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ENVIRONMENTAL RESEARCH S TECHNOLOGY INK,
DISCLAIMER
Publication of this report does not signify that the contents
necessarily reflect the views and policies of the U.S. Environmental
Protection Agency, nor does mention of trade names or commercial
products constitute endorsement or recommendation for use.
111
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
TABLE OF CONTENTS
Page
LIST OF ILLUSTRATIONS vii
LIST OF TABLES vii
1. INTRODUCTION 1-1
1.1 Background 1-1
1.2 The Mesoscale Puff Element Model (MESOPUFF) 1-2
1.3 Integrated Mesoscale Modeling System 1-4
1.4 Organization of the Report 1-4
2. MESOPUFF TECHNICAL DISCUSSION 2-1
2.1 Basic Mass Conservation Equations 2-1
2.2 The Grid System 2-3
2.3 Specification of Model Inputs 2-3
2.4 Puff Trajectory, Dispersion and Sampling
Algorithms 2-5
2.4.1 Lagrangian Trajectory Function 2-5
2.4.2 The Puff Dispersion Function 2-9
2.4.3 The Plume Sampling Function 2-11
2.5 Conversion of Sulfur Dioxide to Sulfate 2-13
2.6 Dry Deposition of Sulfur Dioxide and Sulfate 2-13
2.7 Plume Rise 2-14
2.8 Treatment of Plume Fumigation 2-15
2.9 Accurate Simulation of the Continuous Plume 2-18
2.10 Comparison to the Conventional Gaussian Plume
Model 2-19
2.11 The MESOPUFF Computer Program 2-21
3. MESOPUFF USER INSTRUCTIONS 3-1
3.1 General 3-1
3.2 Description of Card-Image Input 3-1
3.3 Other Considerations 3-10
3.3.1 Meteorological Considerations and
MESOPAC Input 3-10
3.3.2 Array Size Considerations 3-10
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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
TABLE OF CONTENTS (Continued)
3.4 MESOPUFF Model Output
3.4.1 Line Printer Output
3.4.2 Direct Access Disk Output
3.5 Execution Time and Core Requirements
4. TEST CASE FOR MESOPUFF
REFERENCES
APPENDIX A TEST CASE MESOPAC INPUT AND OUTPUT
APPENDIX B TEST CASE MESOPUFF OUTPUT
APPENDIX C TEST CASE NAMELIST FILE
ABSTRACT
Page
3-11
3-11
3-11
3-14
4-1
VI
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OONMENTAL RESEARCH* TECHNOLOGY
LIST OF ILLUSTRATIONS
Figure Page
1-1 Schematic Representation of Puff Superposition
Approach 1-3
1-2 Integrated Modeling System 1-5
2-1 One Possible Arrangement of Sampling and Basic
Computational Grids 2-4
2-2 Calculation of the Trajectory of a Puff Centerpoint 2-8
2-3 Calculation of the Concentration C(i,j) by the
Sampling Function 2-12
2-4 Response of Two Plume Elements to Changes in
Mixing Depth 2-17
2-5 MESOPUFF Model: Percentage Deviation with Puff
Separation Distance 2-20
2-6 MESOPUFF vs. the Conventional Gaussian Plume 2-23
2-7 MESOPUFF Computer Program Flowchart 2-24
4-1 MESOPUFF Test Case Parameter and Emission Source
Inventory Input 4-2
4-2 Test Case Library File (MESOFILE) 4-3
4-3 MESOPUFF 24-Hour Average SO Concentration Calcomp
Plot, 16 June, 1978 (from MESOFILE) 4-4
4-4 MESOPUFF 24-Hour Average SO Concentration Line
Printer Plot, 16 June, 1978 (from MESOFILE) 4-5
4-5 Bulk Statistical Comparison of MESOGRID to
MESOPUFF, 16 June, 1978 (from MESOFILE) 4-6
LIST OF TABLES
Table page
2-1 Coefficients for Dispersion Parameter Formulas 2-10
2-2 Comparison of Cu/Q Values for MESOPUFF and
Turner Workbook - Computed Values 2-22
3-1 Logical Unit File Structure 3-12
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ENVIRONMENTAL RESEARCH 5 TECHNOLOGY INC
1. INTRODUCTION
1.1 Background
In response to a growing national commitment to the use of indigenous
coal reserves to meet energy generation demands, several regions of the
country will see greatly expanded use of coal and oil shale resources
for steam electric power plants and other coal-based energy resource
development. But, mandated by federal National Ambient Air Quality
Standards, and by the PSD major source review procedures, additional
coal-based energy resource development (ERD) will only be permitted
where consistent with the maintenance of human health, welfare, and
environmental quality. Accordingly, the siting and generation capacity
of such ERD facilities will be constrained by their potential impacts on
regional ambient air quality.
Various plans have been proposed for regional development of
multiple major new facilities and suitable air quality simulation tools
are needed to assess the impacts of different energy development
scenarios on regional-scale air quality. To meet this need in the
public interest, the National Oceanic and Atmospheric Administration
(NOAA) has sponsored a study by Environmental Research § Technology,
Inc. (ERT) to develop, compare, evaluate, and exercise a number of
alternative approaches to regional-scale ambient air quality modeling.
A major objective of this study is to provide a suite of air quality
simulation models that are both technically sound and computationally
practical for assessing regional-scale impacts of energy development
scenarios.
As described in the companion report, Volume 1 (Bass et al. 1979)
three different air quality transport-diffusion modeling approaches have
been developed, implemented and compared for simulation of point-source
plume dispersion on the mesoscale [e.g., dispersion at ranges of 100 to
1,000 kilometers (km)].
The models are optimized for regional-scale impacts; in Volume 1,
the ambient air concentrations calculated by MESOPUFF in the near field
of sources, that is, less than 100 km, are not realistic. The current
version of MESOPUFF (presented in this volume) has been augmented to
handle near-field impacts in a more realistic manner - see Section 2.1.
Both worst ^ase and average dispersion situations are treated, with
meteorological inputs constructed from rawinsonde data that is readily
available for the region. The models are computationally practical for
simulating the impact of multiple point sources over periods of several
days to several weeks, and are easy to use for a variety of decision-
making and regulatory applications. Finally, the models are intended to
serve as flexible testbeds for further research, development and
simulation tasks.
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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
The three new models are, respectively:
• MESOPLUME, a mesoscale variable-trajectory Gaussian "plume-
segment" model (Benkley and Bass 1979a) , adapted by ERT from
the plume segment approach taken in the STRAM model (Hales et
al. 1977),
• MESOPUFF, a mesoscale variable-trajectory Gaussian "puff"
superposition model, adapted by ERT from the puff approach
taken in the MESODIF model (Start and Wendell 1974); and
• MESOGRID, a mesoscale numerical grid model (Morris et al.
1979), adapted from the method of moments approach taken in
the SULFA3D model (Egan et al. 1976).
This report, the third in a series entitled "Development of
Mesoscale Air Quality Simulation Models", describes the MESOPUFF model
in technical detail; illustrates its application; and provides a User's
Guide to the model. However, to obtain a fuller understanding of the
model's capabilities, limitations and recommended usage, the user should
be familiar with the relevant materials contained in the following
related reports:
• the companion report (Volume 1) describing the extensive
series of comparison and model sensitivity analyses performed
with these models (Bass et al. 1979);
• the companion report (Volume 6) describing the specially
designed MESOSCALE meteorological preprocessor program,
MESOPAC (Benkley and Bass I979b);
• the companion report (Volume 5) describing the specially
designed model postprocessing and analysis system, MESOFILE
(Scire et al. 1979).
1.2 The Mesoscale Puff Element Model (MESOPUFF)
MESOPUFF is a regional-scale variable-trajectory Gaussian puff
model. The MESOPUFF modeling algorithm has been adapted from that
described by Start and Wendell (1974). It differs from the conventional
Guassian plume approach in that MESOPUFF simulates the deformation of a
continuous plume by a temporally-varying, vertically-uniform horizontal
wind field. MESOPUFF simulates a continuous point source by superposing
discrete puffs. Each puff is advected in a Lagrangian sense--its time
history is independent of preceding or succeeding puffs. The dimensions
of an individual puff are proportional to its travel distance (or travel
time). The representation of a continuous plume by the discrete puff
approach is depicted schematically in Figure 1-1.
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ENVIRONMENTAL RESE ARCH s TEC--"SiOLOO.> 'NC
Figure 1-1 Schematic Representation of Puff Superposition Approach
o
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o
t-
o
00
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MESOPUFF accommodates multiple point sources and includes modules
for plume rise, plume growth^ fumigation, linear conversion of sulfur
dioxide (S02) to sulfate (SO^) and dry deposition of S02 and S04.
With suitable choices of input parameters, MESOPUFF can reproduce
the results of a conventional Gaussian plume model in the near field of
a source (as close as 5 km).
1.3 Integrated Mesoscale Modeling System
The MESOPUFF model has been incorporated as .an independent model
element within an efficient, easy to use integrated mesoscale modeling
system. This integrated system, depicted in Figure 1-2, comprises
components for meteorological preprocessing, mesoscale transport-
diffusion, and post-processing. Standardizing model input/output func-
tions in this system permits easy combination of results from two or
more model runs, or direct and cost-effective comparison of simulations
performed with two or more different models (see, for example, Bass et
al. 1979). The meteorology preprocessor MESOPAC drives identically any
of the three mesoscale transport-diffusion models. In turn, each of
these models in turn identically communicates its results to the
MESOFILE postprocessing system - responsible for file management, dis-
play, and statistical analysis of all model output fields.
