Applied dispersion modelling based on meteorological scaling parameters

A method for calculating the dispersion of plumes in the atmospheric boundary layer is presented. The method is easy to use on a routine basis. The inputs to the method are fundamental meteorological parameters, which act as distinct scaling parameters for the turbulence. The atmospheric boundary layer is divided into a number of regimes. For each scaling regime we suggest models for the dispersion in the vertical direction. The models directly give the crosswind-integrated concentrations at the ground, x_y, for nonbuoyant releases from a continuous point source. Generally the vertical concentration profile is proposed to be other than Gaussian. The lateral concentration profile is always assumed to be Gaussian, and models for determining the lateral spread σ_y are proposed. The method is limited to horizontally homogeneous conditions and travel distances less than 10km. The method is evaluated against independent tracer experiments over land. The overall agreement between measurements and predictions is very good and better than that found with the traditional Gaussian plume model.     

KAPPA-G,A Non-Gaussian Plume Dispersion Model: Description and Evaluation Against Tracer Measurements

This paper presents a mixed methodology for the simulation of atmospheric disperson phenomena in which vertical diffusion is computed using an analytical solution of the K-theory equation, while horizontal diffusion is simulated by the Gaussian formula. This new formulation, while maintaining a simple analytical form for the concentration field, incorporates the effects of power-law vertical profiles of both wind speed and eddy diffusivity. The performance of this approach, which has been implemented into a full computer package (KAPPA-G), is evaluated by comparison with data from SF₆ tracer experiments.     

Sensitivity of the DERMA long-range Gaussian dispersion model to meteorological input and diffusion parameters

The Danish Emergency Response Model of the Atmosphere (DERMA) is described and applied to the first ETEX experiment. By using analysed low-resolution numerical weather-prediction data from the global model of the European Centre for Medium-range Weather Forecast (ECMWF) as well as higher-resolution data from two versions of the High Resolution Limited Area Model (HIRLAM), which are operational at the Danish Meteorological Institute (DMI), the sensitivity of DERMA to the resolution of meteorological data is analysed by comparing DERMA results with concentration measurements. Furthermore, the sensitivity to boundary-layer height and diffusion parameters is studied. These parameters include the critical bulk Richardson number, which is used to estimate the atmospheric boundary-layer height, the horizontal eddy diffusivity and the Lagrangian turbulence time scale. The parameters, which provide the best performance of DERMA, are 0.25 for the critical bulk Richardson number, 6×10³ m² s^-1 for the horizontal eddy diffusivity, and 3 h for the Lagrangian time scale. DERMA is much more sensitive to boundary-layer parameters when using high-resolution DMI-HIRLAM data than when using data of lower resolution from the ECMWF. Finally, the bulk Richardson number method of boundary-layer height calculation applied to DMI-HIRLAM data is verified directly against routine radiosondes released under the tracer gas plume. The boundary-layer height estimates based on analysed NWP model data agree well with observations, and the agreement deteriorates as a function of forecast length.     

Evaluation of a Gaussian and a Lagrangian model against a roadside data set,with emphasis on low wind speed conditions

The evaluation of the high percentiles of concentration distributions is required by most national air quality guidelines, as well as the EU directives. However, it is problematic to compute such high percentiles in stable, low wind speed or calm conditions. This study utilizes the results of a previous measurement campaign near a major road at Elimäki in southern Finland in 1995, a campaign specifically designed for model evaluation purposes. In this study, numerical simulations were performed with a Gaussian finite line source dispersion model CAR-FMI and a Lagrangian dispersion model GRAL, and model predictions were compared with the field measurements. In comparison with corresponding results presented previously in the literature, the agreement of measured and predicted data sets was good for both models considered, as measured using various statistical parameters. For instance, considering all NO_x data (N=587), the so-called index of agreement values varied from 0.76 to 0.87 and from 0.81 to 1.00 for the CAR-FMI and GRAL models, respectively. The CAR-FMI model tends to slightly overestimate the NO_x concentrations (fractional bias FB=+14%), while the GRAL model has a tendency to underestimate NO_x concentrations (FB=−16%). The GRAL model provides special treatment to account for enhanced horizontal dispersion in low wind speed conditions; while such adjustments have not been included in the CAR-FMI model. This type of Lagrangian model therefore predicts lower concentrations, in conditions of low wind speeds and stable stratification, in comparison with a standard Lagrangian model. In low wind speed conditions the meandering of the flow can be quite significant, leading to enhanced horizontal dispersion. We also analyzed the difference between the model predictions and measured data in terms of the wind speed and direction. The performance of the CAR-FMI model deteriorated as the wind direction approached a direction parallel to the road, and for the lowest wind speeds. However, the performance of the GRAL model varied less with wind speed and direction; the model simulated better the cases of low wind speed and those with the wind nearly parallel to the road.     

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.     

An analytical model for crosswind integrated concentrations released from a continuous source in a finite atmospheric boundary layer

An analytical model for the crosswind integrated concentrations released from a continuous source in a finite atmospheric boundary layer is formulated by considering the wind speed as a power law profile of vertical height above the ground and eddy diffusivity as an explicit function of downwind distance from the source and vertical height. A closed form analytical solution of the resulting advection–diffusion equation for these profiles of wind speed and eddy diffusivity with the physically relevant boundary conditions is derived using the separation of variables technique that leads to a Sturm–Liouville eigen value problem. Various particular cases of the model are deduced.The model is evaluated with the observations obtained from Prairie Grass experiment in various stability classes varying from very unstable to neutral and stable conditions and Hanford diffusion experiment in stable conditions. The agreement is found to be good between the computed and observed concentrations in both the diffusion experiments. For Prairie Grass experiment, the model is predicting 78% cases with in a factor of two and gives a value of NMSE as 0.075. On the other hand, for Hanford observations in stable conditions, it predicts 70% cases with in factor of two. An extensive analysis of statistical measures with the downwind distances from the source reveals that the model is performing well close to the source.     

Modeling Short Range Air Dispersion from Area Sources of Non-buoyant Toxics

A model based on K-theory has been developed for describing the short range air dispersion from area sources of non-buoyant toxics. Model parameter estimation is via boundary layer theory. Lateral dispersion by plume meander is considered but ail other sources of horizontal dispersion are neglected. The model can be applied on and near area sources and it can be adapted for predictions of downwind concentrations with a wide variety of meteorological Inputs.

The model has been evaluated by simulating the data obtained during atmospheric tracer studies and by comparison to vinyl chloride concentrations near the BKK landfill in southern California. The model appears to represent a useful and accurate tool for regulatory planning and risk assessment close to area sources of toxics.     

A multi-layer model for pollutant dispersion with dry deposition to the ground

This paper presents a semi-analytical solution for the steady advection–diffusion equation that allows simulating the vertical turbulent dispersion of air pollution with deposition to the ground. The performances of the solution, with a proper parameterization of the vertical profiles of wind and eddy diffusivity, were evaluated against Hanford diffusion experiment dataset using two tracers (Doran and Horst, 1985): a non-depositing gas (SF₆) and depositing particles (ZnS). Results show that the dispersion model with the K-parameterization included produces a good fitting of the measured ground-level concentration data and there are no big differences between the parameterizations taken from literature. A comparison with other models was shown and discussed.     

Numerical simulation of flow and dispersion around an isolated cubical building: The effect of the atmospheric stratification

The aim of this work is to investigate atmospheric flow and dispersion of contaminants in the vicinity of single buildings under different stability conditions. The mathematical model used is based on the solution of equations of conservation of mass, linear momentum and energy with the use of a non-standard κ–? turbulence model. The modifications proposed in the κ–? model are the inclusion of the Kato and Launder correction in the production of turbulent kinetic energy and the use of a modified wall function. Results are presented of numerical simulations of dispersion around a cubical obstacle, under neutral, stable and unstable atmospheric conditions. Experimental data from wind tunnel and field trials obtained by previous authors are used to validate the numerical results. The numerical simulation results show a reasonable level of agreement with field and wind tunnel concentration data. The deviation between model results and field experimental data is of the same order as the deviation between field and wind tunnel data.     

