Lagrangian Particle Dispersion Research Articles

Lagrangian particle dispersion (HYSPLIT) model analysis of the sea breeze case with extreme mean daily PM10 concentration in Split, Croatia.

The case of a sea breeze where the mean daily PM10 concentration reached the recommended limit value for human health for the period from 2007 to 2009 at the air quality station AMS3 Split-1 in Split, Croatia, is analysed. The Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) atmospheric model MM5 and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model are used to simulate the lower atmospheric flow and dispersion within 100km from the coast. The simulation is made with four point sources in the hinterland of Split: Kaštel-Sućurac, Solin and Klis, where the local cement plants are located, and Vranjic, where an asbestos-cement plant is located. Statistical analysis and rotational statistics showed good agreement of the measurement data with the modelled wind speed and direction at 10m and temperature at 2m height. The backward trajectories show that the pollutants are caught in the sea breeze circulation from all sources and in the early afternoon the plume is placed over parts of Split from all sources. From the peak concentrations during the selected day, it can be concluded that pollution from Kaštel-Sućurac had the greatest impact on the high PM10 concentrations measured at the Split-1 station.

Вибір моделей поширення радіоактивних аерозолів усередині й зовні нового безпечного конфайнмента Чорнобильської АЕС

The New Safe Confinement (NSC) is a facility that protects the environment from radioactive aerosols (RA) during the extraction of radioactive materials. However, it is not able to provide complete insulation of the internal volume, therefore, to reduce the damage. It is necessary to use auxiliary means, such as ventilation, a special microclimate inside, etc., but this reduces, not eliminates RA leaks. The paper considers approaches for control and the possibility of minimizing RA emissions by simultaneous modeling of the distribution of RA both inside a relatively small volume of the NSC of the Chornobyl NPP (ChNPP) using an internal model, and in the vicinity of the NSC with the help of an external model. The internal and external models are significantly different because RA inside the NSC are distributed by convective air currents very slowly and settle on an area of approximately 0.03 km2 , while outside of the ChNPP industrial site they are intensively distributed by fast multidirectional wind currents and settle on a significant area of approximately 3 km2. This leads to significant differences in the requirements to internal and external models. Differences were found in such categories as parameters of RA source, topology and dimensions of simulation volume, time step for transient simulation, computation speed requirements, spatial resolution of the mesh etc. Three most popular approaches of RA distribution modelling were analyzed — three-dimensional internal and external CFD models, external models of the Gaussian plume and dispersion of Lagrangian particles. Each has an advantage in some categories and disadvantages in others, based on this trade-off, the suitability of the models is judged. Another important requirement is inside-outside models integration with the following communication scenario: outside model is to provide pressure map on the NSC exterior shell at different weather conditions; inside model is to calculate RA generation rate and distribution to holes (leaks in the NSC structure); with known RA source at the leaks, outside model assesses RA deposition on the surface of interest (industrial site).

Prediction and Source Contribution Analysis of PM2.5 Using a Combined FLEXPART Model and Bayesian Method over the Beijing-Tianjin-Hebei Region in China

Fine particulate matter (PM2.5) has a serious impact on human health. Forecasting PM2.5 levels and analyzing the pollution sources of PM2.5 are of great significance. In this study, the Lagrangian particle dispersion (LPD) model was developed by combining the FLEXPART model and the Bayesian inventory optimization method. The LPD model has the capacity for real-time forecasting and determination of pollution sources of PM2.5, which refers to the contribution ratio and spatial distribution of each type of pollution (industry, power, residential, and transportation). In this study, we applied the LPD model to the Beijing-Tianjin-Hebei (BTH) region to optimize the a priori PM2.5 emission inventory estimates during 15–20 March 2018. The results show that (1) the a priori estimates have a certain degree of overestimation compared with the a posteriori flux of PM2.5 for most areas of BTH; (2) after optimization, the correlation coefficient (R) between the forecasted and observed PM2.5 concentration increased by an average of approximately 10%, the root mean square error (RMSE) decreased by 30%, and the IOA (index of agreement) index increased by 16% at four observation sites (Aotizhongxin_Beijing, Beichenkejiyuanqu_Tianjin, Dahuoquan_Xintai, and Renmingongyuan_Zhangjiakou); and (3) the main sources of pollution at the four sites mainly originated from industrial and residential emissions, while power factory and transportation pollution accounted for only a small proportion. The concentration of PM2.5 forecasts and pollution sources in each type of analysis can be used as corresponding reference information for environmental governance and protection of public health.

