Development of a numerical prediction model for a long-term averaged concentration of air pollutants and its application in Kanto Area

Abstract

For the prediction of annual mean concentration distribution of air pollutants in mesoscale area it is too expensive to accumulate instantaneous values predicted by a three-dimensional unsteady model. In this study we aimed to develop a numerical model, which uses annual mean statistics of wind, emission intensity and so on as inputs, and outputs annual mean concentration distribution. The focus was located on the estimation of horizontal diffusion coefficient. This model was applied to the prediction of annual mean concentration distribution of NOx in Kanto area. The results are compared with observations and the results estimated by an unsteady model.