Application of HYDRUS 1D model for assessment of phenol–soil adsorption dynamics

Laboratory-scale batch, vertical, and horizontal column experiments were conducted to investigate the attenuative capacity of a fine-grained clayey soil of local origin in the surrounding of a steel plant wastewater discharge site in West Bengal, India, for removal of phenol. Linear, Langmuir, and Freundlich isotherm plots from batch experimental data revealed that Freundlich isotherm model was reasonably fitted (R ²?=?0.94). The breakthrough column experiments were also carried out with different soil bed heights (5, 10, and 15 cm) under uniform flow to study the hydraulic movements of phenol by evaluating time concentration flow behavior using bromide as a tracer. The horizontal migration test was also conducted in the laboratory using adsorptive phenol and nonreactive bromide tracer to explore the movement of solute in a horizontal distance. The hydrodynamic dispersion coefficients (D) in the vertical and horizontal directions in the soil were estimated using nonlinear least-square parameter optimization method in CXTFIT model. In addition, the equilibrium convection dispersion model in HYDRUS 1D was also examined to simulate the fate and transport of phenol in vertical and horizontal directions using Freundlich isotherm constants and estimated hydrodynamic parameters as input in the model. The model efficacy and validation were examined through statistical parameters such as the coefficient of determination (R ²), root mean square error and design of index (d).     

Simulation of the evolution of particle size distributions containing coarse particulate in the atmospheric surface layer with a simple convection-diffusion-sedimentation model

The Fugitive Dust Model (FDM) and Industrial Source Complex (ISC), widely used coarse particulate dispersion models, have been shown inaccurate due to the neglect of vertical variations in atmospheric wind speed and turbulent diffusivity (Vesovic et al., 2001), omission of the gravitational advection velocity, and an underestimation of the ground deposition velocity (Kim and Larson, 2001). A simple, transient two-dimensional convection-diffusion-sedimentation model is proposed to simulate the evolution in particle size distribution of an aerosol ‘puff’ containing coarse particulate in the atmospheric surface layer. Monin-Okhubov similarity theory, accompanied by empirical observations made by Businger et al. (1971), is adopted to characterize the surface layer wind speed and turbulent diffusivity profiles over a wide range of atmospheric conditions. A first order analysis of the crossing trajectories effect suggests simulation data presented here are not significantly affected by particle inertia. The model is validated against Suffield experimental data in which coarse particulate deposition was measured out to a distance of 800 m from the source (Walker, 1965). Good agreement is found for the decay in ground deposits with distance from the source for stable atmospheres. Deposition data was also simulated for unstable atmospheric stratification and the current model was determined to modestly underestimate the peak concentration with increasing accuracy further downwind of the release. The current model's effective deposition velocity was compared to that suggested by Kim et al. (2000) and shows improvement with respect to FDM. Lastly, the model was used to simulate the dispersion of nine lognormal aerosol puffs in the lowest 50 m of the atmospheric surface layer for four classes of atmospheric stability. The simulated mass median aerodynamic diameters (MMAD) at multiple downwind sampling locations were calculated and plotted with distance from the source. The first 50 m from the source was found to have a substantial impact on the evolution of MMAD for stable atmospheric conditions. Away from the source, it was observed that particle size distributions were truncated by removal of all particles larger than about 60 μm. A particle Peclet number was also defined to quantify the relative importance of turbulent dispersion and sedimentation on particle motion in the vertical direction.     

Mathematical modelling of flue-gas desulphurisation using lime slurry in a turbulent contact absorber

A mathematical model has been developed for absorption of SO₂ from flue gases using lime slurry in Turbulent Contact Absorbers (TCA). In this model, the TCA was simulated by considering it as a falling film absorption system. Turbulent effects were taken into account by using eddy viscosity and eddy diffusivity. The system of partial differential equations of mass transfer with moving boundaries was solved numerically in order to obtain the concentration profiles of the reactants, the thickness of the reaction zone and the outlet gas concentration. A bench-scale TCA was built up, and the mathematical model was evaluated against experimental data obtained from the built device. The model predictions showed good agreement with the experimental data and literature data.     

