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                                                                ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                               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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                                                             tNVIRONMENT/W RESEARCH & TECHNO OGY INC
                           TABLE OF CONTENTS
                                                                  Page
LIST OF ILLUSTRATIONS                                             vii
LIST OF TABLES                                                    ix
1.   INTRODUCTION                                                 1-1
     1.1  Background                                              1-1
     1.2  The Mesoscale Plume Segment Model (MESOPLUME)           1-2
     1.3  Integrated Mesoscale Modeling System                    1-4
     1.4  Organization of the Report                              1-4
2.   MESOPLUME TECHNICAL DISCUSSION                               2-1
     2.1  Basic Mass Conservation Equations                       2-1
     2.2  The Grid System                                         2-2
     2.3  Specification of Model Inputs                           2-4
     2.4  Plume Trajectory, Dispersion and Sampling
          Algorithms                                              2-4
          2.4.1     Lagrangian Trajectory Function                2-4
          2.4.2     The Plume Dispersion Function                 2-9
          2.4.3     The Plume Sampling Function                   2-11
     2.5  Conversion of Sulfur Dioxide to Sulfate                 2-15
     2.6  Dry Deposition of Sulfur Dioxide and Sulfate            2-16
     2.7  Plume Rise                                              2-17
     2.8  Treatment of Plume Fumigation                           2-18
     2.9  Comparison to the Conventional Gaussian Plume Model     2-21
     2.10 The Computer Program                                    2-24
3.   MESOPLUME USER INSTRUCTIONS                                  3-1
     3.1  General                                                 3-1
     3.2  Description of Card-Image Input                         3-1
     3.3  Other Considerations                                    3-9
          3.3.1     Meteorological Considerations and MESOPAC
                    Input                                         3-9
          3.3.2     Array Size Considerations                     3-10
     3.4  MESOPLUME Model Output                                  3-10
          3.4.1     Line Printer Output                           3-10
          3.4.2     Direct Access Disk Output                     3-11

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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC


                             Table of Contents  (Continued)

            3.5  Execution  Time and Core Requirements                     3-14
       4.    TEST CASE FOR MESOPLUME                                       4-1
       REFERENCES
       APPENDIX A     TEST  CASE MESOPAC INPUT  AND OUTPUT
       APPENDIX B     TEST  CASE MESOPLUME OUTPUT
       APPENDIX C     TEST  CASE NAMELIST FILE
       ABSTRACT
                                            VI

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                         LIST OF ILLUSTRATIONS

Figure                                                                 Page

1-1       Schematic Representation of Segmented Plume Approach         1-3

1-2       Integrated Modeling System                                   1-5

2-1       One Possible Arrangement of Sampling and Basic
          Computational Grids                                          2-3

2-2       Calculation of the Trajectory of a Plume Segment Endpoint    2-7

2-3       Calculation of the Concentration C(i,j) by the Sampling
          Function                                                     2-12

2-4       A Schematic Representation of Adjacent Plume Segments
          in Rapidly Decelerating Flow                                 2-14

2-5       A Schematic Representation of Adjacent Plume Segments
          in Highly Curvilinear Flow                                   2-14

2-6       Response of Two Plume Elements to Changes in Mixing Depth    2-20

2-7       MESOPLUME Versus the Conventional Gaussian Plume             2-23

2-8       MESOPLUME Computer Program Flowchart                         2-25

4-1       MESOPLUME Test Case Parameter and Emission Source
          Inventory Input                                              4-2

4-2       Test Case Library File (MESOFILE)                            4-3

4-3       MESOPLUME 24-Hour Average SO  Concentration Calcomp Plot,
          16 June, 1978 (from MESOFILEJ                                4-4

4-4       MESOPLUME 24-Hour Average SO- Concentration Line Printer
          Plot, 16 June, 1978 (from MESOFILE)                          4-5

4-5       Bulk Statistical Comparison of MESOPUFF to MESOPLUME,
          16 June, 1978 (from MESOFILE)                                4-6
                                   vn

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                                                                ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                             LIST OF TABLES

Table                                                                    Page

2-1       Coefficients  for Dispersion Parameter  Formulas               2-10

2-2       Comparison  of Cu/Q Values for MESOPLUME and Turner
          Workbook  -  Computed Values                                    2-22

3-1       Logical Unit  File Structure                                   3-12
                                    IX

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                                                               ENVIRONMENTAL RESEARCH 8 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, as 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 may 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, 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 compu-
tationally 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 models 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
MESOPLUME in the near field of sources, that is, less than 100 km, are
not realistic.*  Both worst-case and average dispersion situations are
treated, with meteorological inputs constructed from rawinsonde data
that is readily available for the region.  The models are computation-
ally 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, these
models are intended to serve as flexible testbeds for further research,
development, and simulation tasks.
^Subsequently, the MESOPUFF model has been augmented to provide realistic
 near-field impacts (see the companion report, Volume 3).
                                   1-1

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ENVIRONMENTAL RESEARCH S, TECHNOLOGY INC
              The  three new models  are,  respectively:

              •    MESOPLUME,.  a mesoscale  variable-trajectory Gaussian "plume-
                   segment" model,  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 (Benkley and Bass 1979a), 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 second in a series entitled "Development of
          Mesoscale Air Quality Simulation  Models", describes the MESOPLUME 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 1979b);

              •    the companion  report (Volume 5) describing the specially
                   designed postprocessing and analysis system,  MESOFILE (Scire
                   et al. 1979) .

          1.2 The  Mesoscale Plume Segment  Model (MESOPLUME)

              MESOPLUME is  a regional-scale variable-trajectory Gaussian plume
          segment model.   The modeling method used in MESOPLUME,  adapted from that
          proposed  by Hales  et  al.  (1977),  differs from the conventional Gaussian
          plume approach in  that MESOPLUME  allows for deformation of the con-
          tinuous plume by a temporally-varying vertically-uniform, horizontal
          wind field.  The plume  is treated as divided  into contiguous segments;
          each segment describes  a portion  of plume behavior between successive
          time periods; and  the end points  of each segment are advected in a
          Lagrangian  sense.  The  representation of a continuous plume by the
          segmented-plume  approach is  depicted schematically in Figure 1-1.
                                             1-2

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                                                                                ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
               Figure 1-1   Schematic Representation of Segmented Plume Approach
o
00
                                                  1-3

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
              MESOPLUME  accommodates multiple  point  sources,  and includes modules
          for plume  rise,  plume  growth^  fumigation,  linear conversion of sulfur
          dioxide  (802) to sulfate  (SO^),  and dry deposition of 862 and SO^.

          1.3  Integrated  Mesoscale  Modeling System

              The MESOPLUME 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
          functions  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 identically communicates its  results to the MESOFILE post-
          processing system -  responsible  for file management, display, and
          statistical analysis of all model output fields.