1.4 Organization of the Report
Section 2 of this report contains a detailed technical description
of the MESOPUFF model; specific user instructions are described in
Section 3; a test case for the MESOPUFF model is presented in Section 4.
A complete Fortran microfiche listing of the MESOPUFF model is
appended.
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EN\,lRONVENTAL RESEARCH A TECH\CXOOV
MESOSCALE
METEOROLOGY
MESOPAC
MESOSCALE
TRANSPORT-
DIFFUSION
MODELS
MESOPLUME
MESOPUFF
MESOGRID
ANALYSIS
MESOFILE
o
o>
Figure 1-2 Integrated Modeling System
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
2. MESOPUFF TECHNICAL DISCUSSION
2.1 Basic Mass Conservation Equations
MESOPUFF, a discretized variable-trajectory version of the
conventional straight-line Gaussian plume model, is designed to take
into account the spatial and temporal variations in the advection,
diffusion, transformation, and removal mechanisms governing plume dis-
persion on regional transport scales. In MESOPUFF, a continuous plume
is modeled by subdivision into a sufficient number of discrete "puffs"
of circular horizontal cross section. The conservation of pollutant
mass in a puff transported a distance As is expressed by the mass
balance equation:
OO CO 00
— OO _ OO
dr de dz
(2-1)
oo oo oo
= £r / / / C dr d6 dz
As
_oo _oo
oo oo oo
- / / / C dr de dz
s+As
_00 _00
where r, 6, z define points relative to the puff center in cylindrical
coordinates, G(r,6,z) (g m~3 s"1) is the rate of change (gain-loss) of
pollutant concentration C(r,6,z;s) (g m~3), AQ (g s l~) is the resultant
rate of change of pollutant mass, and u(m s T) is the wind speed. In
the MESOPUFF model u is constant from s to As, where s is defined as
the total distance a puff has traveled since it was emitted.*
For a discrete puff lying below the mixing height H, the circularly
symmetric ground-level puff concentration C(r,0,0;s) is defined as
C(r,0,0;s)
Q(s)
exp
2TT O (S)
-r
(2-2)
where Q(s) is the pollutant mass flux, and ay(s) the "radial" Gaussian
plume dispersion coefficient at distance s. The use of a "radial"
Gaussian dispersion coefficient is a convenient computational device,
nothing more. The functions gi(z) and g2(z) are dependent upon the
*By contrast in the MESOPLUME (plume segment) model, s is the current
distance of a plume segment endpoint from the emitting source, measured
along the plume axis; for temporally varying flows, the two definitions
can yield significantly different values of s.
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ENVIRONMENTAL RESEARCH 4 TECHNOLOGY INC
vertical distribution of concentration in the puff. Replacing H by Hm,
the maximum mixing depth encountered by a puff (see Section 2.8),
MESOPUFF permits the user to specify one of two possible algorithms for
the distribution function g(z), namely
1) a uniform vertical distribution algorithm within H such that
gi(z) = Hm and g2(z) = 1.0, and
2) a Gaussian, multiple reflection algorithm where
• for az < 2H gi(z) = /2rT az and g2(z) is a function that
accounts for multiple reflection effects (g(2) > 1), and
• for az >_ 2Hm, gl(z) = Hm, and g2(z) = 1.0.
For regional-scale transport, e.g., at distances from 100 to
1,000 km from a source, either algorithm will produce substantially
similar results, as a rule, because at travel distances >100 km az is
likely to be greater than 2H .
Using the uniform vertical distribution function (1), the ground
level puff concentration C(r,0,0;s) at distance s is
C(r,0,0;s) =
Q(s)
2TT o (s) H
y m
exp
-r
(2-3)
At distance s+As, the ground level concentration becomes
2
C(r,0,0;s+As) =
Q(s+As)
2TT a (s+As) H
y ^ J m
exp
2 a (s+As)
X
(2-4)
To ensure that a series of discrete puffs overlap along the variable
plume axis with sufficient density to approximate a continuous plume,
an individual puff (as described by Equation 2-2) , should not travel a
distance As any larger than a in one time step At. Where wind speeds
are large enough that this condition would be violated it if ecessary
to subdivide further the time step used to interpolate puff concentrations
to grid points.
The MESOPUFF model solves the mass balance equation (2-1) inde-
pendently for both sulfur dioxide (S02) and sulfate (S<\). The "gain"
functions for each species include terms for the loss (gain) of S02
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ENVIRONMENTAL RESEARCH A TECHNOLOGY INC
by linear decay of S02 to SO^, and also include terms for dry
deposition of either species - see Sections 2.5 and 2.6.
2.2 The Grid System
To facilitate the interaction of the MESOPUFF model with a number
of input and output routines and pre- and postprocessors, a simple
Cartesian coordinate system has been adopted for MESOPUFF. All spatial
model input data (emission source inventories and meteorological fields)
are referenced to the same grid, called the "basic computational" grid.
To improve the resolution of the plume sampling function (see
Section 2.4.3), MESOPUFF uses a sampling grid that is a subset of the
basic computational grid. The origin of the sampling grid may be placed
anywhere on the basic computational grid (other than on the northern or
eastern grid boundaries). The resolution of the sampling grid is a
multiple of the resolution of the basic computational grid. Currently,
the maximum allowable size of both the basic computational and sampling
grids is 40 by 40 horizontal grid indices. Figure 2-1 illustrates one
possible arrangement of basic computational and sampling grids. [More
detailed instructions for defining the dimensions and resolutions of the
two grids are contained in Section 3.2.] Note that the grid index of
the origin (1,1) is assigned Cartesian coordinates x = 0, y = 0. The
sampling grid in this example originates at (i = 2, j = 2) or (x = 1,
y = 1) on the basic computational grid, and a spatial resolution four
times finer than the basic computational grid.
2.3 Specification of Model Inputs
MESOPUFF is, at present, driven by the meteorological fields
produced by the MESOPAC MESOscale meteorology PACkage (Benkley and Bass
1979b), but an alternative meteorological preprocessing system with
appropriate grid resolution could be substituted by the user. MESOPUFF
requires the following fields (usually at hourly intervals) interpolated
to each model grid point:
• horizontal (u,v) wind components,
• mixing depth, and
• Pasquill-Gifford-Turner (PGT) stability class.
Examples of the MESOPAC meteorolog:- ,1 input used by MESOPUFF are shown
in Appendix A. Use of MESOPAC model output by the MESOPUFF model is
straightforward - the Cartesian coordinate system is identical in both
models. Note that the horizontal (u,v) wind components are considered
invariant with height. Vertical wind components are not used. The
fields of PGT stability class are used by MESOPUFF in doing plume rise
and plume growth calculations.
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
y = 5.0
i = 6
y = 4.0
i = 5
y = 3.0
j = 4
y = 2.0
Y =
Ay = Ad
y = 0.0
j = 1
x = 0.0
I I
x=1.0
i=2
• Ax = Ad-
I I
—h + +"
1
x = 2.0
i=3
x = 3.0
i=4
x = 4.0
i=5
x = 5.0
i = 6
Figure 2-1 One Possible Arrangement of Sampling and Basic Computational
Grids
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ENVIRONMENTAL RESEARCH* TECHNOLOGY
2.4 Puff Trajectory, Dispersion and Sampling Algorithms
The computational scheme of the MESOPUFF model has three distinct
functional elements: (1) a Lagrangian puff trajectory function, (2) a
puff dispersion function, and (3) a puff sampling function. The
Lagrangian trajectory function is used to advect the centerpoint of each
puff during a basic time step. The radius of each puff is determined by
the puff dispersion function. Given the size and location of each puff,
the puff sampling function computes the concentration exposure received
during the time interval at each grid point by summing up the individual
puff contributions at each grid point.
2.4.1 Lagrangian Trajectory Function
This section describes how the centerpoint of a puff is advected
during a time step, it has been adapted (but largely verbatim) from
Hales et al. (1977, pages 15-18).
Let the components of the wind in the x and y grid directions along
the trajectory be designated by u[t;x(t) ,y (t) ] and v [t ;x(t) ,y (t) ] ,
respectively,
where
x(t) = - / u[t';x(t'),y(t')]dt'
, t
y(t) = ^ / v[t';x(t'),y(t')]dt'
o
x(0) = XQ ; y(0) = yQ
u(0;x(0),y(0)) = u(xQ,y0)
v(0;x(0),y(0)) = v(xQ,y0)
and Xg,yg are the initial coordinates (origin) of a trajectory of total
length s. (The grid space unit Ad is used in the program to convert to
nondimensional spatial units on the computational grid.) The vectors
u(t;...) and v(t;...) provide a Lagrangian description of the velocity
field. Increments of advection over a further time interval At are
therefore given by
t + At
Ax = -^ / u[t';x(t'),y(t')] dt' ; (2-5a)
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• EWIROfAlENTALRESEARCHSTECHNOLOGV
t+At
Ay = |j J v[t';x(t'),y(t')] dt' . (2-5b)
After the new coordinates x(t+At) and y(t+At) are calculated for each
incremented puff centerpoint, a check is made to see if any of these
values are off the grid. If so, the affected puff is deleted from
further consideration.
The integration of the wind components over the trajectory is
approximated by a two-step iteration method involving bilinear inter-
polation in space and in time (see Figure 2-2) .
The various positions in Figure 2-2 are best defined by equations:
= x(t) + u[t;x(t),y(t)] At ; (2-6a)
= y(t) + v[t;x(t),y(t)] At ; (2-6b)
l,yl] At ; (2-6c)
ljyi] At ; (2-6d)
x(t+At) = 0.5[x(t) + x2] ; (2-6e)
y(t+At) = 0.5[y(t) + y2] . (2-6f)
Thus, the new position (x(t+At),y(t+At)) is found by adding the
vector average of two advection increments to the former position
(x(t),y(t)). The first advection increment is calculated by advecting
the plume increment for the entire interval At using the wind effective
at [x(t),y(t)] at time t. The addition of this increment to the posi-
tion [x(t),y(t)] yields the position (xi,yi). However, (x1}yi) is not
assumed to be the actual end of the advection increment because the wind
may change along the trajectory. A second advection increment is cal-
culated using (x^yj) as the starting point and the wind at that point
effective at the end of the time increment. The addition of this advec-
tion increment to position (x^yj) yields position (x2,y2)- Then the
new puff position (x(t+At),y(t+At)) is taken to be the point halfway
along the line from (x(t),y(t)) to (x2,y2).
The bilinear interpolation by which the effective wind components
u(t), and v(t) are calculated works as follows. Let t and tn+^ be the
effective times of the two gridded wind fields closest to time t. Time
interpolation weights t} and t2 are defined by:
2-6
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(2-7b)
Next, the location of (x(t),y(t)) is noted on Figure 2-2. The coor-
dinate values are between 3 and 4 for x(t) and between 2 and 3 for y(t)
Accordingly:
Xq = x(t) - 3 ; (2-8a)
X = 1 - X ; (2-8b)
p q ^ J
Y = y(t) - 2 ; (2-8c)
This yields
Y = 1 - Y . (2-8d)
p q
u(t) = t. X Y u(t ;3,2) + t_ X Y u(t .;3,;
Ipp n' ' 2pp v n+1 '
Iqp n'' 2qp
Similar equations hold for v(t), u(t+At), and v(t+At). Therefore, the
advection Equation 2-5 is calculated from
Ax = - (u(t) + u(t+At)}At; (2-10a)
Ay = " fv(t) + v(t+At)}At. (2-10b)
The subsequent positions are given by
x(t+At) = x(t) + Ax ; (2-lla)
y(t+At) = y(t) + Ay . ' (2-llb)
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Figure 2-2 Calculation of the Trajectory of a Puff Centerpoint
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2.4.2 The Puff Dispersion Function
ENVIRONMENTAL RESEARCH & TECHNOLOGV INC
This section, describing the evaluation of the puff dispersion
parameters, has been taken largely verbatim, with modifications, from
Hales et al. (1977, pp. 23-24). The puff dispersion parameters ay and
az are calculated for distances out to 100 km using plume growth
formulas fitted to the curves of Turner (1970) . For distances greater
than 100 km the plume growth rates given by Heffter (1965) are used.
The growth of a puff with travel time t or along the plume trajectory
distance s from the source is represented by
do
a (s+As) = a (s) + As -7—^
y^ y^ ' ds
s+As/2
(2-12)
da
a (t+At) = a (t) + At -^~
t+At/2
(2-13)
Similar equations for a are used. These terms allow for spatial and
temporal changes in stability class to be included, without violating
the entropy principle (puff centerpoint concentrations cannot increase
with downwind distance).
The integral formulas for a and az for travel distances less than
100 km are of the following forms
0 9
a (s,a) = Y s ' (meters);
(2-14)
a^(s,a) =
L S
a
(meters)
(2-15)
Here a is a stability index designated as A, B, C, D, E, or F correspond-
ing to the PGT stability categories. The coefficients Ya, Za, and ba
are given in Table 2-1 as a function of stability index a and yield
values of a and oz in meters when s is specified in meters. Because
the integral formulas are not valid if the stability class changes over
the travel distance s, the differentiated forms of 2-14 and 2-15 are
actually used to carry out the computations in 2-12.
da
__
ds
= 0.9 Y s
a
-0.1
(2-16)
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TABLE 2-1
COEFFICIENTS FOR DISPERSION PARAMETER FORMULAS
Puff Growth Coefficients
Stability
Index a
A
B
C
D
E
F
0
0
0
0
0
0
Y
a
.36
.25
.19
.13
.096
.063
0
0
0
0
0
0
L
a.
.00023
.058
.11
.57
.85
.77
b
a
2.10
1.09
0.91
0.58
0.47
0.42
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ENVIRONMENTAL RESEARCH ST6CHMOI.OGV INC
do.
= b Z s . (2-17)
ds a a
MESOPUFF assumes that a a_ = 0 at the origin (s = 0).
The derivative formulas used to grow oy and az for travel distances
greater than 100 km are those given by Heffter (1965) :
da
-^- (m s ) = 0.5 (2-18)
da
dt
(m s ) = 0.5 (2K ) ' t ' (2-19)
2.4.3 The Plume Sampling Function
Each puff resident on the grid is sampled, using the plume sampling
function, to evaluate the average concentration experienced at each
sampling grid intersection during the previous time step. For example,
consider the hypothetical puff depicted in Figure 2-3. The puff center-
point is at (x,y) and the puff radius is truncated at 3 ay. This is a
reasonable simplification - much less than 1% of the area under a
Gaussian distribution function lies beyond 3 a from the peak value.
During the time step considered, the grid point intersections (21,12),
(22,12), and (22,13) are each impacted by the hypothetical puff; each
grid point is assigned a certain average concentration resulting from
the presence of the puff during the time step At. The grid point con-
centration C(i,j) calculated at (22,12) is computed by Equation 2-2:
C(22,12) = Qtx,y)
2 — exP
°y (x,y) gl(z)
2
-r
(2-20)
If a continuous plume has been properly simulated, a grid point impacted
by the plume will receive individual doses ^-rom more than one puff (as
was previously depicted in Figure 1-1). It is also possible that two
plumes overlap; in this case, puffs from both plumes can impact a grid
point. The total concentration, CT(i,j) at each grid point is therefore
computed as the sum of individual puff contributions:
MT
I C (i,j) (2-21)
M=l
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ENVIRONMENTALRESEARCH&TECHNOLOGY INC
j= 15
j= 14
j= 13
j= 12
i = 20
i = 21
i = 22
i = 23
Figure 2-3 Calculation of the Concentration C(i,j) by the Sampling Function
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ENVIRONMENTAL RESEARCH A TECHNOLOGY INC
where M is the total number of puffs impacting the grid intersection
(i,j) during the time step of interest.
2.5 Conversion of Sulfur Dioxide to Sulfate
MESOPUFF represents the conversion of S02 to SO^ as a simple
linear rate function—the changes in mass of each pollutant in one time
step At are given by the time-discretized equations:
AQn(S02) = k1 Qn(S02) At (2-22a)
AQn(S04) = -1.5 kx Qn(S02) At (2-22b}
where Qn(S02) is the mass of S02 at the beginning of the nth time step
and kjfs"1) is the conversion rate constant. MESOPUFF uses the nominal
value kj =-5.56 x 10~5 (that is, 2% per hour) - suggested by Hales
et al. (1977), unless otherwise specified by the user.
Note that the conversion of S02 to SO^ represented by Equation 2-22
is (1) independent of the vertical or horizontal distribution of S02
within a plume and (2) independent of whether a plume lies above or
below the mixing height.
For the solutions to be adequate representations of the continuous
exponential equations (e.g., Q(S02) = kiQ(S02)), Q should not change
appreciably over the time interval At. Since this is frequently not the
case, the time interval At is optionally subdivided into as many subin-
tervals At' as are required to ensure that no more than a specified
fraction AQf of the mass Q is removed by decay during a subinterval At'.
This process is described further in the next section.
2.6 Dry Deposition of Sulfur Dioxide and Sulfate
The changes of mass AQ (g) of each pollutant resulting from dry
deposition are given by:
AQn(S02) = -(vd(S02) Qn(S02) At) / Hm (2-23a)
AQn(SOJ = -(v, (SO") Qn(SO~:) At) / H (2-23b)
4 d 4 4 m
where Q (S02) and Q (SO^) are the masses of S02 and SO^, respectively,
in the puff at the beginning of the nth time step, vd(S02) and v^fSO^)
are the deposition velocities of each pollutant, and Hm is the vertical
depth of the puff element (see Section 2.8). MESOPUFF uses the nominal
2-13
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ENVIRONMENTAL RESEARCH & TECHNOLOGY 'NC
values vd(S02) = 0.01 (m/s) and VjCSO^) = 0.001 (m/s) , as suggested by
Hales et al. (1977), unless otherwise specified by the user.