Firewood residential heating – local versus remote influence on the aerosol burden

Abstract. We report the first-time use of the Lagrangian particle dispersion model (LPDM) FLEXPART to simulate isotope ratios of the biomass burning tracer levoglucosan. Here, we combine the model results with observed levoglucosan concentrations and δ13C to assess the contribution of local vs. remote emissions from firewood domestic heating to the particulate matter sampled during the cold season at two measurements stations of the Environmental Agency of North Rhine-Westphalia, Germany. For the investigated samples, the simulations indicate that the largest part of the sampled aerosol is 1 to 2 d old and thus originates from local to regional sources. Consequently, ageing, also limited by the reduced photochemical activity in the dark cold season, has a minor influence on the observed levoglucosan concentration and δ13C. The retro plume ages agree well with those derived from observed δ13C (the “isotopic” ages), demonstrating that the limitation of backwards calculations to 7 d for this study does not introduce any significant bias. A linear regression analysis applied to the experimental levoglucosan δ13C vs. the inverse concentration confirms the young age of aerosol. The high variability in the observed δ13C implies that the local levoglucosan emissions are characterized by different isotopic ratios in the range of −26.3 ‰ to −21.3 ‰. These values are in good agreement with previous studies on levoglucosan source-specific isotopic composition in biomass burning aerosol. Comparison between measured and estimated levoglucosan concentrations suggests that emissions are underestimated by a factor of 2 on average. These findings demonstrate that the aerosol burden from home heating in residential areas is not of remote origin. In this work we show that combining Lagrangian modelling with isotope ratios is valuable to obtain additional insight into source apportionment. Error analysis shows that the largest source of uncertainty is limited information on isotope ratios of levoglucosan emissions. Based on the observed low extent of photochemical processing during the cold season, levoglucosan can be used under similar conditions as a conservative tracer without introducing substantial bias.

JRII special sonic anemometer study: A first comparison of building wakes measurements with different levels of numerical modelling approaches

After the summer 2015 chlorine releases during the Jack Rabbit II field experiment at Dugway Proving Ground, a special sonic anemometer study was carried out in October 2015 and March 2016. The goal was to provide documented wind fields in similar conditions to the actual releases and to study building wakes without risk for the instruments. This study included 30 sonic anemometers that were placed around these “buildings” to best capture the recirculating regions. Building wakes are important for the dispersion of pollutants in cities and around industrial plants and therefore we have selected two time periods during March 2016, in order to present model to model and model to data comparisons. There are four models involved in the comparison ranging from a diagnostic wind model with wake parameterization and Lagrangian particle dispersion and a CFD model with a k-ε turbulence closure and solving the Eulerian dispersion equation. Detailed comparisons are carried out for the wind speed and for the turbulence level. Six virtual releases are added in the simulations to investigate how the wake resolving method can affect the dispersion. For the wind speed comparison, the models give fair to good comparison with the sonic measurements. However, for the turbulence comparison the results clearly show a need for improvement, even for the k-ε closure, which still provides the best results. For the concentrations, for which there is no corresponding measurements, we find that the simulations are much closer than for the turbulence comparison.

Extended 3D-PTV for direct measurements of Lagrangian statistics of canopy turbulence in a wind tunnel

Direct estimation of Lagrangian turbulence statistics is essential for the proper modeling of dispersion and transport in highly obstructed canopy flows. However, Lagrangian flow measurements demand very high rates of data acquisition, resulting in bottlenecks that prevented the estimation of Lagrangian statistics in canopy flows hitherto. We report on a new extension to the 3D Particle Tracking Velocimetry (3D-PTV) method, featuring real-time particle segmentation that outputs centroids and sizes of tracer particles and performed on dedicated hardware during high-speed digital video acquisition from multiple cameras. The proposed extension results in four orders of magnitude reduction in data transfer rate that enables to perform substantially longer experimental runs, facilitating measurements of convergent statistics. The extended method is demonstrated through an experimental wind tunnel investigation of the Lagrangian statistics in a heterogeneous canopy flow. We observe that acceleration statistics are affected by the mean shear at the top of the canopy layer and that Lagrangian particle dispersion at small scales is dominated by turbulence in the wake of the roughness elements. This approach enables to overcome major shortcomings from Eulerian-based measurements which rely on assumptions such as the Taylor’s frozen turbulence hypothesis, which is known to fail in highly turbulent flows.

Quantifying oceanic moisture exports to mainland China in association with summer precipitation

Oceanic moisture exports (OMEs) are considered the major moisture sources for precipitation over Mainland China during the boreal summer season. In this study, a Lagrangian particle dispersion and transport model [FLEXible PARTicle dispersion model (FLEXPART)] driven with European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA)-Interim data was used to conduct 35-year modeling of the summer season (May–August) for 1980–2014. Based on the 6-h output over 35 years, a relatively sophisticated approach was adopted that considers the change in specific humidity with trajectory tracking to diagnose OME-based precipitation during the summer season in China. We specifically explored the spatiotemporal structure of OME-based precipitation over Mainland China with a focus on quantifying the relative contributions of three specific oceanic sub-regions: the Arabian Sea (AS), the Bay of Bengal (BOB), and the South China Sea (SCS). The relevance of the OME anomalies from the three sub-regions and the observed precipitation changes on an interannual scale were also explored. The main research conclusions are summarized as follows: (1) The diagnosed OME-based precipitation and gauge observations exhibit similar spatial patterns in both seasonal and sub-seasonal scales, further evidencing the robustness of the approach used in this study. (2) Climatologically, the OMEs originating from the AS, the BOB, and the SCS made roughly equivalent contributions to the entire areal-averaged precipitation over Mainland China on a seasonal scale, but the preferred regions influenced by the three oceanic sources differ strongly from each other. (3) The relative contributions of OME from three specific subsections to precipitation varied significantly on the sub-seasonal scale. During the onset of summer monsoons, the AS region ranked first as an important oceanic source, followed by the BOB and the SCS, whereas during the withdrawal of summer monsoons, this order was reversed. (4) The interannual anomalies of OME-based precipitation from the SCS and the BOB regions are negatively correlated with those outside the AS region.

Modelling airborne dispersion for disaster management

Industrial disasters, like any other disasters, can happen anytime, anywhere and in any form. Airborne industrial disaster is a kind of catastrophic event involving the release of particles such as chemicals and industrial wastes into environment in gaseous form, for instance gas leakages. Unlike solid and liquid materials, gases are often colourless and odourless, the particles are too tiny to be visible to the naked eyes; hence it is difficult to identify the presence of the gases and to tell the dispersion and location of the substance. This study is to develop an application prototype to perform simulation modelling on the gas particles to determine the dispersion of the gas particles and to identify the coverage of the affected area. The prototype adopted Lagrangian Particle Dispersion (LPD) model to calculate the position of the gas particles under the influence of wind and turbulent velocity components, which are the induced wind due to the rotation of the Earth, and Convex Hull algorithm to identify the convex points of the gas cloud to form the polygon of the coverage area. The application performs intersection and overlay analysis over a set of landuse data at Pasir Gudang, Johor industrial and residential area. Results from the analysis would be useful to tell the percentage and extent of the affected area, and are useful for the disaster management to evacuate people from the affected area. The developed application can significantly increase efficiency of emergency handling during a crisis. For example, by using a simulation model, the emergency handling can predict what is going to happen next, so people can be well informed and preparations works can be done earlier and better. Subsequently, this application helps a lot in the decision making process.

Modelled atmospheric contribution to nitrogen eutrophication in the English Channel and the southern North Sea

Eutrophication of the coastal waters results in algal blooms which may be harmful to the marine ecosystem and coastal economy. The main sources of nutrients are the rivers but an unquantified amount of nitrogen is also transported from ground sources via the atmosphere and deposited to the sea directly by rain and turbulent diffusion. A Lagrangian Particle Dispersion (LPD) model based on the open source code FLEXPART (http://flexpart.eu) is described that quantifies the dissolved nitrogen coming from the air in the English Channel and Southern North Sea (the ‘2Seas’ geographical region). The model uses meteorological records, emissions data and LPD computations to simulate the motion and deposition of nitrogen compounds. The emission sources contributing to the deposition are individually identified, and calculated concentrations are compared with ground measurements in selected locations. The highest calculated atmospheric depositions to the sea in the considered region are found to be along the Belgium–Netherlands coast.

