Multi-scale analysis of the energy metabolic processes in the Beijing–Tianjin–Hebei (Jing-Jin-Ji) urban agglomeration

• Published in: Ecological modelling 2018-02, Vol.369, p.66-76
• Main Authors: Hao, Yan, Zhang, Menghui, Zhang, Yan, Fu, Chenling, Lu, Zhongming
• Format: Article
• Language: English
• Subjects: Ecological network analysis; Jing-Jin-Ji; Multi-scale analysis; Urban agglomeration; Urban energy metabolism
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2017.12.012

•We constructed a multi-scale urban energy metabolic network model.•We analyzed the Beijing–Tianjin–Hebei agglomeration’s energy metabolism at two scales.•We describe the Beijing–Tianjin–Hebei structural and functional attributes. The area of the Beijing–Tianjin–Hebei (Jing-Jin-Ji) region is about 2.25% of China land area. But the energy consumption and carbon emission of Jing-Jin-Ji region account for more than 10% of China’s total consumption and emissions. To reduce the region’s energy consumption and carbon emission, we studied energy flow process in this region. The previous research on energy flow is concentrated on a single scale, with little multi-scale integration. In this study, based on framework of urban metabolism, we used ecological network analysis method to study the region’s energy metabolism and ecological relationship among nodes at two scales: in 3-node and 13-node models of the agglomeration. The integral (direct + indirect) energy consumption in the 3-node model first increased, then decreased, from 2002 to 2010; consumption in the 13-node model first decreased, then increased. The direct and integral energy flows showed that Hebei provided the most energy to Beijing in the 3-node network; in the 13-node network, Tangshan provided the most energy to the other 12 cities. In terms of the ecological relationships among the nodes, the 13-node model showed proportionally more competition relationships than the 3-node model. The relationships among Beijing, Tianjin, and Hebei were dominated by exploitation and control. Based on the analysis of flow and relationship, the importance of multi-scale model research is verified, which serves different research objectives and helps researchers choose the appropriate scale model under different data acquisition precision and research depth.