As described before, MESOPUFF can optionally ensure that the mass Q
does not change within one subinterval At' by more than a user-specified
fraction AQf. Taking into account both S02 removal mechanisms (decay
and deposition) , the expression used by MESOPUFF to specify the sub-
interval At' is
AQ,(SO ) AQ (SO ) H
In other words, the subinterval size At' can optionally be chosen by
MESOPUFF at the beginning of each basic interval At such that no
more than a specified fraction AQf of S02 mass is removed by either
mechanism (or, no more than 2AQf by both mechanisms combined) within
At'. It should be emphasized that the conversion and removal rates are
not affected by this restriction. Further discussion of the optional
sampling mechanism is contained in Section 2.9.
2.7 Plume Rise
The effective emission height he of each plume segment is computed
as he = hs + hp, where hs is the stack height (m) and hp is the plume
rise (m) . The plume rise equations used by the MESOPUEF model are
those described by Briggs (1975) for equilibrium (final) plume rise.
For unstable and neutral conditions with h' < H (i.e., the plume does
not rise into an elevated stable layer)
h = h' = 1.6 F1/3 (3.5 x*)2/5 u'1 ; (2-25a)
For unstable and neutral conditions with h' > H (i.e., the plume pene-
trates into an elevated stable layer)
, 1 i 1/3
h = MIN {h1 , (1.8 zj: + 18.75 F um S ) }; (2-25b)
for stable conditions when u > 1.37 m/s
h = 2.6 F1/3 S- u- ; (2-25c)
for stable conditions when u < 1.37 m/s
h = 5.0 F1/4 S-3/8 . (2-25d)
2-14
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
where:
4 3
F = buoyancy flux (m /s )
x* = 34.49 F0'4 for F > 55
= 14.0 F0-625 for F <_ 55
S = (g/T)(30/32)
g = 9.8 m s"2
T = 290°K
86/3z = 0.0137°K m'1
H = mixing depth (m)
zb = H - hs (m) ^
u = wind speed (m s )
u = MAX {u, 1.37}
m
2.8 Treatment of Plume Fumigation
When the "uniform vertical distribution" option is elected, MESOPUFF
takes the spatial and temporal variations in the mixing height into
consideration to determine the extent of ground level impact.
(a) For a puff element emitted at an effective stack height which
is less than the mixing height, MESOPUFF assigns the element a
height of zero and immediately mixes the entire mass of the
puff uniformly through the mixing depth (the mixing lid acts
as a perfect reflector). Equations 2-3 and 2-4 are then
applied to compute ground level concentrations.
(b) For a puff element which is emitted at an effective stack
height greater than the mixing height, no effect of the puff
is felt at ground. However, if subsequently the mixing height
becomes greater than the height of the puff centerpoint, the
entire puff element is immediately mixed uniformly through the
mixing depth, the puff height is set equal to zero, and
Equations 2-3 and 2-4 again apply. The mixing depth encountered
by a puff element is likely to change over time and space.
MESOPUFF assumes that a puff element residing in the mixed
layer is mixed through the maximum mixing depth Hm encountered
by the puff in its progression through the computational
space-time grid.
The restriction of a uniform puff through a characteristic depth
such as Hm is imperative for a one-layer model such as MESOPUFF - so
that parcels of material, once entrained, are not bifurcated in the
2-15
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ENVIRONMENTAL RESEARCH i TECHNOLOGY .
vertical when the height of the mixing lid changes (as sensed by a
parcel in transport). Therefore, in the MESOPUFF model a puff, once
entrained, is uniformly mixed through a realistic height, consistent
with the following assumptions:
(a) When convection ceases in the late afternoon, turbulent
energy in the afternoon mixed layer dissipates. Once the
energy of the large convective cells is completely damped, the
remaining small scale energy is not sufficient to yield a
vertical entrainment rate comparable to the daytime entrain-
ment rate produced by large convective eddies.
(b) The stable lid capping the convective layer most likely
maintains some integrity after convection ceases, and acts to
prohibit any additional vertical entrainment of plume material.
(c) A modeling approach that redistributes mass into a shallower
layer when the mixing depth decreases will violate the second
law of thermodynamics.
Since no mechanism remains for turbulent transfer of pollutant
material either upwards or downwards once the mixing depth decreases, it
is asserted that the height most appropriate to define the extent of
vertical mixing of a puff is the maximum mixing height that the puff
encounters during any portion of its travel.
To schematically illustrate the interaction of the MESOPUFF
vertical distribution algorithm and the mixing depth progression
algorithm used by MESOPAC (Benkley and Bass (1979b), Benkley and
Schulman 1979)) a hypothetical example is given in Figure 2-4.
Here, consider two puffs of material released at different times
from a source with an effective stack height of 250 m; the first puff
release is made at 0300 GMT on the first day, the second puff release at
0300 GMT on the second day. Assume that the hypothetical source is
located in the western United States so that 0000 GMT corresponds to
late afternoon—the usual time of maximum mixing depth.
The first puff is entrained at 0600 GMT on Day 1 as the nocturnal
boundary layer oscillates slightly .upward in height. MESOPUFF immedi-
ately mixes the puff uniformly throughout this mixing depth.
This puff is mixed uniformly through 900 m by 0000 GMT on Day 2,
and remains mixed through 900 m subsequent to that time, even though the
height of the mixed layer collapses. The second puff, emitted at
0300 GMT on Day 2 is fumigated at 1500 GMT and is mixed uniformly
through 700 m by the end of the afternoon. Therefore, the first puff,
emitted at 0300 GMT on Day 1, remains uniformly mixed through a deeper
vertical layer than the second puff; this is consistent with the greater
extent of mixing on the first day as compared to the second day.
2-16
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FNViRONMENTAiOESEAPCHi TECHNOLOGY (
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ENVIRONMENTAL RESEARCH * TECHNOLOGY INC
Both options can be exercised jointly; however, the larger of
(rip, ns) should be an even multiple of the smaller. As an example,
suppose the basic time step is 1 hour, with np = 2 and ns = 4; puffs
will be released every half-hour from each source, puff trajectories
will also be updated every half-hour, and puffs will be sampled eve^y
quarter-hour, or twice per puff release step.
If the dynamic sampling step option is invoked in MESOPUFF (see
Section 2.6) the actual sampling frequency n used by MESOPUFF during
any basic model time step will be taken as tne larger of (a) the user-
specified np and (b) the dynamically-computed np.
Some guidance in selecting the appropriate puff release and
sampling rates for a MESOPUFF simulation is provided by Figure 2-5,
which depicts the strong effect of increasing the distance between
adjacent puff centerpoints upon the ability of MESOPUFF to recreate a
continuous plume. It is seen that when adjacent puff centerpoints are
separated by 2 av, concentrations computed by MESOPUFF will differ by no
more than about ± 2% from concentrations as computed by MESOPUFF in the
limit as puff separation distances go to zero; by contrast, if the
centerpoint of adjacent puffs are separated by about 4 oy, deviations
can be as large as 50% or more.
Because puffs are assigned zero width when released, it follows
that for a given combination of puff release rate, sampling rate, and
wind speed, a certain amount of time must elapse before adjacent puffs
have grown wide enough to provide the degree of overlap necessary to
simulate a continuous plume. But, because high rates of puff release
and puff sampling quickly becomes cost-prohibitive (see Section 3.5),
some near-field inaccuracies must be tolerated if long-distance trans-
port is to be modeled in a cost-effective manner. Therefore, if one
wishes to model plume impact at distances greater than 100 km, for
example, the puff release rate and puff sampling rate should be chosen
so that, for the maximum expected wind speeds, adjacent puffs will
overlap sufficiently within say, a downwind range of 50-100 km.
2.10 Comparison to the Conventional Gaussian Plume Model
From the point of view of possible regulatory applications, one of
the most attractive features of MESOPUFF is its ability to recreate the
results of the conventional Turner Workbook plume model (using PGT
coefficients). When MESOPUFF is run with appropriate uniform mete-
orology and fine steady-state spatial resolution, it can reproduce the
Turner Workbook results to a high degree. This can be demonstrated, for
example, under the following test conditions:
• The horizontal grid spacing of the model is reduced, e.g., to
5 km.
2-19
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
C
o
_
»
Q
0)
O)
(0
+••
C
0)
u
Puff Separation Distance (in units of oy)
Figure 2-5 MESOPUFF Model: Percentage Deviation with Puff
Separation Distance
2-20
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ENVIRONMENTAL RESEARCH a TECHNOLOGY 'NC
• The meteorological fields (wind direction, wind speed, mixing
height and PGT stability class) used to drive MESOPUFF are
taken to be spatially uniform and constant in time.
• MESOPUFF is run with one source until quasi-steady-state
conditions are well established; that is, puffs are created at
the same uniform rate at which they disappear off the edge of
the grid.
• Consecutive puffs are emitted (or sampled) with sufficient
frequency to simulate a continuous plume (see Section 2-9).
Under these special test conditions, MESOPUFF simulates very well
the Turner Workbook plume concentrations out to distances of 100 km from
an emission source. (The PGT a and az curves, represented in the model
by piecewise linear power law fits, are only defined to 100 km.)
Table 2-2 and Figure 2-6 provide a representative illustration of how
closely MESOPUFF results compare to those obtained for the conventional
Gaussian plume model using the PGT "D" curve for Oy, and a uniform
vertical distribution. Overall, the comparison is excellent—the very
small fractional differences (typically less than 2%) are attributable
mostly to inexact fitting of the PGT curves by the power law functions
used in MESOPUFF.
MESOPUFF includes the option for a Gaussian distribution in the
vertical with multiple reflections (see Section 2.1). MESOPUFF is
therefore applicable both in the near field of a source (where a
vertical Gaussian profile is appropriate and in the far-field of a
source (where a uniform vertical distribution can normally be assumed).
The current version of MESOPUFF does not include a transitional plume
rise algorithm but transitional plume rise is not important beyond 5 km,
even for the largest power plants.
In sum, if input parameters are chosen appropriately, MESOPUFF can
be used for dispersion calculations even as close as, say, 5 km from a
source; and, importantly, MESOPUFF can reproduce a conventional Gaussian
model.
2.11 The MESOPUFF Computer Program
MESOPUFF is a highly modular computer program which shares with
MESOPLUN'u: and MESOGRID standarized input/output features and, where
possible, identical program modules. The computer program flow chart
(Figure 2-7) outlines the order of execution of the individual modules
described at length in the 'MESOPUFF Technical Discussion'.
2-21
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ENVIRONMENTAL RESEARCH 5 TECHNOLOGY INC
TABLE 2-2
COMPARISON OF Cu/Q VALUES FOR MESOPUFF AND
TURNER WORKBOOK-COMPUTED VALUES
(u = 2.78 m s'1, PGT Class = D, H = 1000 m,
uniform vertical distribution)
Distance
(km)
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
PGT
a (m)
y
300
550
780
1,000
1,220
1,420
1,620
1,820
2,020
2,200
2,400
2,600
2,775
2,975
3,200
3,375
3,550
3,700
3,850
4,000
Turner Workbook
(C u Q'1)
ll.SOxlO"7
7.25
5.11
3.99
3.27
2.80
2.46
2.19
1.97
1.81
1.66
1.53
1.44
1.34
1.25
1.18
1.12
1.08
1.04
1.00
MESOPUFF
(C u Q'1)
12.01xlO~7
7.47
5.18
4.02
3.28
2.80
2.43
2.15
1.94
1.77
1.62
1.49
1.39
1.30
1.22
1.15
1.09
1.04
1.00
0.96
Fractional
Deviation
0.02
0.03
0.01
0.01
0.00
0.00
-0.01
-0.02
-0.02
-0.02
-0.02
-0.03
-0.03
-0.03
-0.02
-0.03
-0.03
-0.04
-0.04
-0.04
2-22
-------
ENVIRONMENTAL RESEARCH STECHNCXOGV ;NC
~ Gaussian - P6T
0 = MESOPUFF
40 60
Dustance (km
80
inn
Figure 2-6 MESOPUFF vs. the Conventional Gaussian Plume
2-23
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Initialize input parameters
(Subroutines IMPARM, BLOCK DATA)
Update hour, day, year
(Subroutine KALEND)
Update meteorology from disk or tape
(Subroutines READER,WETHO,WETHER)
Initialize direct access files
(Subroutine FILMAN)
NPUFFS=NOLDY+NPUFTSx|MSOURC ;
JP=0
NPUFFS=0; NN=0
JP=NPUFFS?
NN=NADVTS?
If (JP>NOLDY)^ompute 'effective stack
height' -PUFHTM(JP) (Subroutine PRISE)
Delete puffs that fell off grid edges
NOLDY=NPUFFS-NFALL
If (LVARSA) increase NSAMAD,
if necessary
MOD (NN,IAVG)=0?
--"
Yes
If (MOD(NN,IPRINF))=0,
output fields to line printer
(Subroutines WRITER, RANGE, DISP, PAGE)
NNN=NPUFTSxNSAMAD?
If (MOD(NN, ISAVEF))=0,
output fields to direct access files
(Subroutine PUTOUT)
NNN=NNN+1
MOD(NNN,NSAMAD)=0?
Sampling function
(Subroutine GRICON)
Lagrangian trajectory function
Dispersion function
(Subroutines S!GMA,VERTDF)
MOD (NNN,NPUFTS)=0?
Calculate removal from decay and dry deposition
Q(JP)=Q(JP)-dQ/dt
(Subroutine REMOV)
Figure 2-7 NESOPUFF Computer Program Flow Chart
2-24
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E V. 'OON'.'ENTAL PeSEARCH A TFCHNCLOGv v:
3. MESOPUFF USER INSTRUCTIONS
3.1 General
A MESOPUFF model simulation requires the following two input data
sets:
• meteorological fields from MESOPAC (unformatted disk or tape
input via logical unit 2) and
• model simulation control parameters and emission source
inventory (cards or card-image disk input via logical unit 5)
A complete description of model simulation control parameter and
emission source inventory input is contained in Section 3.2.
For most convenient operation, MESOPUFF should interface with the
output of the MESOPAC meteorological preprocessor (see Section 3.3).
Output of a MESOPUFF simulation can be routed to either (or both) of the
following:
• line printer (logical unit 6) and
• direct-access disk storage system (logical units 13, 15, 21,
22, 23, and 24).
The direct access storage system allows for automatic storage, catalog-
ing, and easy retrieval of all output data files from MESOPUFF. Avail-
ability of on-line direct-access disk storage enables the user to invoke
the powerful MESOFILE file-management system, designed especially for
interface with the regional-scale models. The MESOFILE system has file
management components that can produce a record of the date of the run,
the run characteristics, the disk file locations of all the concen-
tration data output, and the values of all the input parameters for the
run. The MESOFILE program allows this information to be retrieved for
all the previous runs made on a particular set of disk files. The
MESOPUFF program contains a file management subroutine (FILMAN) which
determines without further user input the proper locations for all of
the various MESOPUFF disk output files. MESOFILE can then be used for
flexible time averaging if any set of fields, summation of different
model simulations (particularly useful when more than 10 sources are to
be simulated), statistical comparison of model results, and graphical
contour display.
3.2 Description of Card-Image Input
This section provides a detailed description of all the card-image
input requirements of the MESOPUFF model, model simulation control
parameters, and emission inventory. The input package has been designed
3-1
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
for use in common by all three mesoscale models (MESOPLUME, MESOPUFF,
and MESOGRID) especially to facilitate intermodel comparison tests. The
common input subroutine (INPARM) reads in all model simulation control
parameters in Fortran NAMELIST format so that input parameters common to
all three models can be included in standardized NAMELIST blocks. A few
model-specific NAMELIST sets, however, are required because of certain
features peculiar to each model algorithm. There are thirteen NAMELIST
blocks included within the INPARM subroutine package, as follows:
(1) MODEL, (2) CONTR, (3) GRID, (4) SIGMA, (5) METD, (6) PUFF1, (7) PUFF2,
(8) PLUM1, (9) PLUM2, (10) GRIDY, (11) REMOV, (12) OUTPT, and (13) SOURC.
NAMELIST blocks PLUM1, PLUM2, and GRIDY are not used by MESOPUFF and
must be omitted from the input data runstream.
The remainder of this section provides detailed descriptions of the
parameters in each NAMELIST set.* These NAMELIST sets are to be included
in the input run stream in the identical sequence described above.
NAMELIST TITLE--MODEL
MODEL defines which model is to be run.
for a MESOPLUME run.
Initialize LPLUME = .TRUE.
Parameter
LPLUME
LPUFF
LGRID
Type
LOGICAL
LOGICAL
LOGICAL
NAMELIST TITLE--CONTR
Definition
If .TRUE., MESOPLUME is
to be run
If .TRUE., MESOPUFF is
to be run
If .TRUE., MESOGRID is
to be run
CONTR initializes computational control variables.
Parameter Type Definition
REAL
Default
.FALSE.
.FALSE.
.FALSE.
DTIME
NADVTS
INTEGER
Length of the basic time step
(hours)
Length of the simulation in
terms of basic time steps
Default
1.0
24
*The description of certain parameters that were retained from an earlier
version of MESOPUFF but not otherwise used or that were included only
to perform various model sensitivity tests, are omitted from this
discussion—these parameters would not be activated by the average
user. However, for a complete list of possible input parameters, the
interested reader should consult the documentation included as comment
cards directly in subroutine INPARM.
3-2
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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
Parameter Type
MTFREQ INTEGER
IAVG
INTEGER
Definition Default
Rate (in terms of 'DTIME') 1
with which wind, mixing
depth, and stability
fields are updated, in terms
of the basic time step.
'MTFREQ'*'DTIME' must be equal
to or an even multiple of the
MESOPAC time step 'ISTEP' (hours)
Number of basic time steps over 24
which output concentration arrays
are to be averaged
NAMELIST TITLE—GRID
GRID initializes parameters defining the three major grids:
meteorological, basic computational, and sampling. The basic
computational grid must be a subset of the meteorological grid and
also must have the same grid spacing. The sampling grid must be a
subset of the basic computational grid; it may have a grid spacing
that is the same as the basic computation grid or denser by an
integer multiple. Currently, the maximum allowable size of both
the basic computational and sampling grids is 40 by 40 horizontal
grid elements.
Parameter
IELMET
JELMET
DELTMT
IASTAR
IASTOP
Type
INTEGER
INTEGER
REAL
INTEGER
INTEGER
Definition Default
Number of elements in the x- 26
direction of the meteorological
grid—must be the same as 'IMAX'
used by MESOPAC (must be <_ 40) .
Number of elements in the y- 26
direction of the meteorological
grid--must be the same as 'JMAX'
used by MESOPAC (must be <_ 40) .
Basic computational grid spacing 40,000.
