4.5 Article

Integrating LIDAR data and four-dimensional flux method to analyzing the transmission of PM2.5 in Shenzhen

Journal

PHYSICS AND CHEMISTRY OF THE EARTH
Volume 110, Issue -, Pages 81-88

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pce.2019.04.001

Keywords

Four-dimensional flux; Pollution transmission; LIDAR data; Shenzhen

Funding

  1. National Key Research and Development Program of China [2016YFC0208803]
  2. Blue Sky Project of Shenzhen, China [Z22015QT0001]

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With the increase economic growth and high energy consumption in Shenzhen, pollutant emission increases gradually which leads to air pollution and affect public health. In order to undertake effective measures for preventing and controlling air pollution, it is essential to understand the transmission characteristics of PM2.5 and identify the cause of air pollution in Shenzhen. Based on LIDAR data of Shenzhen, China, the transmission characteristics of PM2.5 across Shenzhen's borders in the winter of 2017 (from December 1, 2017 to February 28, 2018) were analyzed using a four-dimensional flux method. In addition, the sources of PM2.5 in Shenzhen from December 8 to 10, 2017 were analyzed. The results revealed that the East Asian winter monsoon was primarily responsible for the transmission of PM2.5 in Shenzhen, from north to south, and its surrounding areas, and high PM2.5 flux was primarily located at the altitude range of 500-1,500 m. During the monsoon transition period, the surface wind directions changed frequently, which resulted in varying transmission directions of PM2.5 fluxes across Shenzhen. During the period from December 8 to10, PM2.5 was continuously transported to the urban areas of Shenzhen via its northern border due to the influence of strong northerly wind. The PM2.5 fluxes were positive over Songgang station (in the northwestern corner of Shenzhen) and Xiapi station (in the northeastern corner of Shenzhen) from December 8 to 9. The analysis revealed that, the PM2.5 source contribution from regional transmission (representing other land areas within the model domain) reached approximately 50%, whereas the local source contribution was only approximately 10% in Shenzhen.

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