Abstract
The essential to achieving the 2060 carbon neutrality target in China lies in the performance of the construction industry. Decoupling economic development from CO2 emissions is the main strategy for reducing emissions in the construction industry. This paper is based on panel data for China and its 30 provinces during 2009–2019. A Tapio decoupling model is constructed to analyze the decoupling state of economic development and CO2 emissions in the construction industry. The logarithmic mean Divisia index model is constructed to continue the decomposition of the drivers of the decoupling state and CO2 emissions. The results show that (1) the economic development level of most provinces is positively correlated with their CO2 emissions; (2) Beijing and Jiangsu reach the ideal strong decoupling state, and Heilongjiang has the worst decoupling state. The same type of decoupling state shows a certain aggregation phenomenon in space; (3) economic output plays a critical role in promoting CO2 emissions and decoupling of the construction industry in China and the provinces. The main driver of decoupling is indirect carbon intensity; (4) energy intensity has a greater impact on CO2 emissions reduction in regions with more developed economic levels. Understanding the drivers of the decoupling state in China’s construction industry provides a valuable basis for energy efficiency and emission reduction efforts in China and other countries.
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Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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The authors appreciate the financial support of the National Natural Science Foundation of China [grant number 72001121].
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Shenghua Yan: methodology, investigation, data curation, software, formal analysis, and writing—original draft. Weigong Chen: project administration, supervision and validation, funding acquisition, and writing—review and editing.
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Yan, S., Chen, W. Analysis of the decoupling state and driving forces of China’s construction industry under the carbon neutrality target. Environ Sci Pollut Res 29, 78457–78471 (2022). https://doi.org/10.1007/s11356-022-21266-y
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DOI: https://doi.org/10.1007/s11356-022-21266-y