(meters)--must be equal to the
grid spacing, DX, used by the
MESOPAC meteorological grid
Element number of the meteoro- 1
logical grid where the basic
computational grid starts
(x-direction).
Element number of the meteoro- 26
logical grid where the basic
computational grid stops
(x-direction).
3-3
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Parameter Type
JASTAR INTEGER
JASTOP
ISASTR
ISASTP
JSASTR
JSASTP
MESHDN
INTEGER
INTEGER
INTEGER
INTEGER
INTEGER
INTEGER
Definition
Element number of the meteoro-
logical grid where the basic
computational grid starts
(y-direction).
Element number of the meteoro-
logical grid where the basic
computational grid stops
(y-direction).
Element number of the meteoro-
logical grid where the
sampling grid starts
(x-direction)--make sure that
'ISASTR1 >_ 'IASTAR' .
Element number of the meteoro-
logical grid where the
sampling grid stops
(x-direction)--make sure that
'ISASTP' <_ 'IASTOP' .
Element number of the meteoro-
logical grid where the
sampling grid starts
(y-direction)--make sure that
'JSASTR' >_ 'JASTAR' .
Element number of the meteoro-
logical grid where the
sampling grid stops
(y-direction)--make sure that
'JSASTP' <_ 'JASTOP'.
A factor by which the basic
computational grid spacing
'DELTMT' is divided to produce
the sampling grid spacing.
Default
26
26
26
NAMELIST TITLE —SIGMA
SIGMA initializes PGT stahility-class-dependent coefficients that
describe the differential forms of a and a ,
cable when 'LLID' = .TRUE.) y Z
(a is not appli-
°y(s + As) = oy(s) + As
where
=
3-4
-------
ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
a (s + As) = a (s) +
As
where
9a,
2
9s~
= a (s + As/2)
Parameter
AY (6)
BY(6)
AZ(6)
BZ(6)
Type
REAL ARRAY
REAL ARRAY
REAL ARRAY
REAL ARRAY
Definition
a for PGT classes A-F,
respectively
b for PGT classes A-F,
respectively
a for PGT classes A-F,
respectively
b for PGT classes A-F,
respectively
NAMELIST TITLE--METD
Defaults
(.33, .22, .17, .12,
.086, .057)
C-.l, -.1, -.1, -.1,
-.1, -.1)
(.00048, .063, .1,
.33, .41, .32)
(1.10, .09, -.09,
-.42, -.53, -.58)
METD initializes parameters that identify the input meteorological
data base.
Parameter
METSRT
INTEGER
METCOD
INTEGER
Definition
Year (2 digits), Julian day
(3 digits), and hour (2 digits)
in the MESOPAC output data file
at which the MESOPUFF run
begins.
4-digit serial number to
identify the meteorological
data used (previously assigned
by the user to the MESOPAC
simulation run that generated
the input meteorology fields).
NAMELIST TITLE--PUFF1
For MESOPUFF only, PUFF1 initializes control parameters.
Parameter Type Definition
NPUFTS INTEGER Number of puffs released per
basic model time step 'DTIME'
for each source.
Default
7700101
1001
Default
3-5
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Parameter
Type
NSAMAD INTEGER
LVARSA LOGICAL
MAXSAM INTEGER
NAMELIST TITLE — PUFF2
Definition Default
Minimum number of times per basic 1
time step 'DTIME' that puffs will
be sampled by sampling grid.
If .TRUE, program will dynami- .TRUE.
cally increase sampling rate at
any basic time step if necessary
so that no more than a fraction
'CONVFR' (see NAMELIST REMOV) is
removed from any puff in any
sampling step.
If 'LVARSA1 = .TRUE., this is the 100
maximum number of sampling steps
allowed in any basic time step.
For MESOPUFF only, PUFF2 initializes computational parameters.
Parameter
Type
NSIGMA INTEGER
LUFORM LOGICAL
Definition Default
Puffs do not impact grid points 3
further than 'NSIGMA1 ay from
the puff centerpoint.
If .TRUE, fumigated puffs .TRUE.
immediately assume a uniform
vertical concentration distri-
bution. If .FALSE, plume
reflection terms are considered
when appropriate.
NAMELIST TITLE--REMOV
REMOV assigns values to the removal rate parameters.
Parameter Type
CONVFR REAL
LDCAY
LOGICAL
Definition Default
Maximum fractional amount of .02
conversion or removal of S02 by
either decay or dry deposition
in any one sampling step (limits
the sampling step size, not the
conversion rate).
If .TRUE., exponential decay of .TRUE.
S02 to SO^ is simulated; If
.FALSE., no decay is simulated.
3-6
-------
ENVIRONMENTAL RESEARCH 4 TECHNOuOG' \C
Parameter
Type
EXTNCT REAL
LDEPOT
LOGICAL
Definition
If 'LDCAY' is .TRUE., conversion
rate of S02 to SO^ (negative,
for loss of S02).
If .TRUE, dry deposition is
simulated for both species.
If .FALSE., dry deposition is
not simulated for either specie.
If 'LDEPOT' is .TRUE., 'DEPVEL(l)'
and, 'DEPVEL(2V are deposition
velocities (m s"1) for S02 and
respectively.
NAMELIST TITLE--OUTPT
OUTPT initializes the output control parameters.
Parameter Type Definition
DEPVEL(2) REAL ARRAY
LPRINT
IPRINF
LOGICAL
INTEGER
Is .TRUE, if line printer out-
put of gridded concentration
arrays is desired.
If 'LPRINT' is .TRUE., specifies
the rate (in terms of 'DTIME')
of gridded concentration array
output (to line printer) in terms
of the basic time step.
Must be equaj^ ^to_ or an even
~IAVGT
multiple of
CONTR).
(see NAMELIST
LSAVE
ISAVEF
LOGICAL
INTEGER
If .TRUE., concentration arrays
are to be saved on disk or tape.
If 'LSAVE' is .TRUE., rate (in
terms of 'DTIME1) of concentration
array output to tape or disk.
Must be_ an even multiple of ' IAVG'
(see
Default
-5.56x10
-6
.TRUE.
(.01,.001)
Default
.TRUE,
24
.FALSE,
24
NAMELIST TITLE —SOURC
SOURC assigns values to the parameters associated with source
characteristics.
3-7
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Parameter
NSOURC
LMISS
Type Definition Default
INTEGER Number of sources (up to 10) 1
LOGICAL If .TRUE., a 24 hour cycle of .FALSE.
emission rate multipliers is to
be read in. If .FALSE., tem-
porally constant emission rates
are assumed.
LOGICAL If .TRUE., a 24 hour cycle of .FALSE.
buoyancy flux multipliers is to
be read in. If .FALSE., tempor-
ally constant buoyancy fluxes
are assumed.
The following formatted (non-NAMELISTED) input follows the NAMELISTED
input described above: For each source (there are a total of 'NSOURC'
sources) the formatted input consists of the following sequence of
cards.
LFLUX
STACK PARAMETERS (1 card per source)
Columns Format Parameter
1-10
11-20
21-30
31-40
41-50
51-60
F10.2
F10.2
F10.2
F10.2
F10.2
F10.2
STAKHT
XXSTAK
YYSTAK
EMISS(l)
EMISS(2)
BFLUX
Definition
Stack height (m) above ground
x-coordinate of source (meteorological
grid units)
y-coordinate of source (meteorological
grid units)
Emission rate (g s"1) for S02
Emission rate (g s"1) for SO^
Buoyancy flux (m4 s~3) for plume rise
EMISSION CYCLE (2 cards per source; needed only i£ LMISS = .TRUE.)
The emission rate Qh(P,I) for hour h, source I, and pollutant P
(1 = S02, 2 = SOi;) is computed as Qh(P,I) = ' "CYCLE(h, I) ' * 'EMISS(P,I)'
Two emission cycle input cards are required for each source; the mul-
tipliers for hours 1-12 are specified on Card #1 and hours 13-24 are on
Card #2. Card #1 is for each source set up as follows.
3-8
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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
Columns Format
1-6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-54
55-60
61-66
67-72
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
Parameter
ECYCLE (1,N)
ECYCLE (2,N)
ECYCLE (3,N)
ECYCLE (4,N)
ECYCLE (5,N)
ECYCLE (6,N)
ECYCLE (7,N)
ECYCLE (8,N)
ECYCLE (9,N)
ECYCLE (10,N)
ECYCLE (11,N)
ECYCLE (12,N)
Definition
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
Emission multiplier for hour
1, source N
2, source N
3, source N
4, source N
5, source N
6, source N
7, source N
8, source N
9, source N
10, source N
11, source N
12, source N
The format for Card #2 (hours 13-24) is identical.
BUOYANCY FLUX CYCLE (2 cards per source, needed only if_ LFLUX = .TRUE.) .
The buoyancy flux F, (P,I) for hour h, source I, and pollutant P
(1 = S02, 2 = SO^) is computed as Fh(P,I) = 'BCYCLE(h,I)' * 'BFLUX(P,I) ' .
Two emission cycle input cards are required for each source; the mul-
tipliers for hours 1-12 are on Card #1, and hours 13-24 are on Card #2.
Card #1 is for each source is set up as follows.
