Prediction of air pollutants concentrations from multiple sources using AERMOD coupled with WRF prognostic model

Abstract

The investigation of pollutants concentrations affected by the multiple sources is essential for air quality management. In this study, the spatial variations of SO2, NO2 and PM10 emitted from multiple industrial sources in Pasir Gudang industrial area, Johor, Malaysia were predicted using American Meteorological Society/Environmental Protection Regulatory Model (AERMOD) air dispersion model coupled with Weather Research and Forecasting (WRF). The WRF model was applied to simulate the hourly surface and upper air meteorological variables for the period of two weeks. The output parameters from WRF such as temperature, wind speed and wind direction were also statistically evaluated in the study. The results of comparing the wind roses from the observed and simulated data in Pasir Gudang station showed the difficulty of prognostic WRF model in predicting wind direction in Malaysia located in a coastal site. The results showed that the maximum ground level concentration of SO2, NO2 and PM10 simulated through AERMOD-WRF in the industrial area was 36.2, 59.8 and 5.4 μg/m3, respectively. The evaluation of AERMOD through the Quantile-Quantile (Q-Q) plots showed that most of the predicted and observed pair points are lying close to the one-to-one line indicating that there is a good agreement between predicted and observed concentrations in the study. The findings of this study can facilitate and assist the local government authorities and policy makers in managing the urban air quality.