Performance Evaluation of Integral and Analytical Plume Rise Algorithms

The purpose of this study was to evaluate the performance of current regulatory algorithms for predicting plume rise for refinerytype sources (short stacks and a wide range of source conditions) and the performance of new or alternate algorithms which may provide better estimates. To meet the objectives, five plume rise algorithms were statistically evaluated against ten field and laboratory plume rise data bases. Two forms of the Briggs plume rise equations were tested because they are almost exclusively used in current EPA regulatory models. Two modified Briggs equations were tested to assess how simple modifications can Improve the accuracy of the estimates. The fifth algorithm was a numerical solution to the basic equations for conservation of mass, momentum, and energy often referred to as an Integral plume rise algorithm. This algorithm was selected because It handles the wide range of source and atmospheric boundary-layer conditions that affect trajectories of plumes from refinery stacks.

Ten independent plume rise data bases were assembled that covered a wide range of source and meteorological conditions. From the data bases, a total of 107 different data sets were obtained and each data set included plume rise observations versus downwind distance for one source and meteorological condition. Each model was run for each data set and the root-mean-square and mean error between model and observation was computed for use in statistically evaluating model performance.

The statistical evaluation of the algorithms showed that the rms error (considering all data bases) for the Integral plume rise algorithm was approximately 30 percent less than the errors for all other algorithms tested. This difference was significant at the 95 percent confidence level. The results suggest that improved plume rise estimates in regulatory models applied to refineries and other appropriate sources could be achieved to reduce costs and improve ambient air quality estimates through the use of an integral plume rise algorithm.     

Validation of the UK Met. Office’s name model against the ETEX dataset

The ETEX 1 data set has been used to assess the performance of the UK Met Office’s long-range dispersion model NAME. In terms of emergency response modelling the model performed well, successfully predicting the overall spread and timing of the plume across Europe. However, in common with most other models, NAME overpredicted the observed concentrations. This is in contrast with other NAME validation studies which indicate either no significant bias or a tendency to underpredict concentrations. This suggests the reasons for overpredicting are specific to the ETEX situation. Explanations include inadequate vertical diffusion or transport, possible venting by convective activity, and experimental errors. An assessment of a range of advection schemes of varying complexity indicated no clear advantage, at present, in using more sophisticated random walk techniques at long range, a simple diffusion coefficient based scheme providing some of the best results. A brief look is also taken at a simulation of the more problematical ETEX 2 release.     

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.     

Modelling plume rise and dispersion from pool fires

This paper describes an investigation into the behaviour of smoke plumes from pool fires, and the subsequent generation of empirical models to predict plume rise and dispersion from such a combustion source. Synchronous video records of plumes were taken from a series of small-scale (0.06–0.25m²) outdoor methanol/toluene pool fire experiments, and used to produce sets of images from which plume dimensions could be derived. Three models were used as a basis for the multiple regression analysis of the data set, in order to produce new equations for improved prediction. Actual plume observations from a large (20.7 m×14.2 m) aviation fuel pool fire were also used to test the predictions. The two theoretically based models were found to give a better representation of plume rise and dispersion than the empirical model based on measurements of small-scale fires. It is concluded that theoretical models tested on small-scale fires (heat output ≈70 kW) can be used to predict plume behaviour from much larger combustion sources (heat output ≈70 MW) under near neutral atmospheric conditions.     

An advanced integral model for cooling tower plume dispersion

An advanced integral model is developed for predicting cooling tower plume rise from single natural draft cooling towers. The theoretical formulation of the model is aimed at avoiding many of the pitfalls and unnecessary assumptions of existing models. The model is based on a careful integration of the three-dimensional partial differential equations of conservation across the plume cross-section; radial profiles of temperature, velocity, and total water are assumed to be Gaussian in shape. The model includes a treatment of plume thermodynamics and tower downwash effects. The model has been calibrated with a wide range of laboratory data. Verification of the model with single-tower field data from Chalk Point, Paradise, Lünen, Gardanne and Philippsburg reveals good results.     

Control of Asphaltic Concrete Plants in Los Angeles County

Characteristics of maximum short-term ground level concentrations from an elevated point source, namely, the effective plume height, the critical wind speed, the distance to the point of maximum concentration, and the maximum concentration, are derived from the gaussian plume model. Both phases of plume development—before and after it has reached its final height—are considered. The plume rise treatment includes both thermal buoyancy and momentum effects. Certain limitations on critical wind speed are discussed. The dispersion model whose basis is established in this paper should be especially useful in applications where on site meteorological data are unavailable.     

