Appendix B to Appendix W of Part 51 - Summaries of Alternative Air Quality Models

Table of Contents B.0 Introduction and Availability B.1 AVACTA II Model B.2 Dense Gas Dispersion Model (DEGADIS) B.3 ERT Visibility Model B.4 HGSYSTEM B.5 HOTMAC/RAPTAD B.6 LONGZ B.7 Maryland Power Plant Siting Program (PPSP) Model B.8 Mesoscale Puff Model (MESOPUFF II) B.9 Mesoscale Transport Diffusion and Deposition Model For Industrial Sources (MTDDIS) B.10 Multi-Source (SCSTER) Model B.11 PANACHE B.12 PLUME Visibility Model (PLUVUE II) B.13 Point, Area, Line Source Algorithm (PAL-DS) B.14 Reactive Plume Model (RPM-IV) B.15 Shoreline Dispersion Model (SDM) B.16 SHORTZ B.17 Simple Line-Source Model B.18 SLAB B.19 WYNDvalley Model B.REF References B.0 Introduction and Availability

This appendix summarizes key features of refined air quality models that may be considered on a case-by-case basis for individual regulatory applications. For each model, information is provided on availability, approximate cost, regulatory use, data input, output format and options, simulation of atmospheric physics and accuracy. The models are listed by name in alphabetical order.

There are three separate conditions under which these models will normally be approved for use:

1. A demonstration can be made that the model produces concentration estimates equivalent to the estimates obtained using a preferred model (e.g., the maximum or high, second-high concentration is within 2% of the estimate using the comparable preferred model);

2. A statistical performance evaluation has been conducted using measured air quality data and the results of that evaluation indicate the model in appendix B performs better for the application than a comparable model in appendix A; and

3. There is no preferred model for the specific application but a refined model is needed to satisfy regulatory requirements.

Any one of these three separate conditions may warrant use of these models. See section 3.2, Use of Alternative Models, for additional details.

Many of these models have been subject to a performance evaluation by comparison with observed air quality data. A summary of such comparisons for models contained in this appendix is included in Moore et al. (1982). Where possible, several of the models contained herein have been subjected to rigorous evaluation exercises, including (1) statistical performance measures recommended by the American Meteorological Society and (2) peer scientific reviews.

A source for some of these models and user's documentation is: Computer Products, National Technical Information Service (NTIS), U.S. Department of Commerce, Springfield, VA 22161, Phone: [phone]. A number of the model codes and selected, abridged user's guides are also available from the Support Center for Regulatory Air Models Bulletin Board System19 (SCRAM BBS), Telephone [phone]. The SCRAM BBS is an electronic bulletin board system designed to be user friendly and accessible from anywhere in the country. Model users with personal computers are encouraged to use the SCRAM BBS to download current model codes and text files.

B.1 AVACTA II Model Reference

Zannetti, P., G. Carboni and R. Lewis, 1985. AVACTA II User's Guide (Release 3). AeroVironment, Inc., Technical Report AV-OM-85/520.

Availability

A 31/2” diskette of the FORTRAN coding and the user's guide are available at a cost of $3,500 (non-profit organization) or $5,000 (other organizations) from: AeroVironment, Inc., 222 Huntington Drive, Monrovia, CA 91016, Phone: [phone].

Abstract

The AVACTA II model is a Gaussian model in which atmospheric dispersion phenomena are described by the evolution of plume elements, either segments or puffs. The model can be applied for short time (e.g., one day) simulations in both transport and calm conditions.

The user is given flexibility in defining the computational domain, the three-dimensional meteorological and emission input, the receptor locations, the plume rise formulas, the sigma formulas, etc. Without explicit user's specifications, standard default values are assumed.

AVACTA II provides both concentration fields on the user specified receptor points, and dry/wet deposition patterns throughout the domain. The model is particularly oriented to the simulation of the dynamics and transformation of sulfur species (SO2 and SO4=), but can handle virtually any pair of primary-secondary pollutants.

a. Recommendations for Regulatory Use

AVACTA II can be used if it can be demonstrated to estimate concentrations equivalent to those provided by the preferred model for a given application. AVACTA II must be executed in the equivalent mode.

AVACTA II can be used on a case-by-case basis in lieu of a preferred model if it can be demonstrated, using the criteria in section 3.2, that AVACTA II is more appropriate for the specific application. In this case the model options/modes which are most appropriate for the application should be used.

b. Input Requirements

A time-varying input is required at each computational step. Only those data which have changed need to be input by the user.

Source data requirements are: Coordinates, emission rates of primary and secondary pollutants, initial plume sigmas (for non-point sources), exit temperature, exit velocity, stack inside diameter.

Meteorological data requirements are: surface wind measurements, wind profiles (if available), atmospheric stability profiles, mixing heights.

Receptor data requirements are: receptor coordinates.

Other data requirements: coordinates of the computational domain, grid cell specification, terrain elevations, user's computational and printing options.

c. Output

The model's output is provided according to user's printing flags. Hourly, 3-hour and 24-hour concentration averages are computed, together with highest and highest-second-highest concentration values. Both partial and total concentrations are provided.

d. Type of Model

AVACTA II is Gaussian segment/puff model.

e. Pollutant Types

AVACTA II can handle any couple of primary-secondary pollutants (e.g., SO2 and SO4=).

f. Source Receptor Relationship

The AVACTA II approach maintains the basic Gaussian formulation, but allows a numerical simulation of both nonstationary and nonhomogeneous meteorological conditions. The emitted pollutant material is divided into a sequence of “elements,” either segments or puffs, which are connected together but whose dynamics are a function of the local meteorological conditions. Since the meteorological parameters vary with time and space, each element evolves according to the different meteorological conditions encountered along its trajectory.

AVACTA II calculates the partial contribution of each source in each receptor during each interval. The partial concentration is the sum of the contribution of all existing puffs, plus that of the closest segment.

g. Plume Behavior

The user can select the following plume rise formulas:

Briggs (1969, 1971, 1972)

CONCAWE (Briggs, 1975)

Lucas-Moore (Briggs, 1975)

User's function, i.e., a subroutine supplied by the user

With cold plumes, the program uses a special routine for the computation of the jet plume rise. The user can also select several computational options that control plume behavior in complex terrain and its total/partial reflections.

h. Horizontal Winds

A 3D mass-consistent wind field is optionally generated.

i. Vertical Wind Speed

A 3D mass-consistent wind field is optionally generated.

j. Horizontal Dispersion

During each step, the sigmas of each element are increased. The user can select the following sigma functions:

Pasquill-Gifford-Turner (in the functional form specified by Green et al., 1980)

Brookhaven (Gifford, 1975)

Briggs, open country (Gifford, 1975)

Briggs, urban, i.e., McElroy-Pooler (Gifford, 1975)

Irwin (1979a)

LO-LOCAT (MacCready et al., 1974)

User-specified function, by points

User-specified function, with a user's subroutine

The virtual distance/age concept is used for incrementing the sigmas at each time step.

k. Vertical Dispersion

During each step, the sigmas of each element are increased. The user can select the following sigma functions:

Pasquill-Gifford-Turner (in the functional form specified by Green et al., 1980)

Brookhaven (Gifford, 1975)

Briggs, open country (Gifford, 1975)

Briggs, urban, i.e., McElroy-Pooler (Gifford, 1975)

LO-LOCAT (MacCready et al., 1974)

User-specified function, with a user's subroutine

The virtual distance/age concept is used for incrementing the sigmas at each time step.

l. Chemical Transformation

First order chemical reactions (primary-to-secondary pollutant)

m. Physical Removal

First order dry and wet deposition schemes

n. Evaluation Studies

Zannetti P., G. Carboni and A. Ceriani, 1985. AVACTA II Model Simulations of Worst-Case Air Pollution Scenarios in Northern Italy. 15th International Technical Meeting on Air Pollution Modeling and Its Application, St. Louis, Missouri, April 15-19.

B.2 Dense Gas Dispersion Model (DEGADIS) Reference

Environmental Protection Agency, 1989. User's Guide for the DEGADIS 2.1—Dense Gas Dispersion Model. EPA Publication No. EPA-450/4-89-019. U.S. Environmental Protection Agency, Research Triangle Park, NC 27711. (NTIS No. PB 90-213893)

Availability

The model code is only available on the Support Center for Regulatory Air Models Bulletin Board System (see section B.0).

Abstract

DEGADIS 2.1 is a mathematical dispersion model that can be used to model the transport of toxic chemical releases into the atmosphere. Its range of applicability includes continuous, instantaneous, finite duration, and time-variant releases; negatively-buoyant and neutrally-buoyant releases; ground-level, low-momentum area releases; ground-level or elevated upwardly-directed stack releases of gases or aerosols. The model simulates only one set of meteorological conditions, and therefore should not be considered applicable over time periods much longer than 1 or 2 hours. The simulations are carried out over flat, level, unobstructed terrain for which the characteristic surface roughness is not a significant fraction of the depth of the dispersion layer. The model does not characterize the density of aerosol-type releases; rather, the user must assess that independently prior to the simulation.

a. Recommendations for Regulatory Use

DEGADIS can be used as a refined modeling approach to estimate short-term ambient concentrations (1-hour or less averaging times) and the expected area of exposure to concentrations above specified threshold values for toxic chemical releases. The model is especially useful in situations where density effects are suspected to be important and where screening estimates of ambient concentrations are above levels of concern.

b. Input Requirements

Data may be input directly from an external input file or via keyboard using an interactive program module. The model is not set up to accept real-time meteorological data or convert units of input values. Chemical property data must be input by the user. Such data for a few selected species are available within the model. Additional data may be added to this data base by the user.

Source data requirements are: emission rate and release duration; emission chemical and physical properties (molecular weight, density vs. concentration profile in the case of aerosol releases, and contaminant heat capacity in the case of a nonisothermal gas release; stack parameters (i.e., diameter, elevation above ground level, temperature at release point).

Meteorological data requirements are: wind speed at designated height above ground, ambient temperature and pressure, surface roughness, relative humidity, and ground surface temperature (which in most cases can be adequately approximated by the ambient temperature).

Receptor data requirements are: averaging time of interest, above-ground height of receptors, and maximum distance between receptors (since the model computes downwind receptor distances to optimize model performance, this parameter is used only for nominal control of the output listing, and is of secondary importance). No indoor concentrations are calculated by the model.

c. Output

Printed output includes in tabular form:

• Listing of model input data;

• Plume centerline elevation, mole fraction, concentration, density, and temperature at each downwind distance;

• σy and σz values at each downwind distance;

• Off-centerline distances to 2 specified concentration values at a specified receptor height at each downwind distance (these values can be used to draw concentration isopleths after model execution);

• Concentration vs. time histories for finite-duration releases (if specified by user).

The output print file is automatically saved and must be sent to the appropriate printer by the user after program execution.

No graphical output is generated by the current version of this program.

d. Type of Model

DEGADIS estimates plume rise and dispersion for vertically-upward jet releases using mass and momentum balances with air entrainment based on laboratory and field-scale data. These balances assume Gaussian similarity profiles for velocity, density, and concentration within the jet. Ground-level denser-than-air phenomena is treated using a power law concentration distribution profile in the vertical and a hybrid top hat-Gaussian concentration distribution profile in the horizontal. A power law specification is used for the vertical wind profile. Ground-level cloud slumping phenomena and air entrainment are based on laboratory measurements and field-scale observations.

e. Pollutant Types

Neutrally- or negatively-buoyant gases and aerosols. Pollutants are assumed to be non-reactive and non-depositing.

f. Source-Receptor Relationships

Only one source can be modeled at a time.

There is no limitation to the number of receptors; the downwind receptor distances are internally-calculated by the model. The DEGADIS calculation is carried out until the plume centerline concentration is 50% below the lowest concentration level specified by the user.

The model contains no modules for source calculations or release characterization.

g. Plume Behavior

Jet/plume trajectory is estimated from mass and momentum balance equations. Surrounding terrain is assumed to be flat, and stack tip downwash, building wake effects, and fumigation are not treated.

h. Horizontal Winds

Constant logarithmic velocity profile which accounts for stability and surface roughness is used.

The wind speed profile exponent is determined from a least squares fit of the logarithmic profile from ground level to the wind speed reference height. Calm winds can be simulated for ground-level low-momentum releases.

Along-wind dispersion of transient releases is treated using the methods of Colenbrander (1980) and Beals (1971).

i. Vertical Wind Speed

Not treated.

j. Horizontal Dispersion

When the plume centerline is above ground level, horizontal dispersion coefficients are based upon Turner (1969) and Slade (1968) with adjustments made for averaging time and plume density.

When the plume centerline is at ground level, horizontal dispersion also accounts for entrainment due to gravity currents as parameterized from laboratory experiments.

k. Vertical Dispersion

When the plume centerline is above ground level, vertical dispersion coefficients are based upon Turner (1969) and Slade (1968). Perfect ground reflection is applied.

In the ground-level dense-gas regime, vertical dispersion is also based upon results from laboratory experiments in density-stratified fluids.

l. Chemical Transformation

Not specifically treated.

m. Physical Removal

Not treated.

n. Evaluation Studies

Spicer, T.O. and J.A. Havens, 1986. Development of Vapor Dispersion Models for Nonneutrally Buoyant Gas Mixtures—Analysis of USAF/N2O4 Test Data. USAF Engineering and Services Laboratory, Final Report ESL-TR-86-24.

Spicer, T.O. and J.A. Havens, 1988. Development of Vapor Dispersion Models for Nonneutrally Buoyant Gas Mixtures—Analysis of TFI/NH3 Test Data. USAF Engineering and Services Laboratory, Final Report.

o. Operating Information

The model requires either a VAX computer or an IBM®—compatible PC for its execution. The model currently does not require supporting software. A FORTRAN compiler is required to generate program executables in the VAX computing environment. PC executables are provided within the source code; however, a PC FORTRAN compiler may be used to tailor a PC executable to the user's PC environment.

