Validation of ADMS against wind tunnel data of dispersion from chemical warehouse fires

Comparisons are presented of the predictions of the atmospheric dispersion modelling system (ADMS) and wind tunnel data for plume dispersion from chemical warehouse fires. The focus of the comparisons is dispersion from structurally intact buildings with open roofs and dispersion of plumes flush with the ground without obstacles, however, dispersion from building shells and doors is also considered. Both buoyancy driven and momentum driven flows are treated, although emphasis is on buoyancy driven flows as these are generally more likely to occur in warehouse fires. The study shows that the ADMS building module is able to reproduce many of the features of dispersion observed in the wind tunnel. These include a recirculating region behind the building in which material may be trapped, a main wake which brings material down towards the surface, and appropriate sensitivity to the buoyancy and momentum of the emitted material, and the location of sources on the building roof. The comparisons suggest that the ADMS building model can be used to predict dispersion from the stages of fire development studied. The precise level of agreement depends (but not in a systematic way) on the buoyancy flux parameter F_B, the momentum flux parameter F_M and the number of roof lights. There are some significant differences between the wind tunnel boundary layer and the simulated atmospheric boundary layer in ADMS which have to be considered when making wind tunnel model comparisons. These relate mainly to the near surface where the wind tunnel underestimates turbulent velocities, the boundary layer height which in the wind tunnel corresponds to an atmospheric boundary layer depth of 82.5 m (atmospheric boundary layers are frequently an order of magnitude deeper), and the boundary layer top where the ADMS boundary layer is capped by an inversion and has low turbulence levels whereas the wind tunnel boundary layer has higher levels of turbulence and no capping inversion.     

Meteorological Considerations in Air Quality Planning

Results from dispersion models which are routinely used for regulatory purposes do not reflect the uncertainties which are Inherent In the input data. To remedy this, a formula for propagating measurement uncertainties of emission rate, wind speed, wind direction, horizontal dispersion parameter, vertical dispersion parameter, effective emission height, and mixing depth is derived for EPA’s Industrial Source Complex Short Term (ISCST) Gaussian dispersion model for the simple case of a single stack-type source and nonbuoyant plume. Values for the uncertainties of the input variables are chosen and used to calculate ambient concentration uncertainties. These calculated uncertainties are compared with the standard deviation of ambient concentrations calculated from 2500 input data sets for each of four stability classes and three downwind distances, which were randomly altered to simulate the effects of measurement uncertainty. The calculated uncertainties do not differ significantly from the standard deviations of the randomized calculations for input data uncertainties as high as 30 percent and Stability Classes A-C. The calculated uncertainties overestimate the actual uncertainty of model calculations for input data uncertainties greater than 20 percent for Stability Class D.     

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.     

Overview of Petroleum Environmental Research Forum (PERF) dense gas dispersion modeling project

This paper provides a background for and an overview of the results of a comprehensive study of transport and dispersion of dense gas plumes over rough surfaces typical of industrial sites. The Petroleum Environmental Research Forum (PERF) 93-16 project involved model development and evaluations using observations from three wind tunnels and from the Kit Fox field experiment. Detailed discussions of the results of the research are given in the other papers in this special issue. The wind tunnel experiments produced data showing that the resulting best-fit vertical entrainment formula was close to (i.e., within about 30%) the vertical entrainment formulas already in use by current models, which were derived primarily from observations over smooth surfaces. Observations from the Kit Fox field experiment demonstrated the validity of the entrainment curves derived from the wind tunnel data. The Kit Fox data were also used to evaluate algorithms for along-wind dispersion and cloud advection speeds for short-duration releases typical of an industrial site, and to evaluate the HEGADAS dense gas dispersion model.     

Observations and predictions of jet diffusion flame behaviour

A simple model has been developed for jet diffusion flames to estimate flame height (h_f) and angle of the flame to the vertical (α_B). The model is based upon the assumption that flame behaviour is dominated by momentum effects. Buoyancy influences on behaviour are assumed to be negligible.Predictions of the model were assessed against flame parameters as observed in a wind tunnel and during field tests with an industrial flare. The wind tunnel studies involved experiments with hydrocarbon (methane, propane, ethylene, butane) diffusion flames. Field experiments involved measuring h_f and α_B of flames resulting from the combustion of acid gas-fuel gas mixtures possessing molecular weights of about 37 g mol⁻¹.The one-to-one correlation coefficient between predicted and observed behaviour resulting from combustion of all hydrocarbon fuels, except methane, was about 0.85. The model significantly underestimated flame heights for methane. This seems to have been due to the neglect of buoyancy effects which could be appreciable for this relatively light gas.Evaluation of results from the tests conducted with the industrial flare showed a one-to-one correlation coefficient between observed and predicted values of h_f to be 0.92. The corresponding magnitude for the correlation coefficient between observed and predicted values of α_B was only 0.71. A partial explanation for this relatively low correlation coefficient lies in the small range of α_B values contained in the population sample.     

