Understanding the structure and determinants of intercity carbon emissions association network in China. (10th June 2022)

• Record Type: Journal Article
• Authors: Cai, Hechang; Wang, Zilong; Zhu, Yongfeng
• Is Part Of: Journal of cleaner production. Volume 352(2022)
• Publication Date: 2022-06-10
• Subjects: Intercity carbon emissions association network -- Temporal exponential random graph model (TERGM) -- Spatial correlation -- Social network analysis; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.131535
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: It is important to understand the structure of the intercity carbon emissions association network and its determinants in promoting urban carbon emissions reductions and even regional high-quality coordinated development. Using carbon emissions data to depict intercity association, the network is constructed, as we: (1) identify network structure through the indegree, outdegree, pagerank and community detection; (2) take a step further in exploring the determinants using temporal exponential random graph models (TERGM) for dynamic network modeling, compared with previous studies only focusing on network description. The results are as follows: (1) The topology of intercity carbon emissions association network is heterogeneous and hierarchical effect tends to increase gradually. (2) The network is highly spatially coupled, and the boundary of the indegree-outdegree partition is relatively clear. A certain spatial correlation as well as spatial coincidence is shown in the indegree-outdegree partition and the pagerank hierarchy. In addition, the spatial correlation shows the core node carbon emissions correlation, and the first rank is at the core of the network. (3) The motif analysis reveals that reciprocal edges play a significant role in promoting network formation. The network structure effects, actor-attribute effects, dyadic predictors, and time-dependent terms have substantial effects on China intercity carbon emissions association network. Highlights: The carbon emissions can be divided into three stages from 2007 to 2017. The carbon emissions association network is extended to the city perspective. Investigate network structure by degree, pagerank and community analysis. Identifying the network determinants using motif analysis and TERGM.