United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
EPA-454/B-95-001
June 19%
EPA
Addendum to the
User's Manual for the Plume Visibility Model,
PLUVUE H (Revised)
MJG 0
DALLAS,
U
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EPA-454/B-95-001
Addendum to the
User's Manual for the Plume Visibility Model,
PLUVUE II (Revised)
•J
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Emissions, Monitoring, and Analysis Division
Research Triangle Park, North Carolina 27711
June 1996
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Table of Contents
Eage
List of Tables v
List of Figures vi
Preface vii
Acknowledgments viii
1.0 Introduction 1
1.1 Overview 1
1.2 Limitations of the System 2
1.3 User's Guide Organization 3
2.0 Technical Overview 5
2.1 PLUVUEII 5
2.1.1 Pollutant Transport, Diffusion, and Removal 6
2.1.2 Atmospheric Chemistry 12
2.1.3 Aerosol Size Distribution 17
2.1.4 Atmospheric Optics 18
2.1.5 Geometry of Plume, Observer, and Sun 24
2.1.6 Quantifying Visibility Impairment 28
2.1.7 1992 Code Modifications 31
2.1.8 1995 Code Modifications 33
2.1.9 Input Data 33-c
2.2 PLUIN2 47
2.3 MIETBL 48
2.3.1 Scattering Theory 48
2.3.2 Mie Calculations 51
2.3.3 Accuracy of the Interpolated Results of
Mie Calculations 53
3.0 User Instructions 57
3.1 Computer Requirements 57
3.2 Operating Instructions for RUNPLUVU 57
111
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Table of Contents (Continued)
Page
3.3 Level-3 Visibility Modeling Example 69
3.3.1 Overview 69
3.3.2 Site Location and Receptors 71
3.3.3 Model Inputs and Assumptions 71
3.3.4 Model Results 75
4.0 References 105
IV
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PREFACE
The User's Manual for the Plume Visibility Model, PLUVUE II (Revised), EPA-454/B-92-008
(NTIS PB93-18223) is the primary source of documentation for the PLUVUE II model. This
Addendum documents revisions made to the PLUVUE II model (dated 96170). The PLUVUE II
model was revised to correct several errors found in the previous version of the model and to make
some minor refinements. The user should replace the related items in the user's manual with the
pages provided herein. Note that the Appendix A, Comparison of the Original Version of PLUVUE
II with the Revised Version for Different Stability Classes, in the user's manual is deleted.
vn
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ACKNOWLEDGMENTS
This addendum has been prepared by L. Willard Richards, Sonoma Technology, Santa Rosa,
California. This effort was funded by the Environmental Protection Agency under Contract
No.68D30020, with Jawad S. Touma as Work Assignment Manager. Considerable assistance was
obtained from John Vimont, National Park Service.
vin
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1.0 INTRODUCTION
1.1 Overview
Sources of air pollution located near Class I areas such as national parks and
wilderness areas are required by the United States Environmental Protection Agency's (EPA)
Prevention of Significant Deterioration (PSD) and Visibility regulations to evaluate the impact
of their facility on such Class I areas. The Workbook for Plume Visual Impact Screening and
Analysis (Revised) (EPA, 1992) recommends the use of a plume visual impact screening
model (VISCREEN) for two successive levels of screening (Levels 1 and 2). A detailed
plume visual impact analysis (Level 3) is conducted using the more sophisticated plume
visibility model, PLUVUE n.
The PLUVUE n model described in this document refers to a restructured and revised
version of the original PLUVUE n model described in the User's Manual for the Plume
Visibility Model (PLUVUE II) (EPA, 1984a and EPA, 1984b). The model was restructured in
order to improve the user interface and computing requirements and revised to remove several
errors in the original PLUVUE n code. The PLUVUE n algorithm is basically the same
algorithm as developed in 1984, except for some changes to correct computer coding errors
and to use "lookup" tables for the calculation of the phase functions, which describe the
intensity of the scattered light as a function of the scattering angle. (For example, the
intensity of the sunlight scattered to the earth by the moon depends on the phase of the moon.)
