Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry
Author(s): |
Zhenshuang Wang
Yanxin Zhou Ning Zhao Tao Wang Zhongsheng Zhang |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 18 January 2022, n. 2, v. 12 |
Page(s): | 201 |
DOI: | 10.3390/buildings12020201 |
Abstract: |
To explore the spatial network structure characteristics and driving effects of carbon emission intensity in China’s construction industry, this paper measures the carbon emission data of China’s construction industry in various provinces from 2006 to 2017 and then combines the modified gravity model and social network analysis method to deeply analyze the spatially associated network structure characteristics and driving effects of the carbon emission intensity in China’s construction industry. The results show that the regional differences of the carbon emissions of the construction industry are significant, and the carbon emission intensity of the construction industry shows a fluctuating trend. The overall network of carbon emission intensity shows an obvious “core-edge” state, and the hierarchical network structure is gradually broken. Economically developed provinces generally play a leading role in the network and play an intermediary role to guide other provinces to develop together with them. Among the network blocks, most of the blocks play the role of “brokers”. The block with the leading economic development has a strong influence on the other blocks. The increase in network density and the decrease in network hierarchy and network efficiency will reduce the construction carbon emission intensity. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10657722 - Published on:
17/02/2022 - Last updated on:
01/06/2022