Articles | Volume 15, issue 22
https://doi.org/10.5194/acp-15-13133-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-13133-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
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
CORRESPONDING AUTHOR
Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
R. V. Martin
Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, USA
A. van Donkelaar
Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
J. Kim
Department of Physics and Atmospheric Sciences, Yonsei University, Seoul, South Korea
Department of Physics and Atmospheric Sciences, Yonsei University, Seoul, South Korea
Q. Zhang
Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing, China
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing, China
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
L. Huang
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing, China
Department of Marine Sciences, Texas A&M University at Galveston, Galveston, Texas, USA
Department of Atmospheric Sciences, Texas A&M University, College Station, Texas, USA
H. Chen
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, China
P. Lin
Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
N. Lin
Department of Atmospheric Sciences, National Central University, Taoyan, Taiwan
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- Fine Particle Constituents and Mortality: A Time-Series Study in Beijing, China C. Chen et al. 10.1021/acs.est.8b00424
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- 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
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- 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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- 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
- Hourly Ground-Level PM2.5 Estimation Using Geostationary Satellite and Reanalysis Data via Deep Learning C. Lee et al. 10.3390/rs13112121
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- 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
- Estimating PM2.5 surface concentrations from AOD: A combination of SLSTR and MODIS J. Handschuh et al. 10.1016/j.rsase.2022.100716
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- 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 Jun 2023
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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