Mathematical modeling of turbulent reacting plumes—I. General theory and model formulation

A new, comprehensive model for a chemically reacting plume is presented that accounts for the effects of incomplete turbulent macro- and micromixing on chemical reactions between plume and atmospheric constituents. The model is modular in nature, allowing for the use of different levels of approximation of the phenomena involved. The core of the model consists of the evolution equations for reaction progress variables appropriate for evolving spatially varying systems. These equations estimate the interaction of mixing and chemical reaction and require input parameters characterizing internal plume behavior, such as relative dispersion and fine scale plume segregation. The model addresses deficiencies in previous reactive plume models. Part II is devoted to atmospheric application of the model.     

Measurements and simulations of the visual effects of particulate plumes

In this paper we present field measurements of the visual effects of particulate plumes from two power plants and a copper smelter. The measurements were conducted at downwind distances ranging from 7 to 34 km and for sun-observer angles ranging from 40 to 160°. The visual effects of the power plant plumes were relatively small due to atmospheric dispersion (Kincaid power plant plume in February 1981) or hazy background (Labadie power plant plume in August 1981). The plume from the San Manuel smelter was more visible because of the clean environment. The measurements of plume contrasts range from − 0.15 to + 0.15. Further development of the EPA plume visibility model to improve the treatment of multiple scattering of light and incorporate light absorption by carbonaceous aerosols is described. Teleradiometer measurements and model simulations are in reasonable agreement for cases in which experimental uncertainties are small. The model appears to underpredict forward scattering of light by plume particles.     

Plume behaviors observed using lidar and SF6 tracer at a flat and hilly site

Two field experiments, one at Kincaid, IL, in flat terrain, the other at Bull Run, TN, in rolling terrain, were conducted under the auspices of the Electric Power Research Institute's (EPRI) Plume Model Validation and Development program. Simultaneous observations were made of ground-level SF₆ concentrations; plume cross-sections using light detection and ranging (lidar); turbulence; and routine meteorology at the surface and aloft. Due to terrain influences, surface wind-speeds at the Bull Run site were significantly lower than those at the Kincaid site, whereas thermal winds at Kincaid were generally larger than at Bull Run. At both sites, a reduction in turbulent intensity and an increase in atmospheric stability with height correlate with a substantial decrease in the rate of vertical plume dispersion. SF₆ ground-level concentration (GLC) patterns over distances of 1–50 km from the source were categorized by shape. The GLC patterns at Bull Run were frequently ‘blobby’, when significant GLCs occurred over an azimuth angle exceeding 90°, whereas patterns at Kincaid were generally coherent and nearly elliptical. Plume behavior was examined for 154 h during which both GLCs of SF₆ tracer and lidar cross-sections of the plume were of good quality. Results show that plume looping was rare at Kincaid, but occurred substantially more often at Bull Run (3%: 14%), with the reverse true for meandering (11%: 14%). Inversions that trapped plume material occurred much more often at Kincaid that at Bull Run (11%: <1%). Correlation of cross-wind concentration distributions of the plume aloft with those cross-wind SF₆ concentrations distributions at the ground were poor at both sites.     

Improving Plume Rise Prediction Accuracy for Stable Atmospheres with Complex Vertical Structure

Accurately predicting the rise of a buoyant exhaust plume is difficult when there are large vertical variations in atmospheric stability or wind velocity. Such conditions are particularly common near shoreline power plants. Simple plume rise formulas, which employ only a mean temperature gradient and a mean wind speed, cannot be expected to adequately treat an atmosphere whose lapse rate and wind velocity vary markedly with height. This paper tests the accuracy of a plume rise model which is capable of treating complex atmospheric structure because it integrates along the plume trajectory. The model consists of a set of ordinary differential equations, derived from the fluid equations of motion, with an entralnment parameterization to specify the mixing of ambient air into the plume. Comparing model predictions of final plume rise to field observations yields a root mean square difference of 24 m, which is 9 % of the average plume rise of 267 m. These predictions are more accurate than predictions given by three simpler models which utilize variants of a standard plume rise formula, the most accurate of the simpler models having a 12% error.     

Dry Removal of Gaseous Fluorine Pollutants

The conservation equations governing buoyant plume rise are solved for the case of non-uniform wind conditions. A power law is selected to represent the actual wind profile. Analytical solutions are presented both for uniformly stable and neutral atmospheric conditions. These solutions are shown to be of the same form as those obtained in the simpler uniform case but with the plume rise now depending explicitly on the wind speed shear. A sensitivity analysis of the effects on plume rise of typical variation in wind shear and entrainment reveals that the two quantities have an almost equal effect therefore justifying the use of the present model. To simplify computations a “uniform wind” is introduced such that when used in conjunction with Briggs' equations the results become consistent with those of the present theory.     

