. Pasquill-Turner stability
assignment method and F-B. Smith dispersion calculation
method. Measured and predicted cumulative frequency
distributions of 1-hour
Plant Station 2
S02 concentrations for Muskingum
O
<_)
TEnCENTAGE OF CONCENTHATIONS
CHEATER THAN INDICATED VALUE
n •» is n n -u la n
-------
rERCENTHGE OF CONCENTRRTIONS
GRERTER THRN INDICATED VflLUE
i ».» ts.j n N n 10 M TO to to «o M n it s
-I 1-
MUSKINGUM RUN 6
CUHULRT1VE FREQUENCY DISTRIBUTION
FOR I HOUR S02 CONCENTRATIONS
RT STflTION .»
TERCENTRGE OF CONCENTRRTIONS
LESS THAN INDICATED VRLUE
Model validation Run No. 8. Pasquill-Turner stability
assignment method and F-B. Smith dispersion calculation
method. Measured and predicted cumulative frequency
distributions of 1-hour S02 concentrations for Muskingum
Plant Station 4
Figure 27e
PERCENTAGE OF CONCENTRATIONS
GRERTER THRN INDICATED VRLUE
I.M •».» M.S » M « to 10 TO 10 50 »0 SO W 10 5
••t,
MUSKINGUM RUN 8
CUMULATIVE FREQUENCT DISTRIBUTION
FOR I HOUR S02 CONCENTRRTIONS
RT STflTION RLL
QHER3URED
AHER3URED MINUS BACKGROUND
^.CRLCULRTEO
.01 .OS .l.t .5 I I I 10 tO n 40 JO «70 to M U 9» U M.S M.9 »>.«
PERCENTflGE OF CONCENTHRTIONS
LESS THRN INDICflTED VflLUE
Model validation Run No. 8. Pasquill-Turner stability
assignment method and F-B. Smith dispersion calculation
method. Measured and predicted cumulative frequency
distributions of 1-hour SOo concentrations for Muskingum
Plant for all stations
80
-------
"D99.39
PEflCENTACE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
«r SO no jo n to S c I .s .f .,
NU3KINGUM RUN 9
CUMULATIVE FREQUENCY DISTRIBUTION
FOB 1 HOUR 302 CONCENTRATIONS
AT STATION 1
MEf)3UflED
^MEASURED MINUS BACKGROUND
^CALCULATED
Figure 28a
.01 .OS .!.« .Sit S 10 to 90 <0 SO CU 70 to „
PEOCENTACk 8F CONCENTRATIONS
LESS THAN IKOUATEO VALUE
Model validation Run No. 9. F-B. Smith stability
assignment and dispersion calculation method. Mea-
sured and predicted cumulative frequency distributions
of 1-hour SO,, concentrations for Muskingum Plant
Station 1
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
«. w 99.9 S9.5 an n to to n K so »o 90 to 10 s t i ,s .e .1
.Ol*o
MU3KJNOUM HUN 9
CUMULATIVE FPEOUENCT QISTPIBUTIOH
FOR 1 HOUR 382 CONCENTRATIONS
AT STATION
f1EP3UREO MINUS BACKGROUND
CALCULATED
.s i e s to n 90 IQ so M TO *o »o
rERCENTflGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
Figure 28b,
Model validation Run No. 9. F-B- Smith stability
assignment and dispersion calculation method. Mea-
sured and predicted cumulative frequency distributions
of 1-hour
Station 2
S00 concentrations for Muskingum Plant
81
-------
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
I 99.9 99.% » M 9SW M TO M $0 10 90 (O 10 t
t t .s ,e .t
MU3KINGUM PUN 9
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
PT STATION 3
(^MEASURED
^MEASURED MINUS BACKGROUND
.•.CALCULATED
Figure 28c
! S tO CO »0 «0 SO «i TO to 90
PERCENTAGE OF CONCENTRATIONS
LESS TMAN INDICATED VALUE
Model validation Run No. 9. F.B. Smith stabilty
assignment and dispersion calculation method. Mea-
sured and predicted cumulative frequency distributions
of 1-hour S0« concentrations for Muskingum Plant
Station 3
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
9.9 99.5 99 M 95 90 M TO >0 So 10 90 CO 10 S C I .5 .t .1 .UI'Q
MUSK INCUR RUMS
CUMULATIVE FREOUENCT DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
AT STATION U
0MEA3URED
^MEASURED MINUS BACKGROUND
^CALCULATED
t s to to n «Q so •!* TO H 50
TERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
n 19 n.s 91.9 ».»
Figure 28d
Model validation Run No. 9. F.B. Smith stability
assignment and dispersion calculation method. Mea-
sured and predicted cumulative frequency distributions
of 1-hour S0« concentrations for Muskingum Plant
Station 4
82
-------
rERCENTBGE OF CONCENTRATIONS
GREflTER THBN INDICATED VALUE
n.i n w
MUSKINGUM RUNS
CUHULPTIYE FREQUENCY DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
AT STATION (ILL
0MER3UREO
AHEASURED MINUS BACKGROUND
+CBLCULBTEO
.01 .as .i.t .5
t S 10 MMWWMTCM W
PERCENTAGE OF CONCENTRRTION3
LE33 THRN INOJCRTCO VPLUE
Figure 28e.
Model validation Run No. 9. F.B- Smith stability
assignment and dispersion calculation method. Mea-
sured and predicted cumulative frequency distributions
of 1-hour S0? concentrations for Muskingum Plant for
all stations
PERCENTAGE OF CONCENTRATIONS
TURN INDICATED VALUE
I Oa TO M M W )* to >'i
.S .t ,
O)-
03.
10-
in-
£2
-------
•b99
^J..
W-
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
.99 ».9 n.S 99 »• IS M 10 10 tO SO HO 90 to 10 S t I ,S .t .1
•(—I—I 1—I I I 1 I t I I I I 1 4 I I I I I .III
MU3KINCUM RUN 10
CUMULATIVE FREOUENCt DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
AT STATION Z
OhEASUREO
AMEASURED MINUS BACKGROUND
^CALCULATED
t 5 10 M 30 «0 So 60 7Q 10 90
PERCENTAGE OF CONCENTRflTIONS
LESS TMBN INDICATED VALUE
91 99 99.S 99.9 99.99
Figure 29b,
Model validation Run No. 10. Variable buoyancy flux.
Measured and predicted cumulative frequency distributions
of 1-hour
Station 2
S09 concentrations for Muskingum Plant
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
.99 n.9 n.S M » 9S 90 90 TO >0 50 10 90 to 10 t C I .5 .t
nUSKINGUH RUN 10
CUnULATIVE FREOUENCT DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
PT STATION 3
OHEA3URED
^MEASURED MINUS BACKGROUND
^.CALCULATED
O
.01 .01 .l.t .S
t s 10 to >o » so
-------
rERCENTAGE 8F CONCENTRATIONS
GREATER THAN INDICATED VALUE
M M 19 M 10 0 SO 10 30 Co
-I—I 1—I 1 I 1 1-
.".-0
MUSKINGUM RUN 10
CUMULATIVE FREQUENCY DISTRIBUTION
FOR I HOUR 302 CONCENTRATIONS
AT STATION ALL
^MEASURED
^MEASURED MINUS BACKGnQUNCi
^CALCULATED
10 CO 90
-------
=>t>
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VHLUE
i n.i n.i •> •• u n n n n to to x to 10 6 i i t .t
•••b
o>
CANAL PlflNT RUN II
CUMULATIVE FREOUENCY DISTRIBUTION
FOR 1 HOUR S03 CONCENTRATIONS
flT STATION 1
gMEASURED
^MEASURED MINUS BACKGROUND
.,. CALCULATED
.01 .at .i.t .t i
C ( ID ZO SO «0 CO M 70 M W
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
Figure 30a
Model validation Run No. 11. Variable buoyancy flux.
Measured and predicted cumulative frequency distribu-
tions of 1-hour SQ~ concentrations for Canal Plant
Station 1
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
,».i> ».• n.: it •• «s M «o TO to 10 no JO eo ID
r i .s .t .1
. co-
I- "~-
(X w~
en ^.
t—
z =•-
UJ
O
-------
Figure 30c
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VfiLUC.
...•b
CANAL PLANT HUN II
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR S02 CONCENTRATIONS
AT STATION 3
^MEASURED
^MEASURED HINUS BACKGROUND
^CALCULATED
.01 .« .1.1
i 10 to JO «0 SO 00 10 »0 «0
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
MM M.t M • n.H
Model validation Run No. 11. Variable buoyancy flux,
Measured and predicted cumulative frequency distribu-
tions of 1-hour S02 concentrations for Canal Plant
Station 3
PERCENTAGE OF CONCENTRATIONS
GREATER THAN INDICATED VALUE
.M M.I M.I MM t5 tO 10 TO «t> SO HO SO M 10 t
o
="!=>
" «-
d
OC
.«-b
-t—t -
1 - 1
1
CANAL PLANT RUN II
CUMULATIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR 302 CONCENTRATIONS
AT STATION U
OHERSUREO
^MEASURED HINUS BACKGROUND
^CALCULATED
t I 10 to » u to «o TO n M
PERCENTAGE OF CONCENTRATIONS
LESS THAN INDICATED VALUE
M M M.S M.t M.M
Figure 30d
Model validation Run No. 11. Variable buoyancy flux
Measured and predicted cumulative frequency distribu-
tions of 1-hour S09 concentrations for Canal Plant
Station 4
87
-------
ff
oc
LU
fEflCENTRGE OF CONCENTRATIONS
GREATER THAN INDICATED VRLUE
N.I MM Wn M TO U (0 » JO tO 1»
CflNflL PLflWT RUN II
CUltULRTIVE FREQUENCY DISTRIBUTION
FOR 1 HOUR SOZ CONCENTRRTIONS
flT 3TRTION RLL
QHERSUREO
AHER3UREO MINUS BACKGROUND
+CALCULRTED
r s to TO jq «o w «o TO »o to
PERCENTflGE OF CONCENTRATIONS
LESS THAN INDICATED WLUE
Figure 30e.
Model validation Run No. 11. Variable buoyancy flux
Measured and predicted cumulative frequency distribu-
tions of 1-hour S0? concentrations for Canal Plant
for all stations
88
-------
SECTION V
CONCLUSIONS AND RECOMMENDATIONS
Based upon the results of this study we would recommend that the methods
currently used for the calculation of dispersion coefficients and the se-
lection of stability classes not be replaced by alternate techniques, at
least until further model validation studies are conducted. Since data
from only two power plants were used in this study the results could
hardly be called definitive. Nevertheless, even from these limited re-
sults, we may draw a number of conclusions:
1. The similarity between the Pasquill-Turner and Gifford-Briggs
dispersion coefficients (except for stability A) will require
that a large number of model validation exercises be carried
to determine which method is more accurate.
2. The use of the Smith-Singer stability assignment and disper-
sion calculation methods in the Single Source Model may yield
unrealistic frequency distributions of 1-hour concentrations-
This observation must be qualified, however; by the fact
that the validation was carried out only for the Muskingum
Plant. Since the rather subjective stability assignment
scheme may have been carried out differently at the
Muskingum Plant, the Smith-Singer version of the Single
Source Model may give better agreement with measured con-
centrations if applied elsewhere.
3. Due to the strong variation of calculated concentrations as a
function of stability, the use of fractional stability assign-
ments should, in principle, lead to more accurate model pre-
dictions. The F.B. Smith stability classification method did
not, however, provide better agreement between measured and
calculated concentration frequency distributions, primarily
because of its tendency to underestimate the stability class.
89
-------
4. The use of a variable buoyancy flux In the Single Source Model
did little to improve the agreement between measured and cal-
culated concentration frequency distributions. This conclu-
sion is similar to others reached when more detailed or appli-
cable emissions or meteorological data has been used in model
validation exercises. The success or failure of the model in
any given application is much more a function of the assumptions
regarding plume rise, dispersion, and terrain effects that form
the theoretical basis for the model.
90
-------
SECTION VI
REFERENCES
1. Mills, M. T. and F. A. Record. Comprehensive Analysis of Time Con-
centration Relationships and the Validation of a Single Source Dis-
persion Model. Publication Number EPA-450/3-75-083. Prepared by
GCA/Technology Division for the U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina. March 1975.
2. Mills, M. T. and R. W. Stern. Model Validation and Time-Concentration
Analysis of Three Power Plants. Publication Number EPA-450/3-76-002.
Prepared by GCA/Technology Division for the U.S. Environmental Protec-
tion Agency, Research Triangle Park, North Carolina. December 1975.
3. Briggs, G. A. Plume Rise USAEC Critical Review Series TID-25075,
National Technical Information Service, Springfield, Va. 22151.
1969.
4. Briggs, G. A. Some Recent Analyses of Plume Rise Observation,
pp. 1029-1032, in Proceedings of the Second International Clean Air
Congress, edited by H. M. Englund and W. T. Berry. Academic Press,
New York. 1971.
5. Briggs, G. A. Discussion on Chimney Plumes in Neutral and Stable
Surroundings. Atmos. Environ. 6, 507-510. July 1972.
6. Gifford, F. A. Atmospheric Dispersion Calculation Using the Generalized
Gaussian Plume Model. Nucl Saf. 1(3). 1960.
7. Turner, D. B. Workbook of Atmospheric Dispersion Estimates. U.S.
Environmental Protection Agency, Office of Air Programs. Publication
Number AP-26.
8. Cramer, H. E. A Practical Method for Estimating the Dispersal of
Atmospheric Contaminants. In: Proceedings of the First National
Conference on Applied Meteorology. Hartford, Connecticut, American
Meteorological Society, p. C-33 - C-55. October 1957.
9. Pasquill, F. The Estimation of the Dispersion of Windborne Material.
Meteorol Mag. 90:33-49. 1961.
91
-------
10. Mead, P. J. Meteorological Aspects of the Peaceful Uses of Atomic
Energy. WMO Tech Note. 3, Part I. 1960.
11. Turner, D. B. A Diffusion Model for an Urban Area. J Appl Meteor.
3:83-91. February 1969.
12. Smith, M. E. and I. A. Singer. An Improved Method of Estimating
Concentrations and Related Phenomena From a Point Source Emission.
J Appl Meteor. 5(5):631-639. October 1966.
13. Smith, M. E. and T. T. Frankenberg. Improvement of Ambient Sulfur
Dioxide Concentrations by Conversion From Low to High Stacks. J Air
Pollu Control Assoc. 25(6)-.595-601. June 1975.
14. Singer, I. A. and M. E. Smith. Atmospheric Dispersion at Brookhaven
National Laboratory. Air and Water Pollution International Journal.
Pergamon Press 1966. Vol. 10, pp. 125-135.
15. Smith, M. E. (ed.). Recommended Guide for the Prediction of the
Dispersion of Airborne Effluent. Am Soc Mech Eng. Second Edition.
1973.
16. Briggs, G. A. Diffusion Estimation for Small Emissions. U.S.
Department of Commerce. NOAA-ERL-ARATDL Contribution Number 79.
Oak Ridge, Tennessee. May 1973.
17. Smith, F. B. A Scheme for Estimating the Vertical Dispersion of
a Plume From a Source Near Ground Level, Chapter XVII. In: Proceed-
ing, N.A.T.O. Committee on the Challenge of Modern Society, Paris,
France, October 2-3, 1972. (Proceedings Number 14, Air Pollution
Technical Information Center, U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina. 1973).
18. List, R. J. Smithsonian Meteorological Tables. Sixth Revised Edition
Published by the Smithsonian Institute, Washington, D.C. 1951.
19. Hosker, R. P. Jr. Estimates of Dry Deposition and Plume Depletion
Over Forests and Grassland. (Presented at the IAEA Symposium on
the Physical Behavior of Radioactive Contaminants in the Atmosphere.
Vienna, Austria. November 12-16, 1973.)
92
-------
APPENDIX A
TURNER SCHEME FOR STABILITY CLASSIFICATION
The following scheme for stability classification was described by D. Bruce
Turner in the February 1964 edition of the Journal of Applied Meteorology:
This system of classifying stability on an hourly basis for research in
air pollution is based upon work accomplished by Dr. F. Pasquill of the
British Meteorological Office. Stability near the ground is dependent
primarily upon net radiation and wind speed. Without the influence of
clouds, insolation (incoming radiation) during the day is dependent upon
solar altitude, which is a function of time of day and time of year. When
clouds exist their cover and thickness decrease incoming and outgoing
radiation. In this system insolation is estimated by solar altitude and
modified for existing conditions of total cloud cover and cloud ceiling
height. At night estimates of outgoing radiation are made by considering
cloud cover. This stability classification system has been made completely
objective so that an electronic computer can be used to compute stability
classes. The stability classes are as follows: (1) Extremely unstable;
(2) unstable; (3) slightly unstable; (4) neutral; (5) slightly stable;
(6) stable; (7) extremely stable. Table A-l gives the stability class as
a function of wind speed and net radiation. The net radiation index ranges
from 4, highest positive net radiation (directed toward the ground), to
-2, highest negative net radiation (directed away from the earth). Insta-
bility occurs with high positive net radiation and low wind speed, sta-
bility with high negative net radiation and light winds, and neutral con-
ditions with cloudy skies or high wind speeds.
93
-------
Table A-l. STABILITY CLASS AS A FUNCTION OF NET RADIATION AND WIND SPEED
Wind speed,
knots
0,1
2,3
4,5
6
7
8,9
10
11
>12
Net radiation index
4
1
1
1
2
2
2
3
3
3
3
1
2
2
2
2
3
3
3
4
2
2
2
3
3
3
3
4
4
4
1
3
3
4
4
4
4
4
4
4
0
4
4
4
4
4
4
4
4
4
-1
6
6
5
5
4
4
4
4
4
-2
7
7
6
6
5
5
5
4
4
The net radiation index used with wind speed to obtain stability class
is determined by the following procedure:
1. If the total cloud cover is 10/10 and the ceiling is
less than 7000 feet, use net radiation index equal
to 0 (whether day or night).
2. For night-time (between sunset and sunrise):
a. If total cloud cover _<4/10, use net radiation
index equal to -2.
b. If total cloud cover >4/10, use net radiation
index equal to -1.
3. For daytime:
a. Determine the insolation class number as a
function of solar altitude from Table A-2.
b. If total cloud cover £5/10, use the net radia-
tion index in Table A-l corresponding to the
insolation class number.
c. If cloud cover >5/10, modify the insolation
class number by following these six steps.
(1) Ceiling <7,000 ft, subtract 2.
94.
-------
Table A-2. INSOLATION AS A FUNCTION OF SOLAR ALTITUDE
Solar altitude
(a)
60° 7000 ft but < 16,000 ft, subtract 1.
(3) Total cloud cover equal 10/10, subtract 1.
(This will only apply to ceilings _> 7000 ft
since cases with 10/10 coverage below
7000 ft are considered in item 1 above.)
(4) If insolation class number has not been
modified by steps (1), (2), or (3) above,
assume modified class number equal to inso-
lation class number.
(5) If modified insolation class number is less
than 1, let it equal 1.
(6) Use the net radiation index in Table A-l
corresponding to the modified insolation
class number.
The Pasquill-Turner technique for stability class assignment is the one
currently employed in the Single Source Model Preprocessor program except
that Table A-l has been expanded to provide a greater resolution according
to wind speed (see Table A-3).
95
-------
Table A-3. ADAPTATION OF TABLE A-l FOR USE IN THE SINGLE SOURCE
MODEL PREPROCESSOR PROGRAM
Wind speed, knots
1
2
3
•4
5
6
7
8
9
10
11
>12
Net radiation index
4
1
1
1
1
1
2
2
2
2
3
3
3
3
1
2
2
2
2
2
2
3
3
3
3
4
2
2
2
2
3
3
3
3
3
3
4
4
4
1
3
3
3
4
4
4
4
4
4
4
4
4
0
4
4
4
4
4
4
4
4
4
4
4
4
-1
7
7
6
5
5
5
4
4
4
4
4
4
-2
7
7
7
7
6
6
5
5
5
5
4
4
96
-------
APPENDIX B
LISTINGS OF THE FRACTIONAL STABILITY PREPROCESSOR
PROGRAM AND CORRESPONDING VERSION OF THE
SINGLE SOURCE MODEL
97
-------
PR.OCWMRE PPTIONS(MAIN);
STMT LEVEL N6ST
1 _ PREP: PROCEDURE OPT IONS(MA IN I;
/* OCTOBE'R 1972 VERSION */
2 _l DEj:LAR!^J>HVJ=IL£_RECORD;
3 'I DECLARE MET FILE RECORD OUTPUT;
_4 !_ _ _ DECLARE IDC FIXED DECIMAL! 5,0),
(YRC,LWD,XHR) FIXED DECIMAL(2 ,0),
lIND,IS_KY,IROgF,IRADXjIREC INITIALJl ) ,1 T J.IDY, IHR^KHRj,! Yj
IX INITIALI65549) ,IMO INITIALU),
ICN,KSTSP,ZONE,KST<24J _INJTJALJ (24) 0)I_FIXED BIN(31)t
• IDF AC (12) INITIAL (0,31, 59, 90,120, 151,18 1,212,243,273,304,334)',
ANGLI3) INIJLAy-6°-»_J5-iiJ.5ii_jJ=_V!XPJR)_FIXEJ) DECIMAL13,0) ,
IFVR FIXED DECIMAL (1,0"),
(YFL,pAYNO,TDAYNO,SIND,COSD,SINTDiCOSTD,SIGMA,DSINtDCQSi
SINLAT.COSLAT,ALAT,ALONG,HCOS.H2,HI,CONST INITIAL!57.29578),
ALF,ALFSN,AMM,TSR,TSS) FLOAT DECIMALT
(S,XAF,XAFPl,XAFMi,XMN,XMNPl,XMNMl ) FIXED DECIMAL(8,3 );
_5_ I DECLARE HSKIP INITIAL(O) FIXED BIN131);
6 1 DECLARE (COEF(4,14) INITIAL (. 3696429~E-K)1 , .3877143E+01,"
.414 3571 E+01,.4479286E+Q1,.462E*01,.4755E+01,..49328 57E*01.r
.36494956+01,.3913232E+01,.4554444E+01,.5839798E*01,
.7017677E*OI, .9922898E-*-01 ,.1471 869E*02i
-. 9542929 E-02 ,-.3097042E-OI ,-. 6 534488E-01 ,--. 103329, -. 11 96898,
-. 13 5526, -.1548445,-. 837421 8E-02,-. 5276575t -01, -.1726251,
-. 42 60 185, -.7 639 839, -.2 15572 7 E+01 ,-.4151976.3+01,
__.__ ___
. 1 52 6299E -02, .173896 1E-O2,. 1946 537E-02,. 12 19336E^O2,
.3AQ75046jr02,.Ilp4257Ej-01jL.2452Q2E-01t.5354:618E-01i _
.28391i7, .5724983,
.20202C2E-06,-.1161616E-05,-.4343434E-05, __ _____
-.71212J2E-05,-.7853535E-05,-.8939394E-05t
-.95 20202 E-05 ,-. 1 17845 IE -03 ,- .2356902E-03 ,
-.53 87205 E-03 ,-• . 77441 o"8E-03 ,- . 1 3 80471 E-02 ,
-.1416177E-01 ,-.284291E-01) , ____^
CLOUD(9) INITIAL(8.,7.,6.,5. ,4. ,3.,2.,1 .,0.)", CMULT(9) INITIAL
( .23,.45f .59,.67,.72,.76,.81,.89,1.07),WIND(7) INITIAL
(8.,6.,5. ,4.,3.,2.,0.),XMULT,WATTS,WATTS1,FKST(241 INITIAH
(24)^ Oi)iPJL,P2,CJ.D,ZjZALF,AO)_F^LOAT DECIMAL;
