52 citations as recorded by crossref.

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12. Self-supervised multi-task learning framework for safety and health-oriented road environment surveillance based on connected vehicle visual perception S. Jia & W. Yao 10.1016/j.jag.2024.103753
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21. Long-Term Variation in Wintertime Atmospheric Diffusion Conditions Over the Sichuan Basin G. Wang et al. 10.3389/fenvs.2021.763504
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23. PM2.5 concentration estimation with 1-km resolution at high coverage over urban agglomerations in China using the BPNN-KED approach and potential application Y. Huang et al. 10.1016/j.atmosres.2021.105628
24. Using a New Top‐Down Constrained Emissions Inventory to Attribute the Previously Unknown Source of Extreme Aerosol Loadings Observed Annually in the Monsoon Asia Free Troposphere S. Wang et al. 10.1029/2021EF002167
25. Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula Y. Youn et al. 10.3390/rs16234400
26. LiDAR-Based Remote Sensing of the Vertical Profile of Aerosol Liquid Water Content Using a Machine-Learning Model T. Wu et al. 10.1109/TGRS.2021.3130204
27. Spatiotemporal changes in aerosol properties by hygroscopic growth and impacts on radiative forcing and heating rates during DISCOVER-AQ 2011 D. Pérez-Ramírez et al. 10.5194/acp-21-12021-2021
28. Tropospheric aerosol hygroscopicity in China C. Peng et al. 10.5194/acp-20-13877-2020
29. Influence of meteorological variables and air pollutants on fog/smog formation in seven major cities of Indo-Gangetic Plain K. Lakra & K. Avishek 10.1007/s10661-024-12662-7
30. Real-time chemical characterization of primary and aged biomass burning aerosols derived from sub-Saharan African biomass fuels in smoldering fires M. James et al. 10.1039/D4EA00110A
31. Hygroscopicity of Different Types of Aerosol Particles: Case Studies Using Multi-Instrument Data in Megacity Beijing, China T. Wu et al. 10.3390/rs12050785
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34. Atmospheric pollution assessment near potential source of natural aerosols in the South Gobi Desert region, China M. Filonchyk et al. 10.1080/15481603.2020.1715591
35. Assessing aerosol-radiation interaction with WRF-chem-solar: Case study on the impact of the “pollution reduction and carbon reduction synergy” policy W. Wen et al. 10.1016/j.atmosres.2024.107537
36. Impact of atmospheric thermodynamic structures and aerosol radiation feedback on winter regional persistent heavy particulate pollution in the Sichuan-Chongqing region, China H. Lu et al. 10.1016/j.scitotenv.2022.156575
37. Measurement report: Spectral and statistical analysis of aerosol hygroscopic growth from multi-wavelength lidar measurements in Barcelona, Spain M. Sicard et al. 10.5194/acp-22-7681-2022
38. Size-resolved hygroscopicity and volatility properties of ambient urban aerosol particles measured by a volatility hygroscopicity tandem differential mobility analyzer system in Beijing A. Yu et al. 10.5194/acp-25-3389-2025
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42. Health and Safety Effects of Airborne Soil Dust in the Americas and Beyond D. Tong et al. 10.1029/2021RG000763
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44. Highly significant impact of mineral dust on aerosol hygroscopicity at New Delhi Z. Arub et al. 10.1016/j.atmosenv.2021.118375
45. Innovative aerosol hygroscopic growth study from Mie–Raman–fluorescence lidar and microwave radiometer synergy R. Miri et al. 10.5194/amt-17-3367-2024
46. Improved PM2.5 predictions of WRF-Chem via the integration of Himawari-8 satellite data and ground observations J. Hong et al. 10.1016/j.envpol.2020.114451
47. Assessing the effectiveness of PM2.5 pollution control from the perspective of interprovincial transport and PM2.5 mitigation costs across China Y. Wang et al. 10.1016/j.ese.2024.100448
48. Increased number concentrations of small particles explain perceived stagnation in air quality over Korea S. Joo et al. 10.5194/acp-25-1023-2025
49. A foehn-induced haze front in Beijing: observations and implications J. Li et al. 10.5194/acp-20-15793-2020
50. Aerosol hygroscopicity: Hygroscopic growth proxy based on visibility for low-cost PM monitoring A. Molnár et al. 10.1016/j.atmosres.2019.104815
51. Confidence Interval Estimation for the Mean of Zero-Inflated Birnbaum–Saunders Distribution N. Ratasukharom et al. 10.1134/S1995080223120272
52. A New Coupling Method for PM2.5 Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model S. Yuan et al. 10.3390/rs14102360