Developing a big data analytics framework for generating the Long-term Gap-free High-resolution Air Pollutant concentration dataset (abbreviated as LGHAP) is of great significance for environmental management and Earth system science analysis. By synergistically integrating multimodal aerosol data acquired from diverse sources via a tensor-flow-based data fusion method, a gap-free aerosol optical depth (AOD) dataset with a daily 1 km resolution covering the period of 2000–2020 in China was generated. Specifically, data gaps in daily AOD imageries from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra were reconstructed based on a set of AOD data tensors acquired from diverse satellites, numerical analysis, and in situ air quality measurements via integrative efforts of spatial pattern recognition for high-dimensional gridded image analysis and knowledge transfer in statistical data mining. To our knowledge, this is the first long-term gap-free high-resolution AOD dataset in China, from which spatially contiguous PM_2.5 and PM₁₀ concentrations were then estimated using an ensemble learning approach. Ground validation results indicate that the LGHAP AOD data are in good agreement with in situ AOD observations from the Aerosol Robotic Network (AERONET), with an R of 0.91 and RMSE equaling 0.21. Meanwhile, PM_2.5 and PM₁₀ estimations also agreed well with ground measurements, with R values of 0.95 and 0.94 and RMSEs of 12.03 and 19.56 µg m⁻³, respectively. The LGHAP provides a suite of long-term gap-free gridded maps with a high resolution to better examine aerosol changes in China over the past 2 decades, from which three major variation periods of haze pollution in China were revealed. Additionally, the proportion of the population exposed to unhealthy PM_2.5 increased from 50.60 % in 2000 to 63.81 % in 2014 across China, which was then reduced drastically to 34.03 % in 2020. Overall, the generated LGHAP dataset has great potential to trigger multidisciplinary applications in Earth observations, climate change, public health, ecosystem assessment, and environmental management. The daily resolution AOD, PM_2.5, and PM₁₀ datasets are publicly available at https://doi.org/10.5281/zenodo.5652257 (Bai et al., 2021a), https://doi.org/10.5281/zenodo.5652265 (Bai et al., 2021b), and https://doi.org/10.5281/zenodo.5652263 (Bai et al., 2021c), respectively. Monthly and annual datasets can be acquired from https://doi.org/10.5281/zenodo.5655797 (Bai et al., 2021d) and https://doi.org/10.5281/zenodo.5655807 (Bai et al., 2021e), respectively. Python, MATLAB, R, and IDL codes are also provided to help users read and visualize these data.

With the increase in economic development over the past thirty years, many large cities in eastern and southwestern China are experiencing increased haze events and atmospheric pollution, causing significant impacts on the regional environment and even climate. However, knowledge on the aerosol physical and chemical properties in heavy haze conditions is still insufficient. In this study, two winter heavy haze events in Beijing that occurred in 2011 and 2012 were selected and investigated by using the ground-based remote sensing measurements. We used a CIMEL CE318 sun–sky radiometer to retrieve haze aerosol optical, physical and chemical properties, including aerosol optical depth (AOD), size distribution, complex refractive indices and aerosol fractions identified as black carbon (BC), brown carbon (BrC), mineral dust (DU), ammonium sulfate-like (AS) components and aerosol water content (AW). The retrieval results from a total of five haze days showed that the aerosol loading and properties during the two winter haze events were comparable. Therefore, average heavy haze property parameters were drawn to present a research case for future studies. The average AOD is about 3.0 at 440 nm, and the Ångström exponent is 1.3 from 440 to 870 nm. The fine-mode AOD is 2.8 corresponding to a fine-mode fraction of 0.93. The coarse particles occupied a considerable volume fraction of the bimodal size distribution in winter haze events, with the mean particle radius of 0.21 and 2.9 μm for the fine and coarse modes respectively. The real part of the refractive indices exhibited a relatively flat spectral behavior with an average value of 1.48 from 440 to 1020 nm. The imaginary part showed spectral variation, with the value at 440 nm (about 0.013) higher than the other three wavelengths (about 0.008 at 675 nm). The aerosol composition retrieval results showed that volume fractions of BC, BrC, DU, AS and AW are 1, 2, 49, 15 and 33%, respectively, on average for the investigated haze events. The preliminary uncertainty estimation and comparison of these remote sensing results with in situ BC and PM_2.5 measurements are also presented in the paper.