Also, a program has been designed to assist the user with the application of the PLUVUE n
visibility model on a personal computer by allowing the user to prepare an input file, select or
create a library of Mie calculations to reduce computational time, and run the PLUVUE n
model. This program is referred to as the RUNPLUVU visibility modeling system. In
addition, this user's guide, which duplicates many of the sections contained in the original
(EPA, 1984a) user's guide, has been transferred to WordPerfect 5.1 for easy downloading
from the EPA's Technology Transfer SCRAM bulletin board.
The objective of the PLUVUE n model is to calculate visual range reduction and
atmospheric discoloration caused by plumes consisting of primary particles (e.g., fly ash),
nitrogen oxides, and sulfur oxides emitted by a single emission source. Primary emissions of
sulfur dioxide (SO2) and nitric oxide (NO) do not scatter or absorb light and therefore do not
cause visibility impairment. However, these emissions are converted in the atmosphere to
secondary species that do scatter or absorb light and thus have the potential to cause visibility
impairment. SO2 emissions are converted to sulfate (SO4=) aerosols. These aerosols are
generally formed or grow to a size (0.1 to 1.0 /xm) that is effective in scattering light. NO
emissions are converted to nitrogen dioxide (NO2) gas, which is effective in absorbing light.
In turn, NO2 is converted to nitric acid vapor (HNO3), which in turn neither absorbs nor
scatters light. In some situations, nitric acid may form ammonium nitrate or organic nitrate
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aerosol, which scatters light. However, in many nonurban plumes, nitrate probably remains
as HNO3 vapor without visual effects. Eventually, all primary particles, secondary aerosols,
and gases in a plume are removed from the atmosphere as a result of surface deposition and
precipitation scavenging. PLUVUE n is designed to predict the transport, atmospheric
diffusion, chemical conversion, optical effects, and surface deposition of point and area source
emissions.
The PLUVUE n model uses a Gaussian formulation for transport and dispersion. The
spectral radiance I(X) (i.e., the intensity of light) at 39 visible wavelengths (0.36 < X < 0.75
/xm) is calculated for views with and without the plume. The changes in the spectrum are
used to calculate various parameters that predict the perceptibility of the plume and contrast
reduction caused by the plume (Latimer et al., 1978). The four key perception parameters for
predicting visual impact are:
• reduction in visual range;
• contrast of the plume against a viewing background at the 0.55 /-im wavelength;
• blue-red ratio of the plume; and
• color change perception parameter AE(LVb').
1.2 Limitations of the System
The plume visibility model PLUVUE H was evaluated with the 1981 VISTTA data
base which was collected in the vicinity of the Kincaid Generating Station near Springfield,
Illinois, and the Magma Copper Smelter near San Manuel, Arizona. Details of the model
evaluation results are given in Seigneur et al. (1983).
For applications to distant Class I areas (more than 50 km from the emission source),
the model is less accurate because of mesoscale wind speed, wind direction, and stability
variations. Thus, the use of a Gaussian-based model for downwind distances greater than 50
km to predict visual effects is probably a conservative approach; however, this has not yet
been demonstrated conclusively. Visual impacts for horizontal lines of sight are inversely
proportional to the vertical extent of plume mixing. This vertical extent of plume mixing is
defined by the vertical plume dispersion parameter (aj and, at farther distances downwind,
by the mixing depth. Thus, errors in predicting vertical plume dimensions will carry
throughout the calculations of plume visibility impacts. However, until field measurements of
mesoscale plume transport and diffusion are carried out, and until better models based on
these data are developed and verified, the EPA does not know of a better approach to model
plume dispersion for the purposes of plume visual impact analysis.