B.3 ERT Visibility Model Reference

ENSR Consulting and Engineering, 1990. ERT Visibility Model: Version 4; Technical Description and User's Guide. Document M2020-003. ENSR Consulting and Engineering, 35 Nagog Park, Acton, MA 01720.

Availability

The user's guide and model code on diskette are available as a package (as PB 96-501978) from the National Technical Information Service (see section B.0).

Abstract

The ERT Visibility Model is a Gaussian dispersion model designed to estimate visibility impairment for arbitrary lines of sight due to isolated point source emissions by simulating gas-to-particle conversion, dry deposition, NO to NO2 conversion and linear radiative transfer.

a. Recommendations for Regulatory Use

There is no specific recommendation at the present time. The ERT Visibility Model may be used on a case-by-case basis.

b. Input Requirements

Source data requirements are: stack height, stack temperature, emissions of SO2, NOX, TSP, fraction of NOX as NO2, fraction of TSP which is carbonaceous, exit velocity, and exit radius.

Meteorological data requirements are: hourly ambient temperature, mixing depth, wind speed at stack height, stability class, potential temperature gradient, and wind direction.

Receptor data requirements are: observer coordinates with respect to source, latitude, longitude, time zone, date, time of day, elevation, relative humidity, background visual range, line-of-sight azimuth and elevation angle, inclination angle of the observed object, distance from observer to object, object and surface reflectivity, number and spacing of integral receptor points along line of sight.

Other data requirements are: ambient concentrations of O3 and NOX, deposition velocity of TSP, sulfate, nitrate, SO2 and NOX, first-order transformation rate for sulfate and nitrate.

c. Output

Printed output includes both summary and detailed results as follows: Summary output: Page 1—site, observer and object parameters; Page 2—optical pollutants and associated extinction coefficients; Page 3—plume model input parameters; Page 4—total calculated visual range reduction, and each pollutant's contribution; Page 5—calculated plume contrast, object contrast and object contrast degradation at the 550nm wavelength; Page 6—calculated blue/red ratio and LE (U*V*W*) values for both sky and object discoloration.

Detailed output: phase functions for each pollutant in four wavelengths (400, 450, 550, 650nm), concentrations for each pollutant along sight path, solar geometry contrast parameters at all wavelengths, intensities, tristimulus values and chromaticity coordinates for views of the object, sun, background sky and plume.

d. Type of Model

ERT Visibility model is a Gaussian plume model for estimating visibility impairment.

e. Pollutant Types

Optical activity of sulfate, nitrate (derived from SO2 and NOX emissions), primary TSP and NO2 is simulated.

f. Source Receptor Relationship

Single source and hour is simulated. Unlimited number of lines-of-sight (receptors) is permitted per model run.

g. Plume Behavior

Briggs (1971) plume rise equations for final rise are used.

h. Horizontal Wind Field

A single wind speed and direction is specified for each case study. The wind is assumed to be spatially uniform.

i. Vertical Wind Speed

Vertical wind speed is assumed equal to zero.

j. Horizontal Dispersion

Rural dispersion coefficients from Turner (1969) are used.

k. Vertical Dispersion

Rural dispersion coefficients from Turner (1969) are used. Mixing height is accounted for with multiple reflection handled by summation of series near the source, and Fourier representation farther downwind.

l. Chemical Transformation

First order transformations of sulfates and nitrates are used.

m. Physical Removal

Dry deposition is treated by the source depletion method.

n. Evaluation Studies

Seigneur, C., R.W. Bergstrom and A.B. Hudischewskyj, 1982. Evaluation of the EPA PLUVUE Model and the ERT Visibility Model Based on the 1979 VISTTA Data Base. EPA Publication No. EPA-450/4-82-008. U.S. Environmental Protection Agency, Research Triangle Park, NC.

White, W.H., C. Seigneur, D.W. Heinold, M.W. Eltgroth, L.W. Richards, P.T. Roberts, P.S. Bhardwaja, W.D. Conner and W.E. Wilson, Jr., 1985. Predicting the Visibility of Chimney Plumes: An Inter-comparison of Four Models with Observations at a Well-Controlled Power Plant. Atmospheric Environment, 19: 515-528.

B.4 HGSYSTEM

(Dispersion Models for Ideal Gases and Hydrogen Fluoride)

Reference

Post, L. (ed.), 1994. HGSYSTEM 3.0 Technical Reference Manual. Shell Research Limited, Thornton Research Centre, Chester, United Kingdom. (TNER 94.059)

Post, L., 1994. HGSYSTEM 3.0 User's Manual. Shell Research Limited, Thornton Research Centre, Chester, United Kingdom. (TNER 94.059)

Availability

The PC-DOS version of the HGSYSTEM software (HGSYSTEM: Version 3.0, Programs for modeling the dispersion of ideal gas and hydrogen fluoride releases, executable programs and source code can be installed from diskettes. These diskettes and all documentation are available as a package from API [[phone]] or from NTIS as PB 96-501960 (see section B.0).

Technical Contacts

Doug N. Blewitt, AMOCO Corporation, 1670 Broadway/MC 2018, Denver, CO, 80201, [phone].

Howard J. Feldman, American Petroleum Institute, 1220 L Street Northwest, Washington, DC 20005, [phone].

Abstract

HGSYSTEM is a PC-based software package consisting of mathematical models for estimating of one or more consecutive phases between spillage and near-field and far-field dispersion of a pollutant. The pollutant can be either a two-phase, multi-compound mixture of non-reactive compounds or hydrogen fluoride (HF) with chemical reactions. The individual models are:

Database program:

DATAPROP Generates physical properties used in other HGSYSTEM models

Source term models:

SPILL Transient liquid release from a pressurized vessel

HFSPILL SPILL version specifically for HF

LPOOL Evaporating multi-compound liquid pool model

Near-field dispersion models:

AEROPLUME High-momentum jet dispersion model

HFPLUME AEROPLUME version specifically for HF

HEGABOX Dispersion of instantaneous heavy gas releases

Far-field dispersion models:

HEGADAS(S,T) Heavy gas dispersion (steady-state and transient version)

PGPLUME Passive Gaussian dispersion

Utility programs:

HFFLASH Flashing of HF from pressurized vessel

POSTHS/POSTHT Post-processing of HEGADAS(S,T) results

PROFILE Post-processor for concentration contours of airborne plumes

GET2COL Utility for data retrieval

The models assume flat, unobstructed terrain. HGSYSTEM can be used to model steady-state, finite-duration, instantaneous and time dependent releases, depending on the individual model used. The models can be run consecutively, with relevant data being passed on from one model to the next using link files. The models can be run in batch mode or using an iterative utility program.

a. Recommendations for Regulatory Use

HGSYSTEM can be used as a refined model to estimate short-term ambient concentrations. For toxic chemical releases (non-reactive chemicals or hydrogen fluoride; 1-hour or less averaging times) the expected area of exposure to concentrations above specified threshold values can be determined. For flammable non-reactive gases it can be used to determine the area in which the cloud may ignite.

b. Input Requirements

HFSPILL input data: reservoir data (temperature, pressure, volume, HF mass, mass-fraction water), pipe-exit diameter and ambient pressure.

EVAP input data: spill rate, liquid properties, and evaporation rate (boiling pool) or ambient data (non-boiling pool).

HFPLUME and PLUME input data: reservoir characteristics, pollutant parameters, pipe/release data, ambient conditions, surface roughness and stability class.

HEGADAS input data: ambient conditions, pollutant parameters, pool data or data at transition point, surface roughness, stability class and averaging time.

PGPLUME input data: link data provided by HFPLUME and the averaging time.

c. Output

The HGSYSTEM models contain three post-processor programs which can be used to extract modeling results for graphical display by external software packages. GET2COL can be used to extract data from the model output files. HSPOST can be used to develop isopleths, extract any 2 parameters for plotting and correct for finite release duration. HTPOST can be used to produce time history plots.

HFSPILL output data: reservoir mass, spill rate, and other reservoir variables as a function of time. For HF liquid, HFSPILL generates link data to HFPLUME for the initial phase of choked liquid flow (flashing jet), and link data to EVAP for the subsequent phase of unchoked liquid flow (evaporating liquid pool).

EVAP output data: pool dimensions, pool evaporation rate, pool mass and other pool variables for steady state conditions or as a function of time. EVAP generates link data to the dispersion model HEGADAS (pool dimensions and pool evaporation rate).

HFPLUME and PLUME output data: plume variables (concentration, width, centroid height, temperature, velocity, etc.) as a function of downwind distance.

HEGADAS output data: concentration variables and temperature as a function of downwind distance and (for transient case) time.

PGPLUME output data: concentration as a function of downwind distance, cross-wind distance and height.

d. Type of Model

HGSYSTEM is made up of four types of dispersion models. HFPLUME and PLUME simulate the near-field dispersion and PGPLUME simulates the passive-gas dispersion downwind of a transition point. HEGADAS simulates the ground-level heavy-gas dispersion.

e. Pollutant Types

HGSYSTEM may be used to model non-reactive chemicals or hydrogen fluoride.

f. Source-Receptor Relationships

HGSYSTEM estimates the expected area of exposure to concentrations above user-specified threshold values. By imposing conservation of mass, momentum and energy the concentration, density, speed and temperature are evaluated as a function of downwind distance.

g. Plume Behavior

HFPLUME and PLUME: (1) are steady-state models assuming a top-hat profile with cross-section averaged plume variables; and (2) the momentum equation is taken into account for horizontal ambient shear, gravity, ground collision, gravity-slumping pressure forces and ground-surface drag.

HEGADAS: assumes the heavy cloud to move with the ambient wind speed, and adopts a power-law fit of the ambient wind speed for the velocity profile.

PGPLUME: simulates the passive-gas dispersion downwind of a transition point from HFPLUME or PLUME for steady-state and finite duration releases.

h. Horizontal Winds

A power law fit of the ambient wind speed is used.

i. Vertical Wind Speed

Not treated.

j. Horizontal Dispersion

HFPLUME and PLUME: Plume dilution is caused by air entrainment resulting from high plume speeds, trailing vortices in wake of falling plume (before touchdown), ambient turbulence and density stratification. Plume dispersion is assumed to be steady and momentum-dominated, and effects of downwind diffusion and wind meander (averaging time) are not taken into account.

HEGADAS: This model adopts a concentration similarity profile expressed in terms of an unknown center-line ground-level concentration and unknown vertical/cross-wind dispersion parameters. These quantities are determined from a number of basic equations describing gas-mass conservation, air entrainment (empirical law describing vertical top-entrainment in terms of global Richardson number), cross-wind gravity spreading (initial gravity spreading followed by gravity-current collapse) and cross-wind diffusion (Briggs formula).

PGPLUME: This model assumes a Gaussian concentration profile in which the cross-wind and vertical dispersion coefficients are determined by empirical expressions. All unknown parameters in this profile are determined by imposing appropriate matching criteria at the transition point.

k. Vertical Dispersion

See description above.

l. Chemical Transformation

Not treated.

m. Physical Removal

Not treated.

n. Evaluation Studies

PLUME has been validated against field data for releases of liquified propane, and wind tunnel data for buoyant and vertically-released dense plumes. HFPLUME and PLUME have been validated against field data for releases of HF (Goldfish experiments) and propane releases. In addition, the plume rise algorithms have been tested against Hoot, Meroney, and Peterka, Ooms and Petersen databases. HEGADAS has been validated against steady and transient releases of liquid propane and LNG over water (Maplin Sands field data), steady and finite-duration pressurized releases of HF (Goldfish experiments; linked with HFPLUME), instantaneous release of Freon (Thorney Island field data; linked with the box model HEGABOX) and wind tunnel data for steady, isothermal dispersion.

Validation studies are contained in the following references.

McFarlane, K., Prothero, A., Puttock, J.S., Roberts, P.T. and H.W.M. Witlox, 1990. Development and validation of atmospheric dispersion models for ideal gases and hydrogen fluoride, Part I: Technical Reference Manual. Report TNER.90.015. Thornton Research Centre, Shell Research, Chester, England. [EGG 1067-1151] (NTIS No. DE 93-000953)

Witlox, H.W.M., McFarlane, K., Rees, F.J. and J.S. Puttock, 1990. Development and validation of atmospheric dispersion models for ideal gases and hydrogen fluoride, Part II: HGSYSTEM Program User's Manual. Report TNER.90.016. Thornton Research Centre, Shell Research, Chester, England. [EGG 1067-1152] (NTIS No. DE 93-000954)

B.5 HOTMAC/RAPTAD Reference

Mellor, G.L. and T. Yamada, 1974. A Hierarchy of Turbulence Closure Models for Planetary Boundary Layers. Journal of Atmospheric Sciences, 31: 1791-1806.

Mellor, G.L. and T. Yamada, 1982. Development of a Turbulence Closure Model for Geophysical Fluid Problems. Rev. Geophys. Space Phys., 20: 851-875.

Yamada, T. and S. Bunker, 1988. Development of a Nested Grid, Second Moment Turbulence Closure Model and Application to the 1982 ASCOT Brush Creek Data Simulation. Journal of Applied Meteorology, 27: 562-578.

Availability

For a cost to be negotiated with the model developer, a 1/4-inch data cartridge or a 4mm DAT tape containing the HOTMAC/RAPTAD computer codes including pre- and post-processors and hard copies of user manuals (User's Manual, Maintenance Manual, Operations Manual, Maintenance Interface Manual, Topo Manual, and 3-Dimensional Plume Manual) are available from YSA Corporation, Rt. 4 Box 81-A, Santa Fe, NM 87501; Phone: [phone]; Fax: [phone]; e-mail: [e-mail]

Abstract

YSA Corporation offers a comprehensive modeling system for environmental studies. The system includes a mesoscale meteorological code, a transport and diffusion code, and extensive Graphical User Interfaces (GUIs). This system is unique because the diffusion code uses time dependent, three-dimensional winds and turbulence distributions that are forecasted by a mesoscale weather prediction model. Consequently the predicted concentration distributions are more accurate than those predicted by traditional models when surface conditions are heterogeneous. In general, the modeled concentration distributions are not Gaussian because winds and turbulence distributions The models were originally developed by using super computers. However, recent advancement of computer hardware has made it possible to run complex three-dimensional meteorological models on desktop workstations. The present versions of the programs are running on super computers and workstations. GUIs are available on Sun Microsystems and Silicon Graphics workstations. The modeling system can also run on a laptop workstation which makes it possible to run the programs in the field or away from the office. As technology continues to advance, a version of HOTMAC/RAPTAD suitable for PC-based platforms will be considered for release by YSA.

HOTMAC, Higher Order Turbulence Model for Atmospheric Circulation, is a mesoscale weather prediction model that forecasts wind, temperature, humidity, and atmospheric turbulence distributions over complex surface conditions. HOTMAC has options to include non-hydrostatic pressure computation, nested grids, land-use distributions, cloud, fog, and precipitation physics. HOTMAC can interface with tower, rawinsonde, and large-scale weather data using a four-dimensional data assimilation method. RAPTAD, Random Puff Transport and Diffusion, is a Lagrangian random puff model that is used to forecast transport and diffusion of airborne materials over complex terrain. Concentrations are computed by summing the concentration of each puff at the receptor location. The random puff method is equivalent to the random particle method with a Gaussian kernel for particle distribution. The advantage of the puff method is the accuracy and speed of computation. The particle method requires the release of a large number of particles which could be computationally expensive. The puff method requires the release of a much less number of puffs, typically 1/10 to 1/100 of the number of particles required by the particle method.

The averaging time for concentration estimates is variable from 5 minutes to 15 minutes for each receptor. In addition to the concentration computation at the receptor sites, RAPTAD computes and graphically displays hourly concentration contours at the ground level. RAPTAD is applicable to point and area sources.

The meteorological data produced from HOTMAC are used as input to RAPTAD. RAPTAD can forecast concentration distributions for neutrally buoyant gas, buoyant gas and denser-than-air gas. The models are significantly advanced in both their model physics and in their operational procedures. GUIs are provided to help the user prepare input files, run programs, and display the modeled results graphically in three dimensions.

a. Recommendation for Regulatory Use

There are no specific recommendations at the present time. The HOTMAC/RAPTAD modeling system may be used on a case-by-case basis.

b. Input Requirements

Meteorological Data: The modeling system is significantly different from the majority of regulatory models in terms of how meteorological data are provided and used in concentration simulations. Regulatory models use the wind data which are obtained directly from measurements or analyzed by using a simple constraint such as a mass conservation equation. Thus, the accuracy of the computation will depend significantly on the quantity and quality of the wind data. This approach is acceptable as long as the study area is flat and the simulation period is short. As the regulations become more stringent and more realistic surface conditions are required, a significantly large volume of meteorological data is required which could become very expensive.

An alternative approach is to augment the measurements with predicted values from a mesoscale meteorological model. This is the approach we have taken here. This approach has several advantages over the conventional method. First, concentration computations use the model forecast wind while the conventional method extrapolates the observed winds. Extrapolation of wind data over complex terrain and for an extended period of time quickly loses its accuracy. Secondly, the number of stations for upper air soundings is typically limited from none to at most a few stations in the study area. The corresponding number in a mesoscale model is the number of grid points in the horizontal plane which is typically 50 X 50. Consequently, concentration distributions using model forecasted winds would be much more accurate than those obtained by using winds which were extrapolated from the limited number of measurements.

HOTMAC requires meteorological data for initialization and to provide boundary conditions if the boundary conditions change significantly with time. The minimum amount of data required to run HOTMAC is wind and potential temperature profiles at a single station. HOTMAC forecasts wind and turbulence distributions in the boundary layer through a set of model equations for solar radiation, heat energy balance at the ground, conservation of momentum, conservation of internal energy, and conservation of mass.

Terrain Data: HOTMAC and RAPTAD use the digitized terrain data from the U.S. Geological Survey and the Defense Mapping Agency. Extraction of terrain data is greatly simplified by using YSA's GUI software called Topo. The user specifies the latitudes and longitudes of the southwest and northeast corner points of the study area. Then, Topo extracts the digitized elevation data within the area specified and converts from the latitudes and longitudes to the UTM (Universal Transverse Mercator) coordinates for up to three nested grids.

Emission Data: Emission data requirements are emission rate, stack height, stack diameter, stack location, stack gas exit velocity, and stack buoyancy.

Receptor Data: Receptor data requirements are names, location coordinates, and desired averaging time for concentration estimates, which is variable from 5 to 15 minutes.

c. Output

HOTMAC outputs include hourly winds, temperatures, and turbulence variables at every grid point. Ancillary codes graphically display vertical profiles of wind, temperature, and turbulence variables at selected locations and wind vector distributions at specified heights above the ground. These codes also produce graphic files of wind direction projected on vertical cross sections.

RAPTAD outputs include hourly values of surface concentration, time variations of mean and standard deviation of concentrations at selected locations, and coordinates of puff center locations. Ancillary codes produce color contour plots of surface concentration, time variations of mean concentrations and ratios of standard deviation to mean value at selected locations, and concentration distributions in the vertical cross sections. The averaging time of concentration at a receptor location is variable from 5 to 15 minutes. Color contour plots of surface concentration can be animated on the monitor to review time variations of high concentration areas.

d. Type of Model

HOTMAC is a 3-dimensional Eulerian model for weather forecasting, and RAPTAD is a 3-dimensional Lagrangian random puff model for pollutant transport and diffusion.

e. Pollutant types

RAPTAD may be used to model any inert pollutants, including dense and buoyant gases.

f. Source-Receptor Relationship

Up to six point or area sources are specified and up to 50 sampling locations are selected. Source and receptor heights are specified by the user.

g. Plume Behavior

Neutrally buoyant plumes are transported by mean and turbulence winds that are modeled by HOTMAC. Non-neutrally buoyant plume equations are based on Van Dop (1992). In general, plumes are non-Gaussian.

h. Horizontal Winds

RAPTAD uses wind speed, wind direction, and turbulence on a gridded array that is supplied hourly by HOTMAC. Stability effect and mixed layer height are incorporated through the intensity of turbulence which is a function of stability. HOTMAC predicts turbulence intensity by solving a turbulence kinetic energy equation and a length scale equation. RAPTAD interpolates winds and turbulence at puff center locations every 10 seconds from the values on a gridded array. RAPTAD can also use the winds observed at towers and by rawinsondes.

i. Vertical Wind Speed

RAPTAD uses vertical winds on a gridded array that are supplied hourly by HOTMAC. HOTMAC computes vertical wind either by solving an equation of motion for the vertical wind or a mass conservation equation. RAPTAD interpolates vertical winds at puff center locations every 10 seconds from the values on a gridded array.

j. Horizontal Dispersion

Horizontal dispersion is based on the standard deviations of horizontal winds that are computed by HOTMAC.

k. Vertical Dispersion

Vertical dispersion is based on the standard deviations of vertical wind that are computed by HOTMAC.

l. Chemical Transformation

HOTMAC can provide meteorological inputs to other models that handle chemical reactions, e.g., UAM.

m. Physical Removal

Not treated.

n. Evaluation Studies

Yamada, T., S. Bunker and M. Moss, 1992. A Numerical Simulation of Atmospheric Transport and Diffusion over Coastal Complex Terrain. Journal of Applied Meteorology, 31: 565-578.

Yamada, T. and T. Henmi, 1994. HOTMAC: Model Performance Evaluation by Using Project WIND Phase I and II Data. Mesoscale Modeling of the Atmosphere, American Meteorological Society, Monograph 47, pp. 123-135.

B.6 LONGZ Reference

Bjorklund, J.R. and J.F. Bowers, 1982. User's Instructions for the SHORTZ and LONGZ Computer Programs, Volumes I and II, EPA Publication No. EPA-903/9-82-004. U.S. Environmental Protection Agency, Region III, Philadelphia, PA.

Availability

The computer code is available on the Support Center for Regulatory Air Models Bulletin Board System and on diskette (as PB 96-501994) from the National Technical Information Service (see section B.0).

Abstract

LONGZ utilizes the steady-state univariate Gaussian plume formulation for both urban and rural areas in flat or complex terrain to calculate long-term (seasonal and/or annual) ground-level ambient air concentrations attributable to emissions from up to 14,000 arbitrarily placed sources (stacks, buildings and area sources). The output consists of the total concentration at each receptor due to emissions from each user-specified source or group of sources, including all sources. An option which considers losses due to deposition (see the description of SHORTZ) is deemed inappropriate by the authors for complex terrain, and is not discussed here.

a. Recommendations for Regulatory Use

LONGZ can be used if it can be demonstrated to estimate concentrations equivalent to those provided by the preferred model for a given application. LONGZ must be executed in the equivalent mode.

LONGZ can be used on a case-by-case basis in lieu of a preferred model if it can be demonstrated, using the criteria in section 3.2 of appendix W, that LONGZ is more appropriate for the specific application. In this case the model options/modes which are most appropriate for the application should be used.

b. Input Requirements

Source data requirements are: for point, building or area sources, location, elevation, total emission rate (optionally classified by gravitational settling velocity) and decay coefficient; for stack sources, stack height, effluent temperature, effluent exit velocity, stack radius (inner), emission rate, and ground elevation (optional); for building sources, height, length and width, and orientation; for area sources, characteristic vertical dimension, and length, width and orientation.

Meteorological data requirements are: wind speed and measurement height, wind profile exponents, wind direction standard deviations (turbulent intensities), mixing height, air temperature, vertical potential temperature gradient.

Receptor data requirements are: coordinates, ground elevation.

c. Output

Printed output includes total concentration due to emissions from user-specified source groups, including the combined emissions from all sources (with optional allowance for depletion by deposition).

d. Type of Model

LONGZ is a climatological Gaussian plume model.

e. Pollutant Types

LONGZ may be used to model primary pollutants. Settling and deposition are treated.

f. Source-Receptor Relationships

LONGZ applies user specified locations for sources and receptors. Receptors are assumed to be at ground level.

g. Plume Behavior

Plume rise equations of Bjorklund and Bowers (1982) are used.

Stack tip downwash (Bjorklund and Bowers, 1982) is included.

All plumes move horizontally and will fully intercept elevated terrain.

Plumes above mixing height are ignored.

Perfect reflection at mixing height is assumed for plumes below the mixing height.

Plume rise is limited when the mean wind at stack height approaches or exceeds stack exit velocity.

Perfect reflection at ground is assumed for pollutants with no settling velocity.

Zero reflection at ground is assumed for pollutants with finite settling velocity.

LONGZ does not simulate fumigation.

Tilted plume is used for pollutants with settling velocity specified.

Buoyancy-induced dispersion is treated (Briggs, 1972).

h. Horizontal Winds

Wind field is homogeneous and steady-state.

Wind speed profile exponents are functions of both stability class and wind speed. Default values are specified in Bjorklund and Bowers (1982).

i. Vertical Wind Speed

Vertical wind speed is assumed equal to zero.

j. Horizontal Dispersion

Pollutants are initially uniformly distributed within each wind direction sector. A smoothing function is then used to remove discontinuities at sector boundaries.

k. Vertical Dispersion

Vertical dispersion is derived from input vertical turbulent intensities using adjustments to plume height and rate of plume growth with downwind distance specified in Bjorklund and Bowers (1982).

l. Chemical Transformation

Chemical transformations are treated using exponential decay. Time constant is input by the user.

m. Physical Removal

Gravitational settling and dry deposition of particulates are treated.

n. Evaluation Studies

Bjorklund, J.R. and J.F. Bowers, 1982. User's Instructions for the SHORTZ and LONGZ Computer Programs, Volume I and II. EPA Publication No. EPA-903/9-82-004. U.S. Environmental Protection Agency, Region III, Philadelphia, PA.

B.7 Maryland Power Plant Siting Program (PPSP) Model Reference

Brower, R., 1982. The Maryland Power Plant Siting Program (PPSP) Air Quality Model User's Guide. Ref. No. PPSP-MP-38. Prepared for Maryland Department of Natural Resources by Environmental Center, Martin Marietta Corporation, Baltimore, MD. (NTIS No. PB 82-238387)

Weil, J.C. and R.P. Brower, 1982. The Maryland PPSP Dispersion Model for Tall Stacks. Ref. No. PPSP-MP-36. Prepared for Maryland Department of Natural Resources by Environmental Center, Martin Marietta Corporation, Baltimore, MD. (NTIS No. PB 82-219155)

Availability

The model code and test data are available on diskette for a nominal cost to defray shipping and handling charges from: Mr. Roger Brower, Versar, Inc., 9200 Rumsey Road, Columbia, MD 21045; Phone: [phone].

Abstract

PPSP is a Gaussian dispersion model applicable to tall stacks in either rural or urban areas, but in terrain that is essentially flat (on a scale large compared to the ground roughness elements). The PPSP model follows the same general formulation and computer coding as CRSTER, also a Gaussian model, but it differs in four major ways. The differences are in the scientific formulation of specific ingredients or “sub-models” to the Gaussian model, and are based on recent theoretical improvements as well as supporting experimental data. The differences are: (1) stability during daytime is based on convective scaling instead of the Turner criteria; (2) Briggs' dispersion curves for elevated sources are used; (3) Briggs plume rise formulas for convective conditions are included; and (4) plume penetration of elevated stable layers is given by Briggs' (1984) model.

a. Recommendations for Regulatory Use

PPSP can be used if it can be demonstrated to estimate concentrations equivalent to those provided by the preferred model for a given application. PPSP must be executed in the equivalent mode.

PPSP can be used on a case-by-case basis in lieu of a preferred model if it can be demonstrated, using the criteria in section 3.2 of appendix W, that PPSP is more appropriate for the specific application. In this case the model options/modes which are most appropriate for the application should be used.

b. Input Requirements

Source data requirements are: emission rate (monthly rates optional), physical stack height, stack gas exit velocity, stack inside diameter, stack gas temperature.

Meteorological data requirements are: hourly surface weather data from the EPA meteorological preprocessor program. Preprocessor output includes hourly stability class, wind direction, wind speed, temperature, and mixing height. Actual anemometer height (a single value) is also required. Wind speed profile exponents (one for each stability class) are required if on-site data are input.

Receptor data requirements are: distance of each of the five receptor rings.

c. Output

Printed output includes:

Highest and second highest concentrations for the year at each receptor for averaging times of 1, 3, and 24-hours, plus a user-selected averaging time which may be 2, 4, 6, 8, or 12 hours;

Annual arithmetic average at each receptor; and

For each day, the highest 1-hour and 24-hour concentrations over the receptor field.

d. Type of Model

PPSP is a Gaussian plume model.

e. Pollutant Types

PPSP may be used to model primary pollutants. Settling and deposition are not treated.

f. Source-Receptor Relationship

Up to 19 point sources are treated.

All point sources are assumed at the same location.

Unique stack height and stack exit conditions are applied for each source.

Receptor locations are restricted to 36 azimuths (every 10 degrees) and five user-specified radial distances.

g. Plume Behavior

Briggs (1975) final rise formulas for buoyant plumes are used. Momentum rise is not considered.

Transitional or distance-dependent plume rise is not modeled.

Penetration (complete, partial, or zero) of elevated inversions is treated with Briggs (1984) model; ground-level concentrations are dependent on degree of plume penetration.

h. Horizontal Winds

Wind speeds are corrected for release height based on power law variation, with different exponents for different stability classes and variable reference height (7 meters is default). Wind speed power law exponents are 0.10, 0.15, 0.20, 0.25, 0.30, and 0.30 for stability classes A through F, respectively.

Constant, uniform (steady-state) wind assumed within each hour.

i. Vertical Wind Speed

Vertical wind speed is assumed equal to zero.

j. Horizontal Dispersion

Rural dispersion parameters are Briggs (Gifford, 1975), with stability class defined by u/w* during daytime, and by the method of Turner (1964) at night.

Urban dispersion is treated by changing all stable cases to stability class D.

Buoyancy-induced dispersion (Pasquill, 1976) is included (using DH/3.5).

k. Vertical Dispersion

Rural dispersion parameters are Briggs (Gifford, 1975), with stability class defined by u/w* during daytime, and by the method of Turner (1964).

Urban dispersion is treated by changing all stable cases to stability class D.

Buoyancy-induced dispersion (Pasquill, 1976) is included (using DH/3.5).

l. Chemical Transformation

Not treated.

m. Physical Removal

Not treated.

n. Evaluation Studies

Londergan, R., D. Minott, D. Wackter, T. Kincaid and D. Bonitata, 1983. Evaluation of Rural Air Quality Simulation Models, Appendix G: Statistical Tables for PPSP. EPA Publication No. EPA-450/4-83-003. Environmental Protection Agency, Research Triangle Park, NC.

Weil, J.C. and R.P. Brower, 1982. The Maryland PPSP dispersion model for tall stacks. Ref. No. PPSP MP-36. Prepared for Maryland Department of Natural Resources. Prepared by Environmental Center, Martin Marietta Corporation, Baltimore, Maryland. (NTIS No. PB 82-219155)

B.8 Mesoscale Puff Model (MESOPUFF II) Reference

Scire, J.S., F.W. Lurmann, A. Bass and S.R. Hanna, 1984. User's Guide to the Mesopuff II Model and Related Processor Programs. EPA Publication No. EPA-600/8-84-013. U.S. Environmental Protection Agency, Research Triangle Park, NC. (NTIS No. PB 84-181775)

A Modeling Protocol for Applying MESOPUFF II to Long Range Transport Problems, 1992. EPA Publication No. EPA-454/R-92-021. U.S. Environmental Protection Agency, Research Triangle Park, NC.

Availability

This model code is available on the Support Center for Regulatory Air Models Bulletin Board System and also on diskette (as PB 93-500247) from the National Technical Information Service (see section B.0).

Abstract

MESOPUFF II is a short term, regional scale puff model designed to calculate concentrations of up to 5 pollutant species (SO2, SO4, NOX, HNO3, NO3). Transport, puff growth, chemical transformation, and wet and dry deposition are accounted for in the model.

a. Recommendations for Regulatory Use

There is no specific recommendation at the present time. The model may be used on a case-by-case basis.

b. Input Requirements

Required input data include four types: (1) input control parameters and selected technical options, (2) hourly surface meteorological data and twice daily upper air measurements, hourly precipitation data are optional, (3) surface land use classification information, (4) source and emissions data.

Data from up to 25 surface National Weather Service stations and up to 10 upper air stations may be considered. Spatially variable fields at hour intervals of winds, mixing height, stability class, and relevant turbulence parameters are derived by MESOPAC II, the meteorological preprocessor program described in the User Guide.

Source and emission data for up to 25 point sources and/or up to 5 area sources can be included. Required information are: location in grid coordinates, stack height, exit velocity and temperature, and emission rates for the pollutant to be modeled.

Receptor data requirements: up to a 40×40 grid may be used and non-gridded receptor locations may be considered.

c. Output

Line printer output includes: all input parameters, optionally selected arrays of ground-level concentrations of pollutant species at specified time intervals.

Line printer contour plots output from MESOFILE II post-processor program. Computer readable output of concentration array to disk/tape for each hour.

d. Type of Model

MESOPUFF II is a Gaussian puff superposition model.

e. Pollutant Types

Up to five pollutant species may be modeled simultaneously and include: SO2, SO4, NOX, HNO3, NO3.

f. Source-Receptor Relationship

Up to 25 point sources and/or up to 5 area sources are permitted.

g. Plume Behavior

Briggs (1975) plume rise equations are used, including plume penetration with buoyancy flux computed in the model.

Fumigation of puffs is considered and may produce immediate mixing or multiple reflection calculations at user option.

h. Horizontal Winds

Gridded wind fields are computed for 2 layers; boundary layer and above the mixed layer. Upper air rawinsonde data and hourly surface winds are used to obtain spatially variable u,v component fields at hourly intervals. The gridded fields are computed by interpolation between stations in the MESOPAC II preprocessor.

i. Vertical Wind Speed

Vertical winds are assumed to be zero.

j. Horizontal Dispersion

Incremental puff growth is computed over discrete time steps with horizontal growth parameters determined from power law equations fit to sigma y curves of Turner out to 100km. At distances greater than 100km, puff growth is determined by the rate given by Heffter (1965).

Puff growth is a function of stability class and changes in stability are treated. Optionally, user input plume growth coefficients may be considered.

k. Vertical Dispersion

For puffs emitted at an effective stack height which is less than the mixing height, uniform mixing of the pollutant within the mixed layer is performed. For puffs centered above the mixing height, no effect at the ground occurs.

l. Chemical Transformation

Hourly chemical rate constants are computed from empirical expressions derived from photochemical model simulations.

m. Physical Removal

Dry deposition is treated with a resistance method.

Wet removal may be considered if hourly precipitation data are input.

n. Evaluation Studies

Results of tests for some model parameters are discussed in:

Scire, J.S., F.W. Lurmann, A. Bass and S.R. Hanna, 1984. Development of the MESOPUFF II Dispersion Model. EPA Publication No. EPA-600/3-84-057. U.S. Environmental Protection Agency, Research Triangle Park, NC.

B.9 Mesoscale Transport Diffusion and Deposition Model for Industrial Sources (MTDDIS) Reference

Wang, I.T. and T.L. Waldron, 1980. User's Guide for MTDDIS Mesoscale Transport, Diffusion, and Deposition Model for Industrial Sources. EMSC6062.1UR(R2). Combustion Engineering, Newbury Park, CA.

Availability

A diskette copy of the FORTRAN coding and the user's guide are available for a cost of $100 from: Dr. I. T. Wang, Environmental Modeling & Analysis, 2219 E. Thousand Oaks Blvd., Suite 435, Thousand Oaks, CA 91362.

Abstract

MTDDIS is a variable-trajectory Gaussian puff model applicable to long-range transport of point source emissions over level or rolling terrain. The model can be used to determine 3-hour maximum and 24-hour average concentrations of relatively nonreactive pollutants from up to 10 separate stacks.

a. Recommendations for Regulatory Use

There is no specific recommendation at the present time. The MTDDIS Model may be used on a case-by-case basis.

b. Input Requirements

Source data requirements are: emission rate, physical stack height, stack gas exit velocity, stack inside diameter, stack gas temperature, and location.

Meteorological data requirements are: hourly surface weather data, from up to 10 stations, including cloud ceiling, wind direction, wind speed, temperature, opaque cloud cover and precipitation. For long-range applications, user-analyzed daily mixing heights are recommended. If these are not available, the NWS daily mixing heights will be used by the program. A single upper air sounding station for the region is assumed. For each model run, air trajectories are generated for a 48-hour period, and therefore, the afternoon mixing height of the day before and the mixing heights of the day after are also required by the model as input, in order to generate hourly mixing heights for the modeled period.

Receptor data requirements are: up to three user-specified rectangular grids.

c. Output

Printed output includes:

Tabulations of hourly meteorological parameters include both input surface observations and calculated hourly stability classes and mixing heights for each station;

Printed air trajectories for the two consecutive 24-hour periods for air parcels generated 4 hours apart starting at 0000 LST; and

3-hour maximum and 24-hour average grid concentrations over user-specified rectangular grids are output for the second 24-hour period.

d. Type of Model

MTDDIS is a Gaussian puff model.

e. Pollutant Types

MTDDIS can be used to model primary pollutants. Dry deposition is treated. Exponential decay can account for some reactions.

f. Source-Receptor Relationship

MTDDIS treats up to 10 point sources.

Up to three rectangular receptor grids may be specified by the user.

g. Plume Behavior

Briggs (1971, 1972) plume rise formulas are used.

If plume height exceeds mixing height, ground level concentration is assumed zero.

Fumigation and downwash are not treated.

h. Horizontal Winds

Wind speeds and wind directions at each station are first corrected for release height. Speed conversions are based on power law variation and direction conversions are based on linear height dependence as recommended by Irwin (1979b).

Converted wind speeds and wind directions are then weighted according to the algorithms of Heffter (1980) to calculate the effective transport wind speed and direction.

i. Vertical Wind Field

Vertical wind speed is assumed equal to zero.

j. Horizontal Dispersion

Transport-time-dependent dispersion coefficients from Heffter (1980) are used.

k. Vertical Dispersion

Transport-time-dependent dispersion coefficients from Heffter (1980) are used.

l. Chemical Transformation

Chemical transformations are treated using exponential decay. Half-life is input by the user.

m. Physical Removal

Dry deposition is treated. User input deposition velocity is required.

Wet deposition is treated. User input hourly precipitation rate and precipitation layer depth or cloud ceiling height are required.

n. Evaluation Studies

Carhart, R.A., A.J. Policastro, M. Wastag and L. Coke, 1989. Evaluation of Eight Short-Term Long-Range Transport Models Using Field Data. Atmospheric Environment, 23: 85-105.

B.10 Multi-Source (SCSTER) Model Reference

Malik, M.H. and B. Baldwin, 1980. Program Documentation for Multi-Source (SCSTER) Model. Program Documentation EN7408SS. Southern Company Services, Inc., Technical Engineering Systems, 64 Perimeter Center East, Atlanta, GA.

Availability

The SCSTER model and user's manual are available at no charge on a limited basis through Southern Company Services. The computer code may be provided on a diskette. Requests should be directed to: Mr. Stanley S. Vasa, Senior Environmental Specialist, Southern Company Services, P.O. Box 2625, Birmingham, AL 35202.

Abstract

SCSTER is a modified version of the EPA CRSTER model. The primary distinctions of SCSTER are its capability to consider multiple sources that are not necessarily collocated, its enhanced receptor specifications, its variable plume height terrain adjustment procedures and plume distortion from directional wind shear.

a. Recommendations for Regulatory Use

SCSTER can be used if it can be demonstrated to estimate concentrations equivalent to those provided by the preferred model for a given application. SCSTER must be executed in the equivalent mode.

SCSTER can be used on a case-by-case basis in lieu of a preferred model if it can be demonstrated, using the criteria in section 3.2 of appendix W, that SCSTER is more appropriate for the specific application. In this case the model options/modes which are most appropriate for the application should be used.

b. Input Requirements

Source data requirements are: emission rate, stack gas exit velocity, stack gas temperature, stack exit diameter, physical stack height, elevation of stack base, and coordinates of stack location. The variable emission data can be monthly or annual averages.

Meteorological data requirements are: hourly surface weather data from the EPA meteorological preprocessor program. Preprocessor output includes hourly stability class wind direction, wind speed, temperature, and mixing height. Actual anemometer height (a single value) is optional. Wind speed profile exponents (one for each stability class) are optional.

Receptor data requirements are: cartesian coordinates and elevations of individual receptors; distances of receptor rings, with elevation of each receptor; receptor grid networks, with elevation of each receptor.