          1.4  Organization of the Report

              Section 2  of this report  contains detailed technical description of
          the MESOPLUME model; specific  user instructions are  described in
          Section 3; a test case for the MESOPLUME model is presented in Section 4.

              A Fortran  microfiche  listing of  the MESOPLUME model is appended.
                                             1-4

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                                                                  ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
    MESOSCALE
   METEOROLOGY
                                          MESOPAC
   MESOSCALE
   TRANSPORT-
   DIFFUSION
     MODELS
                MESOPLUME
MESOPUFF
MESOGRID
     ANALYSIS
                                          MESOFILE
o
r-t
O
                        Figure 1-2   Integrated Modeling System
                                        1-5

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                                                               ENVIRONMENTAL RESEARCH* TECHNOLOGY INC
                  2.  MESOPLUME TECHNICAL DISCUSSION
2.1  Basic Mass Conservation Equations

     MESOPLUME, a variable-trajectory version of the conventional
straight-line Gaussian plume model, is designed to take into  account  the
spatial and temporal variations in the horizontal advection,  diffusion,
transformation, and removal mechanisms governing the dispersion  of  a
plume on regional transport scales.  In MESOPLUME, a continuous  plume is
modeled by subdividing the plume into a number of contiguous  'plume
segment' elements.  The conservation of pollutant mass over a plume
segment of length As is expressed by the mass balance equation:
     AQ  =    /  /   G(s,r,z) dr dz  As
                             (2-1)
               /  /   u C dr dz
        / u C dr dz
                                 s+As
where s, r, and z are the_longitudinal , lateral, and vertical plume
directions, G(s,r,z) (g m~3s 0 is the rate of change  (gain-loss) of
pollutant concentration C(s,r,z) (g m 3) by conversion and removal
processes, AQ (g s -1) is the rate of change of pollutant mass flux from
s to s + As, and u (m s"1) is the wind speed.  In MESOPLUME, G(s,r,z)
and u are constant over the plume segment, and s is the current distance
of a plume segment endpoint from the emitting source, measured along the
plume axis.
     MESOPLUME permits the user to specify two possible vertical
distribution functions; (1) a vertical Gaussian profile, ignoring any
effects of the mixing lid H; or (2) a uniform vertical distribution
below the mixing lid.

     For Case 1, the ground-level axial plume concentration C(s,r,0) is
defined at the upwind edge of a plume segment by the expression:
       C(s,r,0)
                         Q(s)
                    IT u a^(s) a (s)
exp
     -r
                                         2a
exp
                -z
               2a
(2-2)
                                   2-1

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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
          where  Q(s)  is  the  pollutant  mass  flux and cy(s),  az(s) are the lateral
          and  vertical Gaussian  plume  dispersion coefficient distributions at
          downwind  distance  s.   Full reflection from the ground is assumed.

              For  Case  2,  if the  plume altitude (z) lies below the mixed lid H,
          the  ground-level  axial concentration is expressed at the upwind edge of
          the  plume segment  by the expression for uniform vertical mixing:
                 C(s,r,0)   =
                                   Q(s)
                              /2~n~ u H  o (s)
                                     m  yk  J
                exp
                      -r
                     2o
                            (2-3)
          where  H   is  the  maximum mixing depth encountered by the plume segment
          (see Section 2.8).   If,  rather,  the plume centerline lies above the
          mixing lid,  no ground-level concentrations are calculated.  At the
          downwind  edge (s+As)  of the plume segment, the ground-level axial con-
          centration  (s+As,r,0)  is expressed as:
              C(s+ds,r,0)   =
{Q(s)+(dQ/dt)}At

•/2-v u H  a (s + As)
       my
exp
                                                      -r
                                                     20
(2-4)
               The MESOPLUME model  solves the mass conservation Equation 2-1
          independently for both sulfur dioxide (802) and sulfate (SOiJ .   The gain
          functions include terms for the loss (gain) of 862 (SO^) by linear decay
          of S02  to SCV and terms for dry deposition of either species (see
          Sections 2.5 and 2.6).

          2.2  The Grid System

               The coordinate system used in the STRAM model has been replaced in
          MESOPLUME by a simple Cartesian coordinate system.  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),
          MESOPLUME uses a sampling grid that is a subset of the basic computa-
          tional  grid.  The origin of the sampling grid may be placed anywhere on
          the basic computational grid (but not 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 points.  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
                                             2-2

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                                                                     ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
       y = 5.0
y = 4.0
j = 5
       y = 3.0
        i = 4
       y = 2.0
y=1.0
i = 2 "
Ay = Ad
       y = 0.0
x = 0.0
 i = 1
                              1      1
                                           I   I
                                         -H+ +
                                         -H ++
                                          4-+ + --


                                                1   1
x = 1.0
 i = 2
                                      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
                                      2-3

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
          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 has a spatial resolution
          four times finer than the basic computational grid.

          2.3   Specification of Model Inputs

               MESOPLUME is, at present, driven by the meteorological fields
          produced by MESOPAC,  a MESOscale meteorology PACkage (Benkley and Bass
          1979b),  but an alternative meteorological preprocessing system with
          appropriate grid resolution could be substituted by the user.  MESOPLUME
          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 meteorological input used by MESOPLUME are shown
          in Appendix A.  Use of MESOPAC model output by the MESOPLUME 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 MESOPLUME in doing plume rise
          and plume growth calculations.

          2.4  Plume Trajectory, Dispersion and Sampling Algorithms

               The computational scheme of the MESOPLUME model has three distinct
          functional elements:    (1) a Lagrangian plume trajectory function, (2) a
          plume dispersion function, and (3) a plume sampling function.  The
          Lagrangian trajectory function is used to advect the endpoints of each
          plume segment during a basic time step; the resultant distance between
          consecutive endpoints defines the length of each plume segment.  The
          widths at the upwind and downwind ends of each plume segment are deter-
          mined by the plume dispersion function.  Given the size and location of
          each plume segment, the plume sampling function computes the concen-
          tration exposure received during the time interval at each grid point
          that lies within the plume segment.

