Comparison between the results of a Monte Carlo atmospheric diffusion model and tracer experiments

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.