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Other limitations are basic to the chemical mechanism used in PLUVUE n to predict
the conversion of sulfur and nitrogen oxides. Although this mechanism is a reasonable
approximation for most applications in nonurban areas, it is not valid for applications in
photochemical (urban) atmospheres or for sources of significant quantities of reactive
hydrocarbons. For such applications, photochemical plume models or regional models should
be used.
Other approximations are used in the atmospheric optics calculations and are discussed
in Latimer et al. (1978). These approximations probably do not introduce significant errors in
most situations; however, this has not yet been demonstrated. Terrain viewing backgrounds
are idealized as white, gray, and black objects. The background atmosphere is treated as two
layers; a homogeneous, surface mixed layer and a relatively clean upper-atmosphere layer.
Diffusion radiation is calculated by integrating an angle-dependent radiance field according to
the algorithm of Isaacs (1981). Errors in predicting diffuse-radiation intensities may
adversely affect the accuracy of spectral radiance calculations, but not necessarily the
accuracy of calculations of plume contrast, color differences, and reduction in visual range.
In PLUVUE n, the calculated visual impact of a plume is quantified using coloration, color
difference, and contrast parameters that are related to human visual perception.
1.3 User's Guide Organization
A technical overview of PLUVUE n, PLUIN2 (algorithm which allows the user to
edit PLUVUE n input files), and MIETBL (algorithm which allows the user to create Mie
library files as input to PLUVUE H) is presented in Section 2.0. Detailed RUNPLUVU user
instructions including the basic computer requirements, detailed operating instructions, and a
Level-3 plume visibility example are presented in Section 3.0. The references are given in
Section 4.0.
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• Light scattering and absorption characteristics of the resultant aerosol; and
• Radiative transfer through the aerosol along different lines of sight.
2.1.1 Pollutant Transport, Diffusion, and Removal
There are two scales that are of interest in visibility impairment calculations. They
require two different types of models:
• A near-source plume model designed to predict the incremental impact of one
emission source (such as a power plant or smelter).
• A regional model designed to predict, over time periods of several days, the
impacts of several emissions sources within a region whose spatial scale is in the
range of 1000 km.
Calculation of near-source visual impacts, which is the design objective of
PLUVUE II, requires a basic model that accurately predicts the spatial distribution of
pollutants and the chemical conversion of NO to NO2 and SOX and NOX to sulfates and nitrates.
The plume model must be capable of handling the spatial scale from emissions at the source to
at least 100 km downwind. Because the regional-scale problem may be caused by the long-
range transport of pollutants over a spatial scale of 1000 km, an air quality model is needed
that can account for multiple sources and for temporal variations in mixing heights, dispersion
parameters, emission rates, reaction rates, and wind speed and direction. This second type of
model, a regional visibility model, is beyond the scope of this user's manual. PLUVUE II is a
near-source plume visibility model.
Initial Dilution in a Buoyant Plume
Modeling of the initial dilution of a plume from the top of the stack to the point of final
plume rise is important when modeling the conversion of nitric oxide (NO) to nitrogen
dioxide (NO2) in a power plant plume because of the quick quenching of the thermal oxidation
of NO. The rate of this reaction is second order with respect to NO concentrations; therefore,
the rate is fastest in the initial stages of plume dilution. It is also important to account for the
initial dilution of buoyant releases because the rate of dilution caused by the turbulent
entrainment of ambient air by a rising plume parcel can be considerably greater than that
indicated by diffusion coefficients based on measurements for nonbuoyant releases (e.g.,
Pasquill-Gifford oy, az). Thus, initial plume dilution during plume rise should be taken into
account to calculate accurately both plume dilution and atmospheric chemistry.
