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Influential Nodes Identification in the Air Pollution Spatial Correlation Weighted Networks and Collaborative
Feipeng Guo1,2, Zifan Wang1,2, Shaobo Ji3
1School of Management and E-Business, Zhejiang Gongshang University, Hangzhou 310018, China.
Summary
China
Area of Science:
- Environmental Science
- Atmospheric Chemistry
- Urban Planning
Background:
- China's 14th Five-Year Plan prioritizes joint air pollution control and greenhouse gas reduction.
- Green and low-carbon development is a key driver for environmental policy.
Purpose of the Study:
- To analyze air pollution spatial correlations in major Chinese urban agglomerations.
- To identify influential cities for targeted air pollution control strategies.
- To propose policy recommendations based on spatial linkages.
Main Methods:
- Construction of air pollution spatial correlation weighted networks for three major urban agglomerations.
- Application of the local-and-global-influence for weighted network (W_LGI) method to identify influential nodes (cities).
- Analysis of intra-city air pollution networks within identified influential cities.
Main Results:
- Identification of influential cities with central positions in air pollution networks.
- Demonstration that influential nodes exhibit strong spatial pollution associations and pollutant transmission capabilities.
- Confirmation of the importance of spatial linkages in air pollution dynamics.
Conclusions:
- Targeting influential cities can enhance air pollution control efficiency.
- Policy suggestions derived from spatial linkage analysis support green development.
- Effective air pollution management contributes to achieving carbon neutrality goals.
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