It is a challenging task to estimate how a pollutant's concentration will vary geographically when it comes from different sources. This may be accomplished by using Gaussian air pollution dispersion models. The most uncertain part of applying dispersion model is the availability of meteorological data. Thus, the present study aims to design a hybrid model (WRF coupled AERMOD) for dispersion analysis in an opencast coal mining region. The results will be used for understanding the seasonal and annual variations of air pollution. Moreover, source apportionment study will be carried out to identify the major pollution sources. An exposure analysis will be carried to assess the level of health hazard to nearby residents. 

For meteorological data, the National Centre for Atmospheric Research's (NCAR) Weather Research and Forecasting (WRF) Model was used to calculate the planetary boundary layer and surface layer parameters needed by AERMOD in order to get around this restriction. For preliminary evaluation of the model, the respirable particulate matter (RPM/PM₁₀) dispersion over Rourkela city, India, was carried out. It is evident from the WRF-based simulated results of meteorological data (temperature and wind fields) closely agreed the actual meteorological data (temperature and wind fields). This indicates that WRF is capable of producing accurate meteorological inputs for AERMOD. The results of hybrid model (WRF coupled AERMOD) indicates that predicted values are usually lower than the observed concentrations over the city. To improve the dependability of the WRF&ndashAERMOD modeling system, more simulations using various WRF parameterizations as well as better pollutant source data will be needed.