The aerosol optical property products of Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis dataset have been extensively investigated on a global or regional scale. However, the understanding of MERRA-2 aerosol component products on an extensive temporal and spatial scale is inadequate. Recently, the aerosol component products have been derived from the observations of Polarization and Directionality of the Earth’s Reflectances/Polarization and Anisotropy of Reflectance for Atmospheric Science coupled with observations from a Lidar (POLDER/PARASOL). This study presents a quantitative evaluation of the MERRA-2 reanalysis dust and black carbon (BC) column concentration using independent satellite-based aerosol component concentration retrievals. Both GRASP/Component and MERRA-2 reanalysis products can capture well the temporal variation in dust column concentration over the dust emission resource and downwind dust-dominated regions with the correlation coefficient (R) varying from 0.80 to 0.98. MERRA-2 reanalysis dust products present higher column concentration than GRASP/Component dust retrievals with relative differences of about 20~70%, except in the Taklamakan Desert and Bay of Bengal, where the relative differences can be negative. The differences in dust column concentration over the African dust regions are larger than that over the Asian dust regions. Similar temporal variations in BC column concentration are characterized by both GRASP/Component BC retrievals and MERRA-2 BC products with R of about 0.70~0.90, except in the North China Plain region. We should pay more caution with the regional applicability of MERRA-2 component products when large differences and high correlation coefficients are obtained simultaneously. The results are favorable for identifying the behavior of MERRA-2 reanalysis component estimation in a new view and demonstrate a practical application of the satellite-based component retrievals, which could make more contributions to the improvement of model estimation in the near future.

With the rapid development of economy and urbanization acceleration, ozone (O₃) pollution has become the main factor of urban air pollution in China after particulate matter. In this study, 90th percentile of maximum daily average (MDA) 8 h O₃ (O₃-8h-90per) and PM_2.5 data from the Tracking Air Pollution in China (TAP) dataset were used to determine the mean annual, seasonal, monthly, and interannual distribution of O₃-8h-90per and PM_2.5 concentrations in Northeast China (NEC). The O₃-8h-90per concentration was highest in Liaoning (>100 μg/m³), whereas the highest PM_2.5 concentration was observed mainly in urban areas of central Liaoning and the Harbin–Changchun urban agglomeration (approximately 60 μg/m³). The O₃-8h-90per concentrations were highest in spring and summer due to more intense solar radiation. On the contrary, the PM_2.5 concentration increased considerably in winter influenced by anthropogenic activities. In May and June, the highest monthly mean O₃-8h-90per concentrations were observed in central and western Liaoning, about 170–180 μg/m³, while the PM_2.5 concentrations were the highest in January, February, and December, approximately 100 μg/m³. The annual mean O₃-8h-90per concentration in NEC showed an increasing trend, while the PM_2.5 concentration exhibited an annual decline. By 2020, the annual mean O₃-8h-90per concentration in southern Liaoning had increased considerably, reaching 120–130 μg/m³. From the perspective of city levels, PM_2.5 and O₃-8h-90per also showed an opposite variation trend in the 35 cities of NEC. The reduced tropospheric NO₂ column is consistent with the decreasing trend of the interannual PM_2.5, while the increased surface temperature could be the main meteorological factor affecting the O₃-8h-90per concentration in NEC. The results of this study enable a comprehensive understanding of the regional and climatological O₃-8h-90per and PM_2.5 distribution at distinct spatial and temporal scales in NEC.

Understanding the seasonal nonlinear relationship between urban heat island (UHI) and multidimensional urban morphological patterns is crucial for regulating the urban thermal environment. To address this, this study quantified the contributions and sensitivities of urban morphology to land surface temperature (LST) variations and revealed their influencing pathways across four seasons in Beijing, using automated machine learning, SHapley Additive exPlanations interpretation, partial dependence analysis, and structural equation modeling. The results showed significant seasonal variations at the grid scale of 200 m. It was revealed that Normalized Difference Vegetation Index (NDVI) emerged as the most significant indicator affecting LST, followed by building height (BH) and building coverage ratio (BCR), while sky view factor and frontal area index had the least impact. BH was more influential than NDVI, affecting LST during winter. Additionally, sensitivity analysis revealed that impervious surface area, BCR, and mean building volume had positive relationships with LST. In contrast, NDVI and BH negatively affected LST with a noticeable cooling effect, particularly in summer. Furthermore, the total effects of all indicators on LST were negative, with the greatest in spring and the least in winter. Three-dimensional indicators generally exhibited more pronounced direct and total effects than two-dimensional indicators, except in winter. These findings can offer valuable insights for regulating seasonal surface UHI to maximize thermal environmental benefits.

