Comparative evaluation of a Eulerian CFD and Gaussian plume models for roadside heavy metal deposition

Efficient and flexible transport systems are an important part of the world's economy and thus, quality of life. Nevertheless, road traffic is an important negative factor regarding air quality, noise and land consumption (Zechmeister et al., 2005). Additionally, it poses a threat to plants and animals, and has direct and indirect consequences for human beings. The US EPA highlights 21 toxic substances that can mainly be assigned to road traffic. Some heavy metals are among them (e.g. Pb, Cd, Cu, Sb, or Zn; US Government, 2001). One of the major problems caused by vehicular traffic at local scales is dry and wet atmospheric deposition near roadside, where the geometry of terrain can be very complex. Modeling is very useful to characterize pollutant dispersion and deposition and to understand source- receptor relationships. In cases where the resolved wind flow and atmospheric turbulence are significantly affected by the presence of buildings or complex terrain, standard analytical models such as Gaussian puff or plume models may not be appropriate; instead, computational fluids dynamics (CFD) models are a more appropriate method for this kind of modeling study. This paper describes the incorporation and adaptation of dry and wet deposition schemes for atmospheric particulate matter dynamics in Mercure-Saturne, a CFD model, which is coupled with a modal aerosol model, capable of following the formation and dispersion of particles. Several sensibility tests were performed to ensure that the coupling of the models was functioning correctly. Cadmium is one of the major heavy metals emitted by road traffic and it was, therefore, selected for a modeling case study near an expressway in France, where roadside measurements are available for a simple case in flat terrain. Emission estimation for cadmium is discussed in details. The CFD simulation results are compared with two Gaussian models results and with measurements at different distances from the road. Even for this simple geometry, the results demonstrate that, near the source, the CFD model has significantly better results than Gaussian models. Farther downwind from the source, the results of the CFD model and Gaussian models are more similar. Spatial patterns of road traffic-related cadmium deposition and factors influencing these patterns are discussed. For a monthly average period, cadmium deposition rates decrease from 5 m to 20 m, 40 m, 80 m, and 160 m by about 60%, 73%, 80%, and 90%, respectively. These road-related deposition rates are compared with background values to characterize the potential impact of road-traffic as a source of pollutant deposition. Perspectives of applications of this model in more realistic settings such as in urban area are discussed.