34 citations as recorded by crossref.

1. Vertical distribution of type-discriminated aerosol concentration from a three-wavelength backscatter spaceborne lidar F. Qayyum et al. https://doi.org/10.1016/j.rse.2026.115399
2. Changes in aerosol loading before, during and after the COVID-19 pandemic outbreak in China: Effects of anthropogenic and natural aerosol Y. Liang et al. https://doi.org/10.1016/j.scitotenv.2022.159435
3. Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the “Air Pollution Complex” T. Zhu et al. https://doi.org/10.1007/s00376-023-2379-0
4. Light-absorbing black carbon and brown carbon components of smoke aerosol from DSCOVR EPIC measurements over North America and central Africa M. Choi et al. https://doi.org/10.5194/acp-24-10543-2024
5. An Improved Aerosol Retrieval Algorithm for FY-4A/AGRI Data Based on the GRASP Framework H. Wang et al. https://doi.org/10.1109/TGRS.2025.3546614
6. FY-4A/AGRI Aerosol Optical Depth Retrieval Capability Test and Validation Based on NNAeroG H. Ding et al. https://doi.org/10.3390/rs14215591
7. Influence of aerosol properties and surface albedo on radiative forcing efficiency of key aerosol types using global AERONET data A. Chen et al. https://doi.org/10.1016/j.atmosres.2022.106519
8. An AERONET-based methodology to retrieve black carbon light absorption and comparison with MERRA-2 data N. Dehkhoda et al. https://doi.org/10.1016/j.apr.2023.101994
9. Climatology of Dust Aerosols over the Jianghan Plain Revealed with Space-Borne Instruments and MERRA-2 Reanalysis Data during 2006–2021 C. Liu et al. https://doi.org/10.3390/rs14174414
10. Features and sources of aerosol properties over the western Pacific Ocean based on shipborne measurements W. Wang et al. https://doi.org/10.1007/s00703-023-00960-7
11. Assessing and improving MERRA-2 black carbon column concentration over china using multi-source data and machine learning Q. Zhang et al. https://doi.org/10.1016/j.atmosres.2025.108652
12. Satellite remote sensing of aerosol single scattering albedo: Instruments, algorithms, and challenges Y. Dong et al. https://doi.org/10.1016/j.jqsrt.2025.109802
13. Global radiative forcing assessment of brown carbon versus black carbon: Source-specific constraints from compiled observations S. Liu et al. https://doi.org/10.1016/j.atmosenv.2026.122010
14. Columnar optical-radiative properties and components of aerosols in the Arctic summer from long-term AERONET measurements Y. Liang et al. https://doi.org/10.1016/j.scitotenv.2023.169052
15. Letter to the Editor regarding Chappell et al., 2023, “Satellites reveal Earth's seasonally shifting dust emission sources” N. Mahowald et al. https://doi.org/10.1016/j.scitotenv.2024.174792
16. Climatology and variability of smoke aerosols from MAIAC EPIC observations over North America (2016–2024) M. Choi et al. https://doi.org/10.3389/frsen.2025.1654779
17. Modeling atmospheric brown carbon in the GISS ModelE Earth system model M. DeLessio et al. https://doi.org/10.5194/acp-24-6275-2024
18. Long-term retrieval and analysis of aerosol components and optical properties in Tianjin, China: Insights from GRASP/component approach and sun-photometer observations (2014–2024) X. Zhang et al. https://doi.org/10.1016/j.atmosres.2025.108695
19. A global black carbon dataset of column concentration and microphysical information derived from MISR multi-band observations and Mie scattering simulations Z. Liu et al. https://doi.org/10.5194/essd-18-507-2026
20. Relative contributions of component-segregated aerosols to trends in aerosol optical depth over land (2007–2019): Insights from CAMS aerosol reanalysis H. Zhao et al. https://doi.org/10.1016/j.atmosenv.2024.120676
21. MAIAC-based climatology of atmospheric iron-oxide dust species from DSCOVR EPIC observations S. Go et al. https://doi.org/10.3389/frsen.2025.1676851
22. Optimized retrievals of aerosol optical properties from directional polarimetric camera using optimal linear mixture of basis aerosol models supported by the non-negative matrix factorization S. Jin et al. https://doi.org/10.1016/j.rse.2026.115504
23. A robust and flexible satellite aerosol retrieval algorithm for multi-angle polarimetric measurements with physics-informed deep learning method M. Tao et al. https://doi.org/10.1016/j.rse.2023.113763
24. Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols O. Hasekamp et al. https://doi.org/10.5194/amt-17-1497-2024
25. Monitoring of aerosol optical-microphysical properties from DPC/GF-5(02): A case study of dust event in north China plain Y. Cao et al. https://doi.org/10.1016/j.atmosenv.2025.121193
26. Preliminary Assessment and Verification of the Langley Plots Calibration of the Sun Photometer at Mt Foyeding Observatory, Beijing Y. Zheng et al. https://doi.org/10.3390/rs14174321
27. Light-absorbing properties of polar- and non-polar brown carbon fractions of aerosols in Delhi A. Alang et al. https://doi.org/10.1016/j.atmosres.2023.107073
28. Aerosol optical and radiative properties and their environmental effects in China: A review H. Che et al. https://doi.org/10.1016/j.earscirev.2023.104634
29. Climatology and interannual variability of type-dependent aerosol optical depth and vertical distribution over southwest China and northern India from multiple satellite and aerosol reanalysis datasets H. Cai et al. https://doi.org/10.1016/j.atmosenv.2022.119528
30. Incorporated constraints on mineral abundances and complex refractive indices for mineral dust components simulation L. Li et al. https://doi.org/10.1080/15481603.2025.2596962
31. Comparative impact of surface reflection models on aerosol component retrieval S. Liu et al. https://doi.org/10.1016/j.atmosres.2025.108507
32. Long-term characteristics of dust aerosols over central China from 2010 to 2020 observed with polarization lidar D. Jing et al. https://doi.org/10.1016/j.atmosres.2023.107129
33. Technical note: Reconstructing missing surface aerosol elemental carbon data in long-term series with ensemble learning Q. Meng et al. https://doi.org/10.5194/acp-25-7485-2025
34. Effects of different aerosol types on surface UV radiation in the 21st century A. Chatzopoulou et al. https://doi.org/10.1016/j.atmosenv.2025.121595