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In a complex environment such as an urban area, accurate prediction of the atmospheric dispersion of airborne harmful materials such as radioactive substances is necessary for establishing response actions and assessing risk or damage. Given the variety of urban atmospheric dispersion models available, evaluation and inter-comparison exercises are vital for assessing quantitatively and qualitatively their capabilities and differences. To that end, the European Commission/Directorate General Joint Research Centre with support from the European Commission/Directorate General-Migration and Home Affairs, and with the contribution of the U.S. Defense Threat Reduction Agency, launched the Urban Dispersion INternational Evaluation Exercise (UDINEE) project. Within UDINEE, nine atmospheric dispersion models are evaluated and intercompared. Sulphur hexafluoride concentrations from puffs released near the ground during the Joint Urban 2003 (JU2003) field experiment are used in UDINEE to evaluate atmospheric dispersion models. The JU2003 experiment is chosen because UDINEE aims at the better understanding of modelling capabilities for radiological dispersal devices in urban areas, and the neutrally-buoyant puff releases performed in the JU2003 experiment are the closest scenario to this purpose. The present study evaluates the capability of models at simulating the presence and concentration levels of the tracer at sampling locations. The fraction of predicted concentrations and time-integrated concentrations within a factor-of-two of observations are less than 0.36 and 0.4 respectively. The analysis reveals an improvement in the performance of models by using time-varying inflow conditions. Since the simulation of the dispersion of puff release is particularly challenging, the results of UDINEE could constitute a benchmark for future model developments.

The capabilities of nine atmospheric dispersion models in predicting near-field dispersion from puff releases in an urban environment are addressed under the Urban Dispersion INternational Evaluation Exercise (UDINEE) project. The model results are evaluated using tracer observations from the Joint Urban 2003 (JU2003) experiment where neutrally-buoyant puffs were released in the downtown area of Oklahoma City, USA. Sulphur hexafluoride concentration time series measured at ten sampling locations during four daytime and four night-time puff releases are used to evaluate how the models simulate the puff passage at the measurement locations. The neutrally-buoyant puff releases in the JU2003 experiment are the closest scenario to radiological dispersal device (RDD) releases in urban areas, and therefore, UDINEE is a first step towards improving the emergency response to an RDD explosion in the urban environment. We investigate for each puff and sampler the model capability of simulating the peak concentration; the peak and puff arrival times; and time duration, defined as the period over which concentrations exceed 10% of the peak concentration. This analysis points out differences on the performance of models: the fraction within a factor-of-two values ranges from 0.10 to 0.6 for peak concentration, from 0 to 1 for the peak and arrival times, and from 0 to 0.8 for the time duration. The results reveal that the characteristics of the release site largely influence the model simulation as it affects initial puff size and the initial downwind spread of the puff.

The role of atmospheric dispersion models is becoming increasingly relevant to assess air pollution urban population exposure for epidemiological studies. Estimating urban air quality is challenging, because of the intrinsic characteristics of cities atmospheric structure, such as high density of primary emissions and presence of local dispersion processes, that produce strong concentration gradients. Therefore, very high spatial resolution simulations may often be required to improve the accuracy of estimations. The objective of this study is developing a microscale hybrid modelling system (HMS) to carry out, in a reasonable computational time, long-term simulations providing hourly concentration fields at building-resolving scale in extended urban areas in order to calculate annual indicators to evaluate exposure. The proposed system couples two atmospheric dispersion models suited for different scales: a Eulerian chemical transport model, FARM (Flexible Air quality Regional Model), accounting for dispersion phenomena due to regional and local emission sources, and a Lagrangian particle micro-scale dispersion model, PMSS (Parallel Micro Swift Spray), used to compute concentrations induced by vehicular traffic inside the city. The HMS has been applied on 12 × 12 km2 domain in Rome with a horizontal resolution of 4 m for calculating NO2 and PM10 concentrations for all year 2015. This study has been carried out in the frame of project BEEP (Big data in Environmental and occupational Epidemiology), that is an Italian research project in epidemiological field. Results show that the combined use of the two models reproduces the spatial and temporal variability of the observed atmospheric pollutants with a good agreement. The statistical analysis performed on daily average concentrations proves that the HMS suits the standard acceptance criteria for urban dispersion model evaluation, with a FAC2 of 0.92 and 0.80 and a Fractional Bias of −0.03 and −0.2 for NO2 and PM10 respectively. Furthermore, the implementation of an innovative kernel method to calculate concentrations in PMSS has made possible to reduce the computational time by 80%, leading to an average computational time of 3 h per simulated day on an HPC (High Performance Computing) system with 180 cores.

