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Preprints
https://doi.org/10.5194/acp-2020-708
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-708
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 Nov 2020

16 Nov 2020

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This preprint is currently under review for the journal ACP.

Meteorological formation mechanism of regional transport in winter heavy air pollution events in the middle Yangtze River area, China

Yongqing Bai1, Tianliang Zhao2, Yue Zhou1, Jie Xiong1, Weiyang Hu2, Yao Gu2, Lin Liu1, Shaofei Kong3, and Huang Zheng3 Yongqing Bai et al.
  • 1Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
  • 2Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • 3Department of Atmospheric Science, School of Environemtal Studies, China University of Geosciences (Wuhan), 430074

Abstract. Anthropogenic emission, meteorological conditions, and regional transport are the three major factors influencing heavy air pollution in China. The Hunan and Hubei provinces in the middle Yangtze River region border China's main air pollution areas, serving as the hub of regional transport of air pollutants. The meteorological formation mechanism of regional transport of air pollutants on heavy air pollution in the Hunan and Hubei provinces still remain urgent to be addressed in depth. In this study, multivariate empirical orthogonal function (MV-EOF) analysis was performed to objectively select eight typical heavy pollution events in the two provinces that occured in January 2015–2019. Based on the regional surface environment, meteorological network data, atmospheric sounding data, ERA-interim reanalysis data, and a numerical simulation experiment, this study investigated the pattern of regional transport of air pollutants in the two provinces and its mechanism of regional meteorological conditions. The results showed that transporting air pollutants mainly passed through two transport pathways, namely the Nanxiang Basin-Yunmeng Plain pathway and the Dabie Mountain's Hilly Area-Yunmeng Plain pathway, existing anomalous near-surface northerly winds in the two provinces and their upstream area accompanied by southward penetration of a shallow cold layer, all of which jointly provide a dynamic condition for regional air pollutant transport. The weak cold-air mass degenerated as it passed through the Hunan–Hubei Plain, causing warm air to accumulate in the near-surface layer of the downstream area, where winds slowed down and converged, buffering the air pollutant transport and resulting in pollutants accumulation; the near-surface atmosphere of the Hunan and Hubei provinces was a non-stagnant condition (dry intrusion of cold air, anomalous northerly winds, and positive anomalies of boundary-layer height), which is conducive to the horizontal transport of air pollutants. However, the mid-high layers, characterized by temperature inversion and the presence of a warm lid, had a stable stratification, inhibiting the diffusion of air pollutants to the upper layers; there is an obvious longitudinal vertical circulation above the Hunan–Hubei Plain, which results in the sinking and accumulation of air pollutants, thereby promoting rapid accumulation of air pollutants in the Hunan and Hubei provinces. In addition, extended empirical orthogonal function (EEOF) analysis was performed, revealing a quasi-4-d periodic oscillation pattern of air pollutants transport in the Hunan and Hubei provinces, which provides a reference for early prediction of its regional transport. The findings are of practical value in broadening the scientific understanding of the differences in the formation mechanism of heavy atmospheric pollution between the various regions of China and promoting environmental and ecological protection of the middle Yangtze Basin.

Yongqing Bai et al.

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Yongqing Bai et al.

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