DECLARE 1 INDATA,
2 1(3 PICTURE_!99999^f
2 IYEAR PICTURE '99',
2 IMONTH PICTURE «99',
2 IDAY PICTURE •99»,
2 IHOUR PICTURE '99'.
2 ICEIL CHAR(3),
2 IDUM1 CHAR(^2],
2 "iDIR PICTURE '9>*,
2 ISPEFD PICTURE '99',
2 IDUM2 CHAR(4),
2 ITEHP PICTURE '999',
2 IDUM3 CHAR(29),"
2 ICOVER CHARM ),
2 IDUM4 CHAR(l),
1 OUTDATA,
2"YR PICTURE '99',
2 MONTH PICTURE ' 99 • ,
2 DAY1 PICTUKC •0=9',
98
-------
PREPt_..PROC€IX»E OPTIONS!MAINJ I
STMT LEVEL NEST
2 KKST<0:23) PICTURE '99»,
2 SPEED(Qt23) PICTURE '999V99',
2 TEMP(0:23) PICTURE '999V9S
2 *FV(0:23) PICTURE '999't
2 FVR<0:23) PICTURE •99~9t»
2 HL_H<_2tp:23» _PICjyRE ^99999V99
8
9
10
11
13
14
17
18
19
21
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
48
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
I
1
1
i
i
i
i
i
i
i
i
2
3
DECLARE TITLEA CHAR(8):
DECLARE TITLEB CHAR i 8 ) ;
Fl: FORMAT(COL(14),F (4,0) , COL (25) ,F(4,0>) ;
ON ENDFILE)) ;
99
-------
PREP: PROCEDURE OPTIONS(HAIN);
STMT
49
50
51
54
56
57
60
61
63
64
65
68
70
73
74
75
77
78
80
81
82
83
85
86
~~87
89
90
91
93
94
95
9*
97
99
100
101
102
103
104
105
106
LEVEL
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
' '~r
i
i
i
i
i
i
2
2
2
2
2
2
1
1
i
i
NEST
3
3
2
3
2
2
3
3
2
2
2
3
2
3
3
/*
2
2
2
2
/*
2
/*
2
2
2
2
/*
2
2
2
/*
2
2
2
2
2
2
2
2
2
2
2
2
2
2
/*
GO TO NEWREC;
END;
IF IYEAR -=YRC THEN DO; PUT SKIP FILE( SYSPRINT) EDIT
{•YEAR IS ', IYEAR, • INSTEAD OF '.YRC,1 IREC=',IRECJ
;
HSKIP=I;
END;
CONVERSION OF ISKY £ IROOF */
IF ICEIL=f • THEN IROOF=998;
ELSE IROOF=ICEIL;
"F irrVER=§-' THEN ISKY=10;
ELSE ISKY=TCOVER;
CDM.cRT TEHPERATIfRE FROM FAHREt«EIT TO KELVIN */
nUTD ATA. TEMP 'KHR)=0. 5556* JITEMP-32.) +273. 15 ;
CONVERT WIND SPEED FROM KNOTS TO METERS/SECOND */
S=ISPEED*0. 51444 ;
IF s360/ THEN
OUTDATA.FVR (KHR ) =OUTDATA .FVR ( KHR ) -360 . ;
DETERMINE STABILITY */
100
-------
PROCEDURE. OPTIONS(KAJN) j
STMT \
107
109
111
113
11*
115
116
117
118
119
120
121
123
124
125
126
127
129
130
132
133
13*. _
133
136
137
138
139
140
141
142
144
145
146
147
148
149
150
151
152
153
155
156
157
160 "
161
162
LEVEL I
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
I
1
1
1
_L._
1
1
1
1
l
1
1
1
1 _
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
H6ST
2
2
2
2
2
2
2
2
2
2
2
3
3
2
2
2
2
2
3
3
2
_2_.._
2
2
2
2
2
2
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
1
IF S>8. THEN GO TO BB ;
IF IHOURTSS THEN GO TO C;
/* DETERMINE THE ANGLE OF ELEVATION */
DAYTIME: Hi= ) ;
ZALF=90.-ALF: _ _.
A0=. 57+ ,0045*ZAL F;
ZALF=ZALF/CONST;
WATT 51=135. 3*AO**(1. /COS (ZALF))*C OS I ZALF);
/* INTERPOLATE INCOMING SOLAR RADIATION FACTOR */
DO 1=2 TO 9;
IF CLDXLOUDdl £ CLD<=CLOUD { 1-1 ) THEN GO TO A;
END;
A: K=I-l;
XNULT=CMULT(Kl-< (CLOUD (K )-CLD)* (CMULT (K )-CMULT( I ) ) /(CLOUD (K )-
CLOUD(I))):
WATTS=WATTS1*XMULT;
IF WATTS<10. THEN GO TO C;
/* FIND STABILITY USING RADIATION, HIND, AND CLOUC COVER */
DO J=2 TO 7;
IF S>=WIND(J) G S<=WIND(J-1) THEN GO TO B;
END;
B ! H^ J~~ 1 *
P1=CCEF<1,M) +COEF(2iM)*HATTS*COEF(3,M)*WATTS**2+COEF(4tM)
*WATTS**3;
P2=COE-ll , J)»COEF(2,J J*WATTS*COEF(3JLJ)*WATTS**L-t-COeF( 4, J)
*WATTS**3;
FKST(KHR>=P1--((WINO(M)- S )*( PI -P2 »/ (HINDI M )-WIND( J J ));
GO TOD;
BB: FKST=3.6;
GO TO D;
/* CALCULATE STABILITY USING CLOUD COVER AND HINDSPEED */
C: DO J=2 TO 7;
IF S>=HIND(J) £ S<=WIND(J-1) THEN GO TO CC;
END;
CC: M*J+6;
MM=J+7;
K=J-l;
P1=COEF(1 ,M)+COEF(2,M)*CLD+COEF(3tM)*CLD**2+COEF(4,M)*CLD**3;
P2=COEF(1,MM)+COEF{2»MM)*CLD+COEF(3,MM)*CLD**2+COEF(4,MH)*
CLD**3;
FKSTIKHR) =?!-( (WINDJK)- S ) * 1 PI -P2 ) / (WIND (K )-W IND( J ) ) ) ;
D: KSf(KHR)=FKST(KHR 1+0.9;
ITEST=10.*(FKST(KHR)+0.4) ;
OUTDATA .KKST < KHR ) =ITEST
IF ITEST>70 THEN OUTDATA .KKST (KHR ) =70 ;
/* CALCULATE MIXING HEIGHT */
IHR«=KHR+1 ;
XHR=IHR;
IF iHR>i4 THEN IF XHR<=TSS THEN DO:
HLHI 1,KHR)=XAF;
HLH(2,KHR)=XAF;
GO TO ^EWPCC; ?NO;
101
-------
PREP: PROCEDURE qPTIONS.IMAINJ ;_
STMT LEVEL NEST
164
165
167
169
170
172
173
175
177
179
180
182
183
185
186
188
190
192
193
194
195
196
197
198
199
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
1
1
1
I
1
1
1
. 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
Z
4
4
3
3
3
2
3
3
4
4
3
3
3
2
3
3
2
3
3
3
2
3
3
3
2
2
1
1
1
1
1
1
__.
IND=2;
IF XHR>TSS THEN DO;
IF KSTtKHRI-*=4 THEN 00;
HLH(2,KHR)=XAF + (XMNPl-XAF)*«XHR-TSSJ/<24.-TSSn;
IND=1 ; END;
HLH(IND,KHR)=XAF-MXAFP1-XAF)*( ( XHR-TSS ) / (38.-TSS ) );
"IF IND=2~ THEN HLHI1 ,KHR )=HLH« 2,KHR ) ;
GO TO NEWREC; END;
IF XHR<=TSR THEN DO;
KSTSP=KST(KHR1 ;
IF KST(KHR)-=4 THEN DO;
HLH12fKHR)=XHN;
IND=1 ; END ;
HLH(IND,KHR)=XAFMl-MXAF-XAFMl)*(f 24.-TSS+XHR ) / I24.-TSS+14. ) ) ;
IF IND~=2 THEN HLH11 ,KHR )=HLH< 2 ,KHR ) ;
GO TO NEWREC; END;
IF KSTSP-=4 THEN DO;
HLH(2»KHR)=XMN+IXAF-XMN)*( ( XHR-TSRL/li^-TSR III
HLH(1,KHR)=XAF*(XHR-TSR)/<14.-TSR) ;
END;
ELSE DO;
HLH(1,KHR)=XAFM1+IXAF-XAFM1)*((24.-TSS+XHR)/C24.-TSS+14.));
HLH(2,KHR)=HLH(1,KHR);
END;
/* READ NEXT HOUR'S MET DATA */
NEWREC: IF HSKIP=0 THEN DO;
READ =TLE(ASHV) INTO! INDATA ) ;
ISEC--:: EC-H;
END;
ELSE HSKIP=0,
HLOOP: END;
/* UPDATE MIXING HEIGHTS */
XMNMI=XMN;
XAFM1=XAF;
XMN = XMNP1 ;
XAF=XAFP1 ;
/* WRITE A DAY'S CALCULATIONS ON TO TAPE */
WRITE FILE(MET) FROMtDUTDATA ) ;
DLOOP: END;
LAST: WRITE FILE(MET) FROM (OUTDATA ) ;
CLOSE FILE(ASHV),FILE;
PUT SKIP FILE (SYSPRINT) EDIT
(• ALL RECORDS HAVE "BEEN [PROCESSED ') «A(33)J;
GO TO AGAIN;
FINI SH : END" >REP; "
102
-------
FORTRAN IV Gl RELEASE 2.0
MAIN
DATE 76153
15/2V/G9
C*** "PROGRAM JMHCaSl (KLUG VALIDATION) OOOC1800
C*** __J1lS_piOGRAM CALCyLA_TES_HOURLY_ANq_2*-HqURLY_ CONCENTRATIONS FOR00001900
•-- " "A YEAR "ABOUT A" SINGLE SOURCE. ' '" " ""' "00002000
OCTOBER 1972_VERS_IO_N_*** _„.___ _ .OP002100
C***bESCRiPtlON OF ARRAYS*** " "00002200
C*** DHRSIL)=RECEPTOR ELEVATION MINUS SOURCE ELEVATION(METERS) 00002300
C***
***
C***
C***
C***
C***
C***
aHOUR(IHOUR") = HOURLY SOURCE"STRENGTH OF S02(GM/SlO
HMAX (RECEPTOR,3 1 1=HOURLY CONCENTRATION, _2fDAYt_ 3fHplJR_
DMAXJRECcPTOR ,2~) 1=24-HOUR CONCENTRATION", 2=DAY~
HMAXYRI5) 1=MAX HOUR CONCENTRATION, 2=DIRECTION, 3=DISTANCE,
5=HOUR
1=«AX 2_4-HOOR CONCENTRATIpN, 2=DIRtCTION, ?=OISTANCE,
CHI(RECEPtOR,26) l-24=HOUR LY "CONCEN'TRATIONS",
26=ANNUAL CONCENTRATION
lUR""!5
00002400
000025OO
C***
0001
OOO 2
0003
NSTA=NUMb£R OF STATIONS UP TO 7
NMOO=NUM8ER OF MODEL STATIONS =NSTA*36
DIMENSION r) TiTLc
PQRMATI ' 1' .20A4//1X)
HAD CARD TO INITIALIZE STABILITY AND TO DETERMINE RURAL I
C***MIXING HEIGHTS
0014
0015
0016
0017
0018
0019
0020
0021
0022
5502
603
604
RE AD (IN, 5502) KSTL , IUR, I DENT ,NS TA
KSTLP=10*KSTL
FORMA TIT 11, 11 , T17.il ,T20,5A4,T45,I1 )
IFINSTA.LT.1.0R.NSTA.GT.7) NSTA=7
^EAD(IN,603) (DHRSIL ) ,L=1 ,NSTA)
FORMAT(7F10.2 )
^RITc I 10,604) (OHRSIL ),L = 1 ,NSTA )
FORMAT!/, IX, 'ELEVATION DIFFERENCES BETWEEN RECEPTOR A\n
CATIONS=' ,7E10.2,/I
WRITE! 10,5504, ) IUR
OR URBAN
_0_OOC3700
' 000038615"
_0 00 03 9 00
00004100
00004200
00004300
"00004400
00004500
00004600
00004700
00004800"
00004900
"OG6C5COO"
OC'005100
00006200
00005300
00005400
00005500
00005600
SOURCE
00005700
00005800
00005900
0000600^
00006100
LOC00006200
00006300
103
-------
FORTRAN IV Gl RELEASE
MAIN
DATE =* 76153
1 5/29/09
0023
5504 FORMATUX, 'IUR=' ,12, /)
C***INITIALIZATIONS
OOC06bOO
0024
0025
0026
0027
0028
0029
6~030
0031
0032
0033
0034
0035
0036
0637
0038
0039
0040
0041
0042
0043
0044
0045
0046
0047
0048
0049
0050
0051
0052
0053
0054
0055
0056
0057
NMOO=NSTA*36
NS=0 " " ' " ~
DO 4 1=1 tNMOO
CHI(I, 26 1=6.0
DO 3 J=l ,3
3 HMAXII, J )=0.0
DO 6 J=l,2
6 OMAXII ,J )=0.0
4 CONTINUE
C***INPUT RECEPTOR RANGES
3 t ADI IH, 605 t RNG
605 FORMATJ7F10.3)
C***CALCJLATE AND STORE SItHAS FOR 6 STAB. C NSTA OIST.
C***DISTANC5 IS ASSUMED TO BE IN K.I LOMETERS***
C***
DO 7 J=l ,NSTA
X=RNG( J)
00 7 KSTP=10,60
CALL SIGMA(X,X,KSTP,SY,SZ)
SYD(J,KSTP1=SY
SZDU,KSTP)=SZ
7 CONTINUE
c***
C***INPUT SOURCES TO PF CONSIDERED
2 NS=NS+1
READdN, 5501 ) SOURCE
iJO FOKM^Tdt.' ,fb.Z,e,X,^f%.2)
VF."S) = 0.78 539 B*VS*0*D
I r (HPINS ).Lt. 0.001 ) GO TCI 5
WHIT? ( 1 0,5 5 5i ) SU'I^CE
55b5 FORMAT! IX, 20A4)
WHITE (10, 201 I NS.HPINSI \ , TS(NS), VS,D,VF(NS)
^01 FORMATI1X, 'NS=' ,12, [ HP=',F7.2,1 TS=',F5.0,' VS=',
*F7.2,' D='iF6.2,f VF = • ,F8 .2//1X )
GO TO 2
5 NS=NS-1
WRITE! 10,203) ( RNG( J ) , J = l , NST A)
203 FORMAT(« " KANGE(KM)= ', 7F7.2,/)
C***
C***6EGIN LOOP ON 'JAYS***
DO 90 IDY=1,365
00006800
00006900
00007000
00007100
OOOC7200
00007300
0000740f
00007SOO
00007600
00007700
00007 &00
00007000
0000800C
00008100
OOOOS200
OP003300
00008*00
OO008500
00009000
00009100
00009200
O0009300
i.i QO 00500
(p
-------
FORTRAN IV Gl RELEASE 2.0
MAIN
DATE - 76153
0058
0059
6060
00$1
0062
0063
0064
OO65
0066
0067
0068
0069
0070
0071
0072
0073
00>*
0075
0076
0077
0078
0079
0080
0081
0082
OO83
0084
0085
0066
0087
0088
0089
0090
0091
0092
0093
0094
VPS=0.0
UPS=0.0
wss=o.o
DO 33 IR=1,NMOD
DO 33 IHR=1,25
33 CHI(IR|IHRI=1.0E-50
HMAXT»0.0
MIH-0
MJH=0
C***
C***INPUT INFORMATION FROM MET FILE***
C***
JODAY=JDAY
READ! 9, 400) JYR , I MO, JOAY, ISTABP, AWS , TEMP , AFV, AFVR ,
*( (HLHU, j), j= 1,24 ),!=!, 2)
400 FORMAT(2I2,I3,24I2,24F5.2,24F4.1,24F3.0,24F3.0,48F8.3)
DO 399 LL=1,24
IF( ISTABP (LL).LT. 10) ISTABP (LL) =10
IF(ISTABPtLL) .GT.70) I STAB P( LL) =70
ISTAB1LL ) = Fl_OAT(ISTABP(LL) I/10.+0.5
399 CONTINUE
C* CHANGE
C IFdDY.GT.10.AND. (JDAY.EO. (JODAY-t-lJ.OR.JDAY.EO.lJ) GOT064O4
IF(JDAY.NE.(JOOAY+1 ) .AND.JDAr.NE.il WRITE ( 16,6403 )
6403 FORMAT! • MET DATA INPUT ERROR •)
WRITE (10, 6400) JYR.IMO.JDAY
6400 FORMATC JYR=*,I2,' IMO=',I2,' JDAY=',I3)
WRITE 110, 6401 ) ISTABP
6401 FORMATC ISTAB= ', 24(12, 3X»
WRITE (10, 6402 I A WS , TEMP , AFV, AFVR, ( (HLH( I LJ ) , J=l , 24) , T=l , 2 )
6402 FORMATt* AHS= • , 24( F4. 1 , 1 X ) / • TEMP=- ,24( F4.0, 1 X) / • 4FV= »,
*24(F4.0,1X ./• AFVR=',24(F4.0,1X)/' HLH1=« , 12 ( F5 . 0, i X ) /6X,
*12(F5.0,lXi/» HLH2=t,12(F5.0,lX)/6X,12(F5.0,lX) )
C* CHANGES
6404 CONTINUE
IOSOR=IDSOR(3)
DO 610 IH=1,NS
DO 610 LOOP3=1,3
ITHIRO=(LOOP3-1)*8
RE AD (10, 606) (IDSOR, ( (OHOURIIH, IHOUR+ITHIRD ) ) ,IHOUR=1 ,8 ) )
606 FORMAT(A4,2I2,8E9.3)
IF(LOOP3.EQ.l ) IOID=IDSOR(1)
IF( (LOOP3.GT. 1.4ND.IOID.NE.IOSOR( 1 ) ) ,OR.( IDSOR (3 ) .NE. ( IOSOR*1 )
E.AND.IDSORI3) .NE.l) ) WRITE 1 IE ,607 ) IDSOR
607 FORHATC ERROR IN S02 INPUT • , A4, 2 I 2X , 12 ) )
C IF( IDY.LT. 10) WKITE(6,608)IOSOR, (OHOUR( IH , IHOUR+ I Tril RD) , IHOUR=1
WRITF(6, 608) IDSOK.IOHOURflH, "IHOUR+ITHIRD ) ,lHOUR=l,8l
608 FORMAT(1X,A4,2(1X,I2 ),8(2X,E10.31)
00011400
0001150O
00011600
00011700
00011800
00011900
00012000
00012100
00012200
00012300
00012400*
00012500
00012600
00012800
00012900
00013000
00013100
00013200
000133OO
00013400
000l350d
00013800
000139OO
00014000
00014100
000 14200
00014300
00014400
00014500
00014600
0001470X)
00014800
00014900
00015000
00015100
00015200
00015300
,8 100015400
00015500
OC015600
105
-------
FORTRAN IV Gl RELEASE 2.0
"IAIN
TATt = 76153
15/29/C19
0095
0096
0097
0098
0099
01OO
0101
0102
0103
0104
0105
0106
0107
0108
0109
0110
0111
0112
0113
0114
0115
Oll6
0117
0118
0119
0120
0121
0122
0123
0124
610 CONTINUE
C»**LOOP ON HOURS
DO 80 IHR=1,24
XWS=AWS( IHR)
FV=AFV(IHR)
FVR=AFVR (IHR)
XMH=HLH( IUR.IHR)
T=TEMPUHRi
C***SUM WIND PERSISTANCE DATA
FVRAD=FV/57. 29578
; UP=XWS*SIN(FVRAD)'~
VP=XWS*COS(FVRAD)
UPS=UPS+UP
VPS=VPS+VP
wss=wss*xws
c***
C***DO NOT ALLOW STABILITY" TO VARY RAPIDLY
c***
IF( (ISTABI IHrt )-KSTL) .GT.i ) GOTO 12
GO TO 13
12 ISTAB(IHR)=KSTL+1
ISTABP(IHR)=KSTLP+10
GO TO 10
13 IF«KSTL-ISTAB( IHR)).GT.l J ISTAB( IHR)=KSTL-1
IFMKSTL-ISTABIIHR11.GT.1J ISTABPdHR )=KSTKP -10
10 IF(IUR.NE.2) GO TO 11
IFdSTABdHR) .&T.4) ISTAB(IHR)=4
IFIISTAB(IHR) .GT.4) I STABPi IHR) =40
11 KST=ISTAB«IHR)
|
GO T0(71, 71, 71*71,75, 76), KST
IF(P-55. ) 72,73,73 __
' "
30 TO 74
XST=34.*F**.4
DISTF=3.5*XST
O0018800
00018900.
"00019000
00019100
00019200
00019301
00019400
OOOJ.950<1
00019600
00019700
00019800
00019900
106
-------
FORTRAN IV Gl RELEASE 2.0
MAIN
DATE * 76153
15/29/0*
0134
01_35
0136
0138'
0139
0140
DHA=1.6*F**0.333333*01STF**0.666667/WS**0.333333
78 HE(IS)=HP(IS)+DHA
0142
0143
79 CONTINUE
C*** _
C***LO"OP ON DIRECTIONS***
C***
DO 25 IDT=ILOW,ITOP"
00020000
po.^zoioo
"60620260
000 A) 300
000«.046b
00020500
00"02060O"
00020700
"000208OO
000^:0900
000^1000
00021100
000/J1200
0145
0146
0147
0148
0149
0150
015T" '
19
C***
IFUDIR.LE.O) GO TO 18
IF( IDIR.LE.36~) GO~TO"l9~
IDIR=IDIR-36
GO TO 19
IDIR=IOIR+36
ANG=(FVR-DIR)/57. 29578
C***CALCULATE YD AND CONCENTRATIONS FOR EACH DISTANCE***
C***YD IS IN METERS
0152
0153
0154
0155
0156
c*** •
DO 25 J=1,NST«
YO=RNG ( J )*ANG*1000.
SY=SYD(J,KSTP)
SZ=SZD( J,KSTP)
C***LOOP ON SOURCES***
0157 DO 310 IH=1,NS
0158
0159
0160
0161
0163
0164
0165
0166
0167
0168
0169
0170
0171
0172
C***IF
40
50
60
U- ^S(IH)
AN=br "~ "" ""
THE SOURCE IS ABOVE THE LID, NO CONCENTRATION IS t 3DED
IF{H-XMH )40,
-------
FORTRAN IV Gl
MAIN
DATE - 76153
15/2V/OV
0173
017*
"0175
01J6
017T
70
120
A2=0.
SUM=O.
~THL=2.*XMH
AN=AN*1._
C~5=AN*THL
CC=H-C5
0_00249GO
~000 25000
_0 00 25 100
00025200
_OC_02530(1
_
0179
CE=H»C5
C6=CC*CC/C2
0181 '
0192
0183
0184
0185
0136
•6T87
0188
0189
0190
0191
0192
OT93-
0194
0195
0196
0197_
Ol98
0199
0200
0201
130
"140
180
190
194
240
260
270
9
C8=CE*CE/C2
I F (_C6j-50 ._) _L3 °.»__
A4=2./EXP(C6)
GO TO 180 __ __
A4=0.
190,194»194
GO TO 240
A6=0 .
TOT=A4+A6
SUM=SUM*TOT"
IF(TOT-O.Ol) 250,260,260
IF+OHOUR"(IH,"iHR)*RC
310 CONTINUE ___ ____ __ ____
C***SAVE MAX 1 -HOUR CONC" FOR TH I S" 2"4-HOUR PERIOD
C***SPECIFY RECEPTOR WHERE MAX OCCURRED
^002550(1
"OOOC560G
000 25 700
000 C5 800
0002590C
0002~60bd
£0026100
~ 00626200
00026300
000
-------
FORTRAN IV Gl
0212
RELEASE 2.0
MAIN
DATE - 76153
15/29/09
0214
T>2i5
0216
0217
0218
~62l~9"
P220
0221
0222
0223
0224
0225
25 CONTINUE
_C»**ENO OF 24 HOUR PERIOD
80" "CONTINUE
C*** _ __ _ _
C***OUfPUT HOURLY "CONCENTRATIONS"FOR THIS DAY
C***24 RECORDS OF NMOD HOURLY CONCENTRATIONS***
C***~"~
DO 36 J=l,24
WRITEOI «CHI0
00030600"
00030700
00030800
00030900
O'OO 31000"
P0031_1_OO
00031200
OOC31300
00031-»00
00031500
00031600
00031700
"00031800
0003190O
00032000
00032100
C***
34
_
0227
0228
IF(CHI(IR,251.LE.DMAX(IR,1)) GO TO 35
DMAX(IR,l)=CHICiR,25)
DMAXCIR,2)=IDY+.05
C***
C***SUM DAILY AVER/GES FOR CALCULATION OF ANNUAL MEAN
0229
C230
0231
0232
C***
35 CHHIK.26^=CHHIR,26)->CHI(IR>25)
C***"COMPUTE"WIND PERSiSTA.JCE
__
PERSf=RSP/(WSS/"24.
____ RATIO=HMAXT/DMAXT
"c*** " "
C.***OUTPUT OAn^Y_C_ON_ __ ___ _
C***l RECORD OF NMOD 24-HOUR CONCENTRATIONS***
0233
_ __ _ _
WRITE m~TCH"l (IR725lVlR=iTNMO"D)
00032200
00032300
00032400
00032 5OO
"00032600
00032700
00032800
00032900
000"33000
00033_100
00033200
000333jnQ
"00033400
00033_500_
00033600
00033700
00033800
00033900
00034000'
00034100
0234
C***OUTPUT MAX 1-HOUR CONC AND HIGHEST 24-HOUR CONC AT ANY RECEPTOR
C WRITE(IP ,601)_lDY,DMAXT,MIp,RNG(MJp),MHH,HMAXT,MIH.RNG(MJH),
C *"RATI~0,PERST,lbENf
601 FORMAT
-------
FORTRAN IV Gl RELEASE 2.0
MAIN
DATE
7e>l53
15/29/09
0235
0236
0237
0238
WRITE!IO,600) IDY,HMAXT,MIH,RNG!MJH) ,
OA^*_ ^«.I3» *_^AX HOUR_LJ^ CQNC =
DIStAN(:~E=',6PF7.1, ' KM"HOUR = ~
*»MAX 24-HOUR CpNC = «,_lP_E 13. 6 ,_' DIRECJION=» , 12, •
*OPF7.1,~» KM'Y
_
02*0
0241
0242
0243
0244
02_45
0246
0247
0248
0249
0250
0251
0252
0253
600
- ___ ._ _ ____
7000 FORMAT! • "RAf"fO=i,F9.3t"' PERSIST*1 ,F9. 3//lX~7
___ I F[HMAXT.LE. HMAXYR (1 ) ) GO_TO_85_ ____
HMAXYR(1)=HMAXT
HMAXYR (2 )=MIH
HMAXYRI3 )=RNG!MJH)
HMAXYR!4 ) = IOY
HMAXYR (5 )=MHH
_85_ I F ( DM A X T . L E .0 MAX YM 1 ) 1 &0__TO_90_ ___
" DMAXVRd )=DMAXT
OMAXYRti )=MIO
DMAXYRO )=RNGIMJD j
DMAXYR(4 ) = IDY
C***ENO DAILY LOOP*** "
90 CONTINUE _ _
,DMAXT,MID, RNG!M JO )
DISTANCED.
C**?CALCyLATE ANNUAL MEANS_AN_D PEJERMINE J.HE_MAXIMUM
C***
AMMAX^O.O
MAXI=0
0255
0256
0257
0258
0259
02~60~
0261
0262
0263
DO 91 1=1,36
J?Q_?_1 J_=lt_NSTA _
IR=i + 36*(J-l ,"•--
CHI (IR ,2Jb t?CH I!IR,26)/365. _
IFICHHIR,26).LE.AMMAX) GO T0~ 9i
MAXI =
00034500
00034600
00034700
00034800
_ 0003490p_
00035000
0003_5lqp_
~~00b~352"00
00035300
00035400
00035500
00035600
0003570q_
'00035800
00035900
00036000
OOC36100
00036200
00036300
~"00b~3~6400
00036500.
00036600
00036700
00036800
00036900
00037000
00037100
0~00372~6o"
00037300
00037400
00037500^
"00037600
00037700
00037800
00037900
91 CONTINUE
C***
C***OUTPUT ANNUAL MEAN AT EACH RECEPTOR AND PRINT RECEPTOR WITH HIGHEST 00038000
C*** ANNUAL MEAN CONCENTRATION 00p38_10p_
'00038200
OOO38300
0265
0266
C***l RECORD OF NMOD MEAN ANNUAL CONCENTRATIONS***
C***
WRITEI8) (CHI(IR,26),IR=1,NMOD) 00038400
^***PUNCH HMAXYR,DMAXYR C AMMAX, HOURLY.OAILY C YEARLY MAXIMA FOR THE YE00038500_
"C'" " WRITE! IP",7iO) HMAXYR VlDENT "" 00"038600
_ _710 _F.ORMA_T_! • MAX_ HJJUR^LY ' , 1PE1 1 .4 ,OPF4.0, OPF5 . 1 ,OPF5 .0 ,OPF4 .0, T61 ,_5A4_)OOfi3_B7_00
'C WRITE! IP"7720) nMAXYR, IDENT ' "" - - - - 00033800
720 FORMAT!1 MAX DAILY •,1PE11.4,OPF4.0,OPF5.1,OPF5.0,T61,5A4) 0003890C
C WRITE (IP,730) AMMAX,MAX I,RNG(MAXJ),ID>NT 00039000
730 FORMAT!1 MAX ANMl'AL • , 1 Pt 1 1 . 4 ,13 , OP P6 . 1 , TSl , 5A4 )
110
-------
FORTRAN IV Rl RELEASE OR THE YEAR AT EACH RECEPTOR
_ WRITE(IO,5500) TITLE _ _ _ _ _
WRITE(IO,705) DMAXYR
705 FORMATdX,'YEARLY MAXIMUM 24-HOUR CC)NC = •, 1PE12.4 •
*OPF4^0VOISTANC~E='.OPF5.1 , ' 'KM~r7T"
WRITPCigt910)__(RNGCIpyM),IpyM=l_,NSTA)
910 FORMATUX," /1X ,f 17,'HIGHEST 24-HOUR CONCENTRATION AT EACH
DIRECTION=»,
OAY="' ,OPF5.1771X j
' RANGE
',7(F5.1,' KM ' ,7X )/lX , T2 , MJ_I_R • )
DO 421 1=1,36
WRITEIIO,8C1: I,(DMAXC(I+36*(J-l)),1 I,J=l,NSTA)
•FaRMATTrx7Tr,T2",T6,7UPE15.5))
WRITE!10,803) I»,IDUM=1,NSTA) _ _
92"0" F'ORMATdX, " " /IX'.Tl't/'HIGHEST 1-HOUR "CONCENTRATION AT E'ACH
*EPTOR'/1X_,T4, -RANGE •,7(F5.),« KM • ,7X I / IX ,T2, • DIR ' )
DO 422 1=1,36
WKlTF(IO,802) I,(HMAX(d»36*IJ-l ) ),1 ) ,J = 1 ,NSTA)
_
CONC^1 , 1PE12 .4, "•"
OAY = ' , OPF5 .0 ,
OiRECTION
' HpUR=',
00040800
00040900
00041000
_0004)100
0004T200
0004_l_30p
00041400"
00041500
"00041600
00041700
"0004T8~0~0
000*1900
RE00042000
00042100
00042200
00042300
00042400
00042500
000*2600
000^2700
000^2800
00_042_9_00_
00043000
00043100
OC043200
00043300
00043400
00043 50J3_
RtC00043600
n 00^3700
000^3800
111
-------
FORTRAN IV 31 K'fA^E' Z.r' *AIV )AT>: - 7<,]lj' 15/«;9/rvy
0297 ^nr FOrt.'nH 1X.T2, I2,T6,7< 1PF] 5.5) )
0298 W
-------
FORTRAN IV r,l
0001
0002
0003
0004
0005
0006
0007
0008
0009
0010
0011
0012
0013
0014
0015
0016
0017
OOJ8
"0019""
0020
0021
0022
J, = L : A r, r. 2 . ' •
7M!
1 'j /
C SUBKOUTINt TO CALCULATE SIGMA Y AND SIGM Z USING F.B_._SHI!^'
"C (SMI TH-SfGMA" i,"PA SOU I LL-SIGMA Y)
GOTO (10f20tJ0,40f50,60),KST
C STABILITY A(10) " ,
10 TH = (24.167_- 2.5334*ALOGUY))/57.295H
SZ = .li2*(X*100b. )**U06/( 1.+ .000538* (X*l 000. )**.8~15)
GO TO Jl_ _ _'
C "STABILITY 8(201
20 TH (18.333 -^1.8096*ALOG(XY)l/57.2958
SZ=.130*(X*1000.)**.950/(1.+.000652*(X*1000.I**.750)
GO TO 71
C STABILITY C(30)
30 !H = I12'5 ~ 1.0a57*ALOO(XYl1/57.2958 _
SZ = .112* (~X*1000. )**.9"20~7( 1 . + .6o0963*rx*106o. )**.718 )"
GO TO 71 _
C STABILITY DI40)
40 TH = (<5.3333-0.72382*ALOG(XY) 1/57.2958 _
SZ = .098* (X*iO"00. )**."889/(l ^ + .00135* ( X*1000. )**.6e8)
GO^TO 71 __
C STABILITY E(5~OT~
50 TH = (6.25 - 0.54287*ALgG(XY))/57.295_8_ _
SZ=.0609*IX*1000. )**.895/( 1 .* .00"i96*( X*1000. I ** .684)"
__ G0_ T0_71_ _
C STABILITY F (60")
_ 60 TH = (4.1667 - 0.36191*ALOGtXY)1/57.2958
SZ=.06TPrfX*1000. )**.783/(l. + .00136*(X*1000. )' *.672 )
71 SY = 1000. * XY !LS.IN_
-------
FORTRAN IV Gl RELEASE 2.0 SIGMA DATE » 76156 12/34/10
OO01 _ SU8ROUTIC SI6»UIX,XY,ICSTjLSY.SlJ_ _
OO02 FkST-FLOAfiKSTI/ib.
OJ>03 _ .. KSTl=FK$T_
OOO* KST2=KSTl*i
OQQ5__ IFfKSTl.LT.il KSTfl _ _
OOO6 IFIKST2.GT.6) KST2-6
0007 CALL SI6HAllX,XY,KSTltSYl*SZl)
OOOe CALL SIGMAl(X,XY»KST2tSY2tS22)
000? DY-SY2-SY1 _
B010 DZ-S22-SZ1
OOU _ DK=FKST-K$T1
0012 SY=SY1+DK*DY
0013 _ _
001* " REfURN
0015 END
114
-------
ELEVATION DIFFERENCES 9ETWEEN RGCEPTOR" AND SOURCE LOCATT.6NS = 0.64E+02" "0 .82c"*62 " 0 . 10E+03 0.13E+03
IUR- 1 .
MUSKINGUM_RIVER POWER PLANT STACK 1 J30JJ.E* S 1^4
S" 1 HP= 251.00 TS= 430. VS= 28.50 D= 7.60 VF = 1292.89
MUSKINGUM RIVER POWER PLANT STACK 2 BOILER 5
NS= 2 HP= 251.00 TS= 425.~VS= 24.80 0= 6.70 VF= 874.36
00062500
00062700
RANGc(KM2= _ _
JYR=73 iM~0^~~l JDAY= 1" "
ISTAB=-70 70 70 70 60 70
AWS= " 2.6 2.6 2.1 3.1 4.1 2.1
TEMP=277. 277. 276. 275. 275. 275.
AFV= 20. 20. 20. 20. 20
AFVR= 20. 22._ 21. _19. 16 _
HtHr=l~062y~l662." T0'0~2 ."T00~2 .' l'00"2""."~
839. 1002. 1002. 1002. 1002.
958. 958. 958. 958.
1002. 1002. 1002. 1002.
0.426E+04 "0.426E+04
0.426E+04 0.439E+04
0.441E+04
0.147E+04
0.~144E+04"
0.147E+04
5.27 4.28 8.26 19.63
HLH2= 958.
995.
1
20
22
MUS4
MUS4
"WS4"
MUS5
MUS5
MUS5
DAY=
1
0.442E+04
0.147E+04
0.142E+o"4
0.152E+04
70 45 70 36 35 29 34
2.6 5.6 3.1 5.1 6.2 5.1 7.2
274. 274. 274. 274. 275. 277. 278.
20. 50. 20. 60. 60. 80. 60.
18_. 50. 18. 60. 64. 83^_ 65 ._
1002. "i'002." "2K '135. " 348. " 5T2 '.
"J>i 988. 980^. 972^, 96J>. JJ57.
958. 958. 959. 966. 973. 980."
98 4^ 959 ^ 935. 911_^ 887. 863.
0.423E + 04 0.424E+04 ~" 0.4~24E+04
0.439E+04 0.444E+04 0.440E+04
0.463E+04
32 34 34 34 47 67 63 59 63
6.2 6".7 6.2 4.6"" 5.1 3.1 3.6 - 3.6 3.
279. 280. 280. 281. 279. 278. 276. 276. 275.
60. 60. 50. 50". 70. 80. 80. 90.~110.
57^ _62_. 50. 46. 70. 8^»_29- _?4^_1H-
"675.
949.
70 70
1 2.6" 3.1
274. 274.
120. 110.
118. 115.
988.
839.
0.424E+04
0.434E+04
0.142E+04
0.142E+04
0.161E+04
0.517E+04
0.143E+04
0.143E+64"
0.1B6E+04
0.512E+04
0.143E+04
0.145E+04
0.1675+04
1
~RTTW>
MAX HOURLr CONC= 6.336607E-O4
MAX 24-HOUR CONC= 6.656564E-05
DIRECTION= 6
OIRECTION= 6
DISTANCE=
DISTANCE'
8.
8.
0.461E+04
0.142E+04
0.144E+04
0.142E+04
KM HOUR=10
KM
0.435E+04
0.426E>04
0.442E+04
0.1436*04
0.134E*04
0.142E+04
0.432E+04
0.426E+04
0.437E+04
0.142J+04
0.139E+04
0.146E+04
9.519 PERSIST=
0.898
JYR-73 IMO"
ISTAB= 70
AHS= 3.1
1 JDAY» 2
70 70" 70
3.1 2.1 2.6
57 " "54
2.6 2.1
53 56
2.6 1.5
48 38 27 25 22
1.0 1.0 1.0 3.1 2.6
fEMP=273. 273. 272. 271. 271. 271. 271. 270. 270. 270. 271.
AFV= 110. 100. 40. 40. 60. 120. 160. 130. 130. 130. 130.
"AFVR = 113. 101. 41. 39. 64. 117 . 158 . 1 29." 126 . 129. 1 30~.
HLH1= 941. 933. 925. 918. 910. 902. 894. 18. 155.
HLH2 =
MUS4
MUS4
MUS4
MUS5
MUSS
MUS5
DAY=
RATIO
702.
839.
839.
1 2
1 2
1 2
1 2
1 2
839. 839. 839
839. 839. 839
839. 839. 839
0.460E+04 0.
0.758E+04 0.
0.840E+04 0.
0.169E+04 0.
0.227E+04 0.
1 2 0.199E+04 0.
2 MAX HOURLY CONC=
MAX 24-HOJR CONC=
5.747 PERSIST=
. 839.
. 839.
. 339.
464E+04
838E+04
629E+04
174c+04
235E*04
817. 788.
939. 339.
772. 683.
0.460E+04
0.843E+04
0.941 E*04
0.174E+04
0.211E+04
760. 731.
639. 839.
595. 506.
0.469E+04
0.340E+04"
0.830E+04
0.174E+04
0.227E*04
21
2.1
272. 273. 274.
50. 80. 360.
5~3. 31. 2.
292. 428. 565
702. 673.
839. 839.
416. 329.
