Estimation Of Airborne Particulate Matter Based On Haze Optimized Transformation (HOT)

The rapid development of the process of urbanization and the rapid increase of motor vehicle, all of which has brought increase of the emissions to the atmosphere and air pollution.Therefore air pollution disasters occurred frequently. And particulate matter pollution is the main form of air pollution in China. Currently, satellite remote sensing has become one of the important means of technology in the monitoring of air pollution.This paper attempted to use Haze Optimized Transformation(HOT) which is image-based to remote sensing monitoring of air pollution for the study area in Nanjing.A feasibility study if HOT could be used in particulate matter of air pollution remote monitoring was carried out based atmospheric radiative transfer model (6S) and MODIS data. This study attempts to provide a new technology and methods for satellite remote sensing monitoring of air pollution to facilitate remote monitoring of air pollution technology.In this paper,the relationships between HOT and aerosol optical thickness,surface type and viewing angles were similated and researched based on 6S model in order to study the sensitivity of HOT characterization of AOT; the relationship between HOT extracted from MODIS data and PM10 obtained from ground monitoring was analysed to build the regression model of them for the study area to achieve the purpose that HOT estimates atmospheric particulate pollution.The result of simulation showed that HOT positively correlated with AOT,The regression analysis for HOT extracted through MODIS images which include winters and springs from 2007 to 2009 in Nanjing and relevant PM10 showed that:HOT and PM10 had significant positive correlation which confidence levelα=0.01.The fitting accuracy of the quadratic model for cities, vegetation, water and mixed surface in the two half years (winter and spring) were 80.16%,80.53%,74.95%,80.16%,respectively;in winter the fitting accuracy were 75.87%,75.22%,74.93%,75.33%, respectively; in spring the fitting accuracy were 84.80%,85.23%,84.27%,84.81%, fitting accuracy is quitly high.Results of this study show that it is feasible that HOT estimate respirable particulate matter pollution(PM10) in surface.This paper provides references for the use of HOT technology to achieve remote monitoring of air pollution particles.