Air pollutant transport plays an important role in local air quality, but field observations of transport fluxes, especially their vertical distributions, are very limited. We characterized the vertical structures of transport fluxes in central Luoyang, Fen-Wei Plain, China, in winter based on observations of vertical air pollutant and wind profiles using multi-axis differential optical absorption spectroscopy (MAX-DOAS) and Doppler wind lidar, respectively. The northwest and the northeast are the two privileged wind directions. The wind direction and total transport scenarios were dominantly the northwest during clear days, turning to the northeast during the polluted days. Increased transport flux intensities of aerosol were found at altitudes below 400 m on heavily polluted days from the northeast to the southwest over the city. Considering pollution dependence on wind directions and speeds, surface-dominated northeast transport may contribute to local haze events. Northwest winds transporting clean air masses were dominant during clean periods and flux profiles characterized by high altitudes between 200 and 600 m in Luoyang. During the COVID-19 lockdown period in late January and February, clear reductions in transport flux were found for NO₂ from the northeast and for HCHO from the northwest, while the corresponding main transport altitude remained unchanged. Our findings provide better understandings of regional transport characteristics, especially at different altitudes.

In this paper, we present the Hefei EMI Cloud Retrieval Algorithm (HECORA), which uses information from the O₂-O₂ absorption band around 477 nm to retrieve effective cloud fraction and effective cloud pressure from satellite observations. The retrieved cloud information intends to improve the atmospheric trace gas products based on the Environment Monitoring Instrument (EMI) spectrometer. The HECORA method builds on OMCLDO2 and presents some evolutions. The Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model has been used to produce the Top of the Atmosphere (TOA) reflectance Look-up Tables (LUT) as a function of the cloud fraction and cloud pressure. Applying the Differential Optical Absorption Spectroscopy (DOAS) technique to the synthetic reflectance LUT, the reflectance spectra can be associated with O₂-O₂ geometrical vertical column densities (VCD_geo) and continuum reflectance. This is the core of the retrieval method, since there is a one-to-one relationship between O₂-O₂ VCD_geo and continuum reflectance, on the one hand, and effective cloud fraction and effective cloud pressure, on the other hand, for a given illumination and observing geometry and given surface height and surface albedo. We first used the VLIDORT synthetic spectra to verify the HECORA algorithm and obtained good results in both the Lambertian cloud model and the scattering cloud model. Secondly, HECORA is applied to OMI and TROPOMI and compared with OMCLDO2, FRESCO+, and OCRA/ROCINN cloud products. Later, the cloud pressure results from TROPOMI observations obtained using HECORA and FRESCO+ are compared with the CALIOP Cloud Layer product. HECORA is closer to the CALIOP results under low cloud conditions, while FRESCO+ is closer to high clouds due to the higher sensitivity of the O₂ A-band to cloud vertical information. Finally, HECORA is applied to the TROPOMI NO₂ retrieval. Validation of the tropospheric NO₂ VCD with ground-based MAX-DOAS measurements shows that choosing HECORA cloud products to correct for photon path variations on the TROPOMI tropospheric NO₂ VCD retrievals has better performance than using FRESCO+ under low cloud conditions. In conclusion, this paper shows that the HECORA cloud products are in good agreement with the well-established cloud products and that they are suitable for correcting the effect of cloud in trace gas retrievals. Therefore, HECORA has the potential to be applied to EMI.

Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO₂ concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO₂ by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO₂ concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO₂ vertical profiles. For instance, in Beijing, MAX-DOAS NO₂ showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO₂ can largely explain the differences between satellite and in situ NO₂ variations. In the post-epidemic era of 2021, satellite NO₂ TVCD and in situ NO₂ concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO₂ pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production.