An Efficient Gaussian-Plume Multiple-Source Air Quality Algorithm

The information presented in this paper is directed to air pollution scientists with an interest in applying air quality simulation models. RAM is the three letter designation for this efficient Gaussian-plume multiple-source air quality algorithm. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. This algorithm can be used for estimating air quality concentrations of relatively stable pollutants for averaging times from an hour to a day in urban areas from point and area sources. The algorithm is applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for each hour. Hourly meteorological data required are wind direction, wind speed, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack gas volume flow and stack gas temperature. Emission information required of area sources consists of south-west corner coordinates, source area, total area emission rate and effective area source height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources to an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: 1 ) those whose coordinates are input by the user, 2) those whose coordinates are determined by thé model and are downwind óf significant point and area sources where maxima are likely to occur, and 3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum.     

Evaluation of a method for estimating pollution concentrations downwind of influencing buildings

A simple method for estimating enhanced dispersion resulting from the overall effect of buildings is presented and evaluated. A framework for applying the method to general plume dispersion modeling problems is suggested and examples are provided. The Gaussian plume equation has been modified to incorporate building wake enhanced dispersion parameters beyond the wake cavity region, and the resulting ground-level plume centerline concentration estimates are compared to 10 sets of field measurements. The results indicate that the method can provide a good correction for the overall effect of adjacent buildings. The effect of building wake enhanced dispersion on maximum ground-level concentrations is to decrease their values for releases near ground-level and to significantly increase their values for elevated releases. For elevated releases, enhanced horizontal dispersion dilutes the plume more rapidly; enhanced vertical dispersion also rapidly dilutes the plume but it can also bring the plume to ground-level while the in-plume concentrations are still high.     

A Theory of Plume Rise Compared with Field Observations

A theory for the rise of a plume in a horizontal wind is proposed in which it is assumed that, for some distance downwind of a high stack, the effects of atmospheric turbulence may be ignored in comparison with the effects of turbulence generated by the plume. The theory, an extension of the local similarity ideas used by Morton, Taylor, and Turner,¹ has two empirical parameters which measure the rate that surrounding fluid is entrained into the plume. Laboratory measurements of buoyant plume motion in laminar unstratified cross flow are used to estimate the empirical parameters. Using this determination of the parameters in the theory, the trajectories of atmospheric plumes may be predicted. To make such a prediction, the observed wind velocity and temperature as functions of altitude, and flow conditions at the stack orifice, are used in numerically integrating the equations. The resulting trajectories are compared with photographs, made by Leavitt, et al.,² of TVA, of plumes from 500 to 600 ft high stacks. Within 10 stack heights downwind of the stack, the root mean square discrepancy between the observed height of the trajectory above ground level and the theoretical value is 14%, which is about the uncertainty in the observed height. The maximum plume rise within the field of observation is within 15% of that predicted by the present theory.     

Maximum ground-level concentrations with downwash--analysis

Equations derived previously for critical downwind distance xc' wind speed uc' and plume rise zc' the values that produce maximum ground-level concentrations (MGLC) chi c under downwash conditions, have been solved. Tables of chi c' xc' uc' and zc' and graphs of the relationships among uc and zc, for a range of stack heights hs' and building heights hb' are presented. Results for two types of sources--a turbine and a reciprocating engine--are discussed. Some comparisons are made to the U.S. Environmental Protection Agency's (EPA) SCREEN3 model.     

The Validity of Several Plume Rise Formulas

The ground level concentration of pollutants downwind of a tall chimney decreases as the effective height of the stack increases. The effective height of the stack is the actual height plus the rise of the plume center-line due to momentum and buoyancy of the effluent. Over twenty formulas to predict plume rise from stack and meteorological parameters have been proposed; none is uniformly accepted. In this paper, 711 plume rise observations were used to test the ability of fifteen of the published and commonly used formulas to predict plume rise. The plume rise data were obtained from single stacks whose heat emission rate varied over four orders of magnitude. None of the formulas tested was found to be significantly better than the others. Research was performed under the auspices of the U.S. Atomic Energy Commission.     

