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
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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56 citations as recorded by crossref.
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- 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
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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
54 citations as recorded by crossref.
- Continuous mapping of fine particulate matter (PM2.5) air quality in East Asia at daily 6 × 6 km2 resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data D. Pendergrass et al. 10.5194/amt-15-1075-2022
- Winter monsoon variability and its impact on aerosol concentrations in East Asia J. Jeong & R. Park 10.1016/j.envpol.2016.11.075
- Short-term effects of fine particulate matter constituents on mortality considering the mortality displacement in Zhejiang province, China J. Fu et al. 10.1016/j.jhazmat.2023.131723
- 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
- Aerosol optical and radiative properties and their environmental effects in China: A review H. Che et al. 10.1016/j.earscirev.2023.104634
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- 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
- Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed Z. Zheng et al. 10.1029/2022MS003099
- New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS) J. Kim et al. 10.1175/BAMS-D-18-0013.1
- Is water vapor a key player of the wintertime haze in North China Plain? J. Wu et al. 10.5194/acp-19-8721-2019
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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
- 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
- Climatology and model prediction of aerosol optical properties over the Indo-Gangetic Basin in north India A. Singh et al. 10.1007/s10661-022-10440-x
- Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China W. Wang et al. 10.3390/rs9080858
- Retrieval of High Temporal Resolution Aerosol Optical Depth Using the GOCI Remote Sensing Data L. Chen et al. 10.3390/rs13122376
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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
- 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
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- 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
- 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
- Satellite Monitoring for Air Quality and Health T. Holloway et al. 10.1146/annurev-biodatasci-110920-093120
- 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
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- 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
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- 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 PM2.5 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
- Near-real-time hourly PM2.5 prediction over East Asia using geostationary satellite products and machine learning J. Lee et al. 10.1016/j.atmosenv.2024.120700
- Recent Developments in Satellite Remote Sensing for Air Pollution Surveillance in Support of Sustainable Development Goals D. Stratoulias et al. 10.3390/rs16162932
- 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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- Impacts of coal burning on ambient PM2.5 pollution in China Q. Ma et al. 10.5194/acp-17-4477-2017
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- 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
- Estimating Ground-Level Hourly PM2.5 Concentrations in Thailand Using Satellite Data: A Log-Linear Model With Sum Contrast Analysis S. Buya et al. 10.1109/JSTARS.2024.3384964
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- Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations S. Zhai et al. 10.5194/acp-21-16775-2021
- 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
- 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
- Hourly Ground-Level PM2.5 Estimation Using Geostationary Satellite and Reanalysis Data via Deep Learning C. Lee et al. 10.3390/rs13112121
- 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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Latest update: 01 Jul 2025
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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