Effects of wind shear on pollution dispersion

Using an accurate numerical method for simulating the advection and diffusion of pollution puffs, it is demonstrated that point releases of pollution grow into a shape reflecting the vertical wind shear profile experienced by the puff within a time scale less than 4 h. For distances beyond several 10 s of kilometers from a release point, shear-related dispersion effects are probably the dominant mechanism affecting the area and magnitude of surface impacts. For assessing long-range pollutant dispersion, the common assumption that pollutants disperse as horizontally spherical “puffs” in the atmosphere is inherently inaccurate since shear-induced horizontal spreading of pollution is not a homogeneous “turbulent-like” diffusion process. A Lagrangian puff model can simulate an area impacted by a pollution puff only if larger shear-dependent horizontal puff dispersions are assumed. However, even if impacted areas are reasonably simulated, peak concentrations will be severely underestimated since atmospheric puffs influenced by even small amounts of wind shear are nonspherical. If horizontal dispersion coefficients in a Lagrangian puff model are adjusted so that peak concentrations are correctly simulated, then the calculated pollution impact area will be severely skewed. In shear environments, no choice of horizontal dispersion coefficients in a single-puff Lagrangian model will yield reasonable correlations with puffs that are skewed into nonspherical shapes by atmospheric wind shear.     

A Gaussian puff model with optimal interpolation for air pollution modelling assessment

A Gaussian plume model was modified to simulate the dispersion of non-reactive air pollutants under non-homogeneous wind conditions through a multi-puff approach. It was applied to the city of Lisbon and evaluated by comparison with measured sulphur dioxide data, showing a reasonable skill to estimate the transport and dispersion of pollutants under complex wind field and different atmospheric conditions. The modelling results were integrated with observed data, based on correlation functions determined from historical values, to obtain the improved analytical results by using optimal interpolation. A significant improvement over the predictions by the Gaussian puff model alone was achieved.     

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.     

Numerical simulation of scalar dispersion downstream of a square obstacle using gradient-transport type models

We present a numerical study of scalar transport released from a line source downstream of a square obstacle to investigate the capabilities and limitations of gradient-transport modeling in predicting atmospheric dispersion. The standard k–? and k–ω models and a Reynolds Stress Transport closure are employed and compared to predict the time-averaged turbulent flow field, while a standard gradient–diffusion model is initially adopted to relate the scalar flux to mean gradients of the concentration field. The analysis of two algebraic closures for turbulent scalar fluxes based on the generalized-gradient–diffusion hypothesis and its quadratic extension is also presented. In spite of the rather simple flow setup, where both the flow and the scalar fields can be assumed homogeneous in the spanwise direction, the analysis clarifies several critical issues concerning gradient-transport type models. We established the dominant role of predicted turbulent kinetic energy on scalar dispersion when a scalar diffusivity is employed, irrespectively of the Reynolds stress closure adopted for the averaged momentum equation. Moreover, the standard gradient–diffusion hypothesis failed to predict the streamwise component of the scalar flux, which is characterized by a counter-gradient-transport mechanism. Although the resulting contribution in the averaged scalar transport equation is small in the present flow configuration, this limitation can become severe for strongly inhomogeneous flows in the presence of point sources, where the spread of the scalar plume is essentially three-dimensional. The predictive capabilities of gradient-transport type modeling are found clearly improved using algebraic closures, which appear to represent a promising tool for predicting atmospheric dispersion in complex flows when unsteady transport mechanisms are not dominant.     