Particle dispersion in homogeneous turbulence using the one-dimensional turbulence model

Lagrangian particle dispersion is studied using the one-dimensional turbulence (ODT) model in homogeneous decaying turbulence configurations. The ODT model has been widely and successfully applied to a number of reacting and nonreacting flow configurations, but only limited application has been made to multiphase flows. Here, we present a version of the particle implementation and interaction with the stochastic and instantaneous ODT eddy events. The model is characterized by comparison to experimental data of particle dispersion for a range of intrinsic particle time scales and body forces. Particle dispersion, velocity, and integral time scale results are presented. The particle implementation introduces a single model parameter βp, and sensitivity to this parameter and behavior of the model are discussed. Good agreement is found with experimental data and the ODT model is able to capture the particle inertial and trajectory crossing effects. These results serve as a validation case of the multiphase implementations of ODT for extensions to other flow configurations.

Eddy-Induced Particle Dispersion in the Near-Surface North Atlantic

Abstract This study investigates the anisotropic properties of the eddy-induced material transport in the near-surface North Atlantic from two independent datasets, one simulated from the sea surface height altimetry and one derived from real-ocean surface drifters, and systematically examines the interactions between the mean- and eddy-induced material transport in the region. The Lagrangian particle dispersion, which is widely used to characterize the eddy-induced tracer fluxes, is quantified by constructing the “spreading ellipses.” The analysis consistently demonstrates that this dispersion is spatially inhomogeneous and strongly anisotropic. The spreading is larger and more anisotropic in the subtropical than in the subpolar gyre, and the largest ellipses occur in the Gulf Stream vicinity. Even at times longer than half a year, the spreading exhibits significant nondiffusive behavior in some parts of the domain. The eddies in this study are defined as deviations from the long-term time-mean. The contributions from the climatological annual cycle, interannual, and subannual (shorter than one year) variability are investigated, and the latter is shown to have the strongest effect on the anisotropy of particle spreading. The influence of the mean advection on the eddy-induced particle spreading is investigated using the “eddy-following-full-trajectories” technique and is found to be significant. The role of the Ekman advection is, however, secondary. The pronounced anisotropy of particle dispersion is expected to have important implications for distributing oceanic tracers, and for parameterizing eddy-induced tracer transfer in non-eddy-resolving models.

Lagrangian and Eulerian lateral diffusivities in zonal jets

Meridional diffusivities from Lagrangian particle dispersion and Eulerian diffusivities from a flux-gradient relationship are estimated in an idealized primitive equation channel model featuring eddy-driven zonal jets. The Eulerian estimate shows an increase with depth and clear minima of meridional diffusivities within the zonal jets, indicating mixing barriers. The Lagrangian estimates agree with the Eulerian method on the vertical variation and also show indications of meridional mimima, although meridional variations are poorly resolved. We found early maxima in the particle spreading rates which should not be related to diffusivities since they are caused by the meandering zonal jets. The meanders also produce rotational eddy fluxes, which can obscure the Eulerian diffusivity estimates. Zonal particle dispersion rates do not converge within the chosen lag interval, because of shear dispersion by the mean flow, i.e. it is not possible to estimate Lagrangian zonal diffusivities representative for regions of similar size of the zonal jet spacing. Removing the zonal mean flow, zonal and meridional dispersion rates converge and show much higher zonal than meridional diffusivities. Further, the pronounced vertical increase and indications of meridional minima in the Lagrangian meridional diffusivities disappear, pointing towards the importance of shear dispersion by the mean flow for the suppression of meridional mixing by zonal jets.

Lagrangian particle dispersion in turbulent flow over a wall mounted obstacle

Large-eddy simulations (LES) of particle-laden turbulent flows are presented in order to investigate the effects of particle response time on the dispersion patterns of a space developing flow with an obstruction, where solid particles are injected inside the wake of an obstacle [Vincont, J.Y., Simoens, S., Ayrault M., Wallace, J.M., 2000. Passive scalar dispersion in a turbulent boundary layer from a line source at the wall and downstream of an obstacle. J. Fluid Mech. 424, 127–167]. The numerical method is based on a fully explicit fractional step approach and finite-differences on Cartesian grids, using the immersed boundary method (IBM) to represent the existence of solid obstacles. Two different turbulence models have been tested, the classical Smagorinsky turbulence model and the filtered structure function model. The dispersed phase was modelled either by an Eulerian approach or a Lagrangian particle tracking scheme of solid particles with Stokes numbers in the range St = 0–25, assuming one-way coupling between the two phases. A very good agreement was observed between the Lagrangian and Eulerian approaches. The effect of particle size was found to significantly differentiate the dispersion pattern for the inhomogeneous flow over the obstacle. Although in homogeneous flows like particle-laden turbulent channels near-wall particle clustering increases monotonically with particle size, for the examined flow over an obstacle, preferential concentration effects were stronger only for an intermediate range of Stokes numbers.

An electrokinetic mixer driven by oscillatory cross flow

An electrokinetic mixer driven by oscillatory cross flow has been studied numerically as a means for generating chaotic mixing in microfluidic devices for both confined and throughput mixing configurations. The flow is analyzed using numerical simulation of the unsteady Navier–Stokes equations combined with the tracking of single and multi-species passive tracer particles. First, the case of confined flow mixing is studied in which flow in the perpendicular channels of the oscillatory mixing element is driven sinusoidally, and 90° out of phase. The flow is shown to be chaotic by means of positive effective (finite time) Lyapunov exponents, and the stretching and folding of material lines leading to Lagrangian tracer particle dispersion. The transition to chaotic flow in this case depends strongly on the Strouhal number (St), and weakly on the ratio of the cross flow channel length to width (L/W). For L/W = 2, the flow becomes appreciably chaotic as evidenced by visual particle dispersion at approximately St = 0.32, and the transitional value of St increases slightly with increasing aspect ratio. A peak degree of mixing on the order of 85% is obtained for the range of parameter values explored here. In the second phase of the analysis, the effect of combining a fixed throughput flow with the oscillatory cross channel motion for use in a continuous mixing operation is examined in a star cell geometry. Chaotic mixing is again observed, and the characteristics of the downstream dispersion patterns depend mainly on the Strouhal number and the (dimensionless) throughput rate. In the star cell, the flow becomes appreciably chaotic as evidenced by visual particle dispersion at approximately St = 1, slightly higher than for the case of cross cell. The star cell mixing behavior is marked by the convergence of the degree of mixing to a plateau level as the Strouhal number is increased at fixed flow rate. Degree of mixing values from 70 to 80% are obtained indicating that the continuous flow is bounded by the maximum degree of mixing obtained from the confined flow configuration.

EVALUATION OF LAGRANGIAN PARTICLE DISPERSION MODELS IN TURBULENT FLOWS

This work evaluates the performance of Lagrangian turbulent particle dispersion models based on the Langevin equation. A family of Langevin models, extensively reported in the open literature, decompose the fluctuating fluid velocity seen by the particle in two components, one correlated with the previous time step and a second one randomly sampled from a Wiener process, i.e., the closure is at the level of the fluid velocity seen by the particle. We will call those models generically the “standard model.” On the other hand, the model proposed by Minier and Peirano (2001) is considered; this approach is based on the probability density function (PDF) and performs the closure at the level of the acceleration of the fluid seen by the particle. The formulation of a Langevin equation model for the increments of fluid velocity seen by the particle allows capturing some underlying physics of particle dispersion in general turbulent flows while keeping simple the mathematical manipulation of the stochastic model, avoiding some pitfalls, and simplifying the derivation of macroscopic relations. The performance of the previous dispersion models is evaluated in the configurations of grid-generated turbulence (Snyder and Lumley, 1971; Wells and Stock, 1983), simple shear flow (Hyland et al., 1999), and confined axisymmetric jet flow laden with solids (Hishida and Maeda, 1987).

Urban Dispersion Modeling: Comparison with Single-Building Measurements

Abstract Two models have been developed to predict airflow and dispersion in urban environments. The first model, the Realistic Urban Spread and Transport of Intrusive Contaminants (RUSTIC) model, is a fast-running urban airflow code that rapidly converges to a numerical solution of a modified set of the compressible Navier–Stokes equations. RUSTIC uses the k–ω turbulence model with a buoyancy production term to handle atmospheric stability effects. The second model, “MESO,” is a Lagrangian particle transport and dispersion code that predicts concentrations of a released chemical or biological agent in urban or rural areas. As a preliminary validation of the models, concentrations simulated by MESO are compared with experimental data from wind-tunnel testing of dispersion around both a multistory rectangular building and a single-story L-shaped building. For the rectangular building, trace gas is forced out at the base of the downwind side, whereas for the L-shaped building, trace gas is forced out of a side door in the inner corner of the “L.” The MESO–RUSTIC combination is set up with the initial conditions of the wind-tunnel experiment, and the steady-state concentrations simulated by the models are compared with the wind-tunnel data. For the multistory building, a dense set of detector locations was available downwind at ground level. For the L-shaped building, concentration data were available at three heights in a lateral plane at a distance of one building height downwind of the lee side. A favorable comparison between model simulations and test data is shown for both buildings.