Any combination of the three receptor input types may be used to consider up to 600 receptor locations.

c. Output

Printed output includes:

Highest and second highest concentrations for the year at each receptor for averaging times of 1-, 3-, and 24-hours, a user-selected averaging time which may be 2-12 hours, and a 50 high table for 1-, 3-, and 24-hours;

Annual arithmetic average at each receptor; and the highest 1-hour and 24-hour concentrations over the receptor field for each day considered.

Optional tables of source contributions of individual point sources at up to 20 receptor locations for each averaging period;

Optional magnetic tape output in either binary or fixed block format includes:

All 1-hour concentrations.

Optional card/disk output includes for each receptor:

Receptor coordinates; receptor elevation; highest and highest, second-highest, 1-, 3-, and 24-hour concentrations; and annual average concentration.

d. Type of Model

SCSTER is a Gaussian plume model.

e. Pollutant Types

SCSTER may be used to model primary pollutants. Settling and deposition are not treated.

f. Source-Receptor Relationship

SCSTER can handle up to 60 separate stacks at varying locations and up to 600 receptors, including up to 15 receptor rings.

User input topographic elevation for each receptor is used.

g. Plume Behavior

SCSTER uses Briggs (1969, 1971, 1972) final plume rise formulas.

Transitional plume rise is optional.

SCSTER contains options to incorporate wind directional shear with a plume distortion method described in appendix A of the User's Guide.

SCSTER provides four terrain adjustments including the CRSTER full terrain height adjustment and a user-input, stability-dependent plume path coefficient adjustment for receptors above stack height.

h. Horizontal Winds

Wind speeds are corrected for release height based on power law exponents from DeMarrais (1959), different exponents for different stability classes; default reference height of 7m. Default exponents are 0.10, 0.15, 0.20, 0.25, 0.30, and 0.30 for stability classes A through F, respectively.

Steady-state wind is assumed within a given hour.

Optional consideration of plume distortion due to user-input, stability-dependent wind-direction shear gradients.

i. Vertical Wind Speed

Vertical wind speed is assumed equal to zero.

j. Horizontal Dispersion

Rural dispersion coefficients from Turner (1969) are used.

Six stability classes are used.

k. Vertical Dispersion

Rural dispersion coefficients from Turner (1969) are used.

Six stability classes are used.

An optional test for plume height above mixing height before terrain adjustment is included.

l. Chemical Transformation

Chemical transformations are treated using exponential decay. Half-life is input by the user.

m. Physical Removal

Physical removal is treated using exponential decay. Half-life is input by the user.

n. Evaluation Studies

Londergan, R., D. Minott, D. Wackter, T. Kincaid and D. Bonitata, 1983. Evaluation of Rural Air Quality Simulation Models. EPA Publication No. EPA-450/4-83-003. U.S. Environmental Protection Agency, Research Triangle Park, NC.

B.11 PANACHE Reference

Transoft Group, 1994. User's Guide of Fluidyn-PANACHE, a Three-Dimensional Deterministic Simulation of Pollutants Dispersion Model for Complex Terrain; Cary, North Carolina.

Availability

For a cost to be negotiated with the model developer, the computer code is available from: Transoft US, Inc., 818 Reedy Creek Road, Cary, NC 27513-3307; Phone: [phone], Fax: [phone].

Abstract

PANACHE is an Eulerian (and Lagrangian for particulate matter), 3-dimensional finite volume fluid mechanics code designed to simulate continuous and short-term pollution dispersion in the atmosphere, in simple or complex terrain. For single or multiple sources, pollutant emissions from stack, point, area, volume, general sources and distant sources are treated. The model automatically treats obstacles, effects of vegetation and water bodies, the effects of vertical temperature stratification on the wind and diffusion fields, and turbulent shear flows caused by atmospheric boundary layer or terrain effects. The code solves Navier Stokes equations in a curvilinear mesh espousing the terrain and obstacles. A 2nd order resolution helps keep the number of cells limited in case of shearing flow. An initial wind field is computed by using a Lagrangian multiplier to interpolate wind data collected on site. The mesh generator, the solver and the numerical schemes have been adopted for atmospheric flows with or without chemical reactions. The model code operates on any workstation or IBM—compatible PC (486 or higher). Gaussian and puff modes are available in PANACHE for fast, preliminary simulation.

a. Recommendations for Regulatory Use

On a case-by-case basis, PANACHE may be appropriate for the following types of situations: industrial or urban zone on a flat or complex terrain, transport distance from a few meters to 50km, continuous releases with hourly, monthly or annual averaging times, chemically reactive or non-reactive gases or particulate emissions for stationary or roadway sources.

b. Input Requirements

Data may be input directly from an external source (e.g., GIS file) or interactively. The model provides the option to use default values when input parameters are unavailable.

PANACHE user environment integrates the pre- and post-processor with the solver. The calculations can be done interactively or in batch mode. An inverse scheme is provided to estimate missing data from a few measured values of the wind.

Terrain data requirements:

• Location, surface roughness estimates, and altitude contours.

• Location and dimensions of obstacles, forests, fields, and water bodies.

Source data requirements:

For all types of sources, the exit temperature and plume mass flow rates and concentration of each of the pollutants are required. External sources require mass flow rate. For roadways, estimated traffic volume and vehicular emissions are required.

Meteorological data requirements:

Hourly stability class, wind direction, wind speed, temperature, cloud cover, humidity, and mixing height data with lapse rate below and above it.

Primary meteorological variables available from the National Weather Service can be processed using PCRAMMET (see section 9.3.3.2 of appendix W) to an input file.

Data required at the domain boundary:

Wind profile (uniform, log or power law), depending on the terrain conditions (e.g., residential area, forest, sea, etc.).

Chemical source data requirements:

A database of selected species with specific heats and molecular weights can be extended by the user. For heavy gases the database includes a compressibility coefficients table.

Solar reflection:

For natural convection simulation with low wind on a sunny day, approximate values of temperature for fields, forests, water bodies, shadows and their variations with the time of the day are determined automatically.

c. Output

Printed output option: pollutant concentration at receptor points, and listing of input data (terrain, chemical, weather, and source data) with turbulence and precision control data.

Graphical output includes: In 3-dimensional perspective or in any crosswind, downwind or horizontal plane: wind velocity, pollutant concentration, 3-dimensional isosurface. The profile of concentration can be obtained along any line on the terrain. The concentration contours can be either instantaneous or time integrated for the emission from a source or a source combination. A special utility is included to help prepare a report or a video animation. The user can select images, put in annotations, or do animation.

d. Type of Model

The model uses an Eulerian (and Lagrangian for particulate matter) 3-dimensional finite volume model solving full Navier-Stokes equations. The numerical diffusion is low with appropriate turbulence models for building wakes. A second order resolution may be sought to limit the diffusion. Gaussian and puff modes are available. The numerical scheme is self adaptive for the following situations:

• A curvilinear mesh or a chopped Cartesian mesh is generated automatically or manually;

• Thermal and gravity effects are simulated by full gravity (heavy gases), no gravity (well mixed light gases at ambient temperature), and Boussinesq approximation methods;

• K-diff, K-e or a boundary layer turbulence models are used for turbulence calculations. The flow behind obstacles such as buildings, is calculated by using a modified K-e.

• For heavy gases, a 3-dimensional heat conduction from the ground and a stratification model for heat exchange from the atmosphere are used (with anisotropic turbulence).

• If local wind data are available, an initial wind field with terrain effects can be computed using a Lagrangian multiplier, which substantially reduces computation time.

e. Pollutant Types

• Scavenging, Acid Rain: A module for water droplets traveling through a plume considers the absorption and de-absorption effects of the pollutants by the droplet. Evaporation and chemical reactions with gases are also taken into account.

• Visibility: Predicts plume visibility and surface deposition of aerosol.

• Particulate matter: Calculates settling and dry deposition of particles based on a Probability Density Function (PDF) of their diameters. The exchange of mass, momentum and heat between particles and gas is treated with implicit coupling procedures.

• Ozone formation and dispersion: The photochemical model computes ozone formation and dispersion at street level in the presence of sunlight.

• Roadway Pollutants: Accounts for heat and turbulence due to vehicular movement. Emissions are based on traffic volume and emission factors.

• Odor Dispersion: Identifies odor sources for waste water plants.

• Radon Dispersion: Simulates natural radon accumulation in valleys and mine environments.

PANACHE may also be used in emergency planning and management for episodic emissions, and fire and soot spread in forested and urban areas or from combustible pools.

f. Source-Receptor Relationship

Simultaneous use of multiple kinds of sources at user defined locations. Any number of user defined receptors can identify pollutants from each source individually.

g. Plume Behavior

The options influencing the behavior are full gravity, Boussinesq approximation or no gravity.

h. Horizontal Winds

Horizontal wind speed approximations are made only at the boundaries based on National Weather Service data. Inside the domain of interest, full Navier-Stokes resolution with natural viscosity is used for 3-dimensional terrain and temperature dependent wind field calculation.

i. Vertical Wind Speed

Vertical wind speed approximations are made only at the boundaries based on National Weather Service data. The domain of interest is treated as for horizontal winds.

j. Horizontal Dispersion

Diffusion is calculated using appropriate turbulence models. A 2nd order solution for shearing flow can be sought when the number of meshes is limited between obstacles.

k. Vertical Dispersion

Dispersion by full gravity unless Boussinesq approximation or no gravity requested. Vertical dispersion is treated as above for horizontal dispersion.

l. Chemical Transformation

PANCHEM, an atmospheric chemistry module for chemical reactions, is available. Photochemical reactions are used for tropospheric ozone calculations.

m. Physical Removal

Physical removal is treated using dry deposition coefficients

n. Evaluation Studies

Goldwire, H.C. Jr, T.G. McRae, G.W. Johnson, D.L. Hipple, R.P. Koopman, J.W. McClure, L.K. Morris and R.T. Cederhall, 1985. Desert Tortoise Series Data Report: 1983 Pressurized Ammonia Spills. UCID 20562, Lawrence Livermore National Laboratory; Livermore, California.

Green, S.R., 1992. Modeling Turbulent Air Flow in a Stand of Widely Spaced Trees, The PHOENICS Journal of Computational Fluid Dynamics and Its Applications, 5: 294-312.

Gryning, S.E. and E. Lyck, 1984. Atmospheric Dispersion from Elevated Sources in an Urban Area: Comparison Between Tracer Experiments and Model Calculations. Journal of Climate and Applied Meteorology, 23: 651-660.

Havens, J., T. Spicer, H. Walker and T. Williams, 1995. Validation of Mathematical Models Using Wind-Tunnel Data Sets for Dense Gas Dispersion in the Presence of Obstacles. University of Arkansas, 8th International Symposium-Loss Prevention and Safety Promotion in the Process Industries; Antwerp, Belgium.

McQuaid, J. (ed), 1985. Heavy Gas Dispersion Trials at Thorney Island. Proc. of a Symposium held at the University of Sheffield, Great Britain.

Pavitskiy, N.Y., A.A. Yakuskin and S.V. Zhubrin, 1993. Vehicular Exhaust Dispersion Around Group of Buildings. The PHOENICS Journal of Computational Fluid Dynamics and Its Applications, 6: 270-285.

Tripathi, S., 1994. Evaluation of Fluidyn-PANACHE on Heavy Gas Dispersion Test Case. Seminar on Evaluation of Models of Heavy Gas Dispersion Organized by European Commission; Mol, Belgium.

B.12 Plume Visibility Model (PLUVUE II) Reference

Environmental Protection Agency, 1992. User's Manual for the Plume Visibility Model, PLUVUE II (Revised). EPA Publication No. EPA-454/B-92-008, (NTIS PB93-188233). U.S. Environmental Protection Agency, Research Triangle Park, NC.

Availability

This model code is available on the Support Center for Regulatory Air Models Bulletin Board System and also on diskette (as PB 90-500778) from the National Technical Information Service (see section B.0).

Abstract

The Plume Visibility Model (PLUVUE II) is used for estimating visual range reduction and atmospheric discoloration caused by plumes consisting of primary particles, nitrogen oxides and sulfur oxides emitted from a single emission source. PLUVUE II uses Gaussian formulations to predict transport and dispersion. The model includes chemical reactions, optical effects and surface deposition. Four types of optics calculations are made: horizontal and non-horizontal views through the plume with a sky viewing background; horizontal views through the plume with white, gray and black viewing backgrounds; and horizontal views along the axis of the plume with a sky viewing background.

a. Recommendations for Regulatory Use

The Plume Visibility Model (PLUVUE II) may be used on a case-by-case basis as a third level screening model. When applying PLUVUE II, the following precautions should be taken:

1. Treat the optical effects of NO2 and particles separately as well as together to avoid cancellation of NO2 absorption with particle scattering.

2. Examine the visual impact of the plume in 0.1 (or 0), 0.5, and 1.0 times the expected level of particulate matter in the background air.

3. Examine the visual impact of the plume over the full range of observer-plume sun angles.

4. The user should consult the appropriate Federal Land Manager when using PLUVUE II to assess visibility impacts in a Class I area.

b. Input Requirements

Source data requirements are: location and elevation; emission rates of SO2, NOX, and particulates; flue gas flow rate, exit velocity, and exit temperature; flue gas oxygen content; properties (including density, mass median and standard geometric deviation of radius) of the emitted aerosols in the accumulation (0.1-1.0μm) and coarse (1.0-10.μm) size modes; and deposition velocities for SO2, NOX, coarse mode aerosol, and accumulations mode aerosol.

Meteorological data requirements are: stability class, wind direction (for an observer-based run), wind speed, lapse rate, air temperature, relative humidity, and mixing height.

Other data requirements are: ambient background concentrations of NOX, NO2, O3, and SO2, and background visual range of sulfate and nitrate concentrations.

