On the Evaluation of Predictions from a Gaussian Plume Model

The performance of a CRSTER equivalent Gaussian plume model (CEQM) is examined using data from the EPRI Plume Model Validation study at the Klncaid, Illinois site. Four-way comparisons are made on the ordered statistics or the cumulative frequency distribution (CFD) of maximum hourly observed and predicted concentrations. Using the uniform random distribution and the lognormal random distribution as simple predictive schemes without any physical context, it Is found that the CEQM predicts a concentration CFD which matches the observed CFD significantly closer than the CFD predicted by the uniform random distribution. The two-parameter lognormal random distribution predicts the concentration CFD better than the CEQM over all concentration ranges; however, the CEQM fits the upper range of the concentration distribution better than the lognormal random distribution,, despite the fact that the predictions are generated using dispersion conditions entirely different from those of the observations. The nature of this ergodicity of distribution is probed by exercising CEQM using randomized input based on the observed frequency distributions of the Input parameters instead of feeding the hour-by-hour model input matched by time into CEQM as is customarily done. The exercise of the model by uncoupling the time linkage in model Input has no systematic effect on the predicted cumulative frequency distribution of concentrations. Only at the highest concentration range (99.5% or higher) do the two sets of predictions begin to diverge.     

A Plume Rise Model Compared with Observations

Dimensional arguments are used to predict plume rise for buoyant plumes in both stable and neutral air, for both calm and windy conditions. Dominant terms are assumed to be windpseed ū, “buoyancy flux” F (proportional to heat efflux), and a stability parameter s (proportional to potential temperature gradient). Observations presented support the dimensional analysis predictions, except that for final rise in a neutral atmosphere they are adeauate only for a conservative estimate of rise. The method is extended to predict maximum ground concentration of effluent gases in the worst situations {windy neutral and fumigation) for open country, valleys, and “canyons.” These predictions are compared ivith limited observations.     

Estimation of Methyl tert -Butyl Ether Plume Length Using the Domenico Analytical Model

Methyl tert -butyl ether (MTBE) plume is controlled by many factors, primarily by groundwater flow velocity, dispersion, natural attenuation. This study employed an analytical model introduced by Domemico (1987, J. Hydrol 91 , 49-58.) to describe the MTBE concentration distribution horizontal pattern and estimated the MTBE plume length. The model was applied to 90 leaking underground storage tank cases in Los Angeles, CA, U.S.A. The analytical model was calibrated with field data for each ease using a Microsoft Excel spreadsheet program. Methyl tert -butyl ether concentrations in one source monitoring well and one to two downgradient centerline monitoring wells were used for each case study. When the centerline well is not available, the closest off-centerline wells were projected to the centerline using an ellipse trigonometry method. The model parameter values for longitudinal dispersivity, groundwater velocity, and degradation rate constant were calibrated using the field data and then used to estimate the maximum distance between source well and the plume edge. This study demonstrates that the Domenico model can be applied to MTBE plume investigation when adequate field data are available. The correlation coefficients calculated based on the results of the 90 case studies indicate that MTBE plume length has a poor correlation with MTBE concentration at the source well, and a moderate negative correlation with the degradation rate constant ( m 0.65) and u / v ratio (0.64). Furthermore, MTBE plume length has a poor correlation with the longitudinal dispersivity ( m 0.4), hydraulic gradient ( m 0.1), and groundwater velocity (0.17).     

Simulation of Stack Plume Opacity

ABSTRACT

The visual impact of primary particles emitted from stacks is regulated according to stack opacity criteria. In-stack monitoring of the flue gas opacity allows plant operators to ensure that the plant meets U.S. Environmental Protection Agency opacity regulations. However, the emission of condensable gases such as SO₃ (that hydrolyzes to H₂SO₄), HCl, and NH₃, which may lead to particle formation after their release from the stack, makes the prediction of stack plume opacity more difficult.

We present here a computer simulation model that calculates the opacity due to both primary particles emitted from the stack and secondary particles formed in the atmosphere after the release of condensable gases from the stack. A comprehensive treatment of the plume rise due to buoyancy and momentum is used to calculate the location at which the condensed water plume has evaporated (i.e., where opacity regulations apply).

