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Club convergence and spatial distribution dynamics of carbon intensity in China’s construction industry

Qiang Du (), Min Wu (), Yadan Xu (), Xinran Lu (), Libiao Bai () and Ming Yu ()
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Qiang Du: Chang’ an Univ
Min Wu: Chang’ an Univ
Yadan Xu: Chang’ an Univ
Xinran Lu: Chang’ an Univ
Libiao Bai: Chang’ an Univ
Ming Yu: Chang’ an Univ

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 94, issue 2, 519-536

Abstract: Abstract Climate change caused by carbon emissions continuously threatens sustainable development. Due to China’s immense territory, there are remarkable regional differences in carbon emissions. The construction industry, which has strong internal industrial differences, further leads to carbon emission disparity in China. Policymakers should consider spatial effects and attempt to eliminate carbon emission inequality to promote the sustainable development of the construction industry and realize emission reduction targets. Based on the classic Markov chain and spatial Markov chain, this paper investigates the club convergence and spatial distribution dynamics of China’s carbon intensity in the construction industry from 2005 to 2014. The results show that the provincial carbon intensity in the construction industry is characterized by “convergence clubs” during the research period, and very low-level and very high-level convergence clubs have strong stability. Moreover, the carbon intensity class transitions of provinces tend to be consistent with that of their neighbors. Furthermore, the transition of carbon intensity types is highly influenced by their regional backgrounds. The provinces with high carbon emissions have a negative influence on their neighbors, whereas the provinces with low carbon emissions have a positive influence. These analyses provide a spatial interpretation to the “club convergence” of carbon intensity.

Keywords: Club convergence; Spatial distribution; Carbon intensity; Markov chain; Spatial Markov chain (search for similar items in EconPapers)
Date: 2018
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