TY - JOUR
T1 - A weighted higher-order network analysis of fine particulate matter (PM2.5) transport in Yangtze River Delta
AU - Wang, Yufang
AU - Wang, Haiyan
AU - Zhang, Shuhua
N1 - Funding Information:
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 ); and the Major Program of Tianjin University of Finance and Economics ( ZD1302 ). The second author is partially supported by the National Natural Science Foundation of China ( 11571324 ) and the National Science Foundation ( DMS-1737861 ). The project was also supported in part by the National Natural Science Foundation of China ( 11626033 ).
Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/4/15
Y1 - 2018/4/15
N2 - Specification of PM2.5 transmission characteristics is important for pollution control, policymaking and prediction. In this paper, we propose weights for motif instances, thereby to implement a weighted higher-order clustering algorithm for a weighted, directed PM2.5 network in the Yangtze River Delta (YRD) of China. The weighted, directed network we create in this paper includes information on meteorological conditions of wind speed and wind direction, plus data on geographic distance and PM2.5 concentrations. We aim to reveal PM2.5 mobility between cities in the YRD. Major potential PM2.5 contributors and closely interacted clusters are identified in the network of 178 air quality stations in the YRD. To our knowledge, it is the first work to incorporate weight information into the higher-order network analysis to study PM2.5 transport.
AB - Specification of PM2.5 transmission characteristics is important for pollution control, policymaking and prediction. In this paper, we propose weights for motif instances, thereby to implement a weighted higher-order clustering algorithm for a weighted, directed PM2.5 network in the Yangtze River Delta (YRD) of China. The weighted, directed network we create in this paper includes information on meteorological conditions of wind speed and wind direction, plus data on geographic distance and PM2.5 concentrations. We aim to reveal PM2.5 mobility between cities in the YRD. Major potential PM2.5 contributors and closely interacted clusters are identified in the network of 178 air quality stations in the YRD. To our knowledge, it is the first work to incorporate weight information into the higher-order network analysis to study PM2.5 transport.
KW - Closely interacted clusters
KW - Major potential PM contributors
KW - PM transport
KW - Weighted higher-order clustering algorithm
KW - Weights for motif instances
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U2 - 10.1016/j.physa.2017.12.096
DO - 10.1016/j.physa.2017.12.096
M3 - Article
AN - SCOPUS:85041464240
SN - 0378-4371
VL - 496
SP - 654
EP - 662
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -