Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China
Abstract The frequent episodes of severe air pollution over China during recent years have posed serious health threats to densely populated eastern China. Although several studies investigated the linkage between enhanced severity and frequency of air pollution and the large‐scale weather patterns...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-10-01
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| Series: | Atmospheric Science Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/asl.938 |
| _version_ | 1828389619465453568 |
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| author | Ziwei Wang Gang Chen Yu Gu Bin Zhao Qiao Ma Shuxiao Wang Kuo‐Nan Liou |
| author_facet | Ziwei Wang Gang Chen Yu Gu Bin Zhao Qiao Ma Shuxiao Wang Kuo‐Nan Liou |
| author_sort | Ziwei Wang |
| collection | DOAJ |
| description | Abstract The frequent episodes of severe air pollution over China during recent years have posed serious health threats to densely populated eastern China. Although several studies investigated the linkage between enhanced severity and frequency of air pollution and the large‐scale weather patterns over China, the day‐to‐day covariability between them, as well as its local and remote mechanisms, has not been systematically documented. The wintertime synoptic covariability between PM2.5 and large‐scale meteorological fields is studied using surface observations of PM2.5 in 2013/2014–2016/2017 and ERA‐Interim meteorological fields through maximum covariance analysis (MCA). The first MCA mode (MCA1) suggests a consistent accumulation of ambient PM2.5 as a result of weakened winds that block the pollutant removal passage in heavily polluted areas of eastern China, as well as moist air from southeast coast favoring haze formation. A northeast–southwest belt that extends into northeastern China and central China on each end is more sensitive to MCA1. The second MCA mode (MCA2) shows a north–south dipole in PM2.5 linked to the contrast of boundary layer height and surface wind speed between northern and southern regions of China. Spatial patterns of both modes are supported by the GEOS‐Chem chemistry transport model with realistic emission inventory. The spatial patterns of the two modes are robust on the interannual time scales. Based on that, we investigate the variability of the first two modes of the identified modes on the multidecadal scale by projecting GPM_500 pattern to 1981–2010. Correlation analysis of the projected time series and climate indices over 30 years indicates the possible linkage of Arctic oscillation, ENSO indices, Pacific decadal oscillation and east Atlantic/western Russia to regional air pollution patterns over China. |
| first_indexed | 2024-12-10T06:33:36Z |
| format | Article |
| id | doaj.art-0e1c0957e63247aa816be35fabd30402 |
| institution | Directory Open Access Journal |
| issn | 1530-261X |
| language | English |
| last_indexed | 2024-12-10T06:33:36Z |
| publishDate | 2019-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | Atmospheric Science Letters |
| spelling | doaj.art-0e1c0957e63247aa816be35fabd304022022-12-22T01:59:00ZengWileyAtmospheric Science Letters1530-261X2019-10-012010n/an/a10.1002/asl.938Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over ChinaZiwei Wang0Gang Chen1Yu Gu2Bin Zhao3Qiao Ma4Shuxiao Wang5Kuo‐Nan Liou6Department of Atmospheric and Oceanic Science School of Physics, Peking University Beijing ChinaDepartment of Atmospheric and Oceanic Sciences University of California Los Angeles CaliforniaDepartment of Atmospheric and Oceanic Sciences University of California Los Angeles CaliforniaDepartment of Atmospheric and Oceanic Sciences University of California Los Angeles CaliforniaSchool of Energy and Power Engineering, Shandong University Jinan ChinaSchool of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University Beijing ChinaDepartment of Atmospheric and Oceanic Sciences University of California Los Angeles CaliforniaAbstract The frequent episodes of severe air pollution over China during recent years have posed serious health threats to densely populated eastern China. Although several studies investigated the linkage between enhanced severity and frequency of air pollution and the large‐scale weather patterns over China, the day‐to‐day covariability between them, as well as its local and remote mechanisms, has not been systematically documented. The wintertime synoptic covariability between PM2.5 and large‐scale meteorological fields is studied using surface observations of PM2.5 in 2013/2014–2016/2017 and ERA‐Interim meteorological fields through maximum covariance analysis (MCA). The first MCA mode (MCA1) suggests a consistent accumulation of ambient PM2.5 as a result of weakened winds that block the pollutant removal passage in heavily polluted areas of eastern China, as well as moist air from southeast coast favoring haze formation. A northeast–southwest belt that extends into northeastern China and central China on each end is more sensitive to MCA1. The second MCA mode (MCA2) shows a north–south dipole in PM2.5 linked to the contrast of boundary layer height and surface wind speed between northern and southern regions of China. Spatial patterns of both modes are supported by the GEOS‐Chem chemistry transport model with realistic emission inventory. The spatial patterns of the two modes are robust on the interannual time scales. Based on that, we investigate the variability of the first two modes of the identified modes on the multidecadal scale by projecting GPM_500 pattern to 1981–2010. Correlation analysis of the projected time series and climate indices over 30 years indicates the possible linkage of Arctic oscillation, ENSO indices, Pacific decadal oscillation and east Atlantic/western Russia to regional air pollution patterns over China.https://doi.org/10.1002/asl.938large‐scale meteorologyPM2.5 spatial patternssynoptic controlteleconnection with climate indices |
| spellingShingle | Ziwei Wang Gang Chen Yu Gu Bin Zhao Qiao Ma Shuxiao Wang Kuo‐Nan Liou Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China Atmospheric Science Letters large‐scale meteorology PM2.5 spatial patterns synoptic control teleconnection with climate indices |
| title | Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China |
| title_full | Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China |
| title_fullStr | Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China |
| title_full_unstemmed | Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China |
| title_short | Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China |
| title_sort | large scale meteorological control on the spatial pattern of wintertime pm2 5 pollution over china |
| topic | large‐scale meteorology PM2.5 spatial patterns synoptic control teleconnection with climate indices |
| url | https://doi.org/10.1002/asl.938 |
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