Briggs (1969) suggested that the characteristic plume radius (R,,) increases linearly with
the height of the plume above the stack and can be represented as follows:
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Gaussian Plume Diffusion
After the plume has achieved its final height (about 1 km downwind), plume
concentrations for uniform wind fields can be predicted using a Gaussian model if
the wind speed u at plume height H (or h, + Ah, where h, is the stack height) and the rate of
diffusion are known for the particular situation so that diffusion coefficients (ay, aj can be
selected:
X =
exp
exp
exp
(1)
Equation (12) is appropriate for a conservative species and can be modified to be appropriate
for a nonconservative species by changing the source term Q.
It is necessary for calculating plume visual impact to integrate, along the line of sight,
the plume extinction coefficient, the magnitude of which depends on primary and secondary
paniculate and nitrogen dioxide concentrations. Equation (12) can be integrated (Ensor et al.,
1973) in the cross-wind direction y, from y = -oo to y = +00, to obtain the optical thickness
of the plume:
'(*)
exp
exp
(2)
where be)(1 is the incremental increase in extinction coefficient in the plume and Q' is the flux
of the plume extinction coefficient over the entire plume cross section at downwind distance
x. In the vertical direction z, from z = 0toz=+oo,the plume optical thickness is
'(*)
exp
(3)
Observer-Plume Orientation
The magnitude of the visual impact of a plume depends on the orientation of the
observer with respect to the plume because the plume optical thickness will vary depending
on this orientation. Figure 1 shows plan and elevation views of an observer and a plume and
indicates that the sight path distance through the constituents of the plume is a function of
angles a and /3. The optical thickness for most combinations of angles a and |3 can be
approximated as follows:
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Background accumulation mode (submicron) aerosol (typically having a mass
median diameter of about 0.3 ^im and a geometric standard deviation of 2).
• Background coarse mode (> 1 jim) aerosol (typically having a mass median
diameter of about 6 /*m and a geometric standard deviation of 2).
• Plume and background carbonaceous aerosol (typically having a mass median
diameter of about 0.1 /im and a geometric standard deviation of 2).
• Plume primary paniculate aerosol (e.g., fly ash emissions).
• Plume secondary sulfate (SO4=) aerosol (typically having a mass median
diameter of 0.1 to 0.3 /xm and a geometric standard deviation of 2).
The expression developed by Winkler (1973) is used to calculate the amount of liquid
water associated with submicron background and plume sulfate aerosol as a function of
relative humidity.
Secondary aerosol is assumed to form in the submicron plume secondary aerosol mode.
A time delay equal to the time between successive downwind distances is introduced to
account for coagulation and condensation time delays.
2.1.4 Atmospheric Optics
In the atmospheric optics component of the plume visibility model, the light scattering
and absorption properties of the aerosol and the resultant light intensity (spectral radiance) for
various illumination and viewing situations are computed.
Calculation of the Scattering and Absorption Properties
After the concentrations of the pollutants are specified by the transport and chemistry
subroutines, their radiative properties must be determined. For NO2, the absorption at a
particular wavelength is a tabulated function (Nixon, 1940) multiplied by the concentration.
For aerosols, however, the procedure is more complicated.
In general, a particle's ability to scatter and absorb radiation at a particular frequency is
a function of size, composition, and shape, which depend on the relative humidity. The
flexibility to specify the size distribution of both primary and secondary particles was desired.
The effect of these parameters on the wavelength dependence of the extinction coefficient and
18
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the angular distribution of the light scattered by particles is calculated by the Mie equations.
These calculations are performed by the MIETBL algorithm and the results saved in tables as
described in Section 2.3. This eliminates the need to repeat the Mie calculations with each
execution of the PLUVUE II model.
Calculation of Light Intensity
The light intensity, or radiance (watts/m2/steradian//*m) at a particular location in the
atmosphere is a function of the direction of observation Q and the wavelength X. Calculation
of the light intensity in a medium follows from the radiative transfer equation. This equation
is a conservation of energy statement that accounts for the light added to the line of sight by
scattering and the light lost because of absorption and scattering. Approximations and
solution techniques applicable to planetary atmospheres have been discussed by Hansen and
Travis (1974) and Irvine (1975).