               2.4.1  Lagrangian Trajectory Function

               This section describes how the endpoints of a plume segment are
          advected during a time step; it has been adapted  (but largely verbatim)
          from Hales et al.  (1977, pages 15-18).
                                             2-4

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                                                                              ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
V
                    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
                                 t
                    x(t)  =  -^  I u[t';x(t'),y(t')]dt'
                                 o
                              ,   t
                    Y(t)  =  •—  / v[t';x(t'),y(t')]df
                                 O

                    x(0)  =  XQ ;  y(0) = yQ


                    u(0;x(0),y(0))  =  u(xQ,y0)

                    v(0;x(0),y(0))  =  v(x,y)
               and XQ,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  =  i-   /   u[t';x(t'),y(t')] dt'  ;                    (2-5a)
                                 t+At
                      Ay  =  ^   /   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 endpoint of a given plume, a check is made to see if any of
               these values are off the grid.   If so, both the affected plume increment
               and all plume increments emitted from the same source previously are
               deleted from further consideration.
                In practice,  however, the exact definition of s in MESOPLUME is the
                current along-the-variable-plume-axis distance of a segment endpoint
                from a source.   In time-varying flows, it may be somewhat different
                from the actual  segment endpoint trajectory length.
                                                  2-5

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
               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:


                    xx  =  x(t) + u[t;x(t),y(t)] At ;                       (2-6a)


                                + v[t;x(t),y(t)] At ;                       (2-6b)


                              + u[t+At;x1,/1] At ;                          (2-bc)
                                       x^/j] At ;                          (2-6d)


               x(t+At)   =  0.5[x(t)  + x2]  ;                                  (2-6e)


               yCt+At)   =  0.5[y(t)  + y]  .                                  (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 (x  y ) .  However,  (x^y..) 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  ,y1) 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, ,y,) yields position  (x?,y7).  Then the
          new plume increment position tx(t+At) ,y (t+At)) is taken to 1
be the point
          halfway along the line from (x(t),y(t)) to (x ,y?) .
               The bilinear interpolation by which the effective wind components
          u(t), and v(t) are calculated works as follows.  Let t  and t     be  the
          effective times of the two gridded wind fields closestnto time t.  Time
          interpolation weights t  and t? are defined by:
                             t - t
                                              t  < t < t  .   ;              (2-7a)
                                                 —            '              ^     J
                                                          .
                           t  .  - t            n —      n+1
                            n+1     n
                               t2.                                          (2-7b)
                                                                                             i
                                             2-6

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                                                                   ENVIRONMENTAL RESEARCH S, TECHNOLOGY INC
Figure  2-2   Calculation of the Trajectory of a Plume Segment  Endpoint
                                     2-7

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
          Next, the location of  (x(t),y(t))  is  noted on Figure 2-2.  The

          coordinate values are between  3  and 4 for x(t) and between 2 and  3  for

          y(t) .  Accordingly:




                    Xq  =  x(t) -  3  ;                                        (2-8a)





                    Xp  =  1 - Xq  ;                                          (2-8b)




                    Y   =  y(t) -  2  ;                                        (2-8c)
                    Y   =  1 - Y   .                                          (2-8d)
                     p          q
          This yields
                  u(t)  =  t. X  Y  u(t  ;3,2)  + t- X  Y  u(t  ^3,2)
                            1  p  p   ^ n'         2  p  p    n+1'
                        +  t, X  Y  u(t  ;4,2)  + t~ X  Y  u(t  ^4,2)        (2-9)
                            1  q  p    n'         2  q  p  ^ n+1'                '
                           t, X  Y  u(t  ;4,3)  + t0 X  Y  u(t  ,;4,3)  .
                            1  q  q   "• n'  '  -"     2  q  q  *• n+1' ' J
          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  =  —• {v(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)
                                              2-8

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                                                               ENVIRONMENTAL RESEARCH 8 TECHNOLOGY INC
     2.4.2  The Plume Dispersion  Function

     This section, describing the evaluation  of the plume dispersion
parameters, has been taken  largely verbatim,  with modifications, from
Hales et al.  (1977, pp.  23-24).   The plume  dispersion parameters ov 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 plume with travel time t or along the plume trajectory
distance s from the source  is represented by
                                 do
                                                                  (2-12)
a (s+As)  =  a (s) + As
 7            y         ~,   s+As/2
                                 da
         a (t+At)  =  a  (t) + At  ,„.
          y            y^        dt
                                   y
                                      t+At/2
                                                         (2-13)
Similar equations for oz are used.  These terms  allow for spatial and
temporal changes in stability class to be included,  without  violating
the entropy principle (centerline concentrations  cannot  increase with
downwind distance) .

     The integral formulas for ay and a  for  travel  distances less than
100 km are of the following forms


          a (s,a)  =  Ya s°'9 (meters);                           (2-14)
          o (s,a)  =  Z  s     (meters).                           (2-15)
           Z           Ot
Here a is a stability index designated as A,  B, C,  D,  E,  or F  for the PGT
stability categories.  The coefficients Y  , Z , and b   are  given in
Table 2-1 as a function of stability index a,aand yiefd values of Oy and
az 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 derivative forms are actually used  to  carry out the
computations:
              do

                   -  °'9  Ya S
                                   2-9

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ENVIRONMENTAL RESEARCH &TECHNOLOGY INC
                                            TABLE 2-1




                        COEFFICIENTS FOR DISPERSION PARAMETER FORMULAS






                                              Plume Growth  Coefficients
Stability
Index a
A
B
C
D
E
F
Y
a
0.36
0.25
0.19
0.13
0.096
0.063
Z
a
0.00023
0.058
0.11
0.57
0.85
0.77
b
a
2.10
1.09
0.91
0.58
0.47
0.42
                                                2-10

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                                                               ENVIRONMENTAL RESEARCH 8 TECHNOLOGY INC
              do              (b -1)
              -j--  =  b  Z  s        .                             (2-17)
              ds       a  a

MESOPLUME assumes that a , az = 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"1)  =  0.5                                         (2-18)
      j~ (m s"1)  =  0.5(2Kz)1/2 t"1/2                           (2-19)
     2.4.3  The Plume Sampling Function

     Each plume segment resident on the grid  (at the  end  of  every time
step At) is sampled, using the plume sampling function, to evaluate  the
average concentration experienced at each sampling and intersection
during the previous time step.  For example, consider the hypothetical
plume segment depicted in Figure 2-3.  The plume segment  centerline  at
time t+At extends from (x,y) to (x+Ax,y+Ay), the positions of  the two
consecutive plume segment endpoints at t+At.  The plume segment  length
is As =  (Ax  + Ay2)1/2.  The lateral extent of a plume segment  is
considered to be truncated at ±3a .  This is a reasonable simplification
much less than 1% of the area under the Gaussian distribution  function
lies beyond ±3a  from its center.  In this example, plume segment radii
of size 3o (s) at the upwind edge (x,y) of the segment and of  size
3a (s+As) ^t the downwind edge (x+Ax,y+Ay) are indicated.  At  time t+At,
the' grid point intersections  (21,12),  (22,12), (22,13),  (23,13),  and
(22,14) are each impacted by the hypothetical plume segment; each grid
point is assigned a certain average concentration C(i,j)  resulting from
the presence of the plume segment over At.  This evaluation  is illus-
trated as follows:  Suppose the grid point concentration  C(i,j)  is to be
calculated at (22,12).  First, the ground-level concentrations C(x,y)
and C(x+Ax, y+Ay) are computed using Equations 2-3 and 2-4 for the case
of uniform vertical distribution.  Next, a point  (x',y')  is  found such
that the line segment of length r constructed from  (x',y') to  the grid
point (i,j) is perpendicular to the plume segment centerline.  The
effective source strength C(x',y') is then computed by linear  inter-
polation:

                      C(x,y) As  + C(x+Ax, y+Ay) As
         C(x',y')  =  	          	L              <2
                                   2-11

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ENVIRONMENTAL RESEARCH 5 TECHNOLOGY INC
                 j = 15
                 = 14
                 = 13
                 = 12
                     i = 20

^-



     i = 21
                                                                            (x+Ax,y+Ay)
                                             \
                                            
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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
The lateral plume dispersion coefficient a  (x,y) is similarly inter-
polated from:
                        a (x,y) As2 + a  (x+Ax, y+Ay)
                                  As  +
                                                                  (2-21)
Finally, the grid point concentration C(22,12) is computed as:
           C(22,12)  =  C(x',y') exp
                                         -r
                                                      (2-22)
If a grid point lies within more than one plume segment at the end  of  a
time step (for example, because plumes of multiple sources overlap), the
total concentration at the grid point CT(i,j) is computed as the  sum of
the individual contributions:
                          m,
               T
CT(i.j)  =    I   Cm(
             m=l
                                                                  (2-23)
where m  is the total number of segments impacting the grid intersection
(i,j) during the time step of interest.  Note that a plume segment  is
only sampled beginning with the second time step of its history and at
every time step thereafter.

     The MESOPLUME model has two peculiarities intrinsic to the basic
advective-diffusive scheme of the model, which can present problems when
the sampling function is applied.  These problems arise from  (1)  the
inverse-wind speed dependence of the concentration algorithm  (Equation  2-2)
and (2) the way in which adjacent plume segments are actually juxtaposed
in a curvilinear flow.  As an example of the inverse-wind speed depen-
dence problem, consider the case illustrated in Figure 2-4, for which
the wind flow along the plume axis rapidly decelerates, and suppose u.,
the average wind speed over segment A, is twice u , the average wind
speed over segment B.*  Neglecting removal processes, MESOPLUME evalu-
ates the concentration C(x,,y ) at the downwind edge of segment A accord-
ing to Equation 2-4:
*This does not imply that the two-dimensional wind field is significantly
 divergent--the local flow about segments A and B may be exactly non-
 divergent if the mass fluxes through the lateral boundaries are "correct."
                                   2-13

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ENVIRONMENTAL RESEARCH 5 TECHNOLOGY INC
                  (x0,yo)

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                                                                ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                          /2-n" u, a (x. ,y,) H
                               A  y  1  1   :
                                                                  (2-24)
                         m
but can also evaluate the concentration C(x, ,y,)L at the  same point
using Equation 2-3 as appropriate to the upwind edge of segment  B  using
u  instead.  Since u  = 2u
 B                  AD
B  =  2C&i>yJ
                                                                  (2-25)
If the grid resolution is such that severe discontinuities in the wind
field occur, the MESOPLUME model will indeed predict plume centerline
concentrations increasing with downwind distance.  This prediction,  a
violation of the second law of thermodynamics, represents a major short-
coming of the plume segment model - it cannot treat stagnation  flows
correctly.

     To address the second problem, that of juxtaposing adjacent plume
segments, consider the situation illustrated in Figure 2-5.  In this
figure two adjacent plume segments are advected in a highly curvilinear
flow.  In this case, for each plume segment, the lateral lines  that
define the plume segment widths  (at the upwind and downwind end points)
are constructed to be perpendicular to the local plume segment  axes.
Therefore, if the average wind direction used to advect segment B is
very different from the average wind direction used to advect segment A,
the plume segments will not be perfectly contiguous, as shown.  In the
example, there is a shaded region in which grid points will receive  two
concentration doses during one time step and also a region where the
plume may actually "pass over" a grid point without impacting it at  all.
This illustrates a second potentially serious shortcoming of the model -
it cannot treat strongly sheared flows (e.g., recirculating flows)
correctly.

     Both of the limitations identified here are intrinsic to the basic
plume-segment approach, rather than to its present implementation.   The
effects of these limitations on MESOPLUME model performance are dis-
cussed in greater detail in the companion model sensitivity document
(Bass et al. 1979) .

2.5  Conversion of Sulfur Dioxide to Sulfate

     MESOPLUME 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)  =  kj Qn(S02) At                             (2-26a)
                                   2-15

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ENVIRONMENTAL RESEARCH&TECHNOLOGY INC
                    AQn(S04)  = -1.5 k  Qn(S02) At                         (2-26b)



         where Q  (802) is the mass of S02 at the beginning  of the  nth time step
         and kifs"1) is the conversion rate constant.  MESOPLUME uses the nominal
         value kl = -5.56 x 10~6, suggested by Hales et  al.  (1977),  unless
         otherwise specified by the user.

              Note that the conversion of S02 to 80^ represented by  Equation 2-26
         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 automatically subdivided into as many
         subintervals At1 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
         deposition are given by:
The changes of mass AQ (g) of each pollutant resulting  from  dry
                   AQn(S02)  =   -(vd(S02) Qn(S02)  At)  /  Hm                (2-27a)


                   AQn(SO=)  -   -Cvd(SOp Qn(SO=)  At)  /  Hm                (2-27b)
         where Q  (802) and Q  (SO^) are the masses  of  862  and 804,  respectively,
          in the plume  segment at  the beginning  of  the  time  step,  Vd(S02)
          v^fSO^) are the deposition velocities  of  each pollutant, and H  is the
          vertical depth of the plume segment  (see  Section  2.8).   MESOPLUME uses
          the nominal values vd(S02) =  0.01  (m/s) and vd(SCQ  = 0.001 (m/s), as
          suggested by  Hales et al .  (1977),  unless  otherwise specified by  the
          user.

              As described before, MESOPLUME  automatically  ensures that the mass
          Q does not change within one  subinterval  At'  by more than a user-
          specified fraction AQ.p.  Taking  into account  both  S02 removal mechanisms
          (decay and deposition),  the expression used by MESOPLUME to specify the
          subinterval At' is
                                            2-16

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                                                               ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
                           AQ (SO )     AQ  (SO ) H
                                                                  t2-28'
In other words, the subinterval size At' is chosen  automatically by
MESOPLUME 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.  Also, individual puff  trajectories are
not updated at each subinterval At'; they remain unchanged over the
basic interval At.

