The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is widely used as an advanced model dataset for the understanding of global climate change. However, independent validation and comparison of MERRA-2 are both insufficient and always desired. Therefore, in this study, the quantitative evaluation of MERRA-2 aerosol products was conducted over China for Aerosol Optical Depth (AOD), Angstrom exponent (AE), absorbing AOD (AAOD) and chemical components (black carbon (BC) and dust (DU)) using Sun sky radiometer Observation NETwork (SONET) ground-based measurements and POLDER-3/PARASOL satellite products generated by the GRASP algorithm. The available MERRA-2 monthly dataset and PARASOL/GRASP monthly and seasonal products were intercompared over China. MERRA-2 AOD (550 nm) show general good agreement with SONET and PARASOL/GRASP. For example, the correlation coefficients are usually 0.6–0.85 with SONET and 0.75–0.85 with PARASOL/GRASP, the bias is usually −0.293 to +0.008 with SONET. For AE and AAOD, the agreement is still reasonable. MERRA-2 is found to overestimate fine mode AE and to display a general underestimation of aerosol absorption over China. In addition, MERRA-2 BC and DU mass concentrations show spatial and quantitative consistency with PARASOL/GRASP components climatological products. The relatively high columnar BC mass concentration is observed around 1.5–2 mg/m³ over the East China industrial region and high DU mass concentration is around 150 mg/m³ near Taklimakan desert. MERRA-2 shows slightly higher BC and lower DU concentration than PARASOL/GRASP over East China. The evaluations with in situ BC measurements near surface verify the overestimation (MAE = +0.44 µg/m²) of MERRA-2 and underestimation (MAE = −0.38 µg/m²) of PARASOL/GRASP. The analysis demonstrates multi-source datasets, such as ground-based, space-borne remote sensing, in situ measurements, model simulation as well as reanalysis data, complement each other and can be used to refine aerosol characterization.

Ten fundamental aerosol models in China are derived from a cluster study based on the ground‐based remote sensing measurements of Sun‐sky radiometer Observation NETwork. The aerosol size distribution decomposition techniques are employed to yield individual fine and coarse mode size distribution functions with independent refractive indices. The total 10,773 records containing 18 kinds of aerosol microphysical parameters are used to yield 10 typical clusters with the verification of clustering robustness. Ten clusters suggest five typical fine particle aerosol models including urban polluted, secondary polluted, combined polluted, polluted fly ash, and continental background, as well as five coarse models including summer fly ash, winter fly ash, primary dust, transported dust, and background dust over China region. The representativeness and coappearance analyses again reveal five dominative aerosol patterns on the base of fundamental models. These models can be used in the chemical model simulation, satellite remote sensing, climate, and environment analyses.

The 3 km Dark Target (DT) aerosol optical depth (AOD) products, 10 km DT and Deep Blue (DB) AOD products from the Collection 6 (C6) product data of Moderate Resolution Imaging Spectroradiometer (MODIS) are compared with Sun-sky Radiometer Network (SONET) measurements at Song Mountain in central China, where ground-based remote sensing measurements of aerosol properties are still very limited. The seasonal variations of AODs are significant in the Song Mountain region, with higher AODs in spring and summer and lower AODs in autumn and winter. Annual mean AODs (0.55 µm) vary in the range of 0.5–0.7, which indicates particle matter (PM) pollutions in this mountain region. Validation against one-year ground-based measurements shows that AOD retrievals from the MODIS onboard Aqua satellite are better than those from the Terra satellite in Song Mountain. The 3 km and 10 km AODs from DT algorithms are comparable over this region, while the AOD accuracy of DB algorithm is relatively lower. However, the spatial coverage of DB products is higher than that of 10 km DT products. Moreover, the optical and microphysical characteristics of aerosols at Song Mountain are analyzed on the basis of SONET observations. It suggests that coarse-mode aerosol particles dominate in spring, and fine-mode particles dominate in summer. The aerosol property models are also established and compared to aerosol types used by MODIS algorithm.

Knowledge of the composition of atmospheric aerosols is important for reducing uncertainty in climate assessment. In this study, an improved algorithm is developed for the retrieval of atmospheric columnar aerosol components from optical remote sensing data. This is achieved by using the complex refractive index (CRI) of a multicomponent liquid system in the forward model and minimizing the differences with the observations. The aerosol components in this algorithm comprise five species, combining eight subcomponents including black carbon (BC), water-soluble organic matter (WSOM) and water-insoluble organic matter (WIOM), ammonium nitrate (AN), sodium chloride (SC), dust-like content (DU), and aerosol water content in the fine and coarse modes (AW_f and AW_c). The calculation of the CRI in the multicomponent liquid system allows for the separation of the water-soluble components (AN, WSOM and AW_f) in the fine mode and SC and AW_c in the coarse mode. The uncertainty in the retrieval results is analyzed based on the simulation of typical models, showing that the complex refractive index obtained from instantaneous optical–physical inversion compares well with that obtained from chemical estimation. The algorithm was used to retrieve the columnar aerosol components over China using the ground-based remote sensing measurements from the Sun–sky radiometer Observation NETwork (SONET) in the period from 2010 to 2016. The results were used to analyze the regional distribution and interannual variation. The analysis shows that the atmospheric columnar DU component is dominant in the northern region of China, whereas the AW is higher in the southern coastal region. The SC component retrieved over the desert in northwest China originates from a paleomarine source. The AN significantly decreased from 2011 to 2016, by 21.9 mg m⁻², which is inseparable from China's environmental control policies.

The strong economic growth in China in recent decades, together with meteorological factors, has resulted in serious air pollution problems, in particular over large industrialized areas with high population density. To reduce the concentrations of pollutants, air pollution control policies have been successfully implemented, resulting in the gradual decrease of air pollution in China during the last decade, as evidenced from both satellite and ground-based measurements. The aims of the Dragon 4 project “Air quality over China” were the determination of trends in the concentrations of aerosols and trace gases, quantification of emissions using a top-down approach and gain a better understanding of the sources, transport and underlying processes contributing to air pollution. This was achieved through (a) satellite observations of trace gases and aerosols to study the temporal and spatial variability of air pollutants; (b) derivation of trace gas emissions from satellite observations to study sources of air pollution and improve air quality modeling; and (c) study effects of haze on air quality. In these studies, the satellite observations are complemented with ground-based observations and modeling.