0.471E+04
0.842E+04
0.340E+04
0.175E+04
202E+04 0.225E+04 0.223E+04 0.224E»04
1.101867E-O3 DIRECTION=20 OISTANCE= 19.6
1 .9172 59£-r
-------
APPENDIX C
CONCENTRATION PROFILES FOR THE CANAL AND MUSKINGUM
PLANTS FOR DIFFERENT SETS OF DISPERSION CURVES
116
-------
O WIND SPEED=1.5 M/SEC
A W.INO SPEEQ=2.0 M/SEC
+ WIND SPEED=2.5 M/SEC
x UINO SPEED=3.0 M/SEC
tf
-7 8 9 "lQl
OOWWWINO DISTftNCE (KM)
Figure C-la. Plume centerline concentration versus downwind distance for stability
Class A at the Canal Plant. Pasquill-Turner dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
o WIND SPEED=2.0 M/SEC
A WIND SPEED=3.0 M/SEC
+ WIND SPEEDS.0 M/SEC
x WIND SPEED=5.0 M/SEC
00
DOWNWIND DISTftNCE (KM)
Figure C-lb. Plume centerline concentration versus downwind distance for stability
Class B at the Canal Plant. Pasquill-Turner dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
0 WIND SPEED=2.0 M/SEC
A WIND SPEEO=5.0 M/SEC
+ WIND SPEEO=8.0 M/SEC
x WIND SPEED=!1.0 M/SEC
<»> WIND SP£EO=14.0 M/SEC
w
DOWNWIND DISTRNCE
1 1
9 9
(KMJ
Figure C-lc
Plume centerline concentration versus downwind distance for stability
Class C at the Canal Plant. Pasquill-Turner dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
WIND
WIND
WIND
WIND
WIND
SPEED=2.0
SPEED=6.0
SPEED=10.0
SPEED=14.0
M/SEC
M/SEC
M/SEC
M/SEC
SPEED=18.0 M/SEC
2: ;
a:
cc
"lu1
I t 1 I i I ;
5 6 -7 8 9 10
DOWNWIND DISTANCE
a 9
(KM)
Figure Old
Plume centerline concentration versus downwind distance for stability
Class D at the Canal Plant. Pasquill-Turner dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
0 WIND SPEED=2.0 M/SEC
A WIND SPEED=3.0 M/SEC
+ WIND SPEED=4.0 M/SEC
x WIND SPEED=5.0 M/SEC
ID
2-
Z '
o -
or
cc.
UJ.
o'7
0°
8 9
OISIftNCE (KM)
B 9
Figure C-le,
Plume centerline concentration versus downwind distance for stability
Class E at the Canal Plant. Pasquill-Turner dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
O WIND SPEED=2.0 M/SEC
A WIND SPEED=3.0 M/SEC
+ WIND SPEEDS.0 M/SEC
x WIND SPEED=5.0 M/SEC
ro
to
DOWNWIND DISTflNCE (KM)
Figure C-lf.
Plume centerline concentration versus downwind distance for stability
Class F at the Canal Plant. Pasquill-Turner dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
o WIND 5PEED=1.5 M/SEC
A WIND SPEEO=2.0 M/SEC
+ WIND 3PEEO=2.5 M/SEC
x WIND SPEEO=3.0 M/SEC
LO
or
Figure C-2a
5 6789
DOWNWIND DISTflNCE
8 9
(KM)
Plume centerline concentration versus downwind distance for stability
Class A at the Canal Plant. Gifford-Briggs dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
0 WIND SPEEQ=2.0 M/SEC
A KINO SPEEO=3.0 M/SEC
4. WIND SPEEO=4.0 M/SEC
x WIND SPEEO=5.0 M/SEC
w
DOWNWIND OISTflNCE
TTTlcf
(KM)
Figure C-2b
Plume centerline concentration versus downwind distance for stability
Class B at the Canal Plant. Gifford-Briggs dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
dJNO
WIND
WIND
WIND
WIND
SPEEO=2.0
SPEEO=5.0
SPEEO=8.0
SPEE.O=ll.O
SPEEO=1>4.0
M/SEC
M/SEC
M/SEC
M/SEC
M/SEC
Ul
5 6789
DOWNWIND DISTflNCE (KM)
B 9
Figure C-2c. Plume centerline concentration versus downwind distance for stability
Class C at the Canal Plant. Gifford-Briggs dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
©
WIND SPEED = c'.C M/SEC
WIND SPEEO=6.0 M/SEC
WIND SPEED=1C.O M/SEC
WIND SPEED = 1>4.0 M/SEC
WIND SPEEO=18.0 M/SEC
ro
cr
ac
-10°
8 9
DOWNWIND OISTflNCE (KM)
Figure C-2d
Plume centerline concentration versus downwind distance for stability
Class D at the Canal Plant. Gifford-Briggs dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
o HINO SPEEO=2.0 M/SEC
A. WIND SPEEO=3.G M/SEC
+ WIND SPEEO=4.0-M/SEC
x WIND SPEEG=5.0 M/SEC
N>
2-
'o
z '^i
o -
CE .
CC
uu.
o'-q
S 6 7 8 9 1Q1
DOWNWIND DJSTflNCE (KM)
5 6 7 8 9 \tf
Figure C-2e. Plume centerline concentration versus downwind distance for stability
Class E at the Canal Plant. Gifford-Briggs dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
WIND SPEEO=3.0 M/SEC
WIND SPEEO=4.0 M/SEC
WIND SPEEO=5.0 M/SEC
to
00
O H
oc -I
-------
£ WING 3FEEC=I.5 K/SEC
A XING SPEE1'=2.0 M/ScC
+ WING SPE£0=2.5 M/SEC
•x UHJD SPEEC;=3.0 M/5EC
to
'_!
1
10'
9 10°
DISTANCE (KM)
6 7 8 9
Figure C-3a. Plume centerline concentration versus downwind distance for stability
Class B2 at the Canal Plant. Smith-Singer dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
X KIND Sr
=2.0 M/SEC
Ej=2.C M/5EC
Er^.G I-/SEC
EO-5.0 M/SEC
to
O
Figure C-3b. Plume centerline concentration versus downwind distance for stability
Class Bl at the Canal Plant. Smith-Singer dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
:FEi>2.3 M/SE'C
EE:=;ii.o K/SEC
DOWNWIND DISTANCE (KM)
Figure C-3c. Plume centerline concentration versus downwind distance for stability
Class C at the Canal Plant. Smith-Singer dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
"- 5?E;i:=::.0 N/StC
M S = ZE:=:-,.O ."./SEC
ND SPEEQ=.8.0 M/SEC
O
CL
cn
UJu.
o
o
.or
6 7 8 9
GOW.MWINQ DISTANCE (KM)
7 8 9
Figure C-3d. Plume centerline concentration versus downwind distance for stability
Class D at the Canal Plant. Smith-Singer dispersion curves used.
Flat terrain assumed. Wind speeds are at stack top
-------
o WIND SPEEO=i.S M/5EL
A WlKiD SPEtb=2.U M/SEC
4. WIND SPEEU=2.5 M/SEC
x WIND SPEEO3.0 M/SEC
u>
u>
0°
S 6 7 8 9 <10'
QOUNWINO DISTflNCE (KM)
5678 9 \(f
Figure C-4a
Plume centerline concentration versus downwind distance for stability
Class A at the Canal Plant. F. B. Smith QZ and Pasquill-Turner o
dispersion curves used. Flat terrain assumed. Wind speeds are at
stack top
-------
o -JIMD SPELU=2.0 M/5EC
A WIND SPEEO=3.0 M'SEL
+ dIND SPEED=4.0 M/SEC
x WIND SPEEO=5.0 M/SEC
Ui
5 6 7 8 3 'iQ1 T"
DOWNWIND OISTflNCE IKMJ
7 8
Tltf
Figure C~4b.
Plume centerline concentration versus downwind distance for stability
Class B at the Canal Plant. F. B. Smith a and Pasquill-Turner a
dispersion curves used. Flat terrain assumed. Wind speeds are at
stack top
-------
o rfINO 2PEED=2.G M/SEC
A WIND SPEED=5.0 M/SEC
+ dIND SPEED=8.0 M/SEL
x HIND SPEtU=11.0 M/SEC
WIND SPEtUMH.O M/SEC
u>
DOWNWIND OISTflNCE iKM)
Figure C-4c.
Plume centerline concentration versus downwind distance for stability
Class C at the Canal Plant. F. B. Smith
dispersion curves used. Flat terrain assumed.
at stack top
a and Pasquill-Turner a
Wind speeds are
-------
o WIND SPEtO=2.0 M/SEC
A WlNb SPEEU=6.U M/SEC
+ WIND SPbED=lO.O M'SEC
x W1NU SPEtO=l4.0 M'SEl
< WIND SPLcU=18.0 M/SEC
LO
ON
10'
T 6 7 8 9
DOWNWIND OISTRNLE
Figure C-4d.
Plume centerline concentration versus downwind distance for stability
Class D at the Canal Plant. F. B. Smith a and Pasquill-Turner a
2 V
dispersion curves used. Flat terrian assumed. Wind speeds are
at stack top
-------
o WIND SPEED=2.0 M/SEC
A WIND SPEtU=3.0 M/SEC
4. W'ND SPEE'J=4.U M/bEC
x WINU SPhtU-S.U M/SEC
s: :
CO
r> -
cc
cc
tf
5 6789
OQUNMINO 01STRNCE IKM)
6 7 8
Figure C-4e. Plume centerline concentration versus downwind distance for stability
Class E at the Canal Plant. F. B. Smith a and Pasquill-Turner a
dispersion curves used.
at stack top
Flat terrian assumed. Wind speeds are
-------
o WIND SPEEU-2.0 1'bEl
A WIND SPE.cO-3.0 M/SEC
+ WIND SPEEDS.U M'SEC
x HIND SPEED-5.0 1'bEC
LO
00
o
^ -^
o H
0'
1 T*T~»
DOWNWIND
To'
Figure C-4f.
Plume centerline concentration versus downwind distance for stability
Class F at the Canal Plant. F. B. Smith
dispersion curves used. Flat
at stack top
a and Pasquill-Turner a
2 y
terrian assumed. Wind speeds are
-------
O WIND SPEEO=2.0 M/SEC.
A WIND SPEEO=2.0 M/SEC.
+ WIND SPEED=6.0 M/SEC.
x WIND SPEEO=6.0 M/SEC.
Z0=10.0 CM
Z0=100.0 CN
ZO=10.0 CM
Z0=100.0 CM
u>
5 6 7 8 9 \Cf
DOWNWIND OISTflNCE (KM)
Figure C-5a.
Effect of surface roughness upon ground level air concentrations
for stability Class A at the Canal Plant. F. B.
Pasquill-Turner ay curves used. Flat terrain assumed
Smith az and
-------
0 WIND SPEED=2.0 M/SEC.
A WIND SPEED=2.0 M/SEC.
+ WIND SPEEO=6.0 M/SEC.
x WIND SPEEO=6.0 M/SEC.
Z0=10.0 CM
Z0=100.0 CM
Z0=10.0 CM
Z0=100.0 CM
S 6 ~7 8 9
DOWNWIND OISTRNCE (KM)
Figure C-5b.
Effect of surface roughness upon ground level air concentrations
for stability Class B at the Canal Plant. F. B. Smith az and
Pasquill-Turner ay curves used. Flat terrain assumed
-------
0 WIND SPEEO=2.0 M/SEC.
A WIND SPEEO=2.0 M/SEC.
+ WIND SPEEO=6.0 M/SEC.
X WIND SPEED=6.0 M/SEC.
Z0=10.0 CM
Z0=100.0 CM
Z0=10.0 CM
Z0=100.0 CM
S G 7 8
OOWNUINO DISTANCE (KM)
6 7 8
Figure C-5c.
Effect of surface roughness upon ground level air concentrations
for stability Class C at the Canal Plant. F. B. Smith crz and
Pasquill-Turner 0y curves used. Flat terrain assumed
-------
O WIND SPEED=2.0 M/SEC.
A WIND SPEED=2.0 M/SEC.
+ WIND SPEEO=6.0 M/SEC.
X WIND SPEED=6.0 M/SEC.
Z0=10.0 CM
Z0=100.0 CM
Z0=10.0 CM
Z0=100.0 CM
CE
oc
•id'
5 67891Q'
DOWNWIND DISTflNCE
(KM)
Figure C-5d. Effect of surface roughness upon ground level air concentrations
for stability Class D at the Canal Plant. F. B. Smith az and
Pasquill-Turner av curves used . Flat terrain assumed
-------
0 WIND SPEED=2.0 M/SEC.
A WIND SPEED=2.0 M/SEC.
+ WIND SPEED=6.0 M/SEC.
x WIND SPEEO=6.0 M/SEC.
Z0=10.0 CM
Z0=100.0 CM
Z0=10.0 CM
Z0=100.0 CM
OJ
cc .
cc
I—
z
UJ.
5 6 7 8 ^ "lO'
DOWNWIND OISTRNCE
(KM)
Figure C-5e.
Effect of surface roughness upon ground level air concentrations
for stability Class F at the Canal Plant. F. B.
Pasquill-Turner O curves used . Flat terrain assumed
Smith a and
£»
-------
a WINJD SPEEDS 0 M/SEC.
A WIND SPEED=2.0 M/SEC.
+ HIND SPEED=6.0 M/SEC.
x WIND SPEED=6.0 M/SEC.
Ji3 .10.0 CNj
ZCM100.0 CM
Z0=10.0 CM
Z0=100.0 CM
10°
DOWNWIND DISTflNCE (KM)
Figure C-5£. Effect of surface roughness upon ground level air concentrations
for stability Class F at the Canal Plant. F. B. Smith az and
Pasquill-Turner az curves used* Flat terrain assumed
-------
xwlNfi
= 3,0 M/5EC
-- .1.5 M/3EC
— h n M /'' -, F f
" • \J I ' k> L_ './
= 4.5 M/SEC
Oi
o -
cc
cc
o ~
o :
5 6 7 8 9 10*
DOWNWIND DISTANCE (KM)
6 7
Figure C-6a. Plume centerline concentration versus downwind distance for stability
Class A at the Muskingum Plant. Pasquill-Turner dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
fi/UNC SPEED= 3.0 M/SEL
^Wi'Nu SPEED- M.r> M'Se.C
+WINU bPEED= S.O M/SEC
XWINLJ SPEED^ 6,0 M/5EC
z:
o -
o :
a:
or
1 6 7 8 9 "lQl
DOWNWIND DISTflNCE (KM)
789
Figure C-6b. Plxnne centerline concentration versus downwind distance for stability
Class B at the Muskingum Plant. Pasquill-Turner dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
MO SPEEO= 5.0 M/SEC
AWJNO SPEEO= 6.0 M/SEC
+WINO SPEEDS 1 . 0 M/SEC
XWINO SPEEO-14.0 M/SEC
-7
cr
oc
UJ
o
T
1
Tl
1 6 7 8 9~
OOWNWINO DISTflNCE (KM)
Figure C-6c,
Pliime centerline concentration versus downwind distance for stability
Class C at the Muskingum Plant. Pasquill-Turner dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
0W-NO SPEED- e.O M/SEC
+WINf) SPEED=14.G M/SEC
XWINU SPEEO=i8.0 M/SEC
00
o.,
CE
GC
DOWNWIND DISTANCE (KM)
Figure C-6d. Plume centerline concentration versus downwind distance for stability
Class D at the Muskingum Plant. Pasquill-Turner dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
OWING SPEED= 2.0 M/SEC
AHIND SPEED^ 3.0 M/SEC
+WINO SPEED= 4.0 M/SEC
XWINO SPEED= 5.0 M/SEC
o •
VO
O :
cc.
tc.
UJ
^
o
'o
0°
Figure C-6e.
$ 4 S 6 7 8 $ "itf $ * H $ 5
DOWNWIND DISTANCE (KM)
Plume centerline concentration versus downwind distance for stability
Class E at the Muskingum Plant. Pasquill-Turner dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
OWINQ SPcEO- 3.0 M 'SEC
^WlrvJD SPEED- J 'j ,1 ?EC
+WINU 3PEEO= M.O M/SEC
XW!ND SPEEO= 4.5 M/SEC
DOWNWIND DISTflNCE (KM)
Figure C-7a. Plume centerline concentration versus downwind distance for stability
Class A at the Muskingum Plant. Gifford-Briggs dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
N(J SPEED= J.O M/5EC
AWINU SPEED-- '4.0 M/SEC
+WIND SPEEO= 5.0 M/SEC
XWIND SPEEO= 6.0 M/SEC
o
o
\
o.
oc
i—
z
LU.
—r~
—r-
8
678 9 "id1
DOWNWIND OISTflNCE
0°
Figure C-7b.
(KM)
Plume centerline concentration versus downwind distance for stability
Class B at the Muskingum Plant. Gifford-Briggs dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
QHINO SPEECH S.Q M/5EC
AWINO SPEED- b.O M/SEC
4.WINQ SPEED-1 1 . 0 M/SEC
XWINO SPEEQ^iy.O M/SEC
Ui
O.
cc
cc
6 7 8 9 "lQl
DOWNWIND OISTPNCE
(KM)
Figure C-7c.
Plume centerline concentration versus downwind distance for stability
Class C at the Muskingum Plant. Gifford-Briggs dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
Ni: SPEED-- 6.0 M/SEC
ArtlNi:; SPiLtO-lQ.O M/SEC
+WINC 5PEEQ-14.0 M/SEC
XWINQ 5PEEQ=18.Q M/SEC
Ln
CO
~?
cr .
-------
NQ SPEED- J.O M/SEf.
MO SPEED- :.5 M/5EC
+WINO SPEEO^ 3.0 M/SEC
XW!NO SPEED- 3.5 M/SEC
Ln
Figure C-8a.
S 6 7 -0 9 iQ
DOWNWIND DISTflNCE (KM)
Plume centerline concentration versus downwind distance for stability
Class B2 at the Muskingum Plant. Smith-Singer dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
OjWINO SPEEO= 3.0 M/SEC
AWINO SPEEQ= 4.0 M/SEC
+WINO SPEEO= 5.0 M/SEC
XWIMO SPEEO= 6.0 M/SEC
ID
o
\.
Ui
CD -
o:
cc
Q°
DOWNWIND OISTflNCE (KM)
Figure C-8b. Plume centerline concentration versus downwind distance for stability
Class Bl at the Muskingum Plant. Smith-Singer dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
SPE.5LO-- S.
+WINO SPEED-11.0 M/5EC
XWINQ SPEEO=l4.ri M/SEC
8 9
Figure C-8c.
DOWNWIND OISTflNCE (KM)
Plume centerline concentration versus downwind distance for stability
Class C at the Muskingum Plant. Smith-Singer dispersion curves
used. Flat terrain assumed. Wind speeds are at stack top
-------
=3.0 M/bEC
A«IND
+WINO
SPEED-
5PEEO=
SPEEO=
3.b M/oEC
q.O M/StC
4.5 M/SEC
Ln
S 6789
DOWNWIND OISTflNCE (KM)
7 8
Figure C-9a.
Plume centerline concentration versus downwind distance for stability
Class A at the Muskingum Plant. F. B. Smith az and Pasquill-Turner
ay dispersion curves used. Flat terrain assumed. Wind speeds are
at stack top
-------
+WIND SPEED^ s.c M/SEC
XWINO 'SPEED- 6.0 M/SEC
00
O.
(X
oc
T 1 1 1 1 1—;
5 6 7 8 9 "lQl
QOWNHIND DISTRNCE
T
(KM)
Figure C-9b.
Plume centerline concentration versus downwind distance for stability
Class B at the Muskingum Plant. F. B. Smith Q7 and Pasquill-Turner
ay dispersion curves used. Flat terrain assumed. Wind speeds are
at stack top
-------
0WIND SPEED= 5.0 M/SEC
AWIND SPEEO= 8.0 M/SEC
+WIND SPEED=11.0 M/SEC
XWINO SPEED=14.0 M/SEC
' O
a:
-------
0WIND SPEED= 6.0 M/SEC
AWIND SPEEO=10.0 M/SEC
+WIND 5PEED=14.0 M/SEC
XWIND SPEED=18.0 M/SEC
w
DOWNWIND DISTflNCE
(KM)
Figure C-9d. Plume centerline concentration versus downwind distance for stability
Class D at the Muskingum Plant. F. B. Smith az and Pasquill-Turner
dispersion curves used.
at stack top
Flat terrain assumed. Wind speeds are
-------
0WINO SPEEO= 2.0 M/SEC
AWINO SPEEO= 3.0 M/SEC
+WINO SPEED= 4.0 M/SEC
XWINO SPEED= 5.0 M/SEC
cc
flC
T 1 1" 1 1 1 i
5 6 7 8 9 \Ql
DOWNWIND DISTflNCE
(KM)
Figure C-9e. Plume centerline concentration versus downwind distance for stability
Class E at the Muskingum Plant. F. B. Smith a and Pasquill-Turner
a-,
dispersion curves used. Flat terrain assumed. Wind speeds are
at stack top
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-450/3-77-OQ3b
2.
4. TITLE AND SUBTITLE
IMPROVEMENTS TO THE SINGLE SOURCE
MODEL, Volume II— Testing and Evaluation of Model
Improvements
5. REPORT DATE.,
January 1977
6. PERFORMING ORGANIZATION CODE
I. RECIPIENT'S ACCESSION-NO.
7. AUTHOR(S)
Michael T. Mills, Roger W. Stern, Linda M. Vincent
8. PERFORMING ORGANIZATION REPORT NO.
GCA-TR-76-6-G(2)
9. PERFORMING ORGANIZATION NAME AND ADDRESS
GCA Corporation
GCA/Technology Division
Burlington Road
Bedford, Massachusetts 01730
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-02-1376
Task Order No. 23
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Research Triangle Park
North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final Report
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
The main purpose of this study was to determine whether alternate methods for
stability index assignment and dispersion calculation would yield better agreement
between measured and calculated cumulation frequency distributions of 1-hour S02
concentrations when used in the EPA Single Source Model. The following dispersion
curves were tested: Pasqui11-Turner, Gifford-Briggs, Smith-Singer and F. B. Smith.
A fractional stability assignment technique based upon the work of F. B. Smith was
also investigated. Based upon model validation results for the Canal Power Plant in
Massachusetts and the Muskingum Power Plant in Ohio, the Pasquill-Turner dispersion
curves and stability index assignment algorithm currently used in the model were
found to give the best agreement with measured concentration distributions. During
the course of the study the incorporation of a variable stack gas exit velocity was
evaluated and found not to appreciably affect the model predictions.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
19. DISTRIBUTION STATEMENT
19. SECURITY CLASS (This Report)
UNCLASSIFIED
21. NO. OF PAGES
174
20. SECURITY CLASS (This page)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
163
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