To compute the spectral light intensity at the observer, we sum (integrate) the scattered
and absorbed light over the path, r, associated with the line of sight fi. The resultant general
expression for the background sky intensity at a particular wavelength is
7,(Q) - 2 / KQ'.t') P(& - 0,^ d& «"' *' , (4)
-
where
T = the optical depth (r = $ Or bext dr, where bm is the extinction
coefficient),
w = the albedo for single scattering (GO = b^/b^ where bicat is the
scattering coefficient),
p(fl' -» fi) = the scattering distribution function for the angle Q' -» fl, and
I = the spectral intensity at r' from direct and diffuse solar radiation.
The intensity seen by an observer in direction Q of a background viewing object of
intensity I0 at distance R is
[
J
(5)
P(Q7 + O.t')
Equations (36) and (37) then completely describe the spectral intensity of the sky and a
background object. Once these two quantities are known, the visual effects of the intervening
atmosphere can be quantified. In evaluating Equations (36) and (37), we encounter two main
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• Plume Contrast
This parameter indicates the relative brightness of a plume compared to a viewing
background. For a sight path through the plume centerline, it is equal to the radiance
with the plume present minus the radiance with the plume absent, all divided by the
radiance with the plume absent. A contrast that is positive indicates a relatively bright
plume and a negative contrast indicates a dark plume. Plumes that subtend angles
between roughly 0.1 and 1 degree and have contrasts with absolute values greater than
0.02 are generally perceptible. A two percent contrast is used to define visual range.
Appendix A of the Workbook for Plume Visual Impact Screening and Analysis
(Revised) should be consulted to determine the dependence of the threshold contrast on
the angle subtended by the plume (EPA, 1992). Plume contrast calculations in
PLUVUE II are done at one wavelength, 0.55 /ma, which is a green color in the middle
of the visible spectrum, which extends from 0.4 /mi (violet) to 0.7 /mi (red).
• Blue-Red Ratio
This parameter indicates the relative coloration of a plume relative to its viewing
background. Blue-red ratios less than one indicate relatively yellow, red, or brown
plumes. Blue-red ratios greater than one indicate plumes that are whiter, grayer, or
bluer than the viewing background. Blue-red ratios less than 0.9 or greater than 1.1
would be indicative of perceptible plumes.
• Color Contrast Parameter (AE)
The color contrast parameter AE is probably the best single indicator of the
perceptibility of a plume due both to its contrast and its color with respect to a
viewing background. AE is calculated for the entire visible spectrum and indicates
the difference between the brightness and color of a plume and its background. The
larger the value of AE, the greater the perceptibility of the plume. Under ideal viewing
conditions, when the viewing background is uniform and the plume is sharp-edged, a
just perceptible AE would be equal to one. For cases of plumes with diffuse edges that
subtend angles between roughly 0.1 and 1 degree, a just perceptible AE threshold
would be greater than one, perhaps two (EPA, 1992).
2.1.7 1992 Code Modifications
In 1989 (SAI, 1989), the PLUVUE II model was revised to include an interpolated scheme to
calculate the phase functions which significantly decreased the execution tune of the PLUVUE II
computer code. The development of an interpolation procedure to calculate phase functions needed
in the visibility model was performed by Richards and Hammarstrand (1988). The phase function
calculation uses "lookup" tables which contain the phase functions for different particle size
distributions. Further details concerning the phase function calculations are given in Section 2.3.
Details concerning the most recent modifications to the PLUVUE II algorithm are as
follows:
31
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• Under Pasquill-Gifford stability class A conditions, PLUVUE II was found to produce
numerical overflows. Diagnostic checks indicated that the interpolation formula based
on a series of logarithms to calculate
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In addition to the code modifications listed above, a number of cosmetic changes have
been made to the code. Headers have been added to all subroutines. Unused variables and
arrays, along with commented out statements, have been eliminated.