Pseudo-source parameters for flares: Derivation,implementation, and comparison

The United States Environmental Protection Agency (US EPA) flare pseudo-source parameters are over 30 years old and few dispersion modellers understand their basis and underlying assumptions. The calculation of plume rise from the user inputs of pseudo-stack diameter, temperature and velocity have the most influence on air dispersion model predictions of ground-level concentrations. Regulatory jurisdictions across Canada, the United States and around the world have adopted their own approach to pseudo-source parameters for flares; all relate buoyancy flux to the heat release rate, none consider momentum flux and flare tip downwash as adopted by the Alberta Energy Regulator (AER). This paper derives the plume buoyancy flux for flares burning a gas in terms of combustion variables readily known or calculated without simplifying assumptions. Dispersion model prediction sensitivity to flared gas composition, temperature and velocity, and ambient conditions are now correctly handled by the AER approach. The AER flare pseudo-source parameters are based on both the buoyancy and momentum flux, thus conserving energy and momentum. The AER approach to calculate the effective source height for flares during varying wind speeds is compared to the US EPA approach. Instead of a constant source for all meteorological conditions, multiple co-located sources with varying effective stack height and diameter are used. AERMOD is run with the no stack tip downwash option as flare stack tip downwash is accounted for in the effective stack height rather than the AERMOD model calculating the downwash incorrectly using the pseudo-source parameters. The modelling approaches are compared for an example flare. Maximum ground level predictions change, generally increasing near the source and decreasing further away, with the AER flare pseudo-source parameters. It's time to update how we model flares.

Implications: What are the implications of continuing to model flare source parameters using the overly simplified US EPA approach? First, the regulators perpetuate the myths that the flare source height, temperature, diameter and velocity are constant for all wind speeds and ambient temperatures. Second, that it is acceptable to make simplifying assumptions that violate the conservation of momentum and energy principles for the sake of convenience. Finally, regulatory decisions based on simplified source modelling result in predictions that are not conservative (or realistic). The AER regulatory approach for flare source parameters overcomes all of these shortcomings. AERflare is a publicly available spreadsheet that provides the “correct” inputs to AERMOD.     

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.     

Turbulent Diffusion Behind Vehicles: Effect of Traffic Speed on Pollutant Concentrations

Recent theoretical and experimental investigations Indicate that turbulent diffusion behind moving vehicles Is Influenced by the speed of the vehicle. Vertical wake induced turbulent diffusion, explicitly treated in the numerical ROADWAY model, is proportional to the square of the wind speed relative to the moving vehicle. Hence, the model predictions of turbulent mixing and pollutant concentrations on and downwind of a roadway are dependent upon the traffic speed. It Is expected from theoretical considerations that the effect of vehicle speed on pollutant concentrations will be more significant during stable atmospheric conditions, because in neutral and unstable conditions the vehicle-wake turbulence is quickly masked by the ambient turbulence. In this study, experimental data are utilized to evaluate the theoretical predictions of the effects of traffic speed on the ambient pollutant concentrations. The effects of vehicle speed upon ambient concentrations are investigated through wind tunnel experiments and field studies that used dual tracers. Consistent with predictions of the ROADWAY model, data obtained near the Long Island Expressway indicate that the influence of traffic speed on the ambient pollutant concentrations Is not significant during unstable and neutral conditions. The Long Island experiment did not provide sufficient field data to assess the model predictions of the traffic speed effect during stable atmospheric conditions.     

An atmospheric dispersion model for the environmental impact assessment of thermal power plants in Japan--a method for evaluating topographical effects

An atmospheric dispersion model was developed for the environmental impact assessment of thermal power plants in Japan, and a method for evaluating topographical effects using this model was proposed. The atmospheric dispersion model consists of an airflow model with a turbulence closure model based on the algebraic Reynolds stress model and a Lagrangian particle dispersion model (LPDM). The evaluation of the maximum concentration of air pollutants such as SO2, NOx, and suspended particulate matter is usually considered of primary importance for environmental impact assessment. Three indices were therefore estimated by the atmospheric dispersion model: the ratios (alpha and beta, respectively) of the maximum concentration and the distance of the point of the maximum concentration from the source over topography to the respective values over a flat plane, and the relative concentration distribution [gamma(x)] along the ground surface projection of the plume axis normalized by the maximum concentration over a flat plane. The atmospheric dispersion model was applied to the topography around a power plant with a maximum elevation of more than 1,000 m. The values of alpha and beta evaluated by the atmospheric dispersion model varied between 1 and 3 and between 1 and 0.4, respectively, depending on the topographical features. These results and the calculated distributions of y(x) were highly similar to the results of the wind tunnel experiment. Therefore, when the slope of a hill or mountain is similar to the topography considered in this study, it is possible to evaluate topographical effects on exhaust gas dispersion with reasonable accuracy using the atmospheric dispersion model as well as wind tunnel experiments.     

Urban tracer dispersion experiments during the second DAPPLE field campaign in London 2004

As part of the DAPPLE programme two large scale urban tracer experiments using multiple simultaneous releases of cyclic perfluoroalkanes from fixed location point sources was performed. The receptor concentrations along with relevant meteorological parameters measured are compared with a three screening dispersion models in order to best predict the decay of pollution sources with respect to distance. It is shown here that the simple dispersion models tested here can provide a reasonable upper bound estimate of the maximum concentrations measured with an empirical model derived from field observations and wind tunnel studies providing the best estimate. An indoor receptor was also used to assess indoor concentrations and their pertinence to commonly used evacuation procedures.     

Validation of a Lagrangian model plume rise scheme using the Kincaid data set

Correct prediction of the initial rise of a plume due to momentum and buoyancy effects is an important factor in dispersion modelling. A new plume rise scheme, based upon conservation equations of mass, momentum and heat, for the Lagrangian model, NAME, is described. The conservation equations are consistent with the well-known analytical plume rise formulae for both momentum- and buoyancy-dominated plumes. The performance of the new scheme is assessed against data from the Kincaid field experiment. Results show that the new scheme adds value to the model and significantly outperforms the previous plume rise scheme. Using data from assessments of atmospheric dispersion models using the Kincaid data set, it is shown that NAME is comparable to other models over short ranges.     

Comparison of emission rate values for odour and odorous chemicals derived from two sampling devices

Field and laboratory measurements identified a complex relationship between odour emission rates provided by the US EPA dynamic emission chamber and the University of New South Wales wind tunnel. Using a range of model compounds in an aqueous odour source, we demonstrate that emission rates derived from the wind tunnel and flux chamber are a function of the solubility of the materials being emitted, the concentrations of the materials within the liquid; and the aerodynamic conditions within the device – either velocity in the wind tunnel, or flushing rate for the flux chamber. The ratio of wind tunnel to flux chamber odour emission rates (OU m^?2 s) ranged from about 60:1 to 112:1. The emission rates of the model odorants varied from about 40:1 to over 600:1.These results may provide, for the first time, a basis for the development of a model allowing an odour emission rate derived from either device to be used for odour dispersion modelling.     

An Atmospheric Dispersion Model for the Environmental Impact Assessment of Thermal Power Plants in Japan—A Method for Evaluating Topographical Effects

Abstract

An atmospheric dispersion model was developed for the environmental impact assessment of thermal power plants in Japan, and a method for evaluating topographical effects using this model was proposed. The atmospheric dispersion model consists of an airflow model with a turbulence closure model based on the algebraic Reynolds stress model and a Lagrangian particle dispersion model (LPDM). The evaluation of the maximum concentration of air pollutants such as SO₂, NO_x, and suspended particulate matter is usually considered of primary importance for environmental impact assessment. Three indices were therefore estimated by the atmospheric dispersion model: the ratios (α and β, respectively) of the maximum concentration and the distance of the point of the maximum concentration from the source over topography to the respective values over a flat plane, and the relative concentration distribution [γ(x)] along the ground surface projection of the plume axis normalized by the maximum concentration over a flat plane. The atmospheric dispersion model was applied to the topography around a power plant with a maximum elevation of more than 1000 m. The values of α and β evaluated by the atmospheric dispersion model varied between 1 and 3 and between 1 and 0.4, respectively, depending on the topographical features. These results and the calculated distributions of γ(x) were highly similar to the results of the wind tunnel experiment. Therefore, when the slope of a hill or mountain is similar to the topography considered in this study, it is possible to evaluate topographical effects on exhaust gas dispersion with reasonable accuracy using the atmospheric dispersion model as well as wind tunnel experiments.     

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.     

A vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel tests and its application in pollutant dispersion studies

A new vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel investigations was developed. The modeling concept is based on fluid dynamical similarity aspects and allows the small-scale modeling of various kinds of vegetation, e.g. field crops, shrubs, hedges, single trees and forest stands. The applicability of the modeling concept was validated in wind tunnel pollutant dispersion studies. Avenue trees in urban street canyons were modeled and their implications on traffic pollutant dispersion were investigated. The dispersion experiments proved the modeling concept to be practicable for wind tunnel studies and suggested to provide reliable concentration results. Unfavorable effects of trees on pollutant dispersion and natural ventilation in street canyons were revealed. Increased traffic pollutant concentrations were found in comparison to the tree-free reference case.     

