Summary: The concentration of air pollutants have in general been steadily increasing during the last three decades. To correctly gauge the impact of various sources of pollutants requires careful modelling of the complex physics processes associated with the chemistry and transport of air pollution. These models are computationally demanding and require today’s fastest high performance computers for practical implementations. The damaging effects are normally due to the combined effects of several air pollutants. Therefore a reliable mathematical model must study simultaneously all relevant air pollutants. This requirement increases the size of the air pollution models. The discretization of models that contain many air pollutants leads to huge computational problems. After the discretization of such an air pollution model, systems of several hundred thousands (or even several millions) of equations arise and these have to be treated numerically during many time-steps (typically several thousands). Such big computational problems can successfully be treated only on big modern vector and/or parallel computers. However, access to a fast high-speed computer is not sufficient. One must also ensure that the great potential power of the computer is correctly exploited. Very often this is a rather difficult task. The efforts to solve this task in the case where the computer under consideration is a massively parallel machine will be discussed in this paper. Tests performed on several such computers will be presented.