A statistical approach for estimating uncertainty in dispersion modeling: An example of application in southwestern USA

A method based on a statistical approach of estimating uncertainty in simulating the transport and dispersion of atmospheric pollutants is developed using observations and modeling results from a tracer experiment in the complex terrain of the southwestern USA. The method takes into account the compensating nature of the error components by representing all terms, except dispersion error and variance of stochastic processes. Dispersion error and the variance of the stochastic error are estimated using the maximum likelihood estimation technique applied to the equation for the fractional error. Mesoscale Model 5 (MM5) and a Lagrangian random particle dispersion model with three optional turbulence parameterizations were used as a test bed for method application. Modeled concentrations compared well with the measurements (correlation coefficients on the order of 0.8). The effects of changing two structural components (the turbulence parameterization and the model grid vertical resolution) on the magnitude of the dispersion error also were examined. The expected normalized dispersion error appears to be quite large (up to a factor of three) among model runs with various turbulence schemes. Tests with increased vertical resolution of the atmospheric model (MM5) improved most of the dispersion model statistical performance measures, but to a lesser extent compared to selection of a turbulence parameterization. Method results confirm that structural components of the dispersion model, namely turbulence parameterizations, have the most influence on the expected dispersion error.

Visualization of the tidal flow in Sasebo and Oomura Bays

Sasebo and Oomura Bays situated in the northwest of Kyushu, Japan form a coupled bay linked by a channel. The tidal flow in and between these bays is visualized by the satellite images and the dispersion of Lagrangian particles is numerically studied. The satellite images are available to visualize the tidal flow at the mouth of Hario-seto from the maximum flood tide to the end of ebb tide at Tainoura. The seawater plume from the mouth of Hario-seto goes southeastward and then rotates anti-clockwise. The time of one rotation is about 6 to 7 periods. The plume extends about 10 km from the mouth of Hario-seto. Lagrangian particles in Sasebo Bay also flow into Oomura Bay through Haiki-seto.

Bhopal gas leak: A numerical simulation of episodic dispersion

A mesoscale meteorological model coupled with a Lagrangian particle dispersion (LPD) model was used to simulate the Bhopal methyl isocyanate (MIC) gas leak. A simple two layer K-closure version of the Pielke primitive equation meteorological model was used to produce the wind and turbulence fields in the planetary boundary layer (PBL). Initialized by a single 3 m s −1 geostrophic wind, the PBL model produced a low wind speed stable surface layer capped by a 250 m high nocturnal inversion. The results compared well with limited meteorological observations. However, the LPD model failed to produce enough vertical and horizontal mixing to match the extent of the affected area which was derived from the mortality statistics. Recommendations to improve the model physics to accomodate enhanced mixing in urban areas and to treat MIC thermodynamics and chemistry are suggested.

Simulation of elevated long-range plume transport using a mesoscale meteorological model

A three-dimensional mesoscale meteorological model was used to construct a modeling system in order to investigate atmospheric dispersion in mesoscale flow fields. The mesoscale model was first coupled to a three-dimensional Monte Carlo (Lagrangian particle) dispersion model, and then an Eulerian dispersion model was embedded into the mesoscale model. Both the Eulerian model and the Monte Carlo model are based on the wind and turbulence fields simulated by the mesoscale model. The modeling system was then applied to the Tennessee Plume Study field experiments on 23 August 1978. The field experiments were basically designed to provide information on the dynamics of plume transport over long distances, and primarily targeted the plume from the Cumberland steam plant. Wind and turbulence fields were first simulated by the mesoscale model. The transport and diffusion of pollutants from the Cumberland steam plant were then simulated by the dispersion models, using these wind and turbulence fields. The results demonstrated that the modeling system generally performed satisfactorily, reproducing the trajectory and spread of the Cumberland plume.