A NEW AIR POLLUTION SOURCES IDENTIFICATION METHOD BASED ON REMOTELY SENSED AEROSOL AND SWARM INTELLIGENCE

In this paper, a novel method was developed to orientate and quantify the air pollution sources based on remotely sensed aerosol data and Glowworm Swarm Optimization (GSO). In practice, based on source apportionment technique, the air pollution sources could just be identified to certain industries, such as transportation, power plants, biomass burning, and et. al. To our knowledge, the problem of orientating and quantifying the pollution to the individual factories is faced for the first time. In this study, the aerosol retrieved from remotely sensed image (MODIS) and GIS were used to locate and quantify the pollution to each enterprise in the study area based on an improved Glowworm Swarm Optimization and meteorological condition. As a result, the polluting contribution of each factory were be listed, and the most polluting factories were be found. Some experiments were carried out to validate the method, and the Key monitoring factories by authority was ferreted out accurately.