Higher-order Network Analysis of Fine Particulate Matter (PM 2.5) Transport in China at City Level

Yufang Wang; Haiyan Wang; Shuhua Chang; Maoxing Liu

doi:10.1038/s41598-017-13614-7

Higher-order Network Analysis of Fine Particulate Matter (PM _2.5) Transport in China at City Level

Yufang Wang, Haiyan Wang, Shuhua Chang, Maoxing Liu

Mathematical and Natural Sciences, School of (SMNS)

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

Specification of PM _2.5 transmission characteristics is important for pollution control and policymaking. We apply higher-order organization of complex networks to identify major potential PM _2.5 contributors and PM _2.5 transport pathways of a network of 189 cities in China. The network we create in this paper consists of major cities in China and contains information on meteorological conditions of wind speed and wind direction, data on geographic distance, mountains, and PM _2.5 concentrations. We aim to reveal PM _2.5 mobility between cities in China. Two major conclusions are revealed through motif analysis of complex networks. First, major potential PM _2.5 pollution contributors are identified for each cluster by one motif, which reflects movements from source to target. Second, transport pathways of PM _2.5 are revealed by another motif, which reflects transmission routes. To our knowledge, this is the first work to apply higher-order network analysis to study PM _2.5 transport.

Original language	English (US)
Article number	13236
Journal	Scientific reports
Volume	7
Issue number	1
DOIs	https://doi.org/10.1038/s41598-017-13614-7
State	Published - Dec 1 2017

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title = "Higher-order Network Analysis of Fine Particulate Matter (PM 2.5) Transport in China at City Level",

abstract = "Specification of PM 2.5 transmission characteristics is important for pollution control and policymaking. We apply higher-order organization of complex networks to identify major potential PM 2.5 contributors and PM 2.5 transport pathways of a network of 189 cities in China. The network we create in this paper consists of major cities in China and contains information on meteorological conditions of wind speed and wind direction, data on geographic distance, mountains, and PM 2.5 concentrations. We aim to reveal PM 2.5 mobility between cities in China. Two major conclusions are revealed through motif analysis of complex networks. First, major potential PM 2.5 pollution contributors are identified for each cluster by one motif, which reflects movements from source to target. Second, transport pathways of PM 2.5 are revealed by another motif, which reflects transmission routes. To our knowledge, this is the first work to apply higher-order network analysis to study PM 2.5 transport.",

author = "Yufang Wang and Haiyan Wang and Shuhua Chang and Maoxing Liu",

note = "Funding Information: The authors would like to acknowledge the help of Lipeng Song, Ying Yan, John Priniski and Adrian Avram for data collections. This project was supported in part by the Major Research Plan of the National Natural Science Foundation of China (91430108), the National Basic Research Program (2012CB955804), the National Natural Science Foundation of China (11171251, 11771322, 11571324), the National Science Foundation (DMS-1737861), and the Major Program of Tianjin University of Finance and Economics (ZD1302). Publisher Copyright: {\textcopyright} 2017 The Author(s).",

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N1 - Funding Information: The authors would like to acknowledge the help of Lipeng Song, Ying Yan, John Priniski and Adrian Avram for data collections. This project was supported in part by the Major Research Plan of the National Natural Science Foundation of China (91430108), the National Basic Research Program (2012CB955804), the National Natural Science Foundation of China (11171251, 11771322, 11571324), the National Science Foundation (DMS-1737861), and the Major Program of Tianjin University of Finance and Economics (ZD1302). Publisher Copyright: © 2017 The Author(s).

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N2 - Specification of PM 2.5 transmission characteristics is important for pollution control and policymaking. We apply higher-order organization of complex networks to identify major potential PM 2.5 contributors and PM 2.5 transport pathways of a network of 189 cities in China. The network we create in this paper consists of major cities in China and contains information on meteorological conditions of wind speed and wind direction, data on geographic distance, mountains, and PM 2.5 concentrations. We aim to reveal PM 2.5 mobility between cities in China. Two major conclusions are revealed through motif analysis of complex networks. First, major potential PM 2.5 pollution contributors are identified for each cluster by one motif, which reflects movements from source to target. Second, transport pathways of PM 2.5 are revealed by another motif, which reflects transmission routes. To our knowledge, this is the first work to apply higher-order network analysis to study PM 2.5 transport.

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Higher-order Network Analysis of Fine Particulate Matter (PM _2.5) Transport in China at City Level

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