Multidecadal ozone trends in China and implications for human health and crop yields: a hybrid approach combining a chemical transport model and machine learning
Jia Mao,Amos P. K. Tai,David H. Y. Yung,Tiangang Yuan,Kong T. Chau,and Zhaozhong Feng
Jia Mao
Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China
Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China
State Key Laboratory of Agrobiotechnology, and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong SAR, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China
Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China
Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China
Kong T. Chau
Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong SAR, China
Zhaozhong Feng
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China
Viewed
Total article views: 5,545 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
4,395
976
174
5,545
446
212
297
HTML: 4,395
PDF: 976
XML: 174
Total: 5,545
Supplement: 446
BibTeX: 212
EndNote: 297
Views and downloads (calculated since 08 Jun 2023)
Cumulative views and downloads
(calculated since 08 Jun 2023)
Total article views: 3,539 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
2,955
490
94
3,539
167
127
164
HTML: 2,955
PDF: 490
XML: 94
Total: 3,539
Supplement: 167
BibTeX: 127
EndNote: 164
Views and downloads (calculated since 11 Jan 2024)
Cumulative views and downloads
(calculated since 11 Jan 2024)
Total article views: 2,006 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
1,440
486
80
2,006
279
85
133
HTML: 1,440
PDF: 486
XML: 80
Total: 2,006
Supplement: 279
BibTeX: 85
EndNote: 133
Views and downloads (calculated since 08 Jun 2023)
Cumulative views and downloads
(calculated since 08 Jun 2023)
Viewed (geographical distribution)
Total article views: 5,545 (including HTML, PDF, and XML)
Thereof 5,542 with geography defined
and 3 with unknown origin.
Total article views: 3,539 (including HTML, PDF, and XML)
Thereof 3,539 with geography defined
and 0 with unknown origin.
Total article views: 2,006 (including HTML, PDF, and XML)
Thereof 1,999 with geography defined
and 7 with unknown origin.
Surface ozone (O3) is well-known for posing great threats to both human health and agriculture worldwide. However, a multidecadal assessment of the impacts of O3 on public health and agriculture in China is lacking without sufficient O3 observations. We used a hybrid approach combining a chemical transport model and machine learning to provide a robust dataset of O3 concentrations over the past 4 decades in China, thereby filling the gap in the long-term O3 trend and impact assessment in China.
Surface ozone (O3) is well-known for posing great threats to both human health and agriculture...
