摘要
We propose a new method to estimate surface-level particulate matter(PM)concentrations by using satellite-retrieved Aerosol Optical Thickness(AOT).This method considers the distribution and variation of Planetary Boundary Layer(PBL)height and relative humidity(RH)at the regional scale.The method estimates surface-level particulate matter concentrations using the data simulated by an atmospheric boundary layer model RAMS and satellite-retrieved AOT.By incorporation MODIS AOT,PBL height and RH simulated by RAMS,this method is applied to estimate the surface-level PM 2.5 concentrations in North China region.The result is evaluated by using 16 ground-based observations deployed in the research region,and the result shows a good agreement between estimated PM 2.5 concentrations and observations,and the coefficient of determination R2 is 0.61 between the estimated PM 2.5 concentrations and the observations.In addition,surface-level PM 2.5 concentrations are also estimated by using MODIS AOT,ground-based LIDAR observations and RH measurements.A comparison between the two estimated PM 2.5 concentrations shows that the new method proposed in this paper is better than the traditional method.The coefficient of determination R2 is improved from 0.32 to 0.62.
We propose a new method to estimate surface-level particulate matter （PM） concentrations by using satellite-retrieved Aerosol Optical Thickness （AOT）. This method considers the distribution and variation of Planetary Boundary Layer （PBL） height and relative humidity （RH） at the regional scale. The method estimates surface-level particulate matter concentrations using the data simulated by an atmospheric boundary layer model RAMS and satellite-retrieved AOT. By incorporation MODIS AOT, PBL height and RH simulated by RAMS, this method is applied to estimate the surface-level PM2.5 concentrations in North China region. The result is evaluated by using 16 ground-based observations deployed in the research region, and the result shows a good agreement between estimated PM2.5 concentrations and observations, and the coefficient of determination R2 is 0.61 between the estimated PM2.5 concentrations and the observations. In addition, surface-level PM2.5 concentrations are also estimated by using MODIS AOT, ground-based LIDAR observations and RH measurements. A comparison between the two es- timated PM2.5 concentrations shows that the new method proposed in this paper is better than the traditional method. The coef- ficient of determination R2 is improved from 0.32 to 0.62.
基金
supported by National Department Public Benefit Research Foundation (Ministry of Environmental Protection of the People’s Republic of China) (Grant No. 201009001)
National Natural Science Foundation of China (Grant No. 41101327)