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 MESOPLUME  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*)2/3 u'1 ;           (2-29a)


For unstable and neutral conditions with h' > H (i.e., the plume pene-
trates into an elevated stable layer)

                                      ,             ,    ,  1/3
               h   =  MIN (h1 , (1.8 z£ + 18.75 F uffl  S  )    };   (2-29b)

For stable conditions when u >_ 1.37 m/s


               h   =  2.6 F1/3 S~1/3 u"1/3 ;                      (2-29c)
For stable conditions when u < 1.37 m/s
               h   =  5.0 F1/4 S 3/8  .                            (2-29d)
where:
         F  =  buoyancy flux  (m /s )

         c*  =  34.49 F°'4 for F > 55

            =  14.0 F°'625 for F < 55
                                   2-17

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                  S  =  (g/T)O0/9z)
                               _2
                  g  =  9.8 m s

                  T  =  290°K

                  z  =  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,
         MESOPLUME takes the spatial and temporal variations in the mixing
         height into consideration to determine the extent of ground level
         pollutant impact:

              (a)  For a plume element centerline less than the mixing height,
                   MESOPLUME arbitrarily assigns the element a height of  zero and
                   immediately mixes the mass of the plume element uniformly
                   through the mixing depth with the mixing lid acting as a
                   perfect reflector.  Equations 2-3 and 2-4 are then applied to
                   compute ground level concentrations.

              (b)  For a plume element centerline greater than the mixing height,
                   no impact of the element is felt at the ground.  However, if
                   subsequently the mixing height becomes greater than the height
                   of the plume element centerline, the entire plume element is
                   immediately mixed uniformly through the mixing depth,  and
                   Equations 2-3 and 2-4 again apply.

              The mixing depth encountered by a plume element is likely to change
         over time and space.  MESOPLUME assumes that a plume element residing in
         the mixed layer is always uniformly mixed throughout the maximum mixing
         depth H  encountered by the element in its progression through the
         computational space-time grid.

              The restriction of a uniform plume element through a character-
         izable depth such as H  is imperative for a one-layer model such as
         MESOPLUME to ensure that parcels of material, once entrained, are not
         bifurcated in the vertical when the height of the mixing lid changes.
         Therefore, in the MESOPLUME model a plume segment, once entrained,  is
         uniformly mixed through a realistic height, consistent with the  follow-
         ing assumptions:
                                            2-18

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
     (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 segment is the maximum mixing height H  that the
segment encounters during any portion of its travel.

     A hypothetical example is given in Figure 2-6 to schematically
illustrate the interaction of the MESOPLUME vertical distribution
algorithm and the mixing depth progression algorithm used by MESOPAC
[Benkley and Bass (1979b), Benkley and Schulman (1979)].  Here, consider
two instantaneous parcels of material released at different times from a
source with an effective stack height of 250 m; the first release is
made at 0300 GMT on the first day; the second release is made 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 parcel is entrained at 0600 GMT on Day 1 as the nocturnal
boundary layer oscillates slightly upward in height.  MESOPLUME immedi-
ately mixes the parcel uniformly throughout this mixing depth.  This
parcel 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 parcel, 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 parcel,
emitted at 0300 GMT on Day 1, remains uniformly mixed through a deeper
vertical layer than the second parcel; this is consistent with the
greater extent of mixing on the first day as compared to the second day.

     This mixing depth/fumigation scheme exhibits at least two short-
comings :

     •    When a plume segment becomes bifurcated in the vertical by
          collapse of the mixing lid, how should the plume segment
          lateral dispersion rate be characterized?  Because MESOPLUME
          is a one-layer model, the same set of horizontal dispersion
                                   2-19

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                          o
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                                    CO
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                                                                                                                     CM
                                                                                                                     00
                                                                                                                     m
                                                                                                                      CM
                                                                                                                      CT>
                                                                                                                      CD
                                                                                                                      n
                                                                                                                      N    ™
                                                                                                                      o    Q
                                                                               Q)



                                                                        CN    i~
                                                                                                                      00
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                                                                                                                                      QJ

                                                                                                                                     Q
                                                                                                                                      W)
                                                                                                                                      c
                                                                                                                                      03
                                                                                                                                      x:
                                                                                                                                      u
                                                                                                                                      c
                                                                                                                                      0)
                                                                                                                                      s
                                                                                                                                      0)
                                                                                                                                      r-H
                                                                                                                                      UJ
                                                                                                                                      a,

                                                                                                                                      o
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                                                                        2-20

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
          coefficients must be applied to both the above-mixing-lid  and
          the below-mixing-lid portions of the bifurcated segment.

     •    The dry deposition algorithm (see Section 2.6) removes  S02 and
          SO^ at a rate proportional to the surface concentration—this
          loss is then redistributed throughout the entire vertical
          extent of the plume.  It would be more realistic to distribute
          the loss only through the current mixing depth, but this is
          not possible in a one-layer plume segment model.

It is felt that these limitations of the scheme are necessary to  a
method that is both computationally practical and yet realistic  for  use
with a one-layer model.  The inclusion of a fumigation cycle is  very
important; the marked effects of plume fumigation on the distribution  of
regional scale ground level concentration patterns are illustrated in
Bass et al. (1979).

2.9  Comparison to the Conventional Gaussian Plume Model

     From the point of view of possible regulatory applications,  one of
the most attractive features of MESOPLUME is its ability to recreate the
results of the conventional Turner Workbook plume model (using PGT
coefficients).  When MESOPLUME is run with appropriate uniform,  steady-
state meteorology and fine 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.

     •    The meteorological fields (wind direction, wind speed,  mixing
          height and PGT stability class) used to drive MESOPLUME are
          ttaken to be spatially uniform and constant in time.

     •    MESOPLUME is run with one source until quasi-steady-state
          conditions are well established; that is, plume segments are
          created at the same uniform rate at which they disappear off
          the edge of the grid.

     Under these special test conditions, MESOPLUME 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 2-7 provide a representative illustration of how
closely MESOPLUME 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 ay curve by the power law function
                                   2-21

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                                          TABLE  2-2
                        COMPARISON OF Cu/Q VALUES FOR MESOPLUME AND
                               TURNER WORKBOOK-COMPUTED VALUES
                          (u = 2.78 m s"1, PGT Class = D, H = 1000 m,
                                uniform vertical distribution)
Distance
(km)
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
PGT
a (m)
y
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)
7.25xlO"7
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
MESOPLUME
(C u Q"1)
7.77xlO~7
5.94
4.11
3.47
2.83
2.50
2.19
1.97
1.78
1.64
1.50
1.42
1.31
1.25
1.17
1.11
1.06
1.00
0.95
Fractional
Deviation
0.07
0.16
0.03
0.06
0.01
0.02
0.00
0.00
-0.02
-0.01
-0.02
-0.01
-0.02
0.00
-0.01
-0.01
-0.02
-0.04
-0.05
                                              2-22

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                                                       ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                                                  = Gaussian  ~  P6T
                                                  = MESOPLUME
                        40             60
                       Dtstance  (km)
00
Figure 2-7   MESOPLUME  vs. the Conventional Gaussian Plume
                          2-23

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
          used in MESOPLUME.  The somewhat larger deviations near the source are
          expected - the results shown here were obtained with a wind velocity  and
          time step corresponding to plume segments about 5 km in length  - so,
          near the source, the linear averaging done by the sampling function does
          not approximate accurately the power law behavior of the plume  center-
          line concentrations.  It is expected that with use of smaller time steps
          and correspondingly shorter plume segments, the comparison of MESOPLUME
          to the Turner Workbook plume in the very near field would be even closer.

               In its present version MESOPLUME does not include an option for  a
          reflected Gaussian vertical distribution, so that at^ distances  where  the
          plume does not yet approach a uniform vertical distribution, MESOPLUME
          will not give correct results.  Under stable flow conditions, for
          example, plumes may not approach a uniform vertical distribution for
          many kilometers downwind.  This version of MESOPLUME should therefore
          only be used at and beyond distances for which the assumption of uniform
          vertical mixing is appropriate - often only at distances of 100 km or
          more.   [It would be very simple to modify the present version,  however,
          to incorporate an optional Gaussian reflected vertical distribution so
          as to make MESOPLUME suitable also for near-field computations.]

          2.10  The Computer Program

               MESOPLUME is a highly modular computer program which shares with
          MESOPUFF and MESOGRID standardized input/output features and, where
          possible, identical program modules.  The computer program flow chart
          (Figure 2-8) outlines the order of execution of the individual  modules
          described at length in the 'MESOPLUME Technical Discussion'.
                                             2-24

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                                                                            ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                                                           Update hour, day, year
                                                           (Subroutine KALEND)
                              NLIMIT=NLIMIT+1
         Initialize input parameters
   (Subroutines INPARM, BLOCK DATA)
        Initialize direct access files
          (Subroutine FILMAN)
                 I
        NINCV(K)=0 ; NLIMIT=0
 Update meteorology from disk or tape
       (Subroutine READER)
       If (MOD(NLIMIT,IPRINF))=0,
        output fields to line printer
(Subroutines WRITER, RANGE, DISP, PAGE)
                 I
      If (MOD(NLIMIT,ISAVEF))=0,
     output fields to direct access files
          (Subroutine PUTOUT)
                                                  Calculate 'effective stack height' of new segment
                                                   {VIRTH(K,NINCV(K»}  (Subroutine PRISE)
                                                                  NP=0
         MOD (NLIMIT,IAVG)=0?
                                                         Release new plume segment
                                                          {NINCV(K)=NINCV(K)+1}
    Lagrangian trajectory function
Delete segments that fell off grid edges
   {NINCV(K)=NINCV(K)-NFALL}
                                                            Dispersion function
                                                       (Subroutines BSTRAC.SIGMA)
                                                  Calculate removal from decay and dry deposition
                                                          Q(K,NP)=Q(K,NP)-dQ/dt
                                                            (Subroutine BSTRAC)
                                                             Sampling function
                                                         (Subroutines SAMPLE, LEIN)
                                                                NP=NP+1
           Figure  2-8    MESOPLUME Computer  Program  Flow Chart
                                        2-25

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                    3.  MESOPLUME USER INSTRUCTIONS


3.1  General

     A MESOPLUME 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, MESOPLUME should interface with the
output of the MESOPAC meteorological preprocessor (see Section 3.3).
Output of a MESOPLUME 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, cataloging,
and easy retrieval of all output data files from MESOPLUME.  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
MESOPLUME program contains a file management subroutine (FILMAN) which
determines without further user input the proper locations for all of
the various MESOPLUME disk output files.  MESOFILE can then be used for
flexible time averaging of 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 MESOPLUME model, model simulation control
parameters, and emission inventory.  The input package has been designed
for use in common by all three mesoscale models (MESOPLUME, MESOPUFF,
                                    3-1

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ENVIRONMENTAL RESEARCH 8, TECHNOLOGY INC
         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 PUFF1, PUFF2,  and GRIDY are not  used  by
         MESOPLUME 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
             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
DTIME


NADVTS
                         INTEGER
Length of the basic time step
(hours)
Length of the simulation in
terms of basic time steps
Default

.FALSE.


.FALSE.


.FALSE.
Default

  1.0


   24
          *The description  of  certain parameters  that  were  retained from the STRAM
          model 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 sub-
          routine INPARM.
                                             3-2

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                                                               ENVIRONMENTAL RESEARCH STECHNOLOGY 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 be the same as the
     basic computation grid; or denser by an integer multiple.  Cur-
     rently, 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
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
          NAMELIST  TITLE —SIGMA
           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' >_ 'JASTAR1 .

  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
               SIGMA  initializes  PGT stability-class-dependent coefficients that
               describe  the  differential  forms  of a  and a .   (a  is not appli-
               cable  when  'LLID'  =  .TRUE.)          y      z     z

                                          3a
                   a  (s  +  As)   =   a (s)  + -~-  As
                   y       J       y^ J    9s
                         where
=  ay(s
                       As/2)
                                             3-4

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
         oz(s + As)  =  oz(s)
                                9a
                      As
               where   3s
                         -  =  a  (s + As/2)  Z
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,
                               2
                              respectively
NAMELIST TITLE--METD
                                                   Defaults

                                              (.33,  .22,  .17,  .12,
                                               .086,  .057)

                                              (-.1,  -.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
  Type

INTEGER
  METCOD
INTEGER
         Definition                 Default

Year (2 digits), Julian day         7700101
(3 digits), and hour  (2 digits)
in the MESOPAC output data file
at which the MESOPLUME run
begins.

4-digit serial number to              1001
identify the meteorological
data used  (previously assigned
by the user to the MESOPAC
simulation run that generated
the input meteorology fields).
NAMELIST TITLE —PLUM1
     For MESOPLUME only, PLUM1 initializes computational parameters.

