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Who drives carbon emissions and what emission reduction potential in the resource curse agglomeration: a case of Xinjiang

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Abstract

The primary problem in achieving carbon emission reduction and carbon peak is to identify the key driving factors and emission reduction potential of the industrial sector, especially in resource-cursed regions like Xinjiang. This study aimed to explore the key driving factors and abatement potential of carbon emissions based on the "energy-environment-economy" hybrid input–output model of Xinjiang during 1997–2017. The result showed that: (1) Industrial carbon emissions have experienced three stages: slow growth-rapid growth-stable growth. (2) Demand change effect and energy intensity effect were the determinants of Xinjiang industrial carbon emission change; Capital formation and domestic trade were the biggest drivers of carbon emissions growth; Especially after entering the "new normal",the driving force of imports in Xinjiang's international trade increased gradually over time. (3) The coal-based energy structure was both the biggest obstacle and the best entry point in carbon emission reduction. (4) Of the 28 key industry sectors, heavy industry including the production and supply of electricity and heat (S22), petroleum processing, coking and nuclear fuel processing (S11), chemical industry (S12), metal smelting and rolling (S14), and energy industries had the greatest potential for carbon reduction. The research findings provide scientific decision-making reference for Xinjiang to accurately grasp the carbon emission reduction potential of the industry and formulate a targeted carbon peak action plan.

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Notes

  1. The new normal means that China's economy has entered a new stage different from the high-speed growth period of the past 30 years, which has three characteristics: in terms of speed, it has changed from high-speed growth to medium–high-speed growth; Structural aspect-the economic structure is constantly optimized and upgraded; Power-from factor-driven and investment-driven to innovation-driven (Zheng et al. 2019).

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Acknowledgements

This paper is supported by Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004), The Natural Science Foundation of China (71963030).

Author information

Authors and Affiliations

  1. Vanke School of Public Health, Tsinghua University, Beijing, 100084, China

    Kuiying Gu

  2. School of Tourism, History, and Culture, Yili Cultural and Tourism Integration Research Center, Yili Normal University, Yining, 835000, China

    Min Yan

  3. Mailman