Research article 27 Nov 2015
Research article | 27 Nov 2015
Estimating ground-level PM2.5 in eastern China using aerosol optical depth determined from the GOCI satellite instrument
J.-W. Xu et al.
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Cited
41 citations as recorded by crossref.
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- Estimating PM2.5 concentrations in Yangtze River Delta region of China using random forest model and the Top-of-Atmosphere reflectance L. Yang et al. 10.1016/j.jenvman.2020.111061
- 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
- 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
- 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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- Estimating ground-level particulate matter concentrations using satellite-based data: a review M. Shin et al. 10.1080/15481603.2019.1703288
- 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
- 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
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- 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
- Impacts of coal burning on ambient PM<sub>2.5</sub> pollution in China Q. Ma et al. 10.5194/acp-17-4477-2017
- 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
- Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China W. Wang et al. 10.3390/rs9080858
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- Ground-level PM2.5 estimation over urban agglomerations in China with high spatiotemporal resolution based on Himawari-8 T. Zhang et al. 10.1016/j.scitotenv.2019.04.299
- The Impact of the Direct Effect of Aerosols on Meteorology and Air Quality Using Aerosol Optical Depth Assimilation During the KORUS‐AQ Campaign J. Jung et al. 10.1029/2019JD030641
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- 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
- 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
- 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
- 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
- Fine Particle Constituents and Mortality: A Time-Series Study in Beijing, China C. Chen et al. 10.1021/acs.est.8b00424
- Remote sensing of ground-level PM2.5 combining AOD and backscattering profile S. Li et al. 10.1016/j.rse.2016.05.025
- A Review on Predicting Ground PM2.5 Concentration Using Satellite Aerosol Optical Depth Y. Chu et al. 10.3390/atmos7100129
38 citations as recorded by crossref.
- Characteristics and source distribution of air pollution in winter in Qingdao, eastern China L. Li et al. 10.1016/j.envpol.2016.12.037
- 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
- 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
- Winter monsoon variability and its impact on aerosol concentrations in East Asia J. Jeong & R. Park 10.1016/j.envpol.2016.11.075
- Review of surface particulate monitoring of dust events using geostationary satellite remote sensing M. Sowden et al. 10.1016/j.atmosenv.2018.04.020
- Mortality burden attributable to PM1 in Zhejiang province, China K. Hu et al. 10.1016/j.envint.2018.09.033
- Introducing the geostationary environment monitoring spectrometer W. Choi 10.1117/1.JRS.12.044005
- 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
- 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
- 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
- Estimating PM2.5 concentrations in Yangtze River Delta region of China using random forest model and the Top-of-Atmosphere reflectance L. Yang et al. 10.1016/j.jenvman.2020.111061
- 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
- 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
- New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS) J. Kim et al. 10.1175/BAMS-D-18-0013.1
- Fuzzy inference system for modeling the environmental risk map of air pollutants in Taiwan C. Chung et al. 10.1016/j.jenvman.2019.06.038
- Is water vapor a key player of the wintertime haze in North China Plain? J. Wu et al. 10.5194/acp-19-8721-2019
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models M. Diao et al. 10.1080/10962247.2019.1668498
- Estimating ground-level particulate matter concentrations using satellite-based data: a review M. Shin et al. 10.1080/15481603.2019.1703288
- 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
- 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
- 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
- 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
- Impacts of coal burning on ambient PM<sub>2.5</sub> pollution in China Q. Ma et al. 10.5194/acp-17-4477-2017
- 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
- Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China W. Wang et al. 10.3390/rs9080858
- 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
- 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
- Ground-level PM2.5 estimation over urban agglomerations in China with high spatiotemporal resolution based on Himawari-8 T. Zhang et al. 10.1016/j.scitotenv.2019.04.299
- The Impact of the Direct Effect of Aerosols on Meteorology and Air Quality Using Aerosol Optical Depth Assimilation During the KORUS‐AQ Campaign J. Jung et al. 10.1029/2019JD030641
- Evaluation of Himawari-8 version 2.0 aerosol products against AERONET ground-based measurements over central and northern China L. Wang et al. 10.1016/j.atmosenv.2020.117357
- Long-term trend and spatial pattern of PM2.5 induced premature mortality in China R. Xie et al. 10.1016/j.envint.2016.09.003
- Remote sensing of PM2.5 during cloudy and nighttime periods using ceilometer backscatter S. Li et al. 10.5194/amt-10-2093-2017
- Interdecadal variation in aerosol optical properties and their relationships to meteorological parameters over northeast China from 1980 to 2017 H. Zhao et al. 10.1016/j.chemosphere.2019.125737
- 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
- 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
- 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
- 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
- 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
3 citations as recorded by crossref.
- Fine Particle Constituents and Mortality: A Time-Series Study in Beijing, China C. Chen et al. 10.1021/acs.est.8b00424
- Remote sensing of ground-level PM2.5 combining AOD and backscattering profile S. Li et al. 10.1016/j.rse.2016.05.025
- A Review on Predicting Ground PM2.5 Concentration Using Satellite Aerosol Optical Depth Y. Chu et al. 10.3390/atmos7100129
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Latest update: 05 Mar 2021
Short summary
1. GOCI (Geostationary Ocean Color Imager) retrieval of AOD is consistent with AERONET AOD (RMSE=0.08-0.1)
2. GOCI-derived PM2.5 is in significant agreement with in situ observations (r2=0.66, rRMSE=18.3%)
3. Population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg/m3, threatening the health of its more than 400 million residents
4. Secondary inorganics (SO42-, NO3-, NH4+) & organic matter are the most significant components of GOCI-derived PM2.5.
1. GOCI (Geostationary Ocean Color Imager) retrieval of AOD is consistent with AERONET AOD...
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