Development and evaluation of the PRIME plume rise and building downwash model

A new Gaussian dispersion model, the Plume Rise Model Enhancements (PRIME), has been developed for plume rise and building downwash. PRIME considers the position of the stack relative to the building, streamline deflection near the building, and vertical wind speed shear and velocity deficit effects on plume rise. Within the wake created by a sharp-edged, rectangular building, PRIME explicitly calculates fields of turbulence intensity, wind speed, and streamline slope, which gradually decay to ambient values downwind of the building. The plume trajectory within these modified fields is estimated using a numerical plume rise model. A probability density function and an eddy diffusivity scheme are used for dispersion in the wake. A cavity module calculates the fraction of plume mass captured by and recirculated within the near wake. The captured plume is re-emitted to the far wake as a volume source and added to the uncaptured primary plume contribution to obtain the far wake concentrations. The modeling procedures currently recommended by the U.S. Environmental Protection Agency (EPA), using SCREEN and the Industrial Source Complex model (ISC), do not include these features. PRIME also avoids the discontinuities resulting from the different downwash modules within the current models and the reported overpredictions during light-wind speed, stable conditions. PRIME is intended for use in regulatory models. It was evaluated using data from a power plant measurement program, a tracer field study for a combustion turbine, and several wind-tunnel studies. PRIME performed as well as or better than ISC/SCREEN for nearly all of the comparisons.     

Development and Evaluation of the PRIME Plume Rise and Building Downwash Model

ABSTRACT

A new Gaussian dispersion model, the Plume Rise Model Enhancements (PRIME), has been developed for plume rise and building downwash. PRIME considers the position of the stack relative to the building, streamline deflection near the building, and vertical wind speed shear and velocity deficit effects on plume rise. Within the wake created by a sharp-edged, rectangular building, PRIME explicitly calculates fields of turbulence intensity, wind speed, and streamline slope, which gradually decay to ambient values downwind of the building. The plume trajectory within these modified fields is estimated using a numerical plume rise model. A probability density function and an eddy diffusivity scheme are used for dispersion in the wake. A cavity module calculates the fraction of plume mass captured by and recirculated within the near wake. The captured plume is re-emitted to the far wake as a volume source and added to the uncaptured primary plume contribution to obtain the far wake concentrations.

The modeling procedures currently recommended by the U.S. Environmental Protection Agency (EPA), using SCREEN and the Industrial Source Complex model (ISC), do not include these features. PRIME also avoids the discontinuities resulting from the different downwash modules within the current models and the reported overpredictions during light-wind speed, stable conditions. PRIME is intended for use in regulatory models. It was evaluated using data from a power plant measurement program, a tracer field study for a combustion turbine, and several wind-tunnel studies. PRIME performed as well as or better than ISC/SCREEN for nearly all of the comparisons.     

Dispersion in neutral boundary layer over astep change in surface roughness—II. Concentration profiles and dispersionparameters

This is a comparative study of dispersion in two different simulated boundary layers over homogeneous surfaces and over a step change (small to large roughness) in surface roughness.Hydrocarbon concentration measurements in the homogeneous boundary layers reflect the differences in generated turbulence for the two surfaces. Comparison of the maximum ground-level concentration as a function of stack height shows typically a factor of two increase for the block-roughness boundary layer (BBL) over that of the smoother fine-Sanspray roughness at the same stack height. This same relative difference is also reflected in the distance of C_max from the stack. The increased turbulence of the block-roughness causes the plume to reach the surface quicker and closer to the stack as compared to the fine-Sanspray boundary layer (FBL). This is also reflected in the relative magnitudes of the lateral and vertical Gaussian dispersion parameters for the two cases. However, their variation with distance from the source are similar and can approximately be described by power laws.Dispersion measurements over the step change in roughness show that the effects of the developing internal boundary layer (IBL) are only significant for low stack heights, with the maximum effect seen for the surface release. For the surface release, the concentration profiles initially follow those of the BBL but tend toward those of the fine-Sanspray boundary layer (FBL) within a short distance downwind. The same trend is present in the Gaussian dispersion parameters. However, the ground-level concentrations are apparently not affected because of the compensating effects of reduced mean velocity and increased turbulence within the IBL. The elevated releases show similar behavior but with a much shallower transition region.In the present case, the incident large-scale turbulence disperses the plume to the extent that the addition of smaller-scale turbulence by the second surface roughness is not noticable. Examination of surface lateral profiles and plume centerline profiles show little or no increased dispersion which could be attributable to a continuous fumigation episode.     

Maximum Ground-Level Concentrations with Downwash: The Urban Stability Mode

Abstract

Gaussian model-based equations for critical downwind distance, wind speed, and plume height that result in maximum ground-level concentrations (MGLC) under downwash conditions for the rural stability mode were presented in a previous paper. This paper presents general equations for the critical downwind distance xc for the urban stability mode. Specific examples are presented for Schulman-Scire and Huber-Snyder downwash treatments for building-enhanced and regular sigmas.     

Groundlevel concentration fluctuations from a buoyant and a non-buoyant source within a laboratory convectively mixed layer

With the use of mixed-layer scaling, the near-surface mean concentration and the concentration fluctuations at moderate distances downwind of a stack emitting a highly buoyant effluent are obtained and compared quantitatively with those from a non-buoyant source that is otherwise identical. The environment is a laboratory mixed layer in a state of free convection with mean wind simulated by towing the stack along a horizontal line. Although the buoyant effluent has a much smaller maximum mean groundlevel concentration occurring at a greater downwind distance than the non-buoyant effluent, the decay of mean concentration from that point downwind is found to be exceedingly slow in the buoyant case.The cumulative frequency distributions of sampled concentrations greater than zero for these same two cases are found to be log-normal in only a bimodal sense, with the weaker concentrations having a greater logarithmic range in amplitude than the stronger concentrations. The ratio of the root-mean-square (r.m.s.) concentration fluctuation to the mean concentration, in the central portion of the mean plume, is found to decay with downwind distance. Homogenization associated with both downstream and vertical mixing is believed responsible for the rapid decay observed.     

Boundary Layer Emission Monitoring

A new methodology is described for determining the atmospheric emission rate of pollutants from large heterogeneous area sources, such as hazardous waste sites. The procedure hinges upon measuring average pollutant concentrations, at three or more different elevations, while traversing the plume downwind of the area source. A helium-filled tethersonde balloon is used to elevate the sampling lines to their appropriate height. During plume traversing the sampling rate is adjusted to be proportional to the sine of the angle between the wind vector and the direction of the traverse path. The average concentrations are corrected for any upwind, background concentration and then used to derive an average vertical concentration profile. This profile Is numerically integrated, with the wind velocity profile, over the pollutant boundary layer to yield the area source emission rate. The methodology was tested on several large industrial effluent lagoons and proved to be easy to use, robust, and precise.     

Principal Plume Dispersion Models: TVA Power Plants

The body of information presented in this paper is directed to those individuals who may be concerned with principal plume dispersion models at coal-burning power plants. About 20 years of comprehensive field surveillance and documentation of dispersion of power plant emissions for a varied range of unit sizes, stack heights, and meteorological conditions have determined the Tennessee Valley Authority’s interpretation of principal plume dispersion models. TVA’s experience indicates that as unit sizes are increased and taller stacks are constructed, the plume dispersion model associated with maximum surface concentrations changes. Maximum surface concentrations for principal plume dispersion models were approximately equal for the early small plants. However, the coning model was considered the critical plume dispersion model because the frequency of recurrence of surface concentrations from this model was appreciably greater than other models.

There were progressive changes because of an increase in unit sizes and stack heights; the magnitude of maximum surface concentrations from the coning model decreased, and the magnitude (relative to the coning model) of concentrations from the inversion breakup model increased. However, with plumes from newer and larger units with higher stacks, the trapping dispersion model became prominent. Finally, by the time unit size had increased to 900 mw and stack height to about 245 meters, as at Bull Run Power Plant, the magnitude of surface concentrations associated with trapping had increased to such a degree that it became the critical dispersion model identified with power plants of this size.     

APCA Financial Statements for 1975-1976

Abstract

A wind tunnel study was completed to determine the effects the presence of a parapet and raised intake configurations have on the dilution of a pollutant between a rooftop stack and building intake. This study was the first to address the effects of building parapets and varying intake configurations. A study of this kind is desirable because it is common practice for architects to attempt to hide stacks with the use of a parapet in order to make industrial buildings more aesthetically pleasing. This is done with no thought to the effect it may have on the intended function of the stacks, which is dispersing gases away from the building to avoid contamination of ventilation air.

