An advanced puff model based on a mixed Eulerian/Lagrangian approach for turbulent dispersion in the convective boundary layer

An advanced model aimed at describing the problem of dispersion in the conv ective boundary layer is proposed. The pollutant particles are grouped in c lusters and modelled as Gaussian puffs. The expansion of each puff is model led according to the concept of relative dispersion and expressed in terms of the spectral properties of the energy containing eddies of the turbulent field. The centre of mass of each puff is moved along a stochastic traject ory, obtained using a Lagrangian stochastic model and filtering the velocit y with a recursive Kalman filter. At any instant, a filtering procedure, de pending both on travel time and on puff size, acts to select spectral compo nents involved in the expansion and in the meandering of the puff. Such an approach requires only a moderate number of puff releases, so that the prop osed model is faster to run than a standard Lagrangian model. On the other hand, unlike the traditional puff model, it allows us to simulate both expa nsion and meandering of the puff. Therefore, it is well suited to simulate dispersion when the turbulent structures are larger than the plume dimensio ns, as for example in convective conditions. Being based on spectral formul ations in both Eulerian and Lagrangian parts, the model is consistent in al l the turbulent parameterizations utilised. Comparisons with a standard Lag rangian particle model as well as with a classical convective experimental dataset show good performance of the proposed model.