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
Drew C. Pendergrass,Shixian Zhai,Jhoon Kim,Ja-Ho Koo,Seoyoung Lee,Minah Bae,Soontae Kim,Hong Liao,and Daniel J. Jacob
Department of Atmospheric Sciences, Yonsei University, Seoul, South
Korea
Particulate Matter Research Institute, Samsung Advanced Institute of Technology (SAIT), Suwon, South Korea
Ja-Ho Koo
Department of Atmospheric Sciences, Yonsei University, Seoul, South
Korea
Seoyoung Lee
Department of Atmospheric Sciences, Yonsei University, Seoul, South
Korea
Minah Bae
Department of Environmental and Safety Engineering, Ajou University, Suwon, South Korea
Soontae Kim
Department of Environmental and Safety Engineering, Ajou University, Suwon, South Korea
Hong Liao
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and
Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Daniel J. Jacob
School of Engineering and Applied Sciences, Harvard University,
Cambridge, MA, USA
Viewed
Total article views: 2,416 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
1,624
739
53
2,416
73
33
44
HTML: 1,624
PDF: 739
XML: 53
Total: 2,416
Supplement: 73
BibTeX: 33
EndNote: 44
Views and downloads (calculated since 20 Oct 2021)
Cumulative views and downloads
(calculated since 20 Oct 2021)
Total article views: 1,294 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
820
441
33
1,294
73
25
29
HTML: 820
PDF: 441
XML: 33
Total: 1,294
Supplement: 73
BibTeX: 25
EndNote: 29
Views and downloads (calculated since 03 Mar 2022)
Cumulative views and downloads
(calculated since 03 Mar 2022)
Total article views: 1,122 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
804
298
20
1,122
8
15
HTML: 804
PDF: 298
XML: 20
Total: 1,122
BibTeX: 8
EndNote: 15
Views and downloads (calculated since 20 Oct 2021)
Cumulative views and downloads
(calculated since 20 Oct 2021)
Viewed (geographical distribution)
Total article views: 2,416 (including HTML, PDF, and XML)
Thereof 2,486 with geography defined
and -70 with unknown origin.
Total article views: 1,294 (including HTML, PDF, and XML)
Thereof 1,381 with geography defined
and -87 with unknown origin.
Total article views: 1,122 (including HTML, PDF, and XML)
Thereof 1,105 with geography defined
and 17 with unknown origin.
This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
This paper uses a machine learning algorithm to infer high-resolution maps of particulate air...