Articles | Volume 13, issue 2
https://doi.org/10.5194/esd-13-1029-2022
https://doi.org/10.5194/esd-13-1029-2022
Research article
 | 
21 Jun 2022
Research article |  | 21 Jun 2022

Complex network analysis of fine particulate matter (PM2.5): transport and clustering

Na Ying, Wansuo Duan, Zhidan Zhao, and Jingfang Fan

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Cited articles

Boers, N., Goswami, B., Rheinwalt, A., Bookhagen, B., Hoskins, B., and Kurths, J.: Complex networks reveal global pattern of extreme-rainfall teleconnections, Nature, 566, 373–377, https://doi.org/10.1038/s41586-018-0872-x, 2019. 
Cai, S., Wang, Y., Zhao, B., Wang, S., Chang, X., and Hao, J.: The impact of the “Air Pollution Prevention and Control Action Plan” on PM2.5 concentrations in Jing-Jin-Ji region during 2012–2020, Sci. Total. Environ., 580, 197–209, https://doi.org/10.1016/j.scitotenv.2016.11.188, 2017. 
Castrejon-Pita, A. A. and Read, P. L.: Synchronization in a Pair of Thermally Coupled Rotating Baroclinic Annuli: Understanding Atmospheric Teleconnections in the Laboratory, Phys. Rev. Lett., 104, 204501, https://doi.org/10.1103/PhysRevLett.104.204501, 2010. 
CNEMC – China National Environmental Monitoring Centre: Real-time National Air Quality, https://air.cnemc.cn:18007, last access: 19 June 2022. 
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Short summary
A complex PM2.5 measurement network has been built to investigate transport patterns and cooperative regions in China. Network-based degree measurements are used to reveal the spatial transport pattern of PM2.5. The study also attempts to investigate the seasonal transport path of PM2.5. In addition, the cooperation regions of PM2.5 are quantified according to their synchronicity characteristics. The proposed study can be applied to other air pollutant data, such as ozone and NOx.
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