Background. Storage tanks in oil and gas processing facilities contain large volumes of flammable compounds. Once the fuel-air mixture is ignited, it may break out into a large fire or explosion. The growing interest in monitoring air quality and assessing health risks makes the evaluation of the consequences of a fire an important issue. Atmospheric dispersion models, which allow for simulation of the spatial distribution of pollutants, represent an increasingly widespread tool for this type of evaluations. Objectives. The present study discusses the set up and results of a modeling study relevant to a hypothesized fire in an oil refinery. Methods. After choosing the most suitable dispersion models, i.e. the Lagrangian model SPRAY and the puff model CALPUFF, estimation of the required input data is discussed, focusing on the source variables, which represent the most uncertain input data. The results of the simulations were compared to regulatory limits to effectively evaluate the environmental consequences. Finally, a sensitivity analysis was employed to identify the most influential variables. Results. The simulation results revealed that ground concentration values were far below the cited long-term limits. However, the most interesting outcome is that depending on the dispersion model and the source type modeled, different results may be obtained. In addition, the sensitivity study indicates that the source area is the most critical variable, since it determines a significantly different behavior depending on the modeled source types, producing, in some cases, variability in the pollutant ground concentrations on selected receptors up to +/− 60%. Conclusions. Depending on the selected model and the algorithms available to describe the physics of emission, the results showed a different sensitivity to the input variables. Although this can be explained from a mathematical point of view, the problem remains of choosing case by case the option that best approximates the real behavior of the incidental source under investigation. Competing Interests. The authors declare no competing financial interests.

When modelling the dispersion of pollutants in the atmosphere, uncertainty in the simulation results that depend on the available data used as input conditions is a critical issue, particularly in the context of emergency response to the accidental release of harmful substances. In the framework of the UDINEE Project, a Lagrangian particle dispersion model is used to simulate puff emissions in four different test cases, using input wind velocity data from two different datasets, both representative of the flow at the time of the release. The effect of the choice of the input data on the final concentration distribution at ground level is discussed and compared with observations. A statistical analysis is applied to estimate the deviation between the results of the two runs. The bias between the two concentration fields, connected to the variability and the uncertainty in the input flow, is found to be of similar magnitude to the typical bias between model predictions and observations.

Unexpected releases of hazardous airborne materials may happen in various circumstances, more frequently in accidental situations, less usually due to malicious activities. In all cases, the risk for the population and the rescue team is real and must be evaluated in order to take appropriate protection measures. Numerical models are more and more used in emergency response tools for predicting the atmospheric dispersion of pollutants and estimating impacted areas. Still, flow and dispersion modelling in a built-up environment may be very challenging given the complex geometry and meteorological conditions. Here, we present and evaluate a modelling approach that is a compromise between accuracy and timeliness of the computations. It is based on a 3D Lagrangian Particle Dispersion model driven by 3D flow and turbulence input provided by either a diagnostic mass-consistent model or a model solving the Reynolds-Averaged Navier-Stokes equations. This modelling system has been validated on a panel of experimental test cases from the Cooperation in Science and Technology (COST) Action ES1006 in both idealized and realistic urban mock-ups, wind tunnel and field trials, continuous and puffs releases. The sensitivity of the model to the meteorological input data is assessed. The results are discussed comparing predicted concentrations to measurements. The performances of the modelling system are evaluated through a statistical analysis. They were found to depend on the type of test case, type of release and location of the source in the built-up domain. Results show that the model is compliant with the validation criteria, established in literature for the reference metrics, in the large majority of the test cases. The modelling system proved to be robust enough to be used in the context of emergency response, when fast but still reliable results are needed.

A main research task of COST Action ES1006 is the evaluation of atmospheric dispersion models by their comparison against test data from qualified field and laboratory experiments and by a model inter-comparison. The model comparison and evaluation carried out for three test cases is presented, addressing the performance of the different modelling approaches, quantifying the scatter of results when different models are applied and assessing the effect of uncertainties.

This paper reports the results of an integrated assessment of traffic impact on a tourist-popular high altitude region which includes mountain passes and road tunnels. A modeling system for air quality assessment and management has been established and revised. The system has been used to evaluate the impact of traffic due to the re-opening of the Mont Blanc tunnel: the increase in NO x concentrations ranges from 50% at the bottom of the upper valley to 150% near to tunnel entrance.

The effect of using in dispersion modeling different parameterizations for the wind velocity fluctuations standard deviations is investigated for low-wind conditions.

Pollutant transport and dispersion in complex orography are usually difficult to model accurately, due to the problem of properly reproducing wind and turbulence fields and interactions between pollutants and orography. In these situations the well-known Gaussian approach is limited. For studies of line sources (i.e. highways), models are available which are adequate for flat terrain and steady-state conditions (i.e. US-EPA recommended CALINE-3 and HIWAY-2). In complex terrain, however, no well-tested models are available. A possible approach to the problem is the use of a wind field model with a Lagrangian dispersion model well suited to consider both orography-induced inhomogeneities and line sources. We present the application of SPRAY particle model to reproduce pollutants dispersion from a highway at the bottom of a deep alpine valley, where pollutants are well confined and stagnation may occur. Model results for NOx are compared to those of the EPA recommended model HIWAY-2 and to measured concentrations.

Spray, a 3D Lagrangian particle model for the simulation of complex flow dispersion, is presented. Its performance is tested against the Environmental Protection Agency wind tunnel concentration distribution of passive tracer released from elevated point sources, located in the lee region of a two-dimensional schematic hill, in a neutrally stratified boundary layer. Based on the measured values of the first two moments of the turbulent flow velocity, the mean fields are computed over a regular grid using a mass-consistent model, whereas the turbulence structure is simply interpolated. From these fields, trajectories of tracer particles are computed using a linear formulation of the Langevin equation, with a correlated, skewed forcing. The self-consistence test (well-mixed condition), aimed at maintaining an initially well-mixed particle distribution uniform in time, has shown satisfactory results in the region under study. The computed concentration field turns out to be in good agreement with th...

A particle model LAMDA suitable for dealing with the atmospheric dispersion is presented. The reliability of the model is tested comparing the results of its simulations to the wind tunnel measurements by Khurshudyanet al. (1981). Two versions of the model, both based on the Langevin equation and askewed distribution of the vertical wind velocity fluctuations, are considered. To develop the second version of the model we derived a proper scheme to produce skewed distributions of particle velocities consistent with the observed first and second moments of turbulent fluctuating velocities, with their horizontal and vertical derivatives, and their cross-correlations. The 2D geometry of the obstacle (in the wind tunnel experiment considered) allowed some simplifications. Due to the lack of some input data (such as the vertical profiles of crosswind standard deviation of wind velocity fluctuations and of the Lagrangian time scales) we looked for three different parametrizations. It was found that particular combinations of measured and parametrized data could give rise to critical vertical regions in which the derived scheme for the generation of random vertical velocity fluctuations cannot be applied. The best vertical distributions of the Lagrangian time scales (third parametrization) were estimated by fitting simple formulations for the average plume height and lateral variances to the measured data. The main results of this work were the model performance in simulating dispersion in shear flow over flat terrain, and its sensivity to the shape of the crosscorrelation term\(\overline {u'w'} \).