Parameter        Type                  Definition                 Default
  MAXSEG
INTEGER
Maximum number of plume segments
per source allowed on the grid
at any time (must be < 100).
100
                                   3-5

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
         Parameter
            LLID
   Type

 LOGICAL
         Definition

If .TRUE., plumes below the
mixing lid are assumed to be
uniformly vertically distributed.
If .FALSE., plumes are assumed
to have a Gaussian distribution
in the vertical, with no
constraining lid.
                                   Default
                                     .TRUE.
         NAMELIST TITLE —PLUM2
              For MESOPLUME only, PLUM2 initializes parameters allowing the use
              of nongridded receptors.
         Parameter

            NRE


          XRES(IO)



          YRES(IO)
   Type

 INTEGER


REAL ARRAY



REAL ARRAY
         Definition

Number of nongridded receptors
(must be <_ 10) .

x-coordinates  of the nongridded
receptors (meteorological grid
units).

y-coordinates  of the nongridded
receptors (meteorological grid
units).
         NAMELIST TITLE —REMOV
              REMOV assigns values to the removal rate parameters.
         Parameter        Type

           CONVFR         REAL
           LDCAY
           EXTNCT
           LDEPOT
  LOGICAL
   REAL
  LOGICAL
          DEPVEL(2)    REAL ARRAY
                                       Default

                                           0


                                       10  *  0.
                                        10
0.
                                                       Default
                                                          .02
                                        .TRUE.
         Definition

Maximum fractional amount of
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
S02 to SOIJ is simulated; If
.FALSE., no decay is simulated.

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)'    (.01,.001)
and, 'DEPVEL(2V are deposition
velocities (m s"1) for S02 and
SOiJ, respectively.
                                      -5.56x10
                                                                                     -6
                                        .TRUE.
                                            3-6

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
NAMELIST TITLE—OUTPT

     OUTPT initializes the output control parameters.

Parameter        Type                  Definition
  LPRINT
  IPRINF
               LOGICAL
               INTEGER
Is .TRUE, if line printer out-
put of gridded concentration
arrays is desired.

If 'LPRINT1 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 equal to or an even
            "lAVG1
                                                                    Default
 .TRUE.
   24
                              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  'DTIME') of concentra-
tion array output to tape or
disk.  Must be an_ even multiple
of ' lAVG^Tsee NAMELIST CONTR) .
.FALSE.


   24
NAMELIST TITLE —SOURC
                                                                    Default
                                                                       1

                                                                     .FALSE.
     SOURC assigns values to the parameters associated with source
     characteristics.

Parameter        Type                   Definition

  NSOURC       INTEGER        Number of sources (up to 10).

  LMISS        LOGICAL        If .TRUE., a 24 hour cycle of
                              emission rate multipliers is to
                              be read in.   If .FALSE., tem-
                              porally constant emission rates
                              are assumed.

  LFLUX        LOGICAL        If .TRUE., a 24 hour cycle of
                              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.
                                                                     .FALSE.
                                   3-7

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
          STACK  PARAMETERS  (1  card per source)
          Columns    Format      Parameter
                             Definition
            1-10     F10.2        STAKHT       Stack height (m) above ground
           11-20     F10.2        XXSTAK       x-coordinate of source (meteorological
                                             grid units)
           21-50     F10.2        YYSTAK       y-coordinate of source (meteorological
                                             grid units)
           31-40     F10.2       EMISS(l)       Emission rate (g s'1) for SC>2
           41-50     F10.2       EMISS(2)       Emission rate (g s'1) for S(JT
                                                             4-3
           51-60     F10.2        BFLUX        Buoyancy flux (m  s  ) for plume rise

          EMISSION  CYCLE  (2  cards per source; needed only if LMISS =  .TRUE.)
              The  emission  rate Qu(P,I)  for hour h, source I, and pollutant P
          (1  = S02,  2  = SO 4)  is computed  as Qh(P,I) = 'ECYCLE(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.
          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.
                                             3-8

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                                                               ENVIRONMENTAL RESEARCH*TECHNOLOGY INC
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)
BCYCLE (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.
3.3  Other Considerations
     3.3.1  Meteorological Considerations and MESOPAC  Input
     The meteorological input for the MESOPLUME 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, MESOPLUME retrieves the meteoro-
logical  data set from logical unit 2.
     Direct compatibility of MESOPLUME input with MESOPAC output is
ensured if the successive runs of MESOPAC and MESOPLUME jointly satisfy
the following constraints on respective run parameters.
     •     The four-digit serial number 'METCOD' used to identify the
          meteorological data sets requested by MESOPLUME must  match the
          'METCOD'  assigned when MESOPAC created and tagged its output
          meteorological data set.
*If desired, another meteorological preprocessing routine can be
 substituted to drive the MESOPLUME model.
                                   3-9

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
               •     The  grid  spacing  'DELTMT'  used by MESOPLUME must be identical
                    to the  grid  spacing  'DX1 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 MESOPLUME 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 MESOPLUME 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
                    MESOPLUME 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, MESOPLUME 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 MESOPLUME are related to numbers of emission
          sources and plume increments,  the  size  of the  grid could be increased
          without a substantial  increase  in  the core required by MESOPLUME.  The
          user  can  specify  up to 10 sources; if a larger source inventory is
          needed, the user  will  run MESOPLUME  with up to 10 sources at a time and
          then  aggregate results with MESOFILE.   MESOPLUME allows for up  to 100
          plume segments per  source to be resident on the grid at any time; thus,
          for example, for  a  1-hour basic time step, the MESOPLUME simulation is
          prematurely terminated if any  segment from any source remains on the
          grid  for  longer than 100  hours.

          3.4  MESOPLUME Model Output

               MESOPLUME 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  MESOPLUME  simulation:

               •    a table that lists the values of all input parameters used in
                    the  run (this output is  always generated);
                                             3-10

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
     •    a brief description of the model run time, concentration
          averaging time, source data, and grid characteristics of the
          model run (this output is always generated) ;

     •    arrays of ground-level concentrations for S02 and SO^ block
          averaged over time intervals of 'IAVG' *  'DTIME' hours and
          output at intervals of 'IPRINF' *  'DTIME' hours during the run
          (these fields are printed only if  'LPRINT' =  .TRUE.);

     •    tables of S02 and S04 ground level concentrations averaged and
          output as above, for a small number of receptor locations
          specified arbitrarily within the computational area  (these
          tables are printed only if 'NRE' > 0 and  'LPRINT' =  .TRUE.);

     •    for each pollutant, arrays of the maximum grid point concen-
          tration values (averaged as above) during the run span (these
          are printed only if 'LPRINT' = .TRUE.);

     •    for each pollutant, arrays of the grid point concentration
          values for SCL and S0~ averaged over the entire run span
          (these are printed only if 'LPRINT' = .TRUE.); and

     •    a table listing the time when the initial plume segment from
          each source first reached the edge of the basic computational
          grid.  This table is a useful adjunct to choosing an "initial-
          ization time" for the simulation; that is, the period of time
          during which the model concentration results are influenced by
          source "startup," and so are not to be considered representa-
          tive of average concentrations for a continuously emitting
          source (or sources) (this table is always generated).

