Fine particulate matter (PM_2.5) is a dynamic and complex mixture of particle matter with an aerodynamic diameter equal or less than 2.5 µm that can seriously affect the air quality and public health. High spatial and temporal resolution PM_2.5 data is a basic requirement for public health risk assessment and epidemiological research. Compared with ground-based datasets, satellite remote sensing provides continuous, wide space coverage and low-cost observation, and the PM_2.5 mass concentrations retrieval based on the satellite aerosol optical depth (AOD) has become a popular topic. This paper systematically scrutinizes the research on the near-surface PM_2.5 concentration retrieved based on satellite AOD products. The basic method of estimating the PM_2.5 concentration based on satellite AOD products is introduced, and the main satellite AOD products used for PM_2.5 retrieval and their accuracy are described in detail. The existing PM_2.5 estimation methods and their pros and cons are also discussed. Finally, the problems identified in PM_2.5 retrieval research and the development direction of PM_2.5 retrieval research are presented in the future.The scale factor method and the physical mechanism and statistical models can accurately estimate the PM_2.5 concentrations at different degrees in different periods, but the scale factor method and the physical mechanism model are less used than the statistical model because of their limitations. Statistical models have been widely used and improved due to their unique descriptive ability of temporal or spatiotemporal heterogeneity and strong nonlinear description ability. However, the current PM_2.5 retrieve research has three main limitations: 1. the non-random missing problem of satellite AOD causes missing PM_2.5 data; 2. inaccuracy of retrieval models, and 3. Poor chemical composition estimation of PM_2.5. Therefore, to accurately reveal the spatial and temporal trends of near-ground PM_2.5 and improve the accuracy of the near-ground PM_2.5 calculated from satellite AOD products, we predict several future research directions. First, the AOD products of new high-spatial-resolution (such as FY-4 and GF-5) and high-temporal-resolution (HIMAWARI-8/-9) satellites could greatly promote the research on PM_2.5 estimation, which is of great significance to the reconstruction of PM_2.5 concentrations with high spatial-temporal resolutions. Second, with the development of atmospheric detection technology, satellite-based, airborne, and ground-based lidar can obtain vertical distribution information, and the particle matter sensor carried on UAVs can achieve the vertical monitoring of PM_2.5, which can be combined with optical remote sensing satellite and ground monitoring data to achieve three-dimensional PM_2.5 concentration retrieval. Finally, PM_2.5 chemical component information is particularly important for analyzing the cause of pollution and exposure characteristics, and its space–time change trend research is an important development direction. However, the ground PM_2.5 component observation network is still imperfect, and overcoming the dependence on ground station network in satellite remote sensing estimation and achieving the high-precision retrieval of chemical composition need further study.This study is helpful in further understanding the principles, advantages, and disadvantages of different PM_2.5 estimation methods, providing inspiration for the new development direction of near-surface PM_2.5 concentrations retrieval based on satellite AOD products, and improving the accuracy and spatial-temporal resolution of near-surface PM_2.5 concentrations retrieval.

PM_2.5;satellite remote sensing;AOD;estimation methods