The Spatial Relationship between CO2 Emissions and Economic Growth in the Construction Industry: Based on the Tapio Decoupling Model and STIRPAT Model

被引:8
|
作者
Li, Long [1 ]
Li, Yinting [1 ]
机构
[1] Harbin Univ Commerce, Sch Energy & Civil Engn, Harbin 150028, Peoples R China
关键词
construction industry; CO2; emissions; economic growth; spatial econometric model; ENVIRONMENTAL KUZNETS CURVE; CARBON-DIOXIDE EMISSIONS; ENERGY; DECOMPOSITION; HYPOTHESIS; INTENSITY;
D O I
10.3390/su15010528
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Studying the relationship between carbon emissions in the construction industry and economic growth in the construction industry is of great significance for the sustainable development of the industry and the country. This paper aims to analyze the decoupling status of various provinces, the spatial relationship between carbon emissions and economic growth, and provide targeted suggestions for promoting the green and sustainable development of the construction industry. The relevant panel data on CO2 emissions from the construction industry in 30 provinces and municipalities during China's "Thirteenth Five-Year Plan" period was collected and organized in this paper. A Tapio decoupling model and a spatial econometric model which is combined with the STIRPAT model are used in the paper. The research indicates that as a whole, China's construction industry is in a state of weak decoupling, and actions to reduce carbon dioxide emissions, bear fruit, and energy efficiency have been improved; the economic growth still promotes CO2 emissions and the relationship between the two is still in the rising phase of the CKC (Carbondioxide Kuznets Curve) curve; economic growth has significant spatial spillover effects, and economic growth in other regions will inhibit carbon dioxide emissions in the region, but its effect is lower than the promotion effect of direct effects. At this stage, the employee factor and technology development level also promote carbon dioxide emissions, and the spatial spillover effect is small. At the same time, the degree of influence of each influencing factor varies in different decoupling provinces.
引用
收藏
页数:12
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