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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 R 2 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 estimated PM2.5 concentrations shows that the new method proposed in this paper is better than the traditional method. The coefficient of determination R 2 is improved from 0.32 to 0.62.