A Lagrangian particle model (LAMDA), previously developed and applied to the simulation of atmospheric dispersion in neutral and convective windy conditions, was modified to deal with stable low wind speed conditions. These last are among the most difficult to be treated. In fact, on the one hand, nearly calm situations, associated to strong stability and air stagnation, make the lower layers of the atmosphere poorly diffusive, and, on the other hand, the large fluctuations in the wind direction (meandering), spread the airborne pollutants over wide angular sectors. An ad hoc algorithm to simulate the effect of meadering on the dispersion is proposed. The model is validated by comparing its simulation results to three tracer experiments held in stable low wind speed conditions by the Idaho National Engineering Laboratory (U.S.A.) in 1974. These experiments present plume spread of different width (48, 138 and 360°, respectively, at an arc located 200 m downwind from the source) and are comprehensive of a wide set of conditions, ranging from strong to weak stability and from low wind speed to calm. The results of the comparison are discussed. The ability of the model to simulate the g.l.c. distributions with a good degree of confidence is illustrated.

Conditions of low windspeed associated to strong stability and air stagnation correspond to highly nonstationary and inhomogeneous diffusion situations. In such «poor» diffusion cases, integrated models (like Gaussian models) are no longer valid. New numerical methodologies, like Monte Carlo methods, are needed. Recently a Monte Carlo particle model for airborne pollutant dispersion has been developed by our team. Its ability to predict ground-level concentrations in convective and neutral conditions with a high degree of accuracy was verified against tracer experiments. In the present paper our model is used to simulate the dispersion under low windspeed conditions. Particular emphasis is given to the problem of wind meandering. We have demonstrated the need of recording the wind statistics over averaging periods of the order of a few minutes and anad hoc algorythm to treat low windspeed situation when only hourly average data are available is suggested. The model results are compared to tracer data obtained by the Idaho National Engineering Laboratory (U.S.A.) in 1974.

In 1991, three institutions from Slovenia and Italy performed a measuring campaign to collect data for the validation of air pollution dispersion models. The target was a local area around the Sostanj Thermal Power Plant in north-east Slovenia. As one of the co-authors of the work we decided to renew the database and to produce the necessary up-to-date information that would allow other researchers to use this experimental database for modern models testing. The measurements data set describes in detail the following situation: Sostanj Thermal Power Plant at that time did not have any desulphurisation plants, therefore the sulphur dioxide (SO2) continuously emitted from its blocks was acting like a tracer in the environment. The area is characterised by very complex meteorological situations. In the paper we will present a description of the experiment (area description, site, terrain, measurement stations location, database) and two most interesting cases suitable for a model validation (emission, ambient concentrations, meteorology).

A particle model SPRAY suitable for dealing with the atmospheric dispersion of buoyant emission in complex terrain has been developed. It is an extension of the model LAMBDA (Anfossi et al. 1991, Brusasca et al. 1989 and 1992) based on the Langevin equation, designed to simulate the dispersion on flat terrain, which was validated in various atmospheric conditions. In this last model the vertical profiles of wind and turbulence, defined at the source locations, were kept constant in all the computational domain.

Most of the up to date dispersion simulations are discussed using ground level concentration (g.l.c.) values only. However it is straightforward that the spatial distribution of the concentration should be carefully computed, in order to assess the capability of a given model to correctly simulate the atmospheric dispersion. Therefore, the vertical and horizontal concentration profiles at various downwind distances and at different levels above ground should also be computed and compared to the corresponding observed values if any, even if this is generally thought of as very severe test for any kind of model.

A Lagrangian particle dispersion model for dense gas dispersion is proposed. It is a new version of MicroSpray oriented to simulate dense gas dispersion in urban or industrial environment, and includes the treatment of obstacles, complex terrain and low wind. The dense gas descent is computed by a 3D dynamical plume rise/descent model, the gravity spreading and bottom boundary condition are accounted for by empirical formulations. The differences between simulations obtained with the new model and with the standard one are presented. The model is validated against tracer field data gathered in the Thorney Island experiment 8.

Dispersion in low wind speed conditions is governed by meandering that disperses plumes over wide angular sectors, thus g.l.c. are lower than predicted by Gaussian models. It was proposed to model these dispersion situations in homogeneous conditions with two coupled Langevin equations, based on low wind speed turbulence analysis. Their parameters were derived from the autocorrelation functions of horizontal wind that exhibit an oscillations and large negative lobes. We propose a new equation system for: general case of inhomogeneous turbulence; total velocity; for the windy situations (based on the "Thomson simplest solution") and verify that these new solutions satisfy the "well-mixed condition".

Dose projection is a tool for decision making in the case of a nuclear emergency situation. In this work the dose projection software developed for the Krsko NPP located in Slovenia is described. This software can be used for a quick emergency evaluation in the case of a hypothetical pressurised water reactor accident, and for emergency exercises. The software was developed to estimate reactor core damage, the status of fission product barriers, potential releases, atmospheric dispersion and finally the dose calculation. The intention was to use all the available automatic on-line measurements of the radiological monitors in the NPP, meteorological monitors in the surroundings and a modern atmospheric dispersion model capable of accurate calculations in the complex orography which is characteristic of the plant location. It is also important that the software is written in a user-friendly way, automated as highly as possible and executed on a widely used Windows platform for PCs. Details are given in the paragraphs Measurements and software modules and Air pollution dispersion calculation module. The program should provide a dose projection at an early stage of the accident (first hours) for distances of a few kilometres from the NPP. The results are available for a 25 km by 25 km area that includes the Krsko basin and some nearby hills and valleys. The results should support the decision of the emergency team in the NPP about evacuation or sheltering in the environment in the early phase of the accident. In the past the software used only a simple Gaussian air pollution dispersion model. Recently it was replaced with a numerical Lagrangean model called "Spray". Since the software was intended to be used for severe accident scenarios, it was also expected that the on-line meteorological and radiological parameters would not be completely available at all possible stages. For the case of missing radiological data, alternative possibilities were included, that require fewer or no measurements. The selection of this alternative is based on the operator's judgement according to the latest available data. Reduction of information certainly decreases the accuracy of the result. The final paragraphs explain the procedures for core status estimation, source term determination and dose projection.

The results of numerical simulations of tracer dispersion in an urban stable boundary layer are presented. Both Gaussian approximation and fourth order closure are considered and a Gram-Charlier probability density function is used in our Lagrangian stochastic model. Different parameterizations for the boundary-layer height and different values of kurtosis are tested. The model is based on the generalized Langevin equation, whose coefficients are solution of the Fokker-Planck equation and plume rise is taken into account. The model accuracy is assessed by means of a model evaluation based on the predicted and observed crosswind integrated concentrations, maximum on the arc and standard deviation of the crosswind concentration distribution on the arc.

A Monte Carlo model and computer code (MC-LAGPAR) for simulating atmospheric transport and diffusion of plumes are described. The turbulent diffusion is simulated by the semi-random motion of Lagrangian particles. The particles are emitted by a point source and dispersed in a computational domain by pseudo-velocities derived from vertical profiles of meteorological variables. The MC-LAGPAR code includes the implementation of special algorithms for the simulation of a dynamic plume rise, chemical decay, deposition and resuspension effects. Furthermore, computer-graphics displays have been developed. The model, here used in its two dimensional version, is validated in the well-known case of homogeneous and stationary turbulence. In this case, we compared the concentration fields obtained by our model with those calculated by the known analytical solution. In both computations, the standard deviations of wind velocities are calculated according to the Taylor formulas. In the nonhomogeneous case, the vertical structure of turbulence is parameterized according to the scheme suggested by Hanna. As an example of the non-homogeneous case, we present numerical simulations in convective (unstable) conditions in which the influence of updraughts and downdraughts is empirically taken into account.

A Lagrangian statistical (Monte Carlo) model for airborne pollutant dispersion is presented. Its ability to simulate the atmospheric dispersion both in homogeneous and inhomogeneous turbulence by comparison with an analytical solution and with the Willis and Deardorff water tank experiments, respectively, has been stated in previous papers. In the present paper the model is used to simulate dispersion in the real atmospheric PBL. The numerical results obtained are verified against experimental data from the Karlsruhe Nuclear Research Center tracer experiments. The model is applied to the problem of predicting the ground level concentration of two different tracers simultaneously released from two heights (160 and 195 m) at the Karlsruhe meteorological tower. Convectively unstable and neutral conditions were prevailing during the two tracer experiments which have been simulated. Model performance was evaluated through two statistical indexes: relative mean bias and normalized mean square error. The cumulative frequency distribution of the point-by-point ratio between observed and predicted ground level concentrations (glcs) was also computed. The simulated concentrations agree very well with observations. The tracer data were also compared to the simulations of 10 Gaussian models. They differed one another for the choice of dispersion sigma curves and for the way to insert the wind speed and direction. None of them proved to perform better than our particle model in all the exercises.

Two Lagrangian particle models, APOLLO and MILORD, were used to simulate the first ETEX experiment. The role played by wind field, mixing height h and horizontal diffusivity KH appeared to be the most important aspects to be studied. The sensitivity to the accuracy of the input advection field was studied through the application of APOLLO using different ECMWF data sets differing in space and time resolution and in being forecasted or analysed, corresponding to the real-time, emergency-like condition, and to the a posteriori benchmark simulation. The role of h and KH was investigated by running both APOLLO and MILORD with different parameterisations, and comparing the model results between them and with the available observations. The model evaluation was carried out through a set of statistical indexes computed on three hourly average concentrations paired in space and time and time-integrated concentrations. It was found that the quality of the input wind field plays a major role in predicting with sufficient accuracy the plume position and extension after the first 24 h from the beginning of the release. The best-model results are obtained with large values of KH (in the range of 2.5×104–4.5×104 m2 s-1), which confirms the need to enhance the horizontal diffusion, in order to include the advection fluctuations unresolved by large-scale meteorological fields. A fixed value of h in the range 1000–1500 m seems to be more efficient than space and time variable h computed with standard algorithms. A reasonable explanation for this result is given, based on the consideration that in the long range, particles diffuse also in the residual layer above the stable nocturnal boundary layer.

Lagrangian particle models are powerful tools to simulate the atmospheric dispersion of gaseous releases. Although having a quite complex mathematical basis (Thomson, 1987, Rodean, 1994), their practical implementation is generally simple and intuitive, allowing to easily take into account complex situations such as the presence of the topography or terrain inhomogeneities, low wind speeds, spatial and temporal variations of meteorological fields. In these models the atmospheric dispersion is simulated by the motion of fictitious particles splitted in a mean part due to the mean wind, and a stochastic fluctuation related to the statistical characteristics of the turbulent flow. It is quite clear that the model accuracy is strongly dependent on the number of emitted particles and the computer time often limits the kind of simulations that can be performed. For this reason, the earlier version of these models were mainly devoted to reproduce the dispersion of a limited number of emissions at local scale. The recent wide and rapid diffusion of very fast computational tools lead to the development of more sophisticated codes, able to take into account more general situations. SPRAY (Tinarelli et al., 1992) is a Lagrangian stochastic particle model designed to perform dispersion simulations in complex terrain. The version 1 of the code, based on a three dimensional form of the Langevin equation for the random velocity with coupled non-gaussian random forcing following Thomson (1984, T84 in the following) and subsequently improved (Tinarelli et al., 1992), was able to satisfactorily reproduce local to regional scale dispersion both over flat (Brusasca et al., 1989, 1992) and complex terrain (Brusasca et al., 1995, Nanni et al., 1996) taking into account the emission from single or multiple sources. The development of a better based theory (Thomson, 1987) and the further demand of more complex regional scale simulations able to cover longer periods with a variety of emissions of different kinds (i.e. main roads, industrial or urban area) called for a new version of the code. The new version 2 of SPRAY code contains some improvements regarding the theoretical approach, turbulence parametrizations and time response characteristics. In this paper we describe these new developments, comparing model performances with those of the previous version through simulations performed both in theoretical and real cases.

A three-dimensional modelling system, made by a mass-consistent wind field model and by a Lagrangian particle model, has been applied to a Mediterranean complex coastal site to describe the atmospheric dispersion of pollutants emitted by a thermal power plant. Different short-term episodes have been simulated to cover the seasonal climate variability. Model results have been compared with local SO2 measurements showing their reliability in reconstructing space and time concentration variations. Modelling results, together with the statistics of the "weather type" associated with each episode, have been used to estimate climatological concentrations for the considered site. The latter methodology can be proposed to assess the air quality in complex areas.