Large-scale meteorological control on the spatial pattern of wintertime PM 2.5 pollution over China
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 pol-lution and the large-scale weather patterns over Chi...
| Published in: | Atmospheric Science Letters |
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| Main Authors: | , , , , , , |
| Language: | unknown |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://www.osti.gov/servlets/purl/1578053 https://www.osti.gov/biblio/1578053 https://doi.org/10.1002/asl.938 |
| Summary: | 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 pol-lution 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 systemati-cally documented. The wintertime synoptic covariability between PM 2.5 and large-scale meteorological fields is studied using surface observations of PM 2.5 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 PM 2.5 as a result of weakened winds that block the pollut-ant 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 PM 2.5 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. |
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