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
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
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, Hunan, China
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
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
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3,479
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4,406
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Total article views: 2,939 (including HTML, PDF, and XML)
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2,299
586
54
2,939
118
83
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XML: 54
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Supplement: 118
BibTeX: 83
EndNote: 109
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Total article views: 1,467 (including HTML, PDF, and XML)
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1,180
269
18
1,467
112
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13
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PDF: 269
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Total: 1,467
Supplement: 112
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Viewed (geographical distribution)
Total article views: 4,406 (including HTML, PDF, and XML)
Thereof 4,406 with geography defined
and 0 with unknown origin.
Total article views: 2,939 (including HTML, PDF, and XML)
Thereof 2,939 with geography defined
and 0 with unknown origin.
Total article views: 1,467 (including HTML, PDF, and XML)
Thereof 1,457 with geography defined
and 10 with unknown origin.
Using an aerosol–climate model, dust pollution in China affected by different spatial and temporal types of El Niño are examined. Both eastern and central Pacific El Niño and short-duration El Niño increase winter dust concentrations over northern China, while long-duration El Niño decreases concentrations. Only long-duration El Niño events can significantly affect dust over China in the following spring. This study has profound implications for air pollution control and dust storm prediction.
Using an aerosol–climate model, dust pollution in China affected by different spatial and...
