In order to improve an accuracy of the real-time odor dispersion modeling system, a sensitivity of CALMET model with different input meteorological data was studied. The performance of CALMET model was tested by comparing the model predictions with the observations at the Daedeok Industrial Complex in Daejeon Metropolitan City. It is shown that the CALMET model with WRF (Weather Research and Forecasting) input data of GFS (Global Forecast System) depicts the measurements better than that of RDAPS (Regional Data Assimilation and Prediction System). The CALMET model could be further improved by selecting options of Divergence minimization, Froude number adjustment and Slope flows without choosing Kinematic Effects in the modeling procedure.

There are many odor complains in Ansan and Siheung industrial complexes. In order to solve the odor problem, it is necessary to identify the major odor emission sources and to understand odor dispersion mechanism in these areas by applying the real-time odor monitoring system. The proposed system mainly consists of the measuring network of odor causing materials and meteorological variables as well as the dispersion modeling system on real-time base. In this study, the effective ways is also proposed to apply the system to ameliorate the odor environments.