2.1.8 1995 Code Modifications
Additional modifications were made in the PLUVUE II code at the end of 1994 to remove
known errors and to improve the realism of the model simulations. The reasons for modifying
the code and the approach used to implement the modifications are described in this section.
• Correct an Error in Subroutine BACKOBJ
Line BAC00620 of the subroutine BACOBJ was changed from
SPECO(I) = SPECO(I) + G(I)
to
SPECO(I) = SPECO(I) + G(I)*(1.0 - TRO)
to remove an error. Here G(I) is the source function (or equilibrium radiance), and
G(I)*(1.0 - TRO) is the contribution of the path radiance (or air light) to the apparent
radiance SPECO(I).
• Provide Realistic Reflectances for Black and White Terrain Backgrounds
The reflectance of the black terrain background was changed from 0.0 to 0.1 and the
reflectance of the white background from 1.0 to 0.9 to more accurately simulate the
reflectances of dark, shaded forests and snow. This refinement has the greatest effect
on the simulation of plumes viewed against a nearby, black background, where even the
slightest scattering of light by the plume can cause large calculated contrasts if it is
assumed that no light is reflected from the background. Data for the radiances of
typical terrain backgrounds compared to the radiance of the horizon sky have been
published by Malm et al. (1982).
• Calculate the Contrast of a Plume Against a Black Terrain Background Assuming that
the Eye is Accommodated to the Radiance of the Horizon Sky
Before this modification, the contrast of the plume against a background was calculated
using the assumption that the eye was accommodated to the radiance of the background.
Warren White has pointed out in unpublished correspondence that for black terrain
backgrounds, it is more likely that the eye is accommodated to the radiance of the
33
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horizon sky just above the terrain than to the radiance of the black background. The
PLUVUE II code was modified to calculate the contrast of a plume against a black
background assuming that the eye is accommodated to the radiance of the horizon sky
and to add this value to the output file.
An example from common experience provides an illustration of the need for this
refinement. When a person is in a relatively dark room, his eyes are accommodated to
the darkness, and objects in the room can be clearly seen. However, if that person
goes outside and looks into the dark room through an open window, his eyes become
accommodated to the outside light and objects in the room become difficult to perceive.
In the same way, a plume against a black background that would be perceptible if the
eye were accommodated to the radiance of the black background could be imperceptible
if the eye is accommodated to the radiance of the horizon sky.
Add Diffuse Skylight to the Illumination of the Reference White
The human visual system has the property that the lightest and brightest object in a
scene is typically perceived as white (MacAdam, 1981). The colors of other objects
are then referred to the color of this object. White clouds in the sky often provide the
reference white in scenes that may include perceptible plumes.
The color difference calculations in PLUVUE II require calculating the spectral
radiance of a reference white. Before this refinement, the reference white was a diffuse
reflector with 100 percent reflectance that was normal to the solar rays and was
illuminated only by the direct solar rays. As a result, the illumination of the reference
white became too small as the sun approached the horizon. This caused the calculated
color differences to become unrealistically large as the sun approached the horizon.
The code was modified so that diffuse skylight was added to the illumination of the
reference white. This was accomplished by calculating the downward flux of both
direct sunlight and diffuse skylight at 39 wavelengths in Subroutine BACCLI, and then
subtracting the contribution of direct sunlight to the downward flux in Subroutine
BACOBJ. This gave a value for the downward flux of diffuse skylight, which was
added to the previously used illumination of the reference white by the direct solar
rays. The contribution of the direct sunlight to the downward flux calculated in
Subroutine BACCLI is calculated as the flux on a horizontal surface. Therefore, this
flux cannot replace the direct solar flux calculated in Subroutine BACOBJ, which is the
flux on a surface normal to the solar rays.
The same subroutine, BACOBJ, is used to both calculate the spectral radiance of the
white, gray and black terrain backgrounds as well as the spectral radiance of the
reference white. Thus, this code modification also increases the illumination of the
terrain backgrounds, especially at low sun angles.
