A review of collaborative remote sensing observation of atmospheric gaseous and particulate pollution with atmospheric environment satellites

Air pollution, as important environmental problem, directly affects daily life and physical health of public. The gradual maturity of polluted gas and particulate matter observation technology has rapidly developed the monitoring of air pollutants near the surface based on satellite platforms. This study aims to clarify the collaborative observation's history for aerosols and gases and then provide a reference for future satellite platform design.In this study, the popular remote sensing methods for trace gases and atmospheric particulates that are concerned on atmospheric environment are first described, and the applicable scenarios, advantages, and disadvantages of each method are discussed. Next, satellite platforms for collaborative observations of trace gases and aerosols are reviewed. According to the characteristics of remote sensing principle for the trace gases, the satellite platform is divided into ultraviolet and infrared bands, and the development course of sensors and satellite platforms are discussed and analyzed. Finally, we discuss the issues to be solved urgently by satellite platforms and remote sensing algorithms aiming to monitor air pollutants near the ground, as well as possible future development directions.For various trace gases, the good universal remote sensing methods are differential absorption spectrometry method and optimal estimation algorithm, which can fully utilize the absorption spectrum lines to achieve inversion of gases. The differential absorption spectroscopy method is effective for the monitoring of trace gases. However, the optimized estimation algorithm can further extract the layered information of trace gases from the hyperspectral information, which is helpful for obtaining a more detailed vertical distribution of trace gases in the atmospheric column. The band residual method and linear fitting method have strong pertinence to specific pollutant gases (such as sulfur dioxide). These simplified algorithms also have great advantages and application value. The core issue of the aerosol inversion algorithm is the signal decoupling of ground and atmosphere. Adding the information from spectrum, angle, polarization, and time series can effectively increase the decoupling capabilities. The algorithms derived from these principles include dark target algorithm, deep blue algorithm, empirical orthogonal function algorithm, polarization algorithm, and time series algorithm. Since the launch of NOAA-9 carrying SBUV/2 and AVHRR/2 in 1984, the collaborative detection of polluted gases and particulate matter has begun. Subsequently, Europe, the United States, South Korea, and China have launched satellites carrying advanced sensors, from the polar orbit to geostationary orbit. In the future, FY-4A of China, Geo-kompsat-2b of South Korea, Sentinel-4 of Europe, and TEMPO of the United States can be forming a global geostationary satellite constellation with high spatial resolution and hourly monitoring capability to achieve collaborative monitoring of polluted gases and particulate matter.On the basis of the summary of trace gas and atmospheric aerosol inversion algorithms, the development history of satellite platforms and sensors is combined from the perspective of cooperative observation of gas and particulate matter. The advantages of cooperative observation of sensors in the ultraviolet, visible, and infrared bands are discussed. The high temporal and spatial resolution air pollution monitoring capabilities of the geostationary satellite constellation in the future and the contribution of Chinese satellites are prospected. © 2022, Science Press. All right reserved.