CFD modelling of small particle dispersion: The influence of the turbulence kinetic energy in the atmospheric boundary layer

When considering the modelling of small particle dispersion in the lower part of the Atmospheric Boundary Layer (ABL) using Reynolds Averaged Navier Stokes simulations, the particle paths depend on the velocity profile and on the turbulence kinetic energy, from which the fluctuating velocity components are derived to predict turbulent dispersion. It is therefore important to correctly reproduce the ABL, both for the velocity profile and the turbulence kinetic energy profile.For RANS simulations with the standard k–ε model, Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the k–ε turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 46–47, 145–153.) proposed a set of boundary conditions which result in horizontally homogeneous profiles. The drawback of this method is that it assumes a constant profile of turbulence kinetic energy, which is not always consistent with field or wind tunnel measurements. Therefore, a method was developed which allows the modelling of a horizontally homogeneous turbulence kinetic energy profile that is varying with height.By comparing simulations performed with the proposed method to simulations performed with the boundary conditions described by Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the k–ε turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 46–47, 145–153.), the influence of the turbulence kinetic energy on the dispersion of small particles over flat terrain is quantified.     

A model for the maximum credible hourly impact on any ground receptor from point sources with thermal plume rise

A pollutant dispersion model is developed, allowing fast evaluation of the maximum credible 1-h average concentration on any given ground-level receptor, along with the corresponding critical meteorological conditions (wind speed and stability class) for stacks with buoyant plumes in urban or rural areas. Site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class, and mixing height. The analysis is based on the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings, respectively, the buoyancy induced dispersion correlation of Pasquill, the wind profile exponent values suggested by Irwin, the buoyant plume rise relations of Briggs, as well as the Benkley and Schulman's model for the minimum mixing heights. The model is particularly suited for air pollution management studies, as it allows fast screening of the maximum impact on any selected receptor and evaluation of the ways to have this impact reduced. It is also suited for regulatory purposes, as it can be used to define the minimum stack size requirements for a given source as a function of the exit gas volume and temperature, the pollutant emission rates and their hourly concentration standards, as well as the source location relative to sensitive receptors.     

A Review of Techniques Available for Estimating Short-Term NO2 concentrations

The Environmental Protection Agency is reviewing the need for a short-term NO₂ standard based on an averaging time of three hours or less. State Implementation plans and New Source Reviews will require air quality simulation techniques capable of estimating ambient NO₂ concentrations. There is a need for multi-source (urban) models and for point source models.

A review of currently available techniques for the estimation of NO₂ concentrations resulting from NO_x point sources is presented. The available methods include simple screening techniques and refined reactive plume models. The screening techniques first use a standard gaussian dispersion model to estimate the maximum 1 hr NO_x concentration caused by the source. The second step involves estimating the fraction of this NO* concentration occurring as NO₂.

Reactive plume models numerically simulate the simultaneous effects of dispersion and chemistry on NO₂ concentrations. Organic as well as inorganic reactions are incorporated. Reactive plume models should be used, where screening techniques indicate the potential for violation of the NO₂ standard.

Current generation reactive plume models neglect the effect of turbulent concentration fluctuation on NO₂ formation and use inappropriately large dispersion coefficients to estimate plume concentrations. Approaches being developed to resolve these problems are discussed.     

Numerical modeling on air quality in an urban environment with changes of the aspect ratio and wind direction

Due to heavy traffic emissions within an urban environment, air quality during the last decade becomes worse year by year and hazard to public health. In the present work, numerical modeling of flow and dispersion of gaseous emissions from vehicle exhaust in a street canyon were investigated under changes of the aspect ratio and wind direction. The three-dimensional flow and dispersion of gaseous pollutants were modeled using a computational fluid dynamics (CFD) model which was numerically solved using Reynolds-averaged Navier–Stokes (RANS) equations. The diffusion flow field in the atmospheric boundary layer within the street canyon was studied for different aspect ratios (W/H?=?1/2, 3/4, and 1) and wind directions (θ?=?90°, 112.5°, 135°, and 157.5°). The numerical models were validated against wind tunnel results to optimize the turbulence model. The numerical results agreed well with the wind tunnel results. The simulation demonstrated that the minimum concentration at the human respiration height within the street canyon was on the windward side for aspect ratios W/H?=?1/2 and 1 and wind directions θ?=?112.5°, 135°, and 157.5°. The pollutant concentration level decreases as the wind direction and aspect ratio increase. The wind velocity and turbulence intensity increase as the aspect ratio and wind direction increase.