期刊
JOURNAL OF CLEANER PRODUCTION
卷 262, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.121193
关键词
Electricity sector; Carbon emissions; Spatial correlation; Social network analysis
资金
- National Natural Science Foundation of China [71625005, 71573119]
This paper constructs a spatial association network of carbon emissions from the electricity sector in Chinese provinces by using an improved gravity model and the data on carbon emissions in 2005-2016 from the electricity sector. Social network analysis and the quadratic assignment procedure were used to analyse spatial association characteristics and influential factors. It is found that the overall structure of the carbon emission spatial network in China's electricity sector was relatively stable and provinces were closely linked. Shanghai, Jiangsu, Tianjin, Beijing and Zhejiang all played a leading role in the network centre position. Spatial adjacency relationships and per capita GDP were positively correlated with carbon emissions from the electricity sector, but electricity intensity and industrial structure were negatively correlated. Urbanisation level does not affect the spatial correlation network of carbon emissions from electricity sector. Based on the results, some policy recommendations are finally made for reducing the carbon emissions from the electricity sector in China. (C) 2020 Elsevier Ltd. All rights reserved.
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