Conversion of H₂SO₄ to particulate sulfate occurs through nucleation and condensation on primary particles. A thermodynamic aerosol equilibrium model is used to calculate the amount of ammonium, chloride, and water present in the particulate phase with the condensed sulfate. The model calculates the stack plume opacity due to both primary and secondary particles. Examples of model simulations are presented for three scenarios that differ by the emission control equipment installed at the power plant: (1) electrostatic precipitators (ESP), (2) ESP and flue gas desulfurization, and (3) ESP and selective catalytic reduction. The calculated opacity is most sensitive to the primary particulate emissions. For the conditions considered here, SO₃ emissions showed only a small effect, except if one assumes that most H₂SO₄ condenses on primary particles. Condensation of NH₄Cl occurs only at high NH₃ emission rates (about 25 ppm stack concentration).     

Formation and Transport of the Madrid Ozone Plume

Abstract

The main results of an experimental study focusing on the formation and transport of photochemical pollution in the Madrid air basin are presented. This southern European, heavily populated urban area is located on an elevated plateau at a height of 700 m, near a mountain range with maximum heights of around 2,400 m. Daily and seasonal cycles of ozone were documented during a one-year survey at three semi-rural sites located 30 km away from the urban center. Maximum hourly values of up to 140 ppb were measured, and the ozone generated within the urban plume on polluted days (when values exceeded 90 ppb) has been estimated at around 40-50 ppb.A meteorological characterization of these smoggy days pointed out the influence of thermally induced local wind flows on the concentration daily cycles at the measuring sites, denoting a preferred advection of the urban plume. Moreover, during intensive summer field campaigns, the use of meteorological and ozone sondes, as well as an instrumented aircraft, revealed some features about the horizontal and vertical distribution of the polluted air masses, as well as their evolution within the planetary boundary layer. Ozone plumes have been detected up to 100 km away from the city, usually mixed in a layer that reaches a height of 1,000-1,500 m in the afternoon. On some occasions, ozone-enriched layers have been detected as high as 4,000 m during morning hours, suggesting possible tropospheric injection induced by topographydriven flows or convective mesoscale systems that are usually present in the center of the Iberian Peninsula in the summer.     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.     

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.     

Lidar Observations of the Diurnal Behavior of the Cumberland Power Plant Plume

Mobile lidar observations were made downwind of TVA’s Cumberland (Tennessee) power plant as part of the STATE (Sulfur Transport and Transformation in the Environment) program. Vertical profiles of aerosol backscatter have been processed and displayed to show plume structure as an intensity-modulated TV presentation. Available meteorological data, especially the pilot balloon and radiosonde measurements collected during the STATE experiment, have been used to aid in the interpretation of the lidar display. The data show: ? Well defined nighttime plumes, which often tilt or display a layered structure in the shape of a “>”.

? Late morning convective breakup of the plume.

? Well mixed convective plumes during the day.

? Reformation of the layered nighttime plume during the late afternoon.

It appears that the nighttime plume behavior can be related qualitatively to the strong directional shear of the wind with height that often accompanies the stable nighttime atmosphere. The nighttime plume shapes frequently differ markedly from the oval shape one expects of a gaussian plume. Daytime plumes are in better conformance to the expected shape except when constricted by the surface or the top of the mixing layer     

A Correlation of Field Observations of Plume Rise

Data from 137 sets of plume observations, comprising nearly 1 500 data points, are correlated with two simple formulae. These formulae, one for the buoyancy-dominated rise region and the other for the stratification-dominated levelled-off region of a plume, represent an approximate form of the entrainment theory of Hoult, et al. (1968)¹ for the case of uniform atmospheric stratification and zero wind shear. The observations, which are those of the Tennessee Valley Authority and of Bringfelt (1968),⁶ were made of plumes whose source strengths ranged from 0.4 to 111 Mw and which were emitted from stacks of heights between 21 and 183 m. The two formulae are found to correlate the data equally well over all values of the stack exit and meteorological parameters, provided only that the bulk mean velocity of the stack gases exceeds the mean wind speed by at least 20%. The ratio of observed to calculated plume rise is found to be distributed log normally about the mean value.

The median rise at large distances downstream was found to differ insignificantly from that given by the effective stack height formula recommended recently¹¹ for large buoyant plumes. Based upon the correlation, two formulae are recommended for computing median plume rise at all distances downstream of the stack. The formulae include an estimate of the expected uncertainty in the predicted rise.     

Plume Rise Estimates for Electric Generating Stations

The Tennessee Valley Authority, under sponsorship of the Public Health Service, National Air Pollution Control Administration, initiated a comprehensive study entitled “Full-Scale Study of Plume Rise at Large Electric Generating Stations” in 1963. The variability of plant sizes, stack heights, and stack configurations accommodated full-scale assessment of plume rise over a wide range of meteorological and operational conditions.     

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.     

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.