41 citations as recorded by crossref.

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2. Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea S. Park et al. 10.5194/acp-19-1097-2019
3. Assessing the effect of long-range pollutant transportation on air quality in Seoul using the conditional potential source contribution function method U. Jeong et al. 10.1016/j.atmosenv.2016.11.017
4. Winter monsoon variability and its impact on aerosol concentrations in East Asia J. Jeong & R. Park 10.1016/j.envpol.2016.11.075
5. Review of surface particulate monitoring of dust events using geostationary satellite remote sensing M. Sowden et al. 10.1016/j.atmosenv.2018.04.020
6. Mortality burden attributable to PM1 in Zhejiang province, China K. Hu et al. 10.1016/j.envint.2018.09.033
7. Introducing the geostationary environment monitoring spectrometer W. Choi 10.1117/1.JRS.12.044005
8. Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models S. Park et al. 10.1016/j.scitotenv.2020.136516
9. Estimation of PM2.5 Mass Concentrations in Beijing–Tianjin–Hebei Region Based on Geographically Weighted Regression and Spatial Downscaling Method L. Zhang & J. Pan 10.1007/s12524-020-01193-6
10. Diurnal variation of aerosol optical depth and PM<sub>2.5</sub> in South Korea: a synthesis from AERONET, satellite (GOCI), KORUS-AQ observation, and the WRF-Chem model E. Lennartson et al. 10.5194/acp-18-15125-2018
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12. GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia M. Choi et al. 10.5194/amt-11-385-2018
13. Impact of the OMI aerosol optical depth on analysis increments through coupled meteorology–aerosol data assimilation for an Asian dust storm E. Lee et al. 10.1016/j.rse.2017.02.013
14. New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS) J. Kim et al. 10.1175/BAMS-D-18-0013.1
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19. Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia Q. Xiao et al. 10.5194/acp-16-1255-2016
20. Comparison of GOCI and Himawari-8 aerosol optical depth for deriving full-coverage hourly PM2.5 across the Yangtze River Delta D. Tang et al. 10.1016/j.atmosenv.2019.116973
21. GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign M. Choi et al. 10.5194/amt-9-1377-2016
22. A spatially structured adaptive two-stage model for retrieving ground-level PM2.5 concentrations from VIIRS AOD in China F. Yao et al. 10.1016/j.isprsjprs.2019.03.011
23. Impacts of coal burning on ambient PM<sub>2.5</sub> pollution in China Q. Ma et al. 10.5194/acp-17-4477-2017
24. Assessment of long-range transboundary aerosols in Seoul, South Korea from Geostationary Ocean Color Imager (GOCI) and ground-based observations S. Lee et al. 10.1016/j.envpol.2020.115924
25. Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China W. Wang et al. 10.3390/rs9080858
26. A multidimensional comparison between MODIS and VIIRS AOD in estimating ground-level PM2.5 concentrations over a heavily polluted region in China F. Yao et al. 10.1016/j.scitotenv.2017.08.209
27. Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models S. Philip et al. 10.1088/1748-9326/aa65a4
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34. Impact of Meteorological Changes on Particulate Matter and Aerosol Optical Depth in Seoul during the Months of June over Recent Decades S. Yang et al. 10.3390/atmos11121282
35. Satellite-based estimation of hourly PM2.5 levels during heavy winter pollution episodes in the Yangtze River Delta, China Q. She et al. 10.1016/j.chemosphere.2019.124678
36. Can MODIS AOD be employed to derive PM2.5 in Beijing-Tianjin-Hebei over China? X. Ma et al. 10.1016/j.atmosres.2016.06.018
37. Development of an infrared pollution index to identify ground-level compositional, particle size, and humidity changes using Himawari-8 M. Sowden et al. 10.1016/j.atmosenv.2020.117435
38. Simultaneous Measurements of Chemical Compositions of Fine Particles during Winter Haze Period in Urban Sites in China and Korea M. Park et al. 10.3390/atmos11030292
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40. Remote sensing of ground-level PM2.5 combining AOD and backscattering profile S. Li et al. 10.1016/j.rse.2016.05.025
41. A Review on Predicting Ground PM2.5 Concentration Using Satellite Aerosol Optical Depth Y. Chu et al. 10.3390/atmos7100129