     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 MESOPLUME.   (Model outputs are
only directed to direct access disk storage when 'LSAVE' = .TRUE.)  As
indicated, six distinct direct access files are used, each with indepen-
dent size characteristics; these file characteristics are currently
frozen within the MESOPLUME code itself via Fortran "Define File" state-
ments and^ may require specific modification for adaptation t£ the user's
host system.

     Concentration Files 21 and 22 contain the S02 and SO^ concentration
fields for each output time step.  An identifying header record iden-
tical 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.
                                   3-11

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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
     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:

     INUMB       -  a model run number which is automatically assigned
                    by the direct access disk output subroutine.

     DATFLD      -  The date of execution (day, month, and year) of the
                    model run [not the day (or days) simulated] .
MODEL
YR/DAY/HR
NGRIDS
IAVG
ISAVEF
                    The particular mesoscale dispersion model chosen
                    from the integrated modeling mesoscale system--in this
                    case, MESOPLUME.

                    The year, Julian day, and hour on which the model
                    simulation begins (Note that the first gridded
                    concentration field is not output until ' ISAVEF'* 'DTIME'
                    hours subsequently, where 'DTIME' is the basic
                    MESOPLUME 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, 'DTIME'.

                    The concentration array direct-access disk output
                    frequency in terms of the basic model time step,
                    'DTIME'.
     I SAFE
               The direct access address of the duplicate File  15
               record.
     IBEGIN      -  The direct access address of the first of the  'NGRIDS'
                    number of arrays output to File 21 for SO  and
                    File 22 for SO".

     ISTOP       -  The direct access address of the last of the  'NGRIDS'
                    number of arrays to File 21 for SO  and File 22 for
                    S0=.
                                  3-13

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ENVIRONMENTAL RESEARCH S. TECHNOLOGY INC
               ICHECK      -   The  run termination status indicator 'ICHECK' = 1
                              indicates  the model simulation terminated normally;
                              'ICHECK' = 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 MESOPLUME simulation is directly propor-
          tional to the number of  time steps N  and varies linearly with the number
          of sources  S.   Various meteorological factors—for example, lower trans-
          port wind speeds--cause  an increase in the average number of plume
          segments resident on the grid  and therefore an increase in running
          costs.   For typical meteorological conditions within the Four Corners
          grid,  and for the spatial extent and  grid resolution used for these
          experiments, MESOPLUME model run times on an IBM 370/158 can be esti-
          mated by:


                   t(sec) = 0.17(S)(N)  +  0.40 (N)                     (3-1)


          On the same installation, MESOPLUME required 230k bytes of core during
          execution.
                                             3-14

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                                                               ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                      4.  TEST CASE FOR MESOPLUME
     A test case is provided in this section to familiarize  the  user
with the operation of the MESOPLUME 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 MESOPLUME 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
MESOPLUME (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 MESOPLUME  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 MESOPLUME test case are stored together with the
results from the MESOPUFF and MESOGRID test cases as discussed in the
MESOPUFF 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 MESOPLUME, 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 MESOPUFF model are compared to those computed by the MESOPLUME
model.
                                   4-1

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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
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                         Inventory Input
                                        4-2

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                                                                ENVIRONMENTAL RESEARCH* TECHNOLOGY INC
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ENVIRONMENTAL RESEARCH 8 TECHNOLOGY INC
                                                                      Day 167 MESOPLUME
                Figure 4-3   MESOPLUME 24-Hour  Average S02 Concentration Calcomp
                             Plot,  16 June,  1978 (from MESOFILE)
                                               4-4

-------
                                                                                                                                                                   ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
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                                                              ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
                              REFERENCES
Bass,  A.,  C.  W.  Benkley,  J.  S.  Scire, and C.  S.  Morris.  1979.
     Development of Mesoscale Air Quality Simulation Models.  Volume I.
     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, 185 pp.

Benkley, C.  W.  and A.  Bass 1979a.  Development of Mesoscale Air Quality
     Simulation Models.  Volume 3.   User's Guide to MESOPUFF (Mesoscale
     Puff) Model.   EPA 600/7-79-XXX, Environmental Protection Agency,
     Research Triangle Park, NC, 124 pp.

Benkley, C.  W.  and A.  Bass.   1979b.   Development of Mesoscale Air
     Quality Simulation Models.  Volume 6.  Users 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 Meso-
     scale Air Quality Simulation Models.  Volume 4.  User's Guide to
     MESOGRID (Mesoscale Grid)  Model.  EPA 600/7-79-XXX, Environmental
     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
                                  REFERENCES  (Continued)
          Start,  G.  E.  and L. L. Wendell.  1974.  Regional  Effluent Dispersion
               Calculations Considering Spatial and Temporal  Meteorological
               Conditions.  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, Publ.  999-AP-26, 88 pp.

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            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
                                                           3. RECIPIENT'S ACCESSIOWNO.
 4 TITLE AND SUBTITLE
  Development of Mesoscale Air Quality  Simulation Models.
                                               5. REPORT DATE
                                                  September 1979
  Volume 2.
  Model
User's Guide to MESOPLUME (Mesoscale Plume)
                                                           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 £ 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
                                               EPA-600/7
 15. SUPPLEMENTARY NOTES
 Performed  under contract to the National  Oceanic and Atmospheric Administration
 16. ABSTRACT
      MESOPLUME  is  a variable-trajectory regional-scale Gaussian segmented  plume
 model especially designed to simulate the  air  quality impacts of multiple  point
 sources  at  long transport distances.  It has been developed to answer the  need for a
 simple,  computationally 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.   MESOPLUME is a natural generalization
 of the conventional Gaussian plume model to situations in which plume transport and
 diffusion may be dominated by spatial and  temporal variations in mesoscale meteorology

      Highly user-oriented,MESOPLUME 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  out-
 puts 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  S00  to
 SO • anH H-ry rlppngi t i rvn nf ?f\  pnrl ^fl 	2	
17.
                                CEY WORDS^AND DOCUMENT ANALYSIS
                  DESCRIPTORS
                                              b.IDENTIFIERS/OPEN ENDED TERMS
                                                            c.  COSATI Field/Group
       * Air  Pollution
       * Algorithms
        Atmospheric Models
        Atmospheric Diffusion
        Transport  Properties
                                                                   13B
                                                                   12A
                                                                   04A
                                                                   07D
                                                                   14B
18. DISTRIBUTION STATEMENT

      Release  to  Public
                                  19. SECURITY CLASS (ThisReport)
                                   Unclassified
21. NO. OF PAGES

      141
                                  20. SECURITY CLASS (Thispage)
                                    Unclassified
                                                            22. PRICE
EPA Form 2220-1 (9-73)

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     jority of documents are multidisciplinary in nature, the Primary Field/Group assignment(s) will be specific discipline, area of human
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    EPA Form 2220-1  (9-73) (Reverse)

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