Columns Format
1-6
7-12
13-18
19-24
25-30
31-36
37-42
43-48
49-54
55-60
61-66
67-72
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
F6.2
Parameter
BCYCLE (1,N)
BCYCLE (2,N)
BCYCLE (3,N)
BCYCLE (4,N)
BCYCLE (5,N)
R' YCLE (6,N)
BCYCLE (7,N)
BCYCLE (8,N)
BCYCLE (9,N)
BCYCLE (10,N)
BCYCLE (11,N)
BCYCLE (12,N)
Definition
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
Buoyancy flux multiplier for hour
1, source N
2, source N
3, source N
4, source N
5, source N
6, source N
7, source N
8, source N
9, source N
10, source N
11, source N
12, source N
The format for Card #2 (hours 13-24) is identical.
3-9
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
3.3 Other Considerations
3.3.1 Meteorological Considerations and MESOPAC Input
The meteorological input for the MESOPUFF model is specified as a
time sequence of spatially variable, gridded fields of horizontal (u,v)
wind components, mixing depth, and PGT stability class.
These fields are generated and written to off-line storage (disk or tape)
by the MESOPAC* Meteorological Preprocessing Program (see Benkley and
Bass 1979b). As mentioned in Section 3.1, MESOPUFF retrieves the
meteorological data set from logical unit 2.
Direct compatibility of MESOPUFF input with MESOPAC output is
ensured if the successive runs of MESOPAC and MESOPUFF jointly satisfy
the following constraints on respective run parameters.
• The four-digit serial number 'METCOD' used to identify the
meteorological data sets requested by MESOPUFF must match the
'METCOD' assigned when MESOPAC created and tagged its output
meteorological data set.
• The grid spacing 'DELTMT' used by MESOPUFF must be identical
to the grid spacing 'DX' used by MESOPAC; of course, the number
of horizontal grid elements 'IELMET' and 'JELMET' used to
specify the met data array sizes in both models must be identical
• The geographical area covered by the MESOPUFF basic computa-
tional grid must be identical to, or a subset of the area
covered by the MESOPAC meteorological grid.
• The chronological time period over which the MESOPUFF simu-
lation run is performed must be a subset of the time period
used by MESOPAC to define the meteorological fields.
• The interval at which the meteorological fields are updated by
MESOPUFF is specified by the product 'DTIME' * 'MTFREQ'
(hours). This time interval must be equal to or an even
multiple of the time interval 'ISTEP' (hours) used by MESOPAC
to generate and output successive sets of meteorological
fields.
3.3.2 Array Size Considerations
Currently, MESOPUFF allows for the basic computational grid to be
as large as 40 elements in each horizontal direction. However, since
most of the large arrays in MESOPUFF are related to the total number of
puffs from all sources combined, the size of the grid could be increased
without a substantial increase in the core required by MESOPUFF. The
user can specify up to 10 sources; if a larger source inventory is
needed, the user can run MESOPUFF with up to 10 sources at a time and
'If desired, another meteorological preprocessing routine can be
substituted to drive the MESOPUFF model.
3-10
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ENVIRONMENTAL RESEARCH &TECHNOLOGV INC
then aggregate results with MESOFILE. MESOPUFF allows for up to
500 puffs (from all sources combined) to be resident on the grid at any
time; thus, for example, for a 1-hour puff emission interval ('DTIME'/
'NPUFTS' = 1.0), the MESOPUFF simulation is prematurely terminated if
the average puff residence time becomes greater than 50 hours.
3.4 MESOPUFF Model Output
MESOPUFF output can be specified in either (or both) of two media
depending on further user needs. The results can be output directly to
the line printer, and/or routed for storage on the direct-access disk
storage system for subsequent postprocessing. This section describes
the types of output data that can be routed through each system. In
most cases, the user may specify whether a certain type of output data
will be received.
3.4.1 Line Printer Output
The following is a complete list of the line printer output options
available from a MESOPUFF simulation:
• a table that lists the values of all input parameters used in
the run (this output is always generated);
• arrays of ground-level concentrations for S02 and SO^ block
averaged over time intervals of 'IAVG1 * 'DTIME' hours and
output at intervals of 'IPRINF1 * 'DTIME' hours during the run
(these fields are printed only if 'LPRINT' = .TRUE.); and
• if, at any time, data for more than 400 puffs are being held
in the puff arrays, MESOPUFF will delete all data in core for
puffs that have previously fallen off the edge of the basic
computational grid. A message will be output informing the
user how many puffs have been deleted and how many puffs
remain on the grid.
3.4.2 Direct Access Disk Output
Table 3-1 describes the logical unit file structure of the direct
access disk storage system expected by MESOPUFF. (Model outputs are
only directed to direct access disk storage when 'LSAVE' = .TRUE.) As
indicated, six distinct direct access files are used, each with inde-
pendent size characteristics; these file characteristics are currently
frozen within the MESOPUFF code itself via Fortran "Define File" state-
ments and may require specific modification for adaptation t^o_ the user's
host system. '
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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
TABLE 3-1
LOGICAL UNIT FILE STRUCTURE
Device Logical
Unit Number
13
15
21
22
23
24
File Name
Library
NAMELIST
SO,, Concentration
SO Concentration
Run Number
Pointer
Record Structure
25 records,
14 words/record
25 records,
800 words/record
1,800 records,
1,610 words/record
1,800 records,
1,610 words/record
1 record,
2 words
1 record,
4 words
3-12
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Concentration Files 21 and 22 contain the S02 and S04 concentration
fields for each output time step. An identifying header record
identical to the format used for File 15 (see File 15 description below)
precedes the concentration fields. Files 21 and 22 can accommodate a
maximum of 1,800 records each; therefore, for example, the results of 10
independent model simulations, each of 179 hours duration with hourly
output, will fit exactly within the 1,800 records allotted.
The library file (13) contains a single-record descriptor for each
model run; File 13 can accommodate a maximum of 25 independent model
runs. A hard copy printout of the library file produced by MESOFILE is
shown in Figure 4-2 in the next section. The parameters defining each
model simulation run are as follows:
I NUMB
DATFLD
MODEL
YR/DAY/HR
NGRIDS
IAVG
ISAVEF
I SAFE
IBEGIN
I STOP
A model run number which is automatically assigned
by the direct access disk output subroutine.
The date of execution (day, month, and year) of the
model run [not the day (or days) simulated].
The particular mesoscale dispersion model chosen from
the integrated modeling mesoscale system—in this
case, MESOPUFF.
The year, Julian day, and hour on which the model
simulation begins (Note that the first gridded
concentration field is not output until
1ISAVEF'*'DTIMEf hours subsequently, where 'DTIME'
is the basic MESOPUFF time step (hours) and 'ISAVEF'
is defined below).
The total number of concentration arrays output for
each pollutant during the model simulation
('NGRIDS' = 'NADVTS'/'ISAVEF1 where 'NADVTS' is the
total number of time steps in the model simulation.)
The concentration array averaging frequency in terms
of the basic time step, 'DTIME1.
The concentration array direct-access disk output
frequency in terms of the basic model time step,
'DTIME'.
The direct access address of the duplicate File 15
record.
The direct access address of the first of the 'NGRIDS'
number of arrays output to File 21 for S02 and
File 22 for SO^.
The direct access address of the last of the 'NGRIDS1
number of arrays to File 21 for S02 and File 22 for
3-13
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
ICHECK - The run termination status indicator 'ICHECK' = 1
indicates the model simulation terminated normally;
'ICHECK1 = 0 indicates it terminated abnormally. In
the latter case, the results of this run must be
deleted from the file management system using the
program BACKUP01 (see Scire et al. 1979) before
another run is made.
NAMELIST File 15 contains a one-record detailed description of the
parameters used for each model run. Each record in File 15 contains:
(1) a duplicate of the corresponding FILE 13 record for the run and
(2) the NAMELIST parameters used to make the run (also output to the
line printer).
Finally, the Run Number and Pointer Files (23 and 24) preserve
information between runs necessary to maintain proper archival sequen-
cing of run outputs — they are invisible to the user.
3.5 Execution Time and Core Requirements
The time required for a MESOPUFF simulation depends on:
• the number of time steps N,
• the number of puff releases np per source per time step,
• the number of puff samples n per time step,
• the number of sources S, and
• various meteorological factors that control the average number
of puffs resident on the grid.
For a single source, the following relationship for MESOPUFF execution
time was found useful for estimating run time for typical meteorological
conditions in the Four Corners area:
t(sec) = 20 + 0.5N + 0.003 (n -1) N2 + 0.002 (n -1) N2 (3-1)
P s
Note that while both np and ns can be varied to simulate a continuous
plume, frequent sampling is often less costly than frequent puff
releases. For one puff release per time step (np = 1) and sampling
frequency dynamically determined, a useful relationship describing the
execution time (on an IBM 370/158) of MESOPUFF with multiple sources and
the computational grid and typical meteorological conditions used is
given by:
t(sec) = 0.38 (S) (N) + 0.43 (N) (3-2)
3-14
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ENVIRONMENTAL RESEARCH 1 'ECHVJOtOGV INC
For runs with more than a few sources (so that the second term on the
right hand side of (3-2) is negligible), the MESOPUFF model is about
twice as expensive to run as MESOPLUME.
On the same computer installation, MESOPUFF required 230k bytes of
core during execution.
