Onboard the Chinese GaoFen-5 (GF5) satellite, the Environmental trace gases Monitoring Instrument (EMI) is a nadir-viewing wide-field spectrometer that was launched on May 9, 2018. EMI measures the back-scattered earthshine solar radiance in the ultraviolet and visible spectral range. By using the differential optical absorption spectrometry (DOAS) method and the EMI measurements in the VIS1 band (405–465 nm), we performed retrievals of NO₂. Some first retrieval results of NO₂ from EMI and a comparison with OMI and TROPOMI products are presented in this paper. The monthly mean total vertical column densities (VCD) of NO₂ show similar spatial distributions to OMI and TROPOMI (r > 0.88) and their difference is less than 27%. A comparison of the daily total VCD shows that EMI could detect the NO₂ patterns in good agreement with OMI (r = 0.93) and TROPOMI (r = 0.95). However, the slant column density (SCD) uncertainty (0.79 × 10¹⁵ molec cm⁻²) of the current EMI algorithm is relatively larger than OMI. The daily variation pattern of NO₂ from EMI in Beijing in January 2019 is consistent with TROPOMI (r = 0.96). The spatial distribution correlation of the tropospheric NO₂ VCD of EMI with OMI and TROPOMI is 0.88 and 0.89, respectively, but shows an overestimate compared to OMI (15%) and TROPOMI (23%), respectively. This study demonstrates the capability of using EMI for global NO₂ monitoring.

The widespread distribution and strong seasonal pattern of highly concentrated summertime formaldehyde (HCHO) were observed using data from the Ozone Monitoring Instrument (OMI) onboard Aura satellite from 2005 to 2015 in Beijing-Tianjin-Hebei, China. The large-scale HCHO concentrations and its close connection with the surface O₃ pollution made the study of summertime HCHO patterns and its major contributors necessary. Accordingly, time series decomposition, Moran’s I and Pearson correlation coefficient (PCC) were adopted to investigate the spatiotemporal variations of HCHO. We found that the HCHO columns regionally increased from 2005 to 2010 and decreased in the north (e.g., Chengde) from 2010 to 2015. Additionally, HCHO Vertical Column Densities (VCDs) exhibited higher values in urban areas. Despite the strong possibilities of major biogenic contributions, anthropogenic sources represented larger spatial PCCs and larger total emission rates. Industrial sources exhibited a large increasing emission amount, and the most similar distribution to HCHO was found in residential sources. By comparison, power-based emissions accounted for a relatively small fraction, and transportation emissions declined rapidly. In conclusion, anthropogenic VOCs might contribute to the summertime HCHO concentrations as well as isoprene, and controls on VOCs and HCHO would be greatly assisted by the satellite-based observations.

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.

The temporal and spatial distributions of tropospheric ozone and its precursors (NO₂, CO, HCHO) are analyzed over Guangxi (GX) in South China. We used tropospheric column ozone (TCO) from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) onboard the Aura satellite (OMI/MLS), NO₂ and HCHO from OMI and CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument in the period 2005–2016. The TCO shows strong seasonality, with the highest value in spring and the lowest value observed in the monsoon season. The seasonal variation of HCHO is similar to that of TCO, while NO₂ and CO show slightly different patterns with higher values in spring and winter compared to lower values in autumn and summer. The surface ozone, NO₂ and CO observed by national air quality monitoring network sites are also compared with satellite-observed TCO, NO₂ and CO, showing good agreement for NO₂ and CO but a different seasonal pattern for ozone. Unlike TCO, surface ozone has the highest value in autumn and the lowest value in winter. To reveal the difference, the vertical profiles of ozone and CO from the measurement of ozone and water vapor by airbus in-service aircraft (MOZAIC) observations over South China are also examined. The seasonal averaged vertical profiles of ozone and CO show obvious enhancements at 2–6 km altitudes in spring. Furthermore, we investigate the dependence of TCO and surface ozone on meteorology and transport in detail along with the ECMWF reanalysis data, Tropical Rainfall Measuring Mission (TRMM) 3BV42 dataset, OMI ultraviolet index (UV index) dataset, MODIS Fire Radiative Power (FRP) and back trajectory. Our results show that the wind pattern at 800 hPa plays a significant role in determining the seasonality of TCO over GX, especially for the highest value in spring. Trajectory analysis, combined with MODIS FRP suggests that the air masses that passed through the biomass burning (BB) region of Southeast Asia (SEA) induced the enhancement of TCO and CO in the upper-middle troposphere in spring. However, the seasonal cycle of surface ozone is associated with wind patterns at 950 hPa, and the contribution of the photochemical effect is offset by the strong summer monsoon, which results in the maximum surface ozone concentration in post-monsoon September. The variations in the meteorological conditions at different levels and the influence of transport from SEA can account for the vertical distribution of ozone and CO. We conclude that the seasonal distribution of TCO results from the combined impact of meteorology and long-term transport.

Formaldehyde (HCHO) is one of the most abundant hydrocarbons in the atmosphere. Its absorption features in the 320–360 nm range allow its concentration in the atmosphere to be retrieved from space. There are two versions of HCHO datasets derived from the Ozone Monitoring Instrument (OMI)—one provided by the Royal Belgian Institute for Space Aeronomy (BIRA-IASB) and one provided by the National Aeronautics and Space Administration (NASA)—referred to as OMI-BIRA and OMI-NASA, respectively. We conducted daily comparisons of OMI-BIRA and multi-axis differential optical absorption spectrometry (MAX-DOAS), OMI-NASA and MAX-DOAS, and OMI-BIRA and OMI-NASA and monthly comparisons of OMI-BIRA and MAX-DOAS and OMI-NASA and MAX-DOAS. Daily comparisons showed a strong impact of effective cloud fraction (eCF), and correlations were better for eCF < 0.1 than for eCF < 0.3. By contrast, the monthly and multi-year monthly mean values yielded correlations of R² = 0.60 and R² = 0.95, respectively, for OMI-BIRA and MAX-DOAS, and R² = 0.45 and R² = 0.78 for OMI-NASA and MAX-DOAS, respectively. Therefore, use of the monthly mean HCHO datasets is strongly recommended. We conducted a sensitivity test for HCHO air mass factor (AMF) calculations with respect to the HCHO profile, the aerosol extinction coefficient (AEC), the HCHO profile–AEC combination, the aerosol optical depth (AOD), and the single scattering albedo (SSA) to explicitly account for the aerosol optical effects on the HCHO AMF. We found that the combination of AEC and HCHO profiles can account for 23–39% of the HCHO AMF variation. Furthermore, a high load of absorptive aerosols can exert a considerable effect (−53%) on the AMF. Finally, we used the HCHO monthly mean profiles from Goddard Earth Observing System coupled to Chemistry (GEOS-Chem), seasonal mean AECs from Cloud-Aerosol LIDAR with Orthogonal Polarization (CALIOP) and monthly climatologies of AOD and SSA from the OMAERUV (OMI level-2 near UV aerosol data product) dataset at Xianghe station to determine the aerosol correction. The results reveal that aerosols can account for +6.37% to +20.7% of the HCHO monthly change. However, the changes are greatest in winter and are weaker in summer and autumn, indicating that the aerosol correction is more applicable under high-AAOD conditions and that there may be other reasons for the significant underestimation between satellite and MAX-DOAS observations.