33-a
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Correct Errors in the Calculation of the Fraction of the Primary Particle Emissions that are
Carbon and Non-carbon
The capability of simulating the optical effects of soot in the primary particle emissions
and in the background air was added to the model when PLUVUEI was converted to
PLUVUE n. On review of the code, it was found that some parts of the code had not been
modified to incorporate this refinement. The code was modified so the correct emission
rates of carbon and non-carbon primary particles were used in all calculations.
Define Some Variables as Characters Instead of Integers to Avoid Errors with Some
Compilers
FORTRAN 90 is replacing FORTRAN 77 as the standard. It was found that the existing
code caused errors with FORTRAN 90 compilers that could be eliminated by defining
some variables as characters instead of integers.
33-b
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2.1.9 Input Data
The input data needed to run PLUVUE II are contained in one file of 80 byte, card-image
records. As is discussed in Sections 2.2 and 3.2, the RUNPLUVU visibility modeling system
allows the user to interactively edit the PLUVUE II input file. The PLUVUE II input data
include the following parameters:
• Wind speed aloft or at the 10-m level
• Stability category
• Lapse rate
• Height of the planetary boundary layer (mixing depth)
• Relative humidity
• SO2, NOX, and particulate emissions rates
• Flue gas flow rate, exit velocity, and exit temperature
• Flue gas oxygen content
• Ambient air temperature at stack height
• Ambient background NOX NO2, O3, and SO2 concentrations
• Properties (including density, mass median radius, and geometric standard deviation) of
background and emitted aerosols in accumulation (0.1-1.0 /*m), coarse (1.0-10.0 /mi),
and carbonaceous aerosol size modes
• Coarse mode background aerosol concentration
• Background visual range or background sulfate and nitrate concentration
• Deposition velocities for SO2, NO,, coarse mode aerosol, and accumulation mode
aerosol
• UTM coordinates of the source location
• Elevation of the source location
• UTM coordinates and elevation of the observer location for an observer-based analysis
• UTM zone for the site and observer locations
• Time, day, month, year, and time zone for the time and date of the simulation
• For an observer-based run, terrain elevation at the points along the plume trajectory at
which the analysis will be performed
• For an observer-based run with white, gray, and black viewing backgrounds, the
distances from the observer to the terrain that will be observed behind the plume
• For an observer-based run, the wind direction
The input data file also has numerous switches or flags to allow the user to select the
particular subset of the complete model that is required. Table 1 lists the input parameters
with formats, summary descriptions, and suggested values for some of the input parameters.
33-c
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TABLE 1 (Continued)
DATA REQUIREMENTS FOR PLUVUE II
Card
16
17
18
19
20
No. Format Variables Description
F10.2
F10.1
F10.1
F10.1
F10.2
F5.1
F5.1
F10.1
F10.3
F10.3
F10.3
F10.3
F10.3
F10.3
F10.3
QPART
FLOW
FGTEMP
FG02
WMAX
UNITS
HSTACK
TAMB
AMBNOX
AMBNO2
03AMB
AMBS02
ROVA
ROVC
ROVS
Total primary paniculate emissions rates from all stacks in tons per
day
Flue gas flow rate (cfm) per stack
Flue gas exit temperature (°F)
Flue gas oxygen concentration (mole percent) [3]""
Flue gas stack exit velocity (m/s)
Number of stacks
Stack height (feet)
Ambient temperature (°F)
Ambient [NOJ in ppm [0]
Ambient [N02] in ppm [0]
Ambient [03] in ppm [0.04]
Ambient [SO2] in ppm [0]
Mass median radius (/*m) for background accumulation mode aerosol
[0.15]
Mass median radius (/xm) for background coarse mode aerosol [3.0]
Mass median radius (urn) for plume
F10.3
ROVP
secondary aerosol [0.10]
Mass median radius (/im) of emitted primary paniculate [1.0]
36
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In MIETBL, the strength of the aerosol light scattering at the desired angles is determined by
linear interpolation using data tabulated every 2°.
To calculate the light scattering properties of a log-normal size distribution of aerosol
particles, it is necessary to perform Mie calculations for a number of different particle sizes in
the size range of interest. These results are then averaged using weighting factors derived
from the relative numbers of particles of each size in the log-normal particle size distribution.
For large particles, averaging over particle sizes is important because the angular
distribution of light scattered by a single size of particles shows many peaks and valleys.
When results for only a few sizes of particles are averaged, some of these peaks and valleys
persist. However, when calculated results for many different particle sizes are weighted
according to a log-normal distribution and averaged, the angular distribution of scattered light
becomes quite smooth.
The default aerosol properties for PLUVUE II which are contained in the Mie default
library are listed in Table 2. The data were obtained from a listing of input parameters
presented in an earlier version of the PLUVUE II User's Manual (Seigneur et al., 1983).
These six aerosol size distributions provide a compact data set that may be used when no
better aerosol size distribution data are available. When using this default library, the only
choice to be made is aerosol diameter (D) = 0.2 /xm for the plume secondary aerosol in
polluted or humid areas (e.g., east of the Mississippi) or D = 0.1 /xm in clean or dry areas
(e.g., the clean areas in the west or Alaska).
54
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Chemistry-1977. NBS Special Pub. 513, National Bureau of Standards, Washington,D.C.
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Reviews, 16:527-610.
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Approximate Techniques. Atmos. Environ., 15:1827-1833.
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Chem. Phys., 8:157-160.
106
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Richards, L.W. and R.G.M. Hammarstrand, 1988: User's Manual for Running PLUVUE and
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89/045. Systems Applications, Inc., San Rafael, CA.
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a Diurnal Range. EPA-600/4-77-015. U.S. Environmental Protection Agency, Research
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107
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i
TECHNICAL REPORT DATA
(Please read Instructions on reverse before completing)
1 1 REPORT NO 2
1 EPA-454/B-95-001
4 TITLE ANT, SUBTITLE
Addendum to the User's Manual for the Plume Visibility
Model, PLUVUE II (Revised)
7 AUTHOR (S)
<> PERFORMING ORGANIZATION NAME AND ADDRESS
Sonoma Technology Inc.
5510 Skylane Blvd., Suite 101
Santa Rosa, CA 95403
12 SPONSORING AGENCY NAME AND ADDREDS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Emissions, Monitoring & Analysis Division
Research Triangle Park, NC 27711
IB SUPPLEMENTARY NOTES
EPA Work Assignment Manager: Jawad S.
3 RECIPIENT'S ACCESSION NO
5 REPORT DATE
June 1996
t> PERFORMING ORGANIZATION CODE
8 PERFORMING ORGANIZATION REPORT NO
10. PROGRAM ELEMENT NO
11. CONTRACT/ GRANT NO.
EPA Contract No. 68D30020
13 TYPE OF REPORT AND PERIOD COVERED
Final Report
14 SPONSORING AGENCY CODE
Touma
1 b ABSTRACT
This addendum documents revisions made to the PLUVUE II model to correct several errors
and make some minor refinements. The user should replace the related items in the
user's manual with the pages in this addendum.
KEY WORDS
a DESCRIPTORS
Air Pollution
Air Quality Dispersion Models
Meteorology
Visibility
Aerosols
18 DISTRIBUTION STATEMENT
Release Unlimited
AND DOCUMENT ANALYSIS
b IDENTIFIERS/OPEN ENDED TERMS c COSATI Field/Group
19 SECURITY CLASS ( Report; 21 NO OF PAGES
Unclassified 22
20 SECURITY CLASS (fage) 22 PRICE
Unclassified
J>A form 2220-1 (R«v. 4-77}
PREVIOUS EDITION IE OBSOLETE
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