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Article

Spatial Association and Effect Evaluation of CO2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis

1
School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
2
Department of Ecosystem Science and Management, Pennsylvania State University, Forest Resources Building, University Park, PA 16802, USA
3
College of Engineering, University of California Berkeley, Berkeley, CA 94720, USA
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(1), 1; https://doi.org/10.3390/su11010001
Received: 29 October 2018 / Revised: 11 December 2018 / Accepted: 17 December 2018 / Published: 20 December 2018
(This article belongs to the Section Sustainable Urban and Rural Development)
Urban agglomeration, an established urban spatial pattern, contributes to the spatial association and dependence of city-level CO2 emission distribution while boosting regional economic growth. Exploring this spatial association and dependence is conducive to the implementation of effective and coordinated policies for regional level CO2 reduction. This study calculated CO2 emissions from 2005–2016 in the Chengdu-Chongqing urban agglomeration with the IPAT model, and empirically explored the spatial structure pattern and association effect of CO2 across the area leveraged by the social network analysis. The findings revealed the following: (1) The spatial structure of CO2 emission in the area is a complex network pattern, and in the sample period, the CO2 emission association relations increased steadily and the network stabilization remains strengthened; (2) the centrality of the cities in this area can be categorized into three classes: Chengdu and Chongqing are defined as the first class, the second class covers Deyang, Mianyang, Yibin, and Nanchong, and the third class includes Zigong, Suining, Meishan, and Guangan—the number of cities in this class is on the rise; (3) the network is divided into four subgroups: the area around Chengdu, south Sichuan, northeast Sichuan, and west Chongqing where the spillover effect of CO2 is greatest; and (4) the higher density of the global network of CO2 emission considerably reduces regional emission intensity and narrows the differences among regions. Individual networks with higher centrality are also found to have lower emission intensity. View Full-Text
Keywords: Chengdu-Chongqing urban agglomeration; CO2 emission; spatial association; effect; social network Chengdu-Chongqing urban agglomeration; CO2 emission; spatial association; effect; social network
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MDPI and ACS Style

Song, J.; Feng, Q.; Wang, X.; Fu, H.; Jiang, W.; Chen, B. Spatial Association and Effect Evaluation of CO2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis. Sustainability 2019, 11, 1. https://doi.org/10.3390/su11010001

AMA Style

Song J, Feng Q, Wang X, Fu H, Jiang W, Chen B. Spatial Association and Effect Evaluation of CO2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis. Sustainability. 2019; 11(1):1. https://doi.org/10.3390/su11010001

Chicago/Turabian Style

Song, Jinzhao, Qing Feng, Xiaoping Wang, Hanliang Fu, Wei Jiang, and Baiyu Chen. 2019. "Spatial Association and Effect Evaluation of CO2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis" Sustainability 11, no. 1: 1. https://doi.org/10.3390/su11010001

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