Convergence of carbon intensity in the Yangtze River Delta, China. (February 2017)

• Record Type: Journal Article
• Authors: Li, Jianbao; Huang, Xianjin; Yang, Hong; Chuai, Xiaowei; Wu, Changyan
• Is Part Of: Habitat international. Volume 60(2017)
• Page Start: 58
• Page End: 68
• Publication Date: 2017-02
• Subjects: Carbon intensity -- Convergence -- Spatial character -- Spatial panel data models -- Yangtze River Delta -- China; Human settlements -- Periodicals; 307
• DOI: 10.1016/j.habitatint.2016.12.012
• Languages: English
• ISSNs: 0197-3975

Abstract

Abstract: As China's industrialization and urbanization have grown rapidly in recent years, China's CO2 emissions rose from 3405.1799 Mt to 10, 249.4630 Mt from 2000 to 2013, and it has reached the highest levels in the word since 2006. Chinese government has emphasized the importance of reducing carbon emissions and set the target of reducing carbon intensity to 60–65% of 2005 levels by 2030. Investigating the convergence of carbon intensity can identify the convergence rate, which is helpful in guiding allocations of carbon intensity reduction. The Yangtze River Delta is one of the key carbon emission regions in China, with higher urbanization levels and larger carbon emissions; thus, we employed prefecture-level panel data derived from grid data between 2000 and 2010 to examine whether the convergence of carbon intensity exists across prefecture-level cities in the Yangtze River Delta. Spatial panel data models were utilized to investigate β-convergence of carbon intensity. The results indicated that carbon intensity showed divergence during 2002–2004 and σ-convergence over other periods (2000–2002 and 2004–2010). Carbon intensity exhibited stochastic convergence, indicating that the shocks to carbon intensity relative to the average level of carbon intensity are only transitory. There was a spatial spillover effect and β-convergence of carbon intensity, suggesting that prefecture-level cities with higher carbon intensity would decrease rapidly in the Yangtze River Delta. Our results highlight the importance of considering the present state of carbon intensity, spatial factors, and socioeconomic factors such as industrial structure and economic levels during allocation planning for reducing carbon intensity. Highlights: Both stochastic convergence and β-convergence of carbon intensity existed in the Yangtze River Delta during 2000–2010. The convergence of carbon intensity was influenced by industrial structure, GDP per capita and spatial factors. Policies for reducing carbon intensity in the Yangtze River Delta are proposed.