The Chengdu–Chongqing Economic Zone (CCEZ), which is located in southwestern China, is the fourth largest economic zone in China. The rapid economic development of this area has resulted in many environmental problems, including extremely high concentrations of nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5). However, current ground observations lack spatial and temporal coverage. In this study, satellite remote sensing techniques were used to analyze the variation in NO₂ and PM_2.5 from 2005 to 2015 in the CCEZ. The Ozone Monitoring Instrument (OMI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) product were used to retrieve tropospheric NO₂ vertical columns and estimate ground-level PM_2.5 concentrations, respectively. Geographically, high NO₂ concentrations were mainly located in the northwest of Chengdu and southeast of Chongqing. However, high PM_2.5 concentrations were mainly located in the center areas of the basin. The seasonal average NO₂ and PM_2.5 concentrations were both highest in winter and lowest in summer. The seasonal average NO₂ and PM_2.5 were as high as 749.33 × 10¹³ molecules·cm⁻² and 132.39 µg·m⁻³ in winter 2010, respectively. Over 11 years, the annual average NO₂ and PM_2.5 values in the CCEZ increased initially and then decreased, with 2011 as the inflection point. In 2007, the concentration of NO₂ reached its lowest value since 2005, which was 230.15 × 10¹³ molecules·cm⁻², and in 2015, the concentration of PM_2.5 reached its lowest value since 2005, which was 26.43 µg·m⁻³. Our study demonstrates the potential use of satellite remote sensing to compensate for the lack of ground-observed data when quantitatively analyzing the spatial–temporal variations in regional air quality.

The tropospheric vertical column density of NO₂ (Trop NO₂ VCD) can be obtained using satellite remote sensing, but it has been discovered that the Trop NO₂ VCD is affected by uncertainties such as the cloud fraction, terrain reflectivity, and aerosol optical depth. A certain error occurs in terms of data inversion accuracy, necessitating additional ground observation verification. This study uses surface NO₂ mass concentrations from the China National Environmental Monitoring Center (CNEMC) sites in Jiangsu Province, China in 2019 and the Trop NO₂ VCD measured by MAX-DOAS, respectively, to verify the Trop NO₂ VCD product (daily and monthly average data), that comes from the TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI). The results show that the spatial distributions of NO₂ in TROPOMI and OMI exhibit a similar tendency and seasonality, showing the characteristics of being high in spring and winter and low in summer and autumn. On the whole, the concentration of NO₂ in the south of Jiangsu Province is higher than that in the north. The Pearson correlation coefficient (r) between the monthly average TROPOMI VCD NO₂ and the CNEMC NO₂ mass concentration is 0.9, which is greater than the r (0.78) between OMI and CNEMC; the r (0.69) between TROPOMI and the MAX-DOAS VCD NO₂ is greater than the r (0.59) between OMI and the MAX-DOAS. As such, the TROPOMI is better than the previous generation of OMI at representing the spatio-temporal distribution of NO₂ in the regional scope. On the other hand, the uncertainties of the satellite products provided in this study can constrain regional air quality forecasting models and top-down emission inventory estimation.

Quantifying spatiotemporal polar ozone changes can promote our understanding of global stratospheric ozone depletion, polar ozone-related chemical processes, and atmospheric dynamics. By means of ground-level measurements, satellite observations, and re-analyzed meteorology, the global spatial and temporal distribution characteristics of the total column ozone (TCO) and ozone profile can be quantitatively described. In this study, we evaluated the ozone datasets from CrIS/NOAA20, AIRS/Aqua, and ERA5/ECWMF for their performance in polar regions in 2020, along with the in situ observations of the Dobson, Brewer, and ozonesonde instruments, which are regarded as benchmarks. The results showed that the ERA5 reanalysis ozone field had good consistency with the ground observations (R > 0.95) and indicated whether the TCO or ozone profile was less affected by the site location. In contrast, both CrIS and AIRS could capture the ozone loss process resulting from the Antarctic/Arctic ozone hole at a monthly scale, but their ability to characterize the Arctic ozone hole was weaker than in the Antarctic. Specifically, the TCO values derived from AIRS were apparently higher in March 2020 than those of ERA5, which made it difficult to assess the area and depth of the ozone hole during this period. Moreover, the pattern of CrIS TCO was abnormal and tended to deviate from the pattern that characterized ERA5 and AIRS at the Alert site during the Arctic ozone loss process in 2020, which demonstrates that CrIS ozone products have limited applicability at this ground site. Furthermore, the validation of the ozone profile shows that AIRS and CrIS do not have good vertical representation in the polar regions and are not able to characterize the location and depth of ozone depletion. Overall, the results reveal the shortcomings of the ozone profiles derived from AIRS and CrIS observations and the reliability of the ERA5 reanalysis ozone field in polar applications. A more suitable prior method and detection sensitivity improvement on CrIS and AIRS ozone products would improve their reliability and applicability in polar regions.

With the initial establishment of global earth observation system in various countries, more and more high-resolution remote sensing data of multisource, multitemporal, multiscale, and different types of satellites are obtained. It is urgent to explore the advanced basic theory of remote sensing information science, design high-performance generic key technologies of remote sensing information system and global positioning system, and study complex engineering system of remote sensing applications and geographic information system. In this article, the basic theory exploration, inversion technology research, and engineering application design and development of generic optical remote sensing product (ORSP) are systematically reviewed. We classify the ORSP scientifically, review the main algorithms and application scope of 16 kinds of generic ORSP, and expound the validation and quality evaluation methods of ORSP in engineering application. Furthermore, we analyze the current core problems and solutions, and prospects for the state-of-the-art research and the future development trend of generic ORSP. This will provide valuable reference for scientific research and construction of high-resolution earth observation system.

With the acceleration of urbanization, ozone (O₃) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O₃ based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O₃ with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index ${\mathrm{G}}_{\mathrm{i}}^{*}$ were adopted to reveal the spatial agglomeration of O₃ pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m⁻³ increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O₃ concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O₃ concentration reached 200 μg·m⁻³ in North China (NC) in June, while the lowest value was 60 μg·m⁻³ in Northeast China (NEC) in December. O₃ is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O₃ concentrations are significantly differentiated in space: O₃ pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O₃ exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC.