Abstract :
Considering the convective boundary layer physical structure and their characteristics, a derivation for the Lagrangian decorrelation timescales to be used in Lagrangian stochastic particle models has been developed. That is, expressions for the Lagrangian decorrelation timescales depending on source distance for inhomogeneous turbulence are proposed. The classical statistical diffusion theory, the observed spectral properties and observed characteristics of energy-containing eddies are used to estimate these parameters. In addition, these decorrelation timescales were introduced in an Lagrangian stochastic particle model and validated with the data of Copenhagen experiments. The results of this new method are shown to agree very well with the measurements of Copenhagen. Furthermore, the present study suggests that the inclusion of the memory effect, important in near regions from an elevated continuous point source, improves the description of the turbulent transport process of atmospheric contaminants. The major advance shown in this paper is the necessity of including the downwind distance-dependent decorrelation timescales in air quality modeling, and it is demonstrated that such theory would suggest that it should yield better results than the asymptotic solution alone. It in fact does yields better results in the near and intermediate fields.