Black carbon (BC), brown carbon (BrC), and mineral dust (DU) are three major light absorbing aerosols, playing important roles in climate change. Better knowledge of their concentrations is necessary for more accurate estimates of their radiative forcing effects of climate. We present a method to retrieve columnar contents of BC, BrC, and DU simultaneously from spectral refractive indices and spectral single scattering albedo obtained from the sun‐sky radiometer measurements. Then, this method is applied to investigate the columnar volume fractions and mass concentrations of BC, BrC, and DU in Beijing, China, based on measurements obtained from 2009 to 2010. Results show that among the three absorbing aerosols, DU dominates the largest volume fraction in the total aerosol volume (20–45%), followed by BrC (5–25%), and BC (< 5%). The retrieved monthly mean content of each absorbing component exhibits clear seasonal variation. BrC dominates in late fall and winter (40–92.5 mg/m²), whereas is extremely low in summer (< 10 mg/m²). DU dominates in spring, ranging from 270 to 405 mg/m² (with volume fraction >30%), while during June–September, the DU fraction is generally lower than 30%. BC is characterized by low levels throughout the year. The monthly mean BC columnar mass concentration ([BC]) ranges from 2.7 to 7.3 mg/m² with winter slightly higher than other seasons. As a preliminary validation, we compare our retrieved [BC] with in situ measurements. Similar day‐to‐day variation trends and good correlations are found between the retrieved [BC] and in situ measurements.

The Taklamakan desert is an important dust source for the global atmospheric dust budget and a cause of the dust weather in East Asia. The characterization of Taklamakan dust in the source region is still very limited. To fill this gap, the DAO (dust aerosol observation) was conducted in April 2019 in Kashi, China. The Kashi site is about 150 km from the western rim of the Taklamakan desert and is strongly impacted by desert dust aerosols, especially in spring time, i.e., April and May. According to sun–sky photometer measurements, the aerosol optical depth (at 500 nm) varied in the range of 0.07–4.70, and the Ångström exponent (between 440 and 870 nm) in the range of 0.0–0.8 in April 2019. In this study, we provide the first profiling of the $\mathrm{2}\mathit{\alpha }+\mathrm{3}\mathit{\beta }+\mathrm{3}\mathit{\delta }$ parameters of Taklamakan dust based on a multiwavelength Mie–Raman polarization lidar. For Taklamakan dust, the Ångström exponent related to the extinction coefficient (EAE, between 355 and 532 nm) is about 0.01 ± 0.30, and the lidar ratio is found to be 45 ± 7 sr (51 ± 8–56 ± 8 sr) at 532 (355) nm. The particle linear depolarization ratios (PLDRs) are about 0.28–0.32 ± 0.07 at 355 nm, 0.36 ± 0.05 at 532 nm and 0.31 ± 0.05 at 1064 nm. Both lidar ratios and depolarization ratios are higher than the typical values of Central Asian dust in the literature. The difference is probably linked to the fact that observations in the DAO campaign were collected close to the dust source; therefore, there is a large fraction of coarse-mode and giant particles (radius >20 µm) in the Taklamakan dust. Apart from dust, fine particles coming from local anthropogenic emissions and long-range transported aerosols are also non-negligible aerosol components. The signatures of pollution emerge when dust concentration decreases. The polluted dust (defined by PLDR₅₃₂≤0.30 and EAE${}_{\mathrm{355}-\mathrm{532}}\ge \mathrm{0.20}$ ) is featured with reduced PLDRs and enhanced EAE_355−532 compared to Taklamakan dust. The mean PLDRs of polluted dust generally distributed in the range of 0.20–0.30. Due to the complexity of the nature of the involved pollutants and their mixing state with dust, the lidar ratios exhibit larger variabilities compared to those of dust. The study provides the first reference of novel characteristics of Taklamakan dust measured by Mie–Raman polarization lidar. The data could contribute to complementing the dust model and improving the accuracy of climate modeling.

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.