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.

The cloud condensation nuclei (CCN) activity and aerosol chemical composition were concurrently measured via a scanning mobility CCN analyzer (SMCA) and an Aerodyne Time-of-Flight Aerosol Chemical Speciation Monitor (ACSM), respectively, during wintertime 2022 in Beijing, China. During the observation period, the mean CCN number concentrations ranged from 1345 ± 1270 cm⁻³ at SS = 0.1% to 3267 ± 2325 cm⁻³ at SS = 0.3%. The mean critical activation diameters (D₅₀) at SS = 0.1%, 0.2%, and 0.3% were 172 ± 13 nm, 102 ± 8 nm, and 84 ± 7 nm, corresponding to the average hygroscopicity parameters (κ_CCN) of 0.34, 0.33, and 0.26, respectively. The diurnal variations in D₅₀ suggested that the local primary emissions significantly enhanced D₅₀ at SS = 0.2% and 0.3%, but had less influence on D₅₀ at SS = 0.1% due to the limited size (<150 nm) of particles emitted from primary sources. As PM_2.5 concentration increases, the dominant driver of CCN activity transitions from sulfate to nitrate. At a specific SS, D₅₀ decreased with increases in the degree of internal mixing, implying that the elevated internal mixing degree during atmospheric aging was beneficial to CCN activation. In this study, the commonly used f44 (or O:C) was weakly correlated with κ_org and failed to describe the variations in κ_org. Instead, the variations in κ_org can be well parameterized with the Org/BC ratio. The correlation between κ derived from bulk chemical compositions and CCN measurements was substantially improved when this κ_org scheme was adopted, emphasizing the importance of considering κ_org variations on deriving κ_chem from aerosol chemical composition.

Geostationary satellites observe the earth surface and atmosphere with a short repeat time, thus, providing aerosol parameters with high temporal resolution, which contributes to the air quality monitoring. Due to the limited information content in satellite data, and the coupling between the signals received from the surface and the atmosphere, the accurate retrieval of multiple aerosol parameters over land is difficult. With the strategy of taking full advantage of satellite measurement information, here we propose a neural network AEROsol retrieval framework for geostationary satellite (NNAeroG), which can potentially be applied to different instruments to obtain various aerosol parameters. NNAeroG was applied to the Advanced Himawari Imager on Himawari-8 and the results were evaluated versus independent ground-based sun photometer reference data. The aerosol optical depth, Ångström exponent and fine mode fraction produced by the NNAeroG method are significantly better than the official JAXA aerosol products. With spectral bands selection, the use of thermal infrared bands is meaningful for aerosol retrieval.

Aerosols can affect vertical thermal structure during heavily polluted episodes (HPEs). Here, we selected four typical HPEs in 2018, which were further subdivided into dust and haze events. The vertical distribution of aerosols extinction coefficient (EC) and variations in columnar optical properties were investigated based on sun-photometer and Lidar observation at an urban site in Beijing. The vertical characteristics in shortwave radiative heating rate (HR) of aerosols were studied using NASA/Goddard radiative transfer model along with observational data. In the haze episode, EC layer is less than 1.5 km and shows strong scattering, with single-scattering albedo (SSA_440nm) of ~0.97. The heating effects are observed at the middle and upper atmosphere, and slight heating effects are found at the lower layer. The mean HR within 1.5 km can be up to 16.3 K day⁻¹ with EC of 1.27 km⁻¹, whereas the HR within 0.5 km is only 1.3 K day⁻¹. In the dust episode, dust aerosols present the absorption with SSA_440nm of ~0.88, which would heat the lower atmosphere to promote vertical turbulence, and the height of EC layer can be up to 2.0–3.5 km. In addition, the strong heating effects of dust layer produced cooling effects near the surface. Therefore, the accurate measurement of aerosols optical properties in HPEs is of great significance for modeling aerosols direct radiative effects.

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.