Preprints
https://doi.org/10.5194/esd-2022-9
https://doi.org/10.5194/esd-2022-9
 
09 Mar 2022
09 Mar 2022
Status: a revised version of this preprint was accepted for the journal ESD and is expected to appear here in due course.

Complex networks analysis of PM2.5: transport and clustering

Na Ying1, Wansuo Duan2, Zhidan Zhao3, and Jinfang Fan4 Na Ying et al.
  • 1China State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
  • 2State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 3China Complexity Computation Lab, Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China
  • 4School of Systems Science, Beijing Normal University, Beijing 100875, China

Abstract. Complex network theory has been applied to reveal the transport patterns and cooperative regions of fine (< 2.5 µm) particulate matter (PM2.5) in the whole of China over a long-term record. The results show the degrees, weighted degrees, and edge lengths of PM2.5 cities follow power-law distributions. Cities in the Beijing-Tianjin-Hebei-Henan-Shandong (BTHHS) region have a strong ability to import PM2.5 pollution to other cities. By analyzing the transport routes, we show that a mass of links extends southward from the BTHHS to the Yangtze River Delta (YRD) regions with one- or two-day time lags. Hence, we conclude that earlier emission reduction in BTHHS and early-warning measures in YRD will help to improve air quality in both regions. Moreover, significant links are concentrated in wintertime, suggesting the impact of the winter monsoon. In addition, cities have been divided into nine clusters according to their synchronicity characteristics. Cities in the same clusters should be regarded as a whole to control the level of air pollution. The results are derived by an economic approach of complex network theory, which avoids the time-consuming of traditional model simulation approach and suggests a highly efficient approach to the studies of transport and cluster of PM2.5. This approach, beyond doubt, is certainly also applicable to the studies of other air pollutants such as ozone, NOx, and so on.

Na Ying et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esd-2022-9', Anonymous Referee #1, 08 Apr 2022
    • AC2: 'Reply on RC1', Na Ying, 20 Apr 2022
  • RC2: 'Comment on esd-2022-9', Anonymous Referee #2, 17 Apr 2022
    • AC1: 'Reply on RC2', Na Ying, 20 Apr 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esd-2022-9', Anonymous Referee #1, 08 Apr 2022
    • AC2: 'Reply on RC1', Na Ying, 20 Apr 2022
  • RC2: 'Comment on esd-2022-9', Anonymous Referee #2, 17 Apr 2022
    • AC1: 'Reply on RC2', Na Ying, 20 Apr 2022

Na Ying et al.

Na Ying et al.

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Short summary
PM2.5 complex network has been built to investigate the transport patterns and cooperative regions in China. Network-based measure degree is used to reveal the spatial transport pattern of PM2.5. The study also attempts to investigate the transport path of PM2.5 seasonally. In addition, the cooperation regions of PM2.5 are quantified according to their synchronicity characteristics. The proposed study can be applied to other air pollutants data, such as ozone, NOx, and so on.
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