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

2021 
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 advanced formulations for the deposition mechanisms of sedimentation, inertial impaction, turbulent impaction and interception. The scheme also considers bouncing effects. The input quantities relate to the canopy elements (Leaf Area Density, leaf equivalent diameter, leaf shape, orientation and roughness parameters), the transporting fluid (local mean velocity, friction velocity) and the particulate matter (PM local mean concentration, median diameter and density). The deposition scheme is coupled with a well-known Lagrangian Stochastic model for pollutant dispersion, the Open-Source code SPRAY-WEB (Universita del Piemonte Orientale et al.). The coupled numerical solution is validated on a laboratory test case representing the dispersion of particulate matter from two line sources within a canopy atmospheric boundary layer. The deposition interfaces are represented by the trees of a scaled spruce forest. Validation refers to the average vertical profile of the deposited mass (not the mean concentration) normalized by the above-canopy mean concentration. Some inter-comparisons are also reported considering uniform Leaf Area Density, the additional effects of molecular diffusion, the height-dependent relative contribution of each deposition mechanism and an alternative deposition scheme. The results of this test case are available as a FOSS tutorial. Considering the Fractional Bias obtained for the deposited mass (FB = 27%), this numerical solution seems suitable to simulating stationary dispersion phenomena within complex canopy boundary layers, assessing the height-dependent dry deposition fluxes of atmospheric PM. The current numerical solution might be improved and applied to elevated obstacles such as electric insulators.
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