In order to study the distribution of PM_2.5 mass concentration in China and monitor the changes of atmospheric environment in China, based on the Aerosol and Carbon dioxide Detection Lidar (ACDL) aerosol data of atmospheric environment monitoring satellites (DQ-1) and the ground-based PM_2.5 observation data of China, the correlation between aerosol optical depth (AOD) and PM_2.5 data was improved through vertical correction and humidity correction, and the seasonal variation of PM_2.5 mass concentration changes in China from June 2022 to May 2023 was estimated using the semi-empirical method. The results show that during the period from June 2022 to May 2023, the PM_2.5 mass concentration in China is the lowest in summer and the highest in winter. Due to the existence of desert in Xinjiang, the annual PM_2.5 mass concentration is relatively high. The PM_2.5 mass concentration in most parts of China is about 30 μg/m3, and the correlation between remote sensing estimation of PM_2.5 annual mean and station data is better than 0.71. This study is of certain significance for enriching regional PM_2.5 inversion methods and expanding the application of ACDL atmospheric data.