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.

AIUS (Atmospheric Infrared Ultraspectral Sounder) is an infrared occultation spectrometer onboard the Chinese GaoFen-5 satellite, which covers a spectral range of 2.4–13.3 μm (750–4100 cm⁻¹) with a spectral resolution of about 0.02 cm⁻¹. AIUS was designed to measure and to study the chemical processes of ozone (O₃) and other trace gases in the upper troposphere and stratosphere over the Antarctic. In this study, the AIUS retrieval methodology is described. A comparison between AIUS measurements and simulated spectra illustrates that AIUS measurements agree well with the simulated spectra. To first evaluate the reliability of the AIUS retrieval algorithm, three retrieval O₃ experiments were performed based on ACE-FTS (Atmospheric Chemistry Experiment—Fourier transform spectrometer) observed spectra. A comparison with the ACE-FTS official products shows that the relative difference of these three retrieval experiments was mostly within 10% between 20 and 70 km. These retrieval experiments demonstrate that the retrieval algorithm described in this study provided reliable results and reliably. Furthermore, O₃, H₂O, and HCl profiles were retrieved from 24 orbits of AIUS measurements and compared with the official Aura /MLS (Microwave Limb Sounder) level-2 v4.2 profiles. The relative difference was mostly within 10% (about 0.02–0.4 ppm) between 18 and 58 km for the O₃ retrieval, within 10% (0–0.5 ppm) between 15 and 80 km for the H₂O retrieval, and within 10% (about 0.1 ppb) between 30 and 60 km for the HCl retrieval. A good agreement in the retrieved trace gas profiles was reached between AIUS and MLS.

Atmospheric profiles are important input parameters for atmospheric radiative transfer models and atmospheric parameter inversions. The construction of regionally representative reference atmospheric profiles can provide basic data for global atmospheric and environmental research. Most reference atmospheric profile databases commonly used lag behind in updating frequency. These databases usually have limited spatial and temporal resolution and differ greatly from the real atmospheric state. To present the real atmospheric state, this article constructs the Global Reference Atmospheric Profile Database (GRAP) based on ACE-FTS satellite products of 2021 and 2022, AIRS satellite products and ERA5 reanalysis data of 2022 u6sing a random forest regression model and a hierarchical mean algorithm. The radiance spectrum of FY-3E HIRAS-II using different profile databases was simulated and compared with the measured spectrum. The results show that GRAP spectral simulations fit better with the measured HIRAS-II spectrum. Comparing the CO₂, CH₄, O₃ and N₂O profiles of GRAP, AFGL, MIPAS, RTTOV and NDACC ground station profiles in equatorial, mid-latitude summer and polar winter, the results show that GRAP has high spatial and temporal resolution and better fits the current real atmospheric state. Comparing the temperature profiles of eight regions in China, the results illustrate that GRAP is a better representation of the state of the atmosphere in the Chinese region. GRAP can provide fundamental atmospheric data for radiative transfer studies and atmospheric parameter inversions.

The Atmospheric Infrared Ultraspectral Sounder (AIUS), the first high-resolution (0.02 cm⁻¹) solar occultation sounder, aboard GF5, was launched in May 2018 from China. However, relevant studies about vertical profiles of atmospheric constituents based on its operational data were not conducted until half a year later. Due to an urgent need for Hin-orbit tests, the real spectra (called reference spectra hereafter) were substituted with simulated spectra calculated from the reference forward model (RFM) plus different random noises at different altitudes. In the generation process of the reference spectra for N₂O, NO₂, and HF species, ACE-FTS (Atmospheric Chemistry Experiment–Fourier Transform Spectrometer instrument on the SCISAT satellite) level 2 products replace corresponding profiles included in the atmospheric background profiles. The optimal estimation method is employed to extract N₂O, NO₂, and HF profiles in this study. Comparing the retrieved results with ACE-FTS level 2 products, the relative deviations for these three species are calculated. For N₂O, the average relative deviation is less than 6% at altitudes below 25 km, while larger deviations are observed in the range of 25–45 km, with the maximum being at ~25%. Additionally, the difference for NO₂ is less than 5% in the 20–45 km range, with a larger discrepancy found below 20 km and above 45 km; the maximum deviation reaches ±40%. For HF, the relative deviation is less than 6% for all tangent heights, implying satisfactory retrieval. The vertical resolution, averaging kernel, and number of degrees of freedom are used to assess the retrieval algorithm, which indicate that the retrieved information content is much more attributable to the reference spectra contribution than to the a priori profile. Finally, a large number of retrieval tests are performed for N₂O, NO₂, and HF in selected areas covering the Arctic region, northern middle latitude, tropics, southern middle latitude, and Antarctic region, and reliable results are obtained. Thus, to a great extent, the algorithm adopted in the AIUS system can process retrievals reliably and precisely.

Atmospheric Infrared Ultraspectral Sounder (AIUS) aboard the Chinese GaoFen-5 satellite was launched on 9 May 2018. It is the first hyperspectral occultation spectrometer in China. The spectral quality assessment of AIUS measurements at the full and representative spectral bands was presented by comparing the transmittance spectra of measurements with that of simulations. AIUS measurements agree well with simulations. Statistics show that more than 73% of the transmittance differences are within ±0.05 and more than 91% of the transmittance differences are within ±0.1. The spectral windows for O${}_3$, H${}_2$O, temperature, CO, CH${}_4$, and HCl were also analyzed. The comparison experiments indicate that AIUS data can provide reliable data for O${}_3$, H${}_2$O, temperature, CO, CH${}_4$, and HCl detection and dynamic monitoring. The H${}_2$O profiles were then retrieved from AIUS measurements, and the precision, resolution, and accuracy of the H${}_2$O profiles are discussed. The estimated precision is less than 1.3 ppmv (21%) below 57 km and about 0.9–2.4 ppmv (20–31%) at 60–90 km. The vertical resolution of H${}_2$O profiles is better than 5 km below 32 km and about 5–8 km at 35–85 km. Comparisons with MLS Level 2 products indicate that the mean H${}_2$O profiles of AIUS have a good agreement with those of MLS. The relative differences are mostly within ±10% at 16–75 km and about 10–15% at 16–20 km in 60${}^{\circ }$–80${}^{\circ }$ S. For 60${}^{\circ }$–65 ${}^{\circ }$ S in December, the relative differences are within ±5% between 22 km and 80 km. The H${}_2$O profiles retrieved from AIUS measurements are credible for scientific research.

Accurately assessing the impact of anthropogenic carbon dioxide (CO₂) emissions on CO₂ concentrations is essential for understanding regional climate change, particularly in high-emission countries like China. This study employed the GEOS-Chem chemical transport model to simulate and compare the spatiotemporal distributions of XCO₂ of three anthropogenic CO₂ emission inventories in mainland China for the 2018–2020 period and analyzed the effects of emission variations on atmospheric CO₂ concentrations. In eastern China, particularly in the Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) regions, column-averaged dry air mole fractions of CO₂ (XCO₂) can exceed 420 ppm during peak periods, with emissions from these areas contributing significantly to the national total. The simulation results were validated by comparing them with OCO-2 satellite observations and ground-based monitoring data, showing that more than 70% of the monitoring stations exhibited a correlation coefficient greater than 0.7 between simulated and observed data. The average bias relative to satellite observations was less than 1 ppm, with the Emissions Database for Global Atmospheric Research (EDGAR) showing the highest degree of agreement with both satellite and ground-based observations. During the study period, anthropogenic CO₂ emissions resulted in an increase in XCO₂ exceeding 10 ppm, particularly in the North China Plain and the YRD. In scenarios where emissions from either the BTH or YRD regions were reduced by 50%, a corresponding decrease of 1 ppm in XCO₂ was observed in the study area and its surrounding regions. These findings underscore the critical role of emission control policies in mitigating the rise in atmospheric CO₂ concentrations in densely populated and industrialized areas. This research elucidates the impacts of variations in anthropogenic emissions on the spatiotemporal distribution of atmospheric CO₂ and emphasizes the need for improved accuracy of CO₂ emission inventories.