ESTIMATION AND EVALUATION OF AIR QUALITY DEGRADATION BY THE SUDDEN BURNING ACTIVITIES

Satellite remote sensing data have been a valuable tool for severe air pollution event monitoring. In this study, we present the results of smoke plume from the sudden burning accident cases such as chemical explosion and forest fires by using the combination of satellite and trajectory analysis (CSTA) method. CSTA uses the satellite detected smoke plume data and a matching forward-trajectories for generating airmass history pattern. Smoke detection based on the polar- and geostationary-orbit satellite observation data were compared to the forward air mass trajectory analysis by the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The use of CSTA for the major event cases reveals remarkable spatial coherence for source-transport pattern. CSTA forecasted points of ES are consistent with the area of satellite detected smoke plume. The success rate of the 24 hour forecast result was about 78.7% in this study. There was good correlation between satellite images and trajectory lines after the explosions, which support the feasibility of using the integration of satellite observed and model derived data for emergency forecasting.