Receptor (observer) data requirements are: location, terrain elevation at points along plume trajectory, white, gray, and black viewing backgrounds, the distance from the observer to the terrain observed behind the plume.

c. Output

Printed output includes plume concentrations and visual effects at specified downwind distances for calculated or specified lines of sight.

d. Type of Model

PLUVUE II is a Gaussian plume model. Visibility impairment is quantified once the spectral light intensity has been calculated for the specific lines of sight. Visibility impairment includes visual range reduction, plume contrast, relative coloration of a plume to its viewing background, and plume perceptibility due to its contrast and color with respect to a viewing background.

e. Pollutant Types

PLUVUE II treats NO, NO2, SO2, H2SO4, HNO3, O3, primary and secondary particles to calculate effects on visibility.

f. Source Receptor Relationship

For performing the optics calculations at selected points along the plume trajectory, PLUVUE II has two modes: plume based and observer based calculations. The major difference is the orientation of the viewer to the source and the plume.

g. Plume Behavior

Briggs (1969, 1971, 1972) final plume rise equations are used.

h. Horizontal Winds

User-specified wind speed (and direction for an observer-based run) are assumed constant for the calculation.

i. Vertical Wind Speed

Vertical wind speed is assumed equal to zero.

j. Horizontal Dispersion

Constant, uniform (steady-state) wind is assumed for each hour. Straight line plume transport is assumed to all downwind distances.

k. Vertical Dispersion

Rural dispersion coefficients from Turner (1969) are used, with no adjustment for surface roughness. Six stability classes are used.

l. Chemical Transformation

The chemistry of NO, NO2, O3, OH, O(1D), SO2, HNO3, and H2SO4 is treated by means of nine reactions. Steady state approximations are used for radicals and for the NO/NO2/O3 reactions.

m. Physical Removal

Dry deposition of gaseous and particulate pollutants is treated using deposition velocities.

n. Evaluation Studies

Bergstrom, R.W., C. Seigneur, B.L. Babson, H.Y. Holman and M.A. Wojcik, 1981. Comparison of the Observed and Predicted Visual Effects Caused by Power Plant Plumes. Atmospheric Environment, 15: 2135-2150.

Bergstrom, R.W., Seigneur, C.D. Johnson and L.W. Richards, 1984. Measurements and Simulations of the Visual Effects of Particulate Plumes. Atmospheric Environment, 18(10): 2231-2244.

Seigneur, C., R.W. Bergstrom and A.B. Hudischewskyj, 1982. Evaluation of the EPA PLUVUE Model and the ERT Visibility Model Based on the 1979 VISTTA Data Base. EPA Publication No. EPA-450/4-82-008. U.S. Environmental Protection Agency, Research Triangle Park, NC.

White, W.H., C. Seigneur, D.W. Heinold, M.W. Eltgroth, L.W. Richards, P.T. Roberts, P.S. Bhardwaja, W.D. Conner and W.E. Wilson, Jr, 1985. Predicting the Visibility of Chimney Plumes: An Inter-comparison of Four Models with Observations at a Well-Controlled Power Plant. Atmospheric Environment, 19: 515-528.

B.13 Point, Area, Line Source Algorithm (PAL-DS) Reference

Petersen, W.B, 1978. User's Guide for PAL—A Gaussian-Plume Algorithm for Point, Area, and Line Sources. EPA Publication No. EPA-600/4-78-013. Office of Research and Development, Research Triangle Park, NC. (NTIS No. PB 281306)

Rao, K.S. and H.F. Snodgrass, 1982. PAL-DS Model: The PAL Model Including Deposition and Sedimentation. EPA Publication No. EPA-600/8-82-023. Office of Research and Development, Research Triangle Park, NC. (NTIS No. PB 83-117739)

Availability

The computer code is available on diskette (as PB 90-500802) from the National Technical Information Service (see section B.0).

Abstract

PAL-DS is an acronym for this point, area, and line source algorithm and is a method of estimating short-term dispersion using Gaussian-plume steady-state assumptions. The algorithm can be used for estimating concentrations of non-reactive pollutants at 99 receptors for averaging times of 1 to 24 hours, and for a limited number of point, area, and line sources (99 of each type). This algorithm is not intended for application to entire urban areas but is intended, rather, to assess the impact on air quality, on scales of tens to hundreds of meters, of portions of urban areas such as shopping centers, large parking areas, and airports. Level terrain is assumed. The Gaussian point source equation estimates concentrations from point sources after determining the effective height of emission and the upwind and crosswind distance of the source from the receptor. Numerical integration of the Gaussian point source equation is used to determine concentrations from the four types of line sources. Subroutines are included that estimate concentrations for multiple lane line and curved path sources, special line sources (line sources with endpoints at different heights above ground), and special curved path sources. Integration over the area source, which includes edge effects from the source region, is done by considering finite line sources perpendicular to the wind at intervals upwind from the receptor. The crosswind integration is done analytically; integration upwind is done numerically by successive approximations.

The PAL-DS model utilizes Gaussian plume-type diffusion-deposition algorithms based on analytical solutions of a gradient-transfer model. The PAL-DS model can treat deposition of both gaseous and suspended particulate pollutants in the plume since gravitational settling and dry deposition of the particles are explicitly accounted for. The analytical diffusion-deposition expressions listed in this report in the limit when pollutant settling and deposition velocities are zero, they reduce to the usual Gaussian plume diffusion algorithms in the PAL model.

a. Recommendations for Regulatory Use

PAL-DS can be used if it can be demonstrated to estimate concentrations equivalent to those provided by the preferred model for a given application. PAL-DS must be executed in the equivalent mode.

PAL-DS can be used on a case-by-case basis in lieu of a preferred model if it can be demonstrated, using the criteria in section 3.2, that PAL-DS is more appropriate for the specific application. In this case the model options/modes which are most appropriate for the application should be used.

b. Input Requirements

Source data: point-sources—emission rate, physical stack height, stack gas temperature, stack gas velocity, stack diameter, stack gas volume flow, coordinates of stack, initial σy and σz; area sources—source strength, size of area source, coordinates of S.W. corner, and height of area source; and line sources—source strength, number of lanes, height of source, coordinates of end points, initial σy and σz, width of line source, and width of median. Diurnal variations in emissions are permitted. When applicable, the settling velocity and deposition velocity are also permitted.

Meteorological data: wind profile exponents, anemometer height, wind direction and speed, stability class, mixing height, air temperature, and hourly variations in emission rate.

Receptor data: receptor coordinates.

c. Output

Printed output includes:

Hourly concentration and deposition flux for each source type at each receptor; and

Average concentration for up to 24 hours for each source type at each receptor.

d. Type of Model

PAL-DS is a Gaussian plume model.

e. Pollutant Types

PAL-DS may be used to model non-reactive pollutants.

f. Source-Receptor Relationships

Up to 99 sources of each of 6 source types: point, area, and 4 types of line sources.

Source and receptor coordinates are uniquely defined.

Unique stack height for each source.

Coordinates of receptor locations are user defined.

g. Plume Behavior

Briggs final plume rise equations are used.

Fumigation and downwash are not treated.

If plume height exceeds mixing height, concentrations are assumed equal to zero.

Surface concentrations are set to zero when the plume centerline exceeds mixing height.

h. Horizontal Winds

User-supplied hourly wind data are used.

Constant, uniform (steady-state) wind is assumed within each hour. Wind is assumed to increase with height.

i. Vertical Wind Speeds

Assumed equal to zero.

j. Horizontal Dispersion

Rural dispersion coefficients from Turner (1969) are used with no adjustments made for surface roughness.

Six stability classes are used.

Dispersion coefficients (Pasquill-Gifford) are assumed based on a 3cm roughness height.

k. Vertical Dispersion

Six stability classes are used.

Rural dispersion coefficients from Turner (1969) are used; no further adjustments are made for variation in surface roughness, transport or averaging time.

Multiple reflection is handled by summation of series until the vertical standard deviation equals 1.6 times mixing height. Uniform vertical mixing is assumed thereafter.

l. Chemical Transformation

Not treated.

m. Physical Removal

PAL-DS can treat deposition of both gaseous and suspended particulates in the plume since gravitational settling and dry deposition of the particles are explicitly accounted for.

n. Evaluation Studies

None Cited.

B.14 Reactive Plume Model (RPM-IV) Reference

Environmental Protection Agency, 1993. Reactive Plume Model IV (RPM-IV) User's Guide. EPA Publication No. EPA-454/B-93-012. U.S. Environmental Protection Agency (ESRL), Research Triangle Park, NC. (NTIS No. PB 93-217412)

Availability

The above report and model computer code are available on the Support Center for Regulatory Air Models Bulletin Board System. The model code is also available on diskette (as PB 96-502026) from the National Technical Information Service (see section B.0).

Abstract

The Reactive Plume Model, RPM-IV, is a computerized model used for estimating short-term concentrations of primary and secondary reactive pollutants resulting from single or, in some special cases, multiple sources if they are aligned with the mean wind direction. The model is capable of simulating the complex interaction of plume dispersion and non-linear photochemistry. If Carbon Mechanism IV (CBM-IV) is used, emissions must be disaggregated into carbon bond classes prior to model application. The model can be run on a mainframe computer, workstation, or IBM-compatible PC with at least 2 megabytes of memory. A major feature of RPM-IV is its ability to interface with input and output files from EPA's Regional Oxidant Model (ROM) and Urban Airshed Model (UAM) to provide an internally consistent set of modeled ambient concentrations for various pollutant species.

a. Recommendations for Regulatory Use

There is no specific recommendation at the present time. RPM-IV may be used on a case-by-case basis.

b. Input Requirements

Source data requirements are: emission rates, name, and molecular weight of each species of pollutant emitted; ambient pressure, ambient temperature, stack height, stack diameter, stack exit velocity, stack gas temperature, and location.

Meteorological data requirements are: wind speeds, plume widths or stability classes, photolytic rate constants, and plume depths or stability classes.

Receptor data requirements are: downwind distances or travel times at which calculations are to be made.

Initial concentration of all species is required, and the specification of downwind ambient concentrations to be entrained by the plume is optional.

c. Output

Short-term concentrations of primary and secondary pollutants at either user specified time increments, or user specified downwind distances.

d. Type of Model

Reactive Gaussian plume model.

e. Pollutant Types

Currently, using the Carbon Bond Mechanism (CBM-IV), 34 species are simulated (82 reactions), including NO, NO2, O3, SO2, SO4, five categories of reactive hydrocarbons, secondary nitrogen compounds, organic aerosols, and radical species.

f. Source-Receptor Relationships

Single point source.

Single area or volume source.

Multiple sources can be simulated if they are lined up along the wind trajectory.

Predicted concentrations are obtained at a user specified time increment, or at user specified downwind distances.

g. Plume Behavior

Briggs (1971) plume rise equations are used.

h. Horizontal Winds

User specifies wind speeds as a function of time.

i. Vertical Wind Speed

Not treated.

j. Horizontal Dispersion

User specified plume widths, or user may specify stability and widths will be computed using Turner (1969).

k. Vertical Dispersion

User specified plume depths, or user may specify stability in which case depths will be calculated using Turner (1969). Note that vertical uniformity in plume concentration is assumed.

l. Chemical Transformation

RPM-IV has the flexibility of using any user input chemical kinetic mechanism. Currently it is run using the chemistry of the Carbon Bond Mechanism, CBM-IV (Gery et al., 1988). The CBM-IV mechanism, as incorporated in RPM-IV, utilizes an updated simulation of PAN chemistry that includes a peroxy-peroxy radical termination reaction, significant when the atmosphere is NOX-limited (Gery et al., 1989). As stated above, the current CBM-IV mechanism accommodates 34 species and 82 reactions focusing primarily on hydrocarbon/nitrogen oxides and ozone photochemistry.

m. Physical Removal

Not treated.

n. Evaluation Studies

Stewart, D.A. and M-K Liu, 1981. Development and Application of a Reactive Plume Model. Atmospheric Environment, 15: 2377-2393.

B.15 Shoreline Dispersion Model (SDM) Reference

PEI Associates, 1988. User's Guide to SDM-A Shoreline Dispersion Model. EPA Publication No. EPA-450/4-88-017. U.S. Environmental Protection Agency, Research Triangle Park, NC. (NTIS No. PB 89-164305)

Availability

The model code is available on the Support Center for Regulatory Air Models Bulletin Board System (see section B.0).

Abstract

SDM is a hybrid multi-point Gaussian dispersion model that calculates source impact for those hours during the year when fumigation events are expected using a special fumigation algorithm and the MPTER regulatory model for the remaining hours (see appendix A).

a. Recommendations for Regulatory Use

SDM may be used on a case-by-case basis for the following applications:

• Tall stationary point sources located at a shoreline of any large body of water;

• Rural or urban areas;

• Flat terrain;

• Transport distances less than 50 km;

• 1-hour to 1-year averaging times.

b. Input Requirements

Source data: location, emission rate, physical stack height, stack gas exit velocity, stack inside diameter, stack gas temperature and shoreline coordinates.

Meteorological data: hourly values of mean wind speed within the Thermal Internal Boundary Layer (TIBL) and at stack height; mean potential temperature over land and over water; over water lapse rate; and surface sensible heat flux. In addition to these meteorological data, SDM access standard NWS surface and upper air meteorological data through the RAMMET preprocessor.

