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• W4312224708 abstract "In recent years, air pollution has become one of the main factors harming the livable environment for human beings. Governments have recognized the importance of controlling air pollution and reached a consensus that regional joint control of air pollution is an effective means of dealing with environmental degradation. In this work, we focus on the impact of fine particulate matter and nitrogen compounds on the air quality of 14 prefecture-level cities in China’s Hunan Province using the insights of complex networks, and further propose a joint treatment scheme for these two pollutants. Multiscale temporal networks are constructed based on the height cross-correlation coefficient, which allows us to assess the variable network structures concerning different time scales. We use four network properties to assess the network structures for the pollutants. Through the Jensen-Shannon divergence of the probability distribution of these network attributes, it is found that NO2 affects AQI more in a short time interval than in a longer time interval. The correlation of both NO2 and PM2.5 among the 14 cities in about 15 days can best reflect the air quality in Hunan Province. In addition, instead of NO2, PM2.5 has become the culprit of air pollution in Hunan Province. The co-movement of the pollutants among the 14 cities is significant. The co-movement of the PM2.5 pollutants can last 45 days, while that of NO2 pollutants will gradually decrease over time. Furthermore, by using spectral clustering based on the network node correlation, we classify the 14 cities into five regions and two regions for PM2.5 and NO2, respectively. It provides a feasible implementation guide for the environmental governance of regional cooperation." @default.
• W4312224708 created "2023-01-04" @default.
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• W4312224708 date "2022-12-28" @default.
• W4312224708 modified "2023-10-14" @default.
• W4312224708 title "Correlation Structure and Co-Movement of Hunan Province’s Air Pollution: Evidence from the Multiscale Temporal Networks" @default.
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• W4312224708 doi "https://doi.org/10.3390/atmos14010055" @default.
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