Validation of a Lagrangian dispersion model implementing different kernel methods for density reconstruction

In this paper the inert version of a Lagrangian particle model named photochemical Lagrangian particle model (PLPM) is described and validated. PLPM implements four density reconstruction algorithms based on the kernel density estimator. All these methods are fully grid-free but they differ each other in considering local or global features of the particles distribution, in treating the Cartesian directions separately or together and in being based on receptors or particles positions in space. Each kernel has been shown to have both advantages and disadvantages, but the overall good performances of the model when compared with the well known Copenhagen and Kincaid data sets are very encouraging in view of its extension to fully chemically active simulations, currently under development.