A dry deposition scheme for particulate matter coupled with a well-known Lagrangian Stochastic model for pollutant dispersion

Environmental Fluid Mechanics - A 3D dry deposition scheme for particulate matter (PM) is presented as a Free-Libre and Open-Source Software (FOSS) library, DePaSITIA (RSE SpA). This combines some...     

A new Lagrangian particle model for the simulation of dense gas dispersion

A Lagrangian stochastic model (MicroSpray), able to simulate the airborne dispersion in complex terrain and in presence of obstacles, was modified to simulate the dispersion of dense gas clouds. This is accomplished by taking into account the following processes: negative buoyancy, gravity spreading and the particle's reflection at the bottom computational boundary. Elevated and ground level sources, continuous and instantaneous emissions, time varying sources, plumes with initial momentum (horizontal, vertical or oblique in any direction), plumes without initial momentum are considered. MicroSpray is part of the model system MSS, which also includes the diagnostic MicroSwift model for the reconstruction of the 3-D wind field in presence of obstacles and orography. To evaluate the MSS ability to simulate the dispersion of heavy gases, its simulation performances are compared in detail to two field experiments (Thorney Island and Kit Fox) and to a chlorine railway accident (Macdona). Then, a comprehensive analysis considering several experiments of the Modelers Data Archive is presented. The statistical analysis on the overall available data reveals that the performance of the new MicroSpray version for dense gas releases is generally reliable. For instance, the agreement between concentration predictions and observations is within a factor of two in the 72% up to 99% of the occurrences for the case studies considered. The values of other performance measures, such as correlation coefficient, geometric mean bias and geometric variance, mostly set in the ranges indicated as good-model performances in the specialized literature.     

The role of wind field, mixing height and horizontal diffusivity investigated through two lagrangian particle models

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 K_H 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 K_H 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 K_H (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.     

Description and preliminary validation of the PMSS fast response parallel atmospheric flow and dispersion solver in complex built-up areas

Noxious atmospheric releases may originate from both accidents and malicious activities. They are a major concern for public authorities or first responders who may wish to have the most accurate situational awareness. Nonetheless, it is difficult to reliably and accurately model the flow, transport, and dispersion processes in large complex built-up environments in a limited amount of time and resources compatible with operational needs. The parallel version of Micro-SWIFT-SPRAY (PMSS) is an attempt to propose a physically sound and fast response modelling system applicable to complicated industrial or urban sites in case of a hazardous release. This paper presents and justifies the choice of the diagnostic flow and Lagrangian dispersion models in PMSS. Then, it documents in detail the development of the parallel algorithms used to reduce the computational time of the models. Finally, the paper emphasizes the preliminary model validation and parallel performances of PMSS based on data from both wind tunnel (Evaluation of Model Uncertainty) and in-field reduced-scale (Mock Urban Setting Test) and real-scale (Oklahoma City) experimental campaigns.     

Comparison of atmospheric modelling systems simulating the flow,turbulence and dispersion at the microscale within obstacles

Three different modelling techniques to simulate the pollutant dispersion in the atmosphere at the microscale and in presence of obstacles are evaluated and compared. The Eulerian and Lagrangian approaches are discussed, using RAMS6.0 and MicroSpray models respectively. Both prognostic and diagnostic modelling systems are considered for the meteorology as input to the Lagrangian model, their differences and performances are investigated. An experiment from the Mock Urban Setting Test field campaign observed dataset, measured within an idealized urban roughness, is used as reference for the comparison. A case in neutral conditions was chosen among the available ones. The predicted mean flow, turbulence and concentration fields are analysed on the basis of the observed data. The performances of the different modelling approaches are compared and their specific characteristics are addressed. Given the same flow and turbulence input fields, the quality of the Lagrangian particle model is found to be overall comparable to the full-Eulerian approach. The diagnostic approach for the meteorology shows a worse agreement with observations than the prognostic approach but still providing, in a much shorter simulation time, fields that are suitable and reliable for driving the dispersion model.