Journal of Meteorological Research

, Volume 32, Issue 1, pp 81–98 | Cite as

Differences in Meteorological Conditions between Days with Persistent and Non-Persistent Pollution in Beijing, China

  • Ting You
  • Renguang Wu
  • Gang Huang
Regular Articles


We compared the regional synoptic patterns and local meteorological conditions during persistent and non-persistent pollution events in Beijing using US NCEP–Department of Energy reanalysis outputs and observations from meteorological stations. The analysis focused on the impacts of high-frequency (period < 90 days) variations in meteorological conditions on persistent pollution events (those lasting for at least 3 days). Persistent pollution events tended to occur in association with slow-moving weather systems producing stagnant weather conditions, whereas rapidly moving weather systems caused a dramatic change in the local weather conditions so that the pollution event was short-lived. Although Beijing was under the influence of anomalous southerly winds in all four seasons during pollution events, notable differences were identified in the regional patterns of sea-level pressure and local anomalies in relative humidity among persistent pollution events in different seasons. A region of lower pressure was present to the north of Beijing in spring, fall, and winter, whereas regions of lower and higher pressures were observed northwest and southeast of Beijing, respectively, in summer. The relative humidity near Beijing was higher in fall and winter, but lower in spring and summer. These differences may explain the seasonal dependence of the relationship between air pollution and the local meteorological variables. Our analysis showed that the temperature inversion in the lower troposphere played an important part in the occurrence of air pollution under stagnant weather conditions. Some results from this study are based on a limited number of events and thus require validation using more data.


persistent and non-persistent pollution events regional synoptic patterns local meteorological conditions temperature inversion stability index Beijing 


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We appreciate the comments of the two anonymous reviewers. The NCEP–DOE reanalysis 2 data were obtained from


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Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center for Monsoon System Research, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.College of Atmospheric SciencesChengdu University of Information TechnologyChengduChina
  3. 3.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  4. 4.Laboratory for Regional Oceanography and Numerical ModelingQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  5. 5.Joint Center for Global Change StudiesBeijingChina
  6. 6.University of Chinese Academy of SciencesBeijingChina

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