MULTISCALE ATMOSPHERIC DISPERSION MODELING BY USE OF ADAPTIVE GRIDDING TECHNIQUES

An accurate prediction of the transport-reaction behaviour of atmosphe ric chemical species is required to fully understand the impact on the environment of pollution emissions. Elevated levels of secondary poll utants such as ozone in the lower atmosphere can be harmful to the hea lth of both plants and animals, and can cause damage to property prese nt in the urban environment. Detailed models of pollution mechanisms m ust therefore be developed through comparisons with field measurements to aid the selection of effective abatement policies. Such models mus t satisfy accuracy requirements both in terms of the number of species represented, and the spatial resolution of species profiles. Computat ional expense often compels current models to sacrifice detail in one of these areas. This paper attempts to address the latter point by pre senting an atmospheric transport-reaction modelling strategy based upo n a finite volume discretisation of the atmospheric dispersion equatio n. The source terms within this equation are provided by an appropriat e reduced chemical scheme modelling the major species in the boundary layer. Reaction and transport discretisations are solved efficiently v ia a splitting technique applied at the level of the non-linear equati ons. The solution grid is generated using time dependant adaptive tech niques, which provide a finer grid around regions of high spatial erro r in order to adequately resolve species concentration profiles. The t echniques discussed are applied in two dimensions employing emissions from both point and area sources. Preliminary results show that the ap plication of adaptive gridding techniques to atmospheric dynamics mode lling can provide more accurately resolved species concentration profi les, accompanied by a reduced CPU time invested in solution. Such a mo del will provide the basis for high resolution studies of the multiple scale interactions between spatially inhomogeneous source patterns in urban and regional environments.