Plume Rise Determination-A New Technique Without Equations

Information on plume rise is important in determining the resulting concentrations of a pollutant on the ground. Practical use of plume rise values may be made in connection with stack design, the use of urban air pollution models, and in evaluating the hazards to a population complex.

This paper presents a new equationless technique for estimating plume rise as well as a comparison of seventeen commonly used plume rise formulas. Data from 10 sets of experiments, involving 615 observations and 26 different stacks, were used to study the relation between plume rise and related meteorological and stack parameters.

An independent data set was used to test the derived methods for determining plume rise. These data were obtained by Bringfelt of Sweden and contained measurements from stacks smaller than that at the Argonne National Laboratory to those approaching the TVA stacks.

A significant improvement in the prediction of plume rise from meteorological and stack parameters resulted from the use of a new technique called the Tabulation Prediction Technique. This is a method whereby an estimate of the value of a dependent variable may be obtained from information on the independent variables. Combinations of the independent variables—wind speed, heat emission rate, momentum rate, and stability—are arranged in an ordered sequence. For each combination of independent variables, the cumulative percentile frequency distribution of the dependent variable based on past measurements is given along with other statistics such as the mean, standard deviation, and interquartile range, i.e., the difference in plume rise between the 75th and 25th percentile values. Thus, one may look up the combination of independent variables just as one looks up words in a dictionary to obtain the percentile frequency distribution of the dependent variable. The mean, for each combination of independent variables may be considered as the best estimate for the given conditions.     

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.     

The Behavior of Buoyant Merging Plumes in The Rocky Mountain Foothills

Natural gas often contains high concentrations of hydrogen sulfide which must be removed before the gas can be transmitted by pipeline. Sour gas plants extract the sulfur, by converting it to elemental sulfur through a modified Claus process. The sulfur recovery is 93% for small plants (10–100 tonnes of sulfur per day) to 99% for large plants (1000–4000 tonnes of sulfur per day). The unrecovered sulfur is Incinerated giving rise to relatively small emissions of SO₂ characterized by high buoyancy and low momentum.

Using a unique aerial probing methodology, plume dispersion studies were conducted on two plants located fn the foothills of southwestern Alberta, Canada. These studies were generally conducted under neutral conditions and with westerly air flows typical of Chinook conditions. Notable variations of the plume dispersion parameters from accepted predictive values were found, indicating that such values cannot be used with confidence to estimate plume rise and dispersion in the mountain foothills.     

Observations Less than the Analytical Limit of Detection: A New Approach

Abstract

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.     

A simple model for the dispersion of pollutants from a road tunnel portal

The dispersion of pollutants from a roadway tunnel portal is mainly determined by the interaction between the ambient wind and the jet stream from the tunnel portal. In principal, Eulerian microscale models by solving the conservation equations for mass, momentum, and energy, are thus able to simulate effects such as buoyancy etc. properly. However, for engineering applications such models need too much CPU time, and are not easy to handle by non-scientific personnel. Only a few dispersion models, applicable for regulatory purposes, have so far appeared in the literature. These models are either empirical models not always applicable for different sites, or they do not capture important physical effects like buoyancy phenomena. Here, a rather simple model is presented, which takes into account most of the important processes considered to govern the dispersion of a jet stream from portals. These are the exit velocity, the buoyancy, the influence of ambient wind direction fluctuations on the position of the jet stream, and traffic induced turbulence. Although the model contains some heuristic elements, it was successfully tested against tracer experiments taken near a motorway tunnel portal in Austria. The model requires relatively little CPU time. Current limitations of the model include the neglect of terrain, building, and vehicle effects on the dispersion, and the neglect of the horizontal dispersion arising from entrainment of ambient air in the jet stream. The latter could lead to an underestimation of plume spreads for higher wind speeds. The validation of the model will be the focus of future research. The experimental data set is also available for the scientific community.     

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.     

Modeling Emissions from Elevated Cylindrical Bins

Abstract

This paper demonstrates how wind tunnel modeling data that accurately describe plume characteristics near an unconventional emission source can be used to improve the near-field downwind plume profiles predicted by conventional air pollution dispersion models. The study considers a vertical, cylindrical-shaped, elevated bin similar to large product storage bins that can be found at many industrial plant sites. Two dispersion models are considered: the U.S. Environmental Protection Agency's ISC2(ST) model and the Ontario Ministry of the Environment and Energy's GAS model. The wind tunnel study showed that plume behavior was contrary to what was predicted using conventional dispersion models such as ISC2(ST) and GAS and default values of input parameters. The wind tunnel data were used to develop a protocol for correcting the dispersion models inputs, resulting in a substantial improvement in the accuracy of the dispersion estimates.