4.2 Article

Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015

期刊

JOURNAL OF ENVIRONMENTAL SCIENCES
卷 56, 期 -, 页码 214-229

出版社

SCIENCE PRESS
DOI: 10.1016/j.jes.2016.06.035

关键词

PM2.5; PM10; Cluster analyses; PSCF; CWT; Beijing

资金

  1. National Key Foundation for Exploring Scientific Instrument [2012YQ060147]
  2. Strategic Priority Research Program of the Chinese Academy of Sciences [XDB05040402]
  3. Key Program of the Chinese 473 Academy of Sciences [KJZD-EW-TZ-G06-01]

向作者/读者索取更多资源

Trajectory clustering, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods were applied to investigate the transport pathways and identify potential sources of PM2.5 and PM10 in different seasons from June 2014 to May 2015 in Beijing. The cluster analyses showed that Beijing was affected by trajectories from the south and southeast in summer and autumn. In winter and spring, Beijing was not only affected by the trajectories from the south and southeast, but was also affected by trajectories from the north and northwest. In addition, the analyses of the pressure profile of backward trajectories showed that backward trajectories, which have important influence on Beijing, were mainly distributed above 970 hPa in summer and autumn and below 950 hPa in spring and winter. This indicates that PM2.5 and PM10 were strongly affected by the near surface air masses in summer and autumn and by high altitude air masses in winter and spring. Results of PSCF and CWT analyses showed that the largest potential source areas were identified in spring, followed by winter and autumn, then summer. In addition, potential source regions of PM10 were similar to those of PM2.5. There were a clear seasonal and spatial variation of the potential source areas of Beijing and the airflow in the horizontal and vertical directions. Therefore, more effective regional emission reduction measures in Beijing's surrounding provinces should be implemented to reduce emissions of regional sources in different seasons. (C) 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

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