Receptor data: coordinates for each receptor.

c. Output

Printed output includes the MPTER model output as well as: special shoreline fumigation applicability report for each day and source; high-five tables on the standard output with “F” designation next to the concentration if that averaging period includes a fumigation event.

d. Type of Model

SDM is hybrid Gaussian model.

e. Pollutant Types

SDM may be used to model primary pollutants. Settling and deposition are not treated.

f. Source-Receptor Relationships

SDM applies user-specified locations of stationary point sources and receptors. User input stack height, shoreline orientation and source characteristics for each source. No topographic elevation is input; flat terrain is assumed.

g. Plume Behavior

SDM uses Briggs (1975) plume rise for final rise. SDM does not treat stack tip or building downwash.

h. Horizontal Winds

Constant, uniform (steady-state) wind is assumed for an hour. Straight line plume transport is assumed to all downwind distances. Separate wind speed profile exponents (EPA, 1980) for both rural and urban cases are assumed.

i. Vertical Wind Speed

Vertical wind speed is assumed equal to zero.

j. Horizontal Dispersion

For the fumigation algorithm coefficients based on Misra (1980) and Misra and McMillan (1980) are used for plume transport in stable air above TIBL and based on Lamb (1978) for transport in the unstable air below the TIBL. An effective horizontal dispersion coefficient based on Misra and Onlock (1982) is used. For nonfumigation periods, algorithms contained in the MPTER model are used (see appendix A).

k. Vertical Dispersion

For the fumigation algorithm, coefficients based on Misra (1980) and Misra and McMillan (1980) are used.

l. Chemical Transformation

Chemical transformation is not included in the fumigation algorithm.

m. Physical Removal

Physical removal is not explicitly treated.

n. Evaluation Studies

Environmental Protection Agency, 1987. Analysis and Evaluation of Statistical Coastal Fumigation Models. EPA Publication No. EPA-450/4-87-002. U.S. Environmental Protection Agency, Research Triangle Park, NC. (NTIS PB 87-175519)

B.16 SHORTZ Reference

Bjorklund, J.R. and J.F. Bowers, 1982. User's Instructions for the SHORTZ and LONGZ Computer Programs, Volumes I and II. EPA Publication No. EPA-903/9-82-004a and b. U.S. Environmental Protection Agency, Region III, Philadelphia, PA.

Availability

The computer code is available on the Support Center for Regulatory Air Models Bulletin Board System and on diskette (as PB 96-501986) from the National Technical Information Service (see section B.0).

Abstract

SHORTZ utilizes the steady state bivariate Gaussian plume formulation for both urban and rural areas in flat or complex terrain to calculate ground-level ambient air concentrations. The model can calculate 1-hour, 2-hour, 3-hour etc. average concentrations due to emissions from stacks, buildings and area sources for up to 300 arbitrarily placed sources. The output consists of total concentration at each receptor due to emissions from each user-specified source or group of sources, including all sources. If the option for gravitational settling is invoked, analysis cannot be accomplished in complex terrain without violating mass continuity.

a. Recommendations for Regulatory Use

SHORTZ can be used if it can be demonstrated to estimate concentrations equivalent to those provided by the preferred model for a given application. SHORTZ must be executed in the equivalent mode.

SHORTZ can be used on a case-by-case basis in lieu of a preferred model if it can be demonstrated, using the criteria in section 3.2, that SHORTZ is more appropriate for the specific application. In this case the model options/modes which are most appropriate for the application should be used.

b. Input Requirements

Source data requirements are: for point, building or area sources, location, elevation, total emission rate (optionally classified by gravitational settling velocity) and decay coefficient; for stack sources, stack height, effluent temperature, effluent exit velocity, stack radius (inner), actual volumetric flow rate, and ground elevation (optional); for building sources, height, length and width, and orientation; for area sources, characteristic vertical dimension, and length, width and orientation.

Meteorological data requirements are: wind speed and measurement height, wind profile exponents, wind direction, standard deviations of vertical and horizontal wind directions, (i.e., vertical and lateral turbulent intensities), mixing height, air temperature, and vertical potential temperature gradient.

Receptor data requirements are: coordinates, ground elevation.

c. Output

Printed output includes total concentration due to emissions from user-specified source groups, including the combined emissions from all sources (with optional allowance for depletion by deposition).

d. Type of Model

SHORTZ is a Gaussian plume model.

e. Pollutant Types

SHORTZ may be used to model primary pollutants. Settling and deposition of particulates are treated.

f. Source-Receptor Relationships

User specified locations for sources and receptors are used.

Receptors are assumed to be at ground level.

g. Plume Behavior

Plume rise equations of Bjorklund and Bowers (1982) are used.

Stack tip downwash (Bjorklund and Bowers, 1982) is included.

All plumes move horizontally and will fully intercept elevated terrain.

Plumes above mixing height are ignored.

Perfect reflection at mixing height is assumed for plumes below the mixing height.

Plume rise is limited when the mean wind at stack height approaches or exceeds stack exit velocity.

Perfect reflection at ground is assumed for pollutants with no settling velocity.

Zero reflection at ground is assumed for pollutants with finite settling velocity.

Tilted plume is used for pollutants with settling velocity specified. Buoyancy-induced dispersion (Briggs, 1972) is included.

h. Horizontal Winds

Winds are assumed homogeneous and steady-state.

Wind speed profile exponents are functions of both stability class and wind speed. Default values are specified in Bjorklund and Bowers (1982).

i. Vertical Wind Speed

Vertical winds are assumed equal to zero.

j. Horizontal Dispersion

Horizontal plume size is derived from input lateral turbulent intensities using adjustments to plume height, and rate of plume growth with downwind distance specified in Bjorklund and Bowers (1982).

k. Vertical Dispersion

Vertical plume size is derived from input vertical turbulent intensities using adjustments to plume height and rate of plume growth with downwind distance specified in Bjorklund and Bowers (1982).

l. Chemical Transformation

Chemical transformations are treated using exponential decay. Time constant is input by the user.

m. Physical Removal

Settling and deposition of particulates are treated.

n. Evaluation Studies

Bjorklund, J.R. and J.F. Bowers, 1982. User's Instructions for the SHORTZ and LONGZ Computer Programs. EPA Publication No. EPA-903/9-82-004. EPA Environmental Protection Agency, Region III, Philadelphia, PA.

Wackter, D. and R. Londergan, 1984. Evaluation of Complex Terrain Air Quality Simulation Models. EPA Publication No. EPA-450/4-84-017. U.S. Environmental Protection Agency, Research Triangle Park, NC.

B.17 Simple Line-Source Model Reference

Chock, D.P., 1980. User's Guide for the Simple Line-Source Model for Vehicle Exhaust Dispersion Near a Road. Ford Research Laboratory, Dearborn, MI.

Availability

Copies of the above reference are available without charge from: Dr. D.P. Chock, Ford Research Laboratory, P.O. Box 2053; MD-3083, Dearborn, MI 48121-2053. The short model algorithm is contained in the User's Guide.

Abstract

The Simple Line-Source Model is a simple steady-state Gaussian plume model which can be used to determine hourly (or half-hourly) averages of exhaust concentrations within 100m from a roadway on a relatively flat terrain. The model allows for plume rise due to the heated exhaust, which can be important when the crossroad wind is very low. The model also utilizes a new set of vertical dispersion parameters which reflects the influence of traffic-induced turbulence.

a. Recommendations for Regulatory Use

The Simple Line-Source Model can be used if it can be demonstrated to estimate concentrations equivalent to those provided by the preferred model for a given application. The model must be executed in the equivalent mode.

The Simple Line-Source Model can be used on a case-by-case basis in lieu of a preferred model if it can be demonstrated, using criteria in section 3.2, that it is more appropriate for the specific application. In this case the model options/modes which are most appropriate for the application should be used.

b. Input Requirements

Source data requirements are: emission rate per unit length per lane, the number of lanes on each road, distances from lane centers to the receptor, source and receptor heights.

Meteorological data requirements are: buoyancy flux, ambient stability condition, ambient wind and its direction relative to the road.

Receptor data requirements are: distance and height above ground.

c. Output

Printed output includes hourly or (half-hourly) concentrations at the receptor due to exhaust emission from a road (or a system of roads by summing the results from repeated model applications).

d. Type of Model

The Simple Line-Source Model is a Gaussian plume model.

e. Pollutant Types

The Simple Line-Source Model can be used to model primary pollutants. Settling and deposition are not treated.

f. Source-Receptor Relationship

The Simple Line-Source Model treats arbitrary location of line sources and receptors.

g. Plume Behavior

Plume-rise formula adequate for a heated line source is used.

h. Horizontal Winds

The Simple Line-Source Model uses user-supplied hourly (or half-hourly) ambient wind speed and direction. The wind measurements are from a height of 5 to 10m.

i. Vertical Wind Speed

Vertical wind speed is assumed equal to zero.

j. Dispersion Parameters

Horizontal dispersion parameter is not used.

k. Vertical Dispersion

A vertical dispersion parameter is used which is a function of stability and wind-road angle. Three stability classes are used: unstable, neutral and stable. The parameters take into account the effect of traffic-generated turbulence (Chock, 1980).

l. Chemical Transformation

Not treated.

m. Physical Removal

Not treated.

n. Evaluation Studies

Chock, D.P., 1978. A Simple Line-Source Model for Dispersion Near Roadways. Atmospheric Environment, 12: 823-829.

Sistla, G., P. Samson, M. Keenan and S.T. Rao, 1979. A Study of Pollutant Dispersion Near Highways. Atmospheric Environment, 13: 669-685.

B.18 SLAB Reference:

Ermak, D.L., 1990. User's Manual for SLAB: An Atmospheric Dispersion Model for Denser-than-Air Releases (UCRL-MA-105607), Lawrence Livermore National Laboratory.

Availability

The computer code can be obtained from: Energy Science and Technology Center, P.O. Box 1020, Oak Ridge, TN 37830, Phone [phone].

The User's Manual (as DE 91-008443) can be obtained from the National Technical Information Service. The computer code is also available on the Support Center for Regulatory Air Models Bulletin Board System (Public Upload/ Download Area; see section B.0.)

Abstract

The SLAB model is a computer model, PC-based, that simulates the atmospheric dispersion of denser-than-air releases. The types of releases treated by the model include a ground-level evaporating pool, an elevated horizontal jet, a stack or elevated vertical jet and an instantaneous volume source. All sources except the evaporating pool may be characterized as aerosols. Only one type of release can be processed in any individual simulation. Also, the model simulates only one set of meteorological conditions; therefore direct application of the model over time periods longer than one or two hours is not recommended.

a. Recommendations for use

The SLAB model should be used as a refined model to estimate spatial and temporal distribution of short-term ambient concentration (e.g., 1-hour or less averaging times) and the expected area of exposure to concentrations above specified threshold values for toxic chemical releases where the release is suspected to be denser than the ambient air.

b. Input Requirements

The SLAB model is executed in the batch mode. Data are input directly from an external input file. There are 29 input parameters required to run each simulation. These parameters are divided into 5 categories by the user's guide: source type, source properties, spill properties, field properties, and meteorological parameters. The model is not designed to accept real-time meteorological data or convert units of input values. Chemical property data are not available within the model and must be input by the user. Some chemical and physical property data are available in the user's guide.

Source type is chosen as one of the following: evaporating pool release, horizontal jet release, vertical jet or stack release, or instantaneous or short duration evaporating pool release.

Source property data requirements are physical and chemical properties (molecular weight, vapor heat capacity at constant pressure; boiling point; latent heat of vaporization; liquid heat capacity; liquid density; saturation pressure constants), and initial liquid mass fraction in the release.

Spill properties include: source temperature, emission rate, source dimensions, instantaneous source mass, release duration, and elevation above ground level.

Required field properties are: desired concentration averaging time, maximum downwind distance (to stop the calculation), and four separate heights at which the concentration calculations are to be made.

Meteorological parameter requirements are: ambient measurement height, ambient wind speed at designated ambient measurement height, ambient temperature, surface roughness, relative humidity, atmospheric stability class, and inverse Monin-Obukhov length (optional, only used as an input parameter when stability class is unknown).

c. Output

No graphical output is generated by the current version of this program. The output print file is automatically saved and must be sent to the appropriate printer by the user after program execution. Printed output includes in tabular form:

Listing of model input data;

Instantaneous spatially-averaged cloud parameters—time, downwind distance, magnitude of peak concentration, cloud dimensions (including length for puff-type simulations), volume (or mole) and mass fractions, downwind velocity, vapor mass fraction, density, temperature, cloud velocity, vapor fraction, water content, gravity flow velocities, and entrainment velocities;

Time-averaged cloud parameters—parameters which may be used externally to calculate time-averaged concentrations at any location within the simulation domain (tabulated as functions of downwind distance);

Time-averaged concentration values at plume centerline and at five off-centerline distances (off-centerline distances are multiples of the effective cloud half-width, which varies as a function of downwind distance) at four user-specified heights and at the height of the plume centerline.

d. Type of Model

As described by Ermak (1989), transport and dispersion are calculated by solving the conservation equations for mass, species, energy, and momentum, with the cloud being modeled as either a steady-state plume, a transient puff, or a combination of both, depending on the duration of the release. In the steady-state plume mode, the crosswind-averaged conservation equations are solved and all variables depend only on the downwind distance. In the transient puff mode, the volume-averaged conservation equations are solved, and all variables depend only on the downwind travel time of the puff center of mass. Time is related to downwind distance by the height-averaged ambient wind speed. The basic conservation equations are solved via a numerical integration scheme in space and time.

e. Pollutant Types

Pollutants are assumed to be non-reactive and non-depositing dense gases or liquid-vapor mixtures (aerosols). Surface heat transfer and water vapor flux are also included in the model.

f. Source-Receptor Relationships

Only one source can be modeled at a time.

There is no limitation to the number of receptors; the downwind receptor distances are internally-calculated by the model. The SLAB calculation is carried out up to the user-specified maximum downwind distance.

The model contains submodels for the source characterization of evaporating pools, elevated vertical or horizontal jets, and instantaneous volume sources.

g. Plume Behavior

Plume trajectory and dispersion is based on crosswind-averaged mass, species, energy, and momentum balance equations. Surrounding terrain is assumed to be flat and of uniform surface roughness. No obstacle or building effects are taken into account.

h. Horizontal Winds

A power law approximation of the logarithmic velocity profile which accounts for stability and surface roughness is used.

i. Vertical Wind Speed

Not treated.

j. Vertical Dispersion

The crosswind dispersion parameters are calculated from formulas reported by Morgan et al. (1983), which are based on experimental data from several sources. The formulas account for entrainment due to atmospheric turbulence, surface friction, thermal convection due to ground heating, differential motion between the air and the cloud, and damping due to stable density stratification within the cloud.

k. Horizontal Dispersion

The horizontal dispersion parameters are calculated from formulas similar to those described for vertical dispersion, also from the work of Morgan et al. (1983).

l. Chemical Transformation

The thermodynamics of the mixing of the dense gas or aerosol with ambient air (including water vapor) are treated. The relationship between the vapor and liquid fractions within the cloud is treated using the local thermodynamic equilibrium approximation. Reactions of released chemicals with water or ambient air are not treated.

m. Physical Removal

Not treated.

n. Evaluation Studies

Blewitt, D.N., J.F. Yohn and D.L. Ermak, 1987. An Evaluation of SLAB and DEGADIS Heavy Gas Dispersion Models Using the HF Spill Test Data. Proceedings, AIChE International Conference on Vapor Cloud Modeling, Boston, MA, November, pp. 56-80.

Ermak, D.L., S.T. Chan, D.L. Morgan and L.K. Morris, 1982. A Comparison of Dense Gas Dispersion Model Simulations with Burro Series LNG Spill Test Results. J. Haz. Matls., 6: 129-160.

Zapert, J.G., R.J. Londergan and H. Thistle, 1991. Evaluation of Dense Gas Simulation Models. EPA Publication No. EPA-450/4-90-018. U.S. Environmental Protection Agency, Research Triangle Park, NC.

B.19 WYNDvalley Model Reference

Harrison, Halstead, 1992. “A User's Guide to WYNDvalley 3.11, an Eulerian-Grid Air-Quality Dispersion Model with Versatile Boundaries, Sources, and Winds,” WYNDsoft Inc., Mercer Island, WA.

Availability

Copies of the user's guide and the executable model computer codes are available at a cost of $295.00 from: WYNDsoft, Incorporated, 6333 77th Avenue, Mercer Island, WA 98040, Phone: [phone].

Abstract

WYNDvalley 3.11 is a multi-layer (up to five vertical layers) Eulerian grid dispersion model that permits users flexibility in defining borders around the areas to be modeled, the boundary conditions at these borders, the intensities and locations of emissions sources, and the winds and diffusivities that affect the dispersion of atmospheric pollutants. The model's output includes gridded contour plots of pollutant concentrations for the highest brief episodes (during any single time step), the highest and second-highest 24-hour averages, averaged dry and wet deposition fluxes, and a colored “movie” showing evolving dispersal of pollutant concentrations, together with temporal plots of the concentrations at specified receptor sites and statistical inference of the probabilities that standards will be exceeded at those sites. WYNDvalley is implemented on IBM compatible microcomputers, with interactive data input and color graphics display.

a. Recommendations for Regulatory Use

WYNDvalley may be used on a case-by-case basis to estimate concentrations during valley stagnation periods of 24 hours or longer. Recommended inputs are listed below.

VariableRecommended valueHorizontal cell dimension250 to 500 meters.Vertical layers3 to 5.Layer depth50 to 100 meters.Background (internal to model)Zero (background should be added externally to model estimates).Lateral meander velocityDefault.DiffusivitiesDefault.Ventilation parameter (upper boundary condition)Default.Dry deposition velocityZero (site-specific).Washout ratioZero (site-specific). b. Input Requirements

Input data, including model options, modeling domain boundaries, boundary conditions, receptor locations, source locations, and emission rates, may be entered interactively, or through existing template files from a previous run. Meteorological data, including wind speeds, wind directions, rain rates (optionally, for wet deposition calculations), and time of day and year, may be of arbitrary time increment (usually an hour) and are entered into the model through an external meteorological data file. Optionally, users may specify diffusivities and upper boundary conditions for each time increment. Source emission rates may be constant or modulated on a daily, weekly, and/or seasonal basis.

c. Output

Output from WYNDvalley includes gridded contour maps of the highest pollutant concentrations at each time step and the highest and second-highest 24-hour average concentrations. Output also includes the deposition patterns for wet, dry, and total fluxes of the pollutants to the surface, integrated over the simulation period. A running “movie” of the concentration patterns is displayed on the screen (with optional printout) as they evolve during the simulation. Output files include tables of daily-averaged pollutant concentrations at every modeled grid cell, and of hourly concentrations at up to eight specified receptors. Statistical analyses are performed on the hourly and daily data to estimate the probabilities that specified levels will be exceeded more than once during an arbitrary number of days with similar weather.

d. Type of Model

WYNDvalley is a three dimensional Eulerian grid model.

e. Pollutant Types

WYNDvalley may be used to model any inert pollutant.

f. Source-Receptor Relationships

Source and receptors may be located anywhere within the user-defined modeling domain. All point and area sources, or portions of an area source, within a given grid cell are summed to define a representative emission rate for that cell. Concentrations are calculated for each and every grid cell in the modeling domain. Up to eight grid cells may be selected as receptors, for which time histories of concentration and deposition fluxes are determined, and probabilities of exceedance are calculated.

g. Plume Behavior

Emissions for buoyant point sources are placed by the user in a grid cell which best reflects the expected effective plume height during stagnation conditions. Five vertical layers are available to the user.

h. Horizontal Winds

During each time step in the model, the winds are assumed to be uniform throughout the modeling domain. Numerical diffusion is minimized in the advection algorithm. To account for terrain effects on winds and dispersion, an ad hoc algorithm is employed in the model to distribute concentrations near boundaries.

i. Vertical Wind Speed

Winds are assumed to be constant with height.

j. Horizontal Dispersion

Horizontal eddy diffusion coefficients may be entered explicitly by the user at every time step. Alternatively, a default algorithm may be invoked to estimate these coefficients from the wind velocities and their variances.

k. Vertical Dispersion

Vertical eddy diffusion coefficients and a top-of-model boundary condition may be entered explicitly by the user at every time step. Alternatively, a default algorithm may be invoked to estimate these coefficients from the horizontal wind velocities and their variances, and from an empirical time-of-day correction derived from temperature gradient measurements and Monin-Obukhov similarities.

l. Chemical Transformation

Chemical transformation is not explicitly treated by WYNDvalley.

m. Physical Removal

WYNDvalley optionally simulates both wet and dry deposition. Dry deposition is proportional to concentration in the lowest layer, while wet deposition is proportional to rain rate and concentration in each layer. Appropriate coefficients (deposition velocities and washout ratios) are input by the user.

n. Evaluation Studies

Harrison, H., G. Pade, C. Bowman and R. Wilson, 1990. Air Quality During Stagnations: A Comparison of RAM and WYNDvalley with PM-10 Measurements at Five Sites. Journal of the Air & Waste Management Association, 40: 47-52.

Maykut, N. et al., 1990. Evaluation of the Atmospheric Deposition of Toxic Contaminants to Puget Sound. State of Washington, Puget Sound Water Quality Authority, Seattle, WA.

Yoshida, C., 1990. A Comparison of WYNDvalley Versions 2.12 and 3.0 with PM-10 Measurements in Six Cities in the Pacific Northwest. Lane Regional Air Pollution Authority, Springfield, OR.

B. REF References

Beals, G.A., 1971. A Guide to Local Dispersion of Air Pollutants. Air Weather Service Technical Report ⊥214 (April 1971).

Bjorklund, J.R. and J.F. Bowers, 1982. User's Instructions for the SHORTZ and LONGZ Computer Programs. EPA Publication No. EPA-903/9-82-004a and b. U.S. Environmental Protection Agency, Region III, Philadelphia, PA.

Briggs, G.A., 1969. Plume Rise. U.S. Atomic Energy Commission Critical Review Series, Oak Ridge National Laboratory, Oak Ridge, TN. (NTIS No. TID-25075)

Briggs, G.A., 1971. Some Recent Analyses of Plume Rise Observations. Proceedings of the Second International Clean Air Congress, edited by H.M. Englund and W.T. Berry. Academic Press, New York, NY.

Briggs, G.A., 1972. Discussion on Chimney Plumes in Neutral and Stable Surroundings. Atmospheric Environment, 6: 507-510.

Briggs, G.A., 1974. Diffusion Estimation for Small Emissions. USAEC Report ATDL-106. U.S. Atomic Energy Commission, Oak Ridge, TN.

Briggs, G.A., 1975. Plume Rise Predictions. Lectures on Air Pollution and Environmental Impact Analyses. American Meteorological Society, Boston, MA, pp. 59-111.

Briggs, G.A., 1984. Plume Rise and Buoyancy Effects. Atmospheric Science and Power Production, Darryl Randerson (Ed.). DOE Report DOE/TIC-27601, Technical Information Center, Oak Ridge, TN. (NTIS No. DE84005177)

Carpenter, S.B., T.L. Montgomery, J.M. Leavitt, W.C. Colbaugh and F.W. Thomas, 1971. Principal Plume Dispersion Models: TVA Power Plants. Journal of Air Pollution Control Association, 21: 491-495.

Chock, D.P., 1980. User's Guide for the Simple Line-Source Model for Vehicle Exhaust Dispersion Near a Road. Environmental Science Department, General Motors Research Laboratories, Warren, MI.

Colenbrander, G.W., 1980. A Mathematical Model for the Transient Behavior of Dense Vapor Clouds, 3rd International Symposium on Loss Prevention and Safety Promotion in the Process Industries, Basel, Switzerland.

DeMarrais, G.A., 1959. Wind Speed Profiles at Brookhaven National Laboratory. Journal of Applied Meteorology, 16: 181-189.

Ermak, D.L., 1989. A Description of the SLAB Model, presented at JANNAF Safety and Environmental Protection Subcommittee Meeting, San Antonio, TX, April, 1989.

Gery, M.W., G.Z. Whitten and J.P. Killus, 1988. Development and Testing of CBM-IV for Urban and Regional Modeling. EPA Publication No. EPA-600/3-88-012. U.S. Environmental Protection Agency, Research Triangle Park, NC. (NTIS No. PB 88-180039)

Gery, M.W., G.Z. Whitten, J.P. Killus and M.C. Dodge, 1989. A Photochemical Kinetics Mechanism for Urban and Regional Scale Computer Modeling. Journal of Geophysical Research, 94: 12,925-12,956.

Gifford, F.A. and S.R. Hanna, 1970. Urban Air Pollution Modeling. Proceedings of the Second International Clean Air Congress, Academic Press, Washington, D.C.; pp. 140-1151.

Gifford, F.A., 1975. Atmospheric Dispersion Models for Environmental Pollution Applications. Lectures on Air Pollution and Environmental Impact Analyses. American Meteorological Society, Boston, MA.

Green, A.E., Singhal R.P. and R. Venkateswar, 1980. Analytical Extensions of the Gaussian Plume Model. Journal of the Air Pollution Control Association, 30: 773-776.

Heffter, J.L., 1965. The Variations of Horizontal Diffusion Parameters with Time for Travel Periods of One Hour or Longer. Journal of Applied Meteorology, 4: 153-156.

Heffter, J.L., 1980. Air Resources Laboratories Atmospheric Transport and Dispersion Model (ARL-ATAD). NOAA Technical Memorandum ERL ARL-81. Air Resources Laboratories, Silver Spring, MD.

Irwin, J.S., 1979a. Estimating Plume Dispersion—A Recommended Generalized Scheme. Fourth Symposium on Turbulence, Diffusion and Air Pollution, Reno, Nevada.

Irwin, J.S., 1979b. A Theoretical Variation of the Wind Profile Power-Law Exponent as a Function of Surface Roughness and Stability. Atmospheric Environment, 13: 191-194.

MacCready, P.B., Baboolal, L.B. and P.B. Lissaman, 1974. Diffusion and Turbulence Aloft Over Complex Terrain. Preprint Volume, AMS Symposium on Atmospheric Diffusion and Air Pollution, Santa Barbara, CA. American Meteorological Society, Boston, MA.

Moore, G.E., T.E. Stoeckenius and D.A. Stewart, 1982. A Survey of Statistical Measures of Model Performance and Accuracy for Several Air Quality Models. EPA Publication No. EPA-450/4-83-001. U.S. Environmental Protection Agency, Research Triangle Park, NC.

Morgan, D.L., Jr., L.K. Morris and D.L. Ermak, 1983. SLAB: A Time-Dependent Computer Model for the Dispersion of Heavy Gas Released in the Atmosphere, UCRL-53383, Lawrence Livermore National Laboratory, Livermore, CA.

Pasquill, F., 1976. Atmospheric Dispersion Parameters in Gaussian Plume Modeling, Part II. EPA Publication No. EPA-600/4-76-030b. U.S. Environmental Protection Agency, Research Triangle Park, NC.

Slade, D.H., 1968. Meteorology and Atomic Energy, U.S. Atomic Energy Commission, 445 pp. (NTIS No. TID-24190)

Turner, D.B., 1964. A Diffusion Model of An Urban Area. Journal of Applied Meteorology, 3: 83-91.

Turner, D.B., 1969. Workbook of Atmospheric Dispersion Estimates. PHS Publication No. 999-AP-26. U.S. Environmental Protection Agency, Research Triangle Park, NC.

Van Dop, H., 1992. Buoyant Plume Rise in a Lagrangian Frame Work. Atmospheric Environment, 26A: 1335-1346.