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Carbon dioxide emissions, urbanization level, and industrial structure: empirical evidence from North China

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Abstract

This paper aims to examine the nexus among carbon dioxide (CO2) emissions, urbanization level and industrial structure in North China over the period 2004–2019, according to an expanded Cobb-Douglas production function. The panel econometric techniques are employed to complete the empirical analysis, including cross-sectional correlation test, panel unit root test, panel co-integration test, and panel Granger causality test. The empirical results support the long-term equilibrium relationship among CO2 emissions, urbanization level and industrial structure in North China, and the urbanization level contributes most to CO2 emissions, followed by fossil energy consumption. Furthermore, the bidirectional causality between CO2 emissions and urbanization level and unidirectional causality from industrial structure to CO2 emissions are found in North China, indicating that urbanization level and industrial structure have significant impacts on CO2 emissions. Finally, according to the empirical findings, several policy suggestions are proposed for the purpose of reducing CO2 emissions in North China.

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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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Acknowledgements

Thanks are due to the North China Electric Power University Library for providing detailed reference for our research, and this paper was support by the National Key R&D Program of China (2020YFB1707800).

Funding

This study is supported by National Key R&D Program of China (2020YFB1707800).

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Dongxiao Niu guided the research, established the model, and implemented the simulation. Zhuoya Siqin wrote this article. Mingyu Li and Hao Zhen checked the language. Xiaolong Yang collected the data. All authors read and approved the final manuscript.

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Correspondence to Dongxiao Niu.

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Siqin, Z., Niu, D., Li, M. et al. Carbon dioxide emissions, urbanization level, and industrial structure: empirical evidence from North China. Environ Sci Pollut Res 29, 34528–34545 (2022). https://doi.org/10.1007/s11356-021-17373-x

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