Simple PDF models for convectively driven vertical diffusion

The mode of vertical velocity in convective boundary layers (CBLs) is usually negative and the probability distribution function (PDF) of w, P_w, is rarely symmetric except near the top and bottom of CBLs. Consequently, vertical diffusion from elevated sources is usually asymmetric and exhibits a descending mode of concentration, causing higher peak surface concentrations than predicted by Gaussian models. The main concentration (χ) effects, we argue, can be modeled using the simplest of PDF diffusion models, with tracers responding to P_w at the source height with straight line trajectories and simple reflection at the surface and z_i, the mixing depth. The critical element is the choice of P_w. Two P_w models are offered, a bi-Gaussian (BG) and a Gaussian-ramp (GR) formulation. Both have some observational support, and the resulting PDF models are mathematically tractable. Analytical solutions for key variables are given; these show some surprising contrasts between the BG and GR models, but both can approximate laboratory and numerical modeling results for ∝χdy patterns. A diverse selection of atmospheric turbulence measurements is presented; for measures that reflect asymmetry in P_w, the data show wide ranges and do not lend support to any particular form of P_w. Recent lidar measurements of oil fog plumes are presented that show a large variability in ∝χdy patterns, even with substantial averaging periods. The only concurrent turbulence measurement that strongly correlates with the observed vertical diffusion of oil fog is the mode of wind elevation angle. A simple adaptation of the BG model is recommended that fits the average peak ∝χdy and distance of occurrence as observed so far.     

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.     

Modeling Atmospheric Mercury Deposition in the Vicinity of Power Plants

Abstract

Two mathematical models of the atmospheric fate and transport of mercury (Hg), an Eulerian grid–based model and a Gaussian plume model, are used to calculate the atmospheric deposition of Hg in the vicinity (i.e., within 50 km) of five coal–fired power plants. The former is applied using two different horizontal resolutions: coarse (84 km) and fine (16.7 km). More than 96% of the power plant Hg emissions are calculated with the plume model to be transported beyond 50 km from the plants. The grid–based model predicts a lower fraction to be transported beyond 50 km: >91% with a coarse resolution and >95% with a fine resolution. The contribution of the power plant emissions to total Hg deposition within a radius of 50 km from the plants is calculated to be <8% with the plume model, <14% with the Eulerian model with a coarse resolution, and <10% with the Eulerian model with a fine resolution. The Eulerian grid–based model predicts greater local impacts than the plume model because of artificially enhanced vertical dispersion; the former predicts about twice as much Hg deposition as the latter when the area considered is commensurate with the resolution of the grid–based model. If one compares the local impacts for an area that is significantly less than the grid–based model resolution, then the grid–based model may predict lower local deposition than the plume model, because two compensating errors affect the results obtained with the grid–based model: initial dilution of the power plant emissions within one or more grid cells and enhanced vertical mixing to the ground.     

Modeling atmospheric mercury deposition in the vicinity of power plants

Two mathematical models of the atmospheric fate and transport of mercury (Hg), an Eulerian grid-based model and a Gaussian plume model, are used to calculate the atmospheric deposition of Hg in the vicinity (i.e., within 50 km) of five coal-fired power plants. The former is applied using two different horizontal resolutions: coarse (84 km) and fine (16.7 km). More than 96% of the power plant Hg emissions are calculated with the plume model to be transported beyond 50 km from the plants. The grid-based model predicts a lower fraction to be transported beyond 50 km: >91% with a coarse resolution and >95% with a fine resolution. The contribution of the power plant emissions to total Hg deposition within a radius of 50 km from the plants is calculated to be <8% with the plume model, <14% with the Eulerian model with a coarse resolution, and <10% with the Eulerian model with a fine resolution. The Eulerian grid-based model predicts greater local impacts than the plume model because of artificially enhanced vertical dispersion; the former predicts about twice as much Hg deposition as the latter when the area considered is commensurate with the resolution of the grid-based model. If one compares the local impacts for an area that is significantly less than the grid-based model resolution, then the grid-based model may predict lower local deposition than the plume model, because two compensating errors affect the results obtained with the grid-based model: initial dilution of the power plant emissions within one or more grid cells and enhanced vertical mixing to the ground.