Seasonal and diurnal characteristics of the vertical profiles of aerosol properties are essential for detecting the regional transport and the climatic radiative effects of aerosol particles. We have studied the seasonal and diurnal characteristics of the vertical distribution of aerosols in urban Beijing from 2017 to 2021 based on long-term Raman–Mie LiDAR observations. The influence of the vertical distribution of aerosols, the meteorological conditions within the boundary layer, the optical–radiometric properties of aerosols, and their interconnections, were investigated during a heavy haze pollution event in Beijing from 8 to 15 February 2020 using both meteorological and sun photometer data. The aerosol extinction coefficient was highest in summer (0.4 km⁻¹), followed by winter (0.35 km⁻¹), and roughly equal in spring and autumn (0.3 km⁻¹). The aerosol extinction coefficient showed clear daily variations and was different in different seasons as a result of the variation in the height of the boundary layer. During the haze pollution event, the particulate matter mainly consisted of scattered spherical fine particles and the accumulation time of pollutants measured via the AOD_440nm and PM_2.5 mass concentration was different as a result of the hygroscopic growth of the aerosol particles. This growth increased scattering and led to an increase in the aerosol optical depth. The vertical transport of particulate matter also contributed to the increase in the aerosol optical depth.

The characteristics of turbulence in the planetary boundary layer (PBL) and the aerosol optical and radiative properties during haze and haze–fog mixed episodes on 22–27 January 2021, in Shenyang, a provincial city in Northeast China, were analyzed using meteorological and aerosol observations. During the haze episode, the hourly mean PM_2.5 concentration reached a maximum of 337 µg m⁻³ and visibility decreased to 1.6 km. The PM_2.5 concentration decreased gradually during the haze–fog mixed episode as a result of the scavenging effects of fog, but visibility mostly remained below 1 km owing to high ambient relative humidity (>90%). During the haze–fog mixed episode, an increasing proportion of PM_2.5 led to a higher ratio of the backward to the total scattering coefficient. As fog occurred, downward shortwave radiation arriving at the surface was significantly reduced, and upward longwave radiation increased and almost equaled the downward longwave radiation, which can be used as a good indicator for distinguishing haze and fog. Mechanical turbulence was weak during both episodes, and latent heat flux varied within a wider range during the haze–fog mixed episode. The PBL dynamic structure affected the vertical distribution of aerosols/fog droplets. Aerosol-rich layers appeared at altitudes below 0.5 km and above 0.6 km during the haze episode. The elevated aerosol layer was related to the aerosol transport from upstream polluted areas caused by strong upper-level turbulence, and it began to mix vertically after sunrise because of convective turbulence. Aerosols and fog droplets were mostly trapped in a shallower PBL with a height of 0.2–0.4 km during the haze–fog mixed episode because of weaker turbulence.

An assessment and verification of the Langley calibration method of the Sun photometer at Mt Foyeding (MFYD) Observatory in Beijing was performed. We explored whether the Langley plot calibration is practicable for this mountainous site by analyzing the aerosol climatology and carrying out a case study. Then, the aerosol optical depth (AOD) results were verified under the reference of AERONET AOD. The results showed that satisfactory atmospheric conditions are present on winter mornings, characterized by a smaller average AOD (~0.09–0.14) and a lower range ratio (~36.97–63.38%) than in the afternoons and over a whole day. The six days selected as the case study all showed stable atmospheric conditions characterized by daily average triplets of <2% for all wavelengths. The residual sum of squares for $V_{0\lambda }$ at all wavelengths was <0.0002 and the residual standard deviation was 0.998) and residual standard deviation values ranging from ~0.006 to 0.011 were observed, with the relative mean bias varying from 0.999 to 1.066. The mean biases were concentrated within ±0.02 for the ultraviolet bands and within ±0.01 for the other bands; therefore, the results of this preliminary assessment and verification indicated that the Langley plots method is suitable for photometer calibration at the MFYD Observatory.