3-15
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ENVIRONMENTAL RESEARCH 8. TECHNOLOGY INC
4. TEST CASE FOR MESOPUFF
A test case is provided in this section to familiarize the user
with the operation of the MESOPUFF model and to verify that the model is
running properly on the host system. The test case included here is a
3-day sequence of MESOPUFF model output for the time period 0000
Greenwich Mean Time (GMT) June 14, 1978 through 0000 GMT June 17, 1978
in the Four Corners area of the southwestern United States see Bass et
al. (1979)]. A 10-source partial emission inventory was selected from
the full set of energy-related major point sources of S02 in the Four
Corners area.
Figure 4-1 contains the run control parameters and emission source
inventory (input on logical unit 5) for this test case. Note that most
of the model input variables assume their default values. Appendix A
contains the entire input data set used by the MESOPAC preprocessor to
generate the meteorological fields that were subsequently read in by
MESOPUFF (on logical unit 2). Appendix A also contains a very small
portion of the MESOPAC model output—included to aid the user in veri-
fying the full test case.
The full set of line printer output for this MESOPUFF test case is
included in Appendix B. Descriptions of the model output fields
assigned to the direct access disk storage system (as echoed in hard
copy form by the MESOFILE system) are shown in Figure 4-2 (the library
file) and in Appendix C (the NAMELIST file). In this example, the
results from the MESOPUFF test case are stored together with the results
from the MESOPLUME and MESOGRID test cases as discussed in the MESOPLUME
user's manual (Benkley and Bass 1979) and the MESOGRID user's manual
(Morris et al. 1979). Appendix C also shows the NAMELIST file; there,
the library record NAMELIST input parameters and emission source data
are stored for future reference.
The MESOFILE postprocessing system (Scire et al. 1979) operates on
the direct access disk output files produced by MESOPUFF, to produce
various forms of result analyses. Figure 4-3 illustrates one such
option--a Calcomp contour plot of the 24-hour average ground-level S02
concentration field for June 16, 1978 as obtained from the test case.
(Concentration isopleth values are not printed directly on the contour
plot, but the user can generate an equivalent line printer plot, as
illustrated in Figure 4-4, which does include the actual isopleth
values.) Figure 4-5 illustrates the bulk statistical descriptors
(described by Bass et al. 1979) used to compare, for example, two time
sequences of model result fields. In this example, the base case
24-hour average ground-level S02 concentration fields for June 16
computed by the MESOGRID model are compared to those computed by the
MESOPUFF model.
4-1
-------
ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
&MODEL LPUFF=.TkUE.
&CUNTR NADVTS=72
&GKID *END
&SIGMA *ENf)
&METD METSKT=7ai65UU,MKTLOU=l003
&PUFF1 SEND
&ENO
REND
SEMI)
(4PUFF2
KREMOV
fe-OUTPT
&SOURC
?36.
Ib2.
152.
Ib2.
Ib3.
229.
76.2
183.
175.
152.
NSOURC=10
8.8
23.4
17.2
23.7
13.5
10.0
8.0
9.7
0.9
1.5
&ENL)
tt.ft
ia.0
Itt.y
13.0
1.2
14. 1
14.5
15.?
8.0
4.1
^560.
343. 6
633.4
48H.
53.7
320.
146.9
1510.fi
268.8
1011.
0
0
0
0
0
0
0
0
0
0
6397.
1503.
2847.
3353.
3016.
b222.
240.
3016.
1047.
11144,
Figure 4-1 MESOPUFF Test Case Parameter and Emission Source
Inventory Input
4-2
-------
ENVIRONMENTAL RESEARCH « TECHNOLOGY 'NC
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Day 167 MESOPUFF
i
Figure 4-3 MESOPUFF 24-Hour Average S02 Concentratit .1 Calcomp
Plot, 16 June, 1978 (from MESOFILE)
4.4
-------
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
REFERENCES
Bass, A., C. W. Benkley, J. S. Scire, and C. S. Morris. 1979. Develop-
ment of Mesoscale Air Quality Simulation Models. Volume 1.
Comparative Sensitivity Studies of Puff, Plume, and Grid Models
for Long-Distance Dispersion EPA 600/7-79-XXX, Environmental
Protection Agency, Research Triangle Park, NC, 177 pp.
Benkley, C. W. and A. Bass. 1979a. Development of Mesoscale Air
Quality Simulation Models. Volume 2. User's Guide to MESOPLUME
(Mesoscale Plume Segment) Model. EPA 600/7-79-XXX, Environmental
Protection Agency, Research Triangle Park, NC, 141 pp.
Benkley, C. W. and A. Bass. 19795. Development of Mesoscale Air
Quality Simulation Models. Volume 6. User's Guide to MESOPAC
(Mesoscale Meteorology Package). EPA 600/7-79-XXX, Environmental
Protection Agency, Research Triangle Park, NC, 60 pp.
Benkley, C. W. and L. L. Schulman. 1979. Estimating Hourly Mixing
Depths from Historical Meteorological Data. J. Appl. Meteor.
18:772-780.
Briggs, G. S. 1975. Plume Rise Predictions. Lectures on Air Pollution
and Environmental Impact Analyses. American Meteorological Society,
Boston, MA, p. 59-111.
Egan, B. A., K. S. Rao, and A. Bass. 1976. A Three-Dimensional
Advective-Diffusive Model for Long Range Sulfate Transport and
Transformation. Seventh International Technical Meeting on Air
Pollution Modeling and its Application, Airlie, VA, September 7-10,
1976, p. 697-714.
Hales, J. M., D. C. Powell and T. D. Fox. 1977. STRAM--An Air
Pollution Model Incorporating Non-linear Chemistry, Variable
Trajectories, and Plume Segment Diffusion. EPA 450/3-77-012.
Environmental Protection Agency, Research Triangle Park, NC,
147 pp.
Heffter, J. L. 1965. The Variations of Horizontal Diffusion Parameters
with Time for Travel Periods of One Hour or Longer. J. Appl.
Meteor. 4:153-156.
Morris, C. S., C. W. Benkley and A. Bass. 1976. Development of
Mesoscale Air Quality Simulation Models. Volume 4. User's Guide
to MESOGRID (Mesoscale Grid) Model. .EPA 600/7-79-XXX. Environ-
mental Protection Agency, Research Triangle Park, NC, 85 pp.
Scire, J. S., J. E. Beebe, C. W. Benkley and A. Bass. 1979. Develop-
ment of Mesoscale Air Quality Simulation Models. Volume 5.
User's Guide to the MESOFILE Postprocessing Package. EPA 600/7-79-XXX,
Environmental Protection Agency, Research Triangle Park, NC, 67 pp.
-------
ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Start, G. E. and L. L. Wendell. 1974. Regional Effluent Dispersion
Calculations Considering Spatial and Temporal Meteorological
Calculations. NOAA Tech. Memo. ERL-ARL-44, National Oceanic and
Atmospheric Administration, Washington, DC, 63 pp.
Turner, D. B. 1970. Workbook of Atmospheric Dispersion Estimates. U.S.
Dept. of H.E.W., Public Health Service, Pub. 999-AP-26, 88 pp.
-------
APPENDIX A
TEST CASE MESOPAC INPUT AND OUTPUT
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1 REPORT NO.
EPA-600/7-79-XXX
2.
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
5 REPORT DATE
Development of Mesoscale Air Quality Simulation Models,
Volume 3. User's Guide to MESOPUFF (Mesoscale Puff)
Model
September 1979
6. PERFORMING ORGANIZATION CODE
7 AUTHOR(S)
Carl W. Benkley
Arthur Bass
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Environmental Research 5 Technology, Inc.
696 Virginia Road
Concord, MA 01742
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
03-6-022-35254/NOAA Contract
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Sciences Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
Contract Report
14. SPONSORING AGENCY CODE
IPI
AG
EPA-600/7
15. SUPPLEMENTARY NOTES
Performed under contract to the National Oceanic and Atmospheric Administration
16. ABSTRACT
MESOPUFF is a variable-trajectory regional-scale Gaussian puff model especially
designed to simulate the air quality impacts of multiple point sources at long trans-
port distances. It has been developed to answer the need for a simple, computation-
ally practical, easy to use and flexible mesoscale point source model - suitable for
decision-making and regulatory applications - particularly at transport distances
beyond the range of applicability of the conventional (Turner Workbook) straight-line
Gaussian plume model. MESOPUFF is a natural generalization of the conventional
Gaussian model to situations in which transport and diffusion may be dominated by
spatial and temporal variations in mesoscale meteorology.
Highly user-oriented, MESOPUFF provides a range of flexible options, and its
clean, modular structure permits further modifications with ease. It is designed to
be driven by user-specified meteorological scenarios, of arbitrary duration, con-
structed by a suitable meteorological preprocessor model (e.g., MESOPAC). It outputs
spatially-gridded concentration arrays averaged over arbitrary time intervals of one
hour or more and is designed to be coupled to a postprocessor model (e.g., MESOFILE)
to provide additional graphical and statistical analyses. Routines are provided for:
plume rise; plume growth^ fumigation; linear conversion of S0? to SO"; and dry
deposition of SO and SO .
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS C. COS AT I Field/Group
* Air Pollution
* Algorithms
* Atmospheric Models
* Atmospheric Diffusion
* Transport Properties
13B
12A
04A
07D
14B
13. DISTRIBUTION STATEMENT
Release to Public
19. SECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
124
20 SECURITY CLASS {Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
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