Three parapet configurations (no parapet and two different parapet heights) and two intake configurations (flush and raised) were investigated. The relative effects of the parapets and the raised intake configurations were also compared and contrasted for five stack heights, two stack locations, and four intake locations.

The parapets were found to produce a cavity zone that extends above the building's roof by as much as two times the physical height of the parapet; increasing stack height had little effect on dispersion until the stack extended beyond this cavity region. The independent use of the parapets and raised intake configuration decreased the number of dilutions occurring between stack and intake when compared to the no parapet and flush intake configurations in all cases. Also substantiated in this study is the widely accepted view that the effect of the parapet addition is to decrease the effective stack height by the parapet height itself.

The results of this investigation were then compared to existing wind tunnel-derived empirical models. The models tested were not able to predict the effects of varying stack height and of varying the relative distance between stack and intake on the dilution of a pollutant between stack and intake under the tested configurations.     

Particle Size Distributions of Kraft Paper Mill Aerosols Obtained by Airborne Sampling

Size distributions of particles at several downwind points in a Kraft paper mill plume have been determined by means of airborne sampling. Size distributions from samples close to the stack were found to have a log normal frequency distribution, but significant deviations from the log normal were found farther downwind. Several possible physical mechanisms are postulated as causes for this behavior. Plume dilution with background particles appears to be the most likely mechanism. The airborne sampling system is described, and electron micrographs of sampled particles are presented.     

A New Method for Determining the Contribution of a Refinery to Local SO2 Levels in an Industrial Region

A new method was developed for determining the contribution of one pollutant source to the air quality in an industrialized region. Although the method is general, it is presented in reference to a 130,000 bbl/day petroleum refinery and its effect on ambient SO₂ concentrations in Sarnia, Ontario. The plumes from SO₂ emitters located upwind of the refinery were represented by a single hypothetical plume which influences monitoring stations located upwind as well as downwind from the refinery. However, the refinery emissions affect only the downwind stations. A simple equation was derived by means of which the concentration at the downwind station could be calculated from the concentration at the upwind station and the refinery emission. This equation contains two coefficients A and B which were evaluated such that the difference between the cumulative frequency distributions of the measured and calculated SO₂ concentrations at the downwind station was minimized. For the meteorological conditions and monitoring stations considered, it was found that the refinery contributed less than 4.5 pphm to ambient SO₂ concentrations over 1 hr periods. This result and the validity of the method are discussed.     

Performance of a Gaussian model for centerline concentrations in the wake of buildings

This paper examines the performance and inherent limitations of a Gaussian plume model for predicting ground-level plume centerline concentrations in the wake of buildings. The Gaussian plume equation has been modified to incorporate building wake enhanced dispersion parameters. Model-predicted concentrations were compared to three sets of field observations. Predicted and observed concentrations were partitioned into groups by source-receptor distance, atmospheric stability class, and source-release height. The group analyses provided a way to identify sources of model error. The variability of errors was found to have values between 50 and 100 % of the mean observed concentration for groups where the mean error was small.     

Maximum Ground-Level Concentrations with Downwash

Equations are derived from the Gaussian plume mode! and prescribe the critical downwind distance, wind speed, and plume rise values that result in maximum ground-level concentrations (MGLC) under downwash conditions. The derivations apply to bent-over plumes and encompass the Schulman-Scire and Huber-Snyder building downwash treatments.     

Stable plume rise in a shear layer

Solutions are given for plume rise assuming a power-law wind speed profile in a stably stratified layer for point and finite sources with initial vertical momentum and buoyancy. For a constant wind speed, these solutions simplify to the conventional plume rise equations in a stable atmosphere. In a shear layer, the point of maximum rise occurs further downwind and is slightly lower compared with the plume rise with a constant wind speed equal to the wind speed at the top of the stack. If the predictions with shear are compared with predictions for an equivalent average wind speed over the depth of the plume, the plume rise with shear is higher than plume rise with an equivalent average wind speed.