Using efficient numerical methods in large-scale air pollution modelling

The air pollution, and especially the reduction of the air pollution to some acceptable levels, is an important environmental problem, which will become even more important in the next two-three decades. This problem can successfully be studied only when high-resolution comprehensive models are developed and used on a routinely basis. However, such models are very time-consuming, also when modern high-speed computers are available. Indeed, if an air pollution model is to be applied on a large space domain by using fine grids, then its discretization will always lead to huge computational problems. Assume, for example, that the space domain is discretized by using a (288x288) grid and that the number of chemical species studied by the model is 35. Then ODE systems containing 2903040 equations have to be treated at every time-step (the number of time-steps being typically several thousand). If a three-dimensional version of the air pollution model is to be used, then the number of equations must be multiplied by the number of layers. The treatment of large air pollution models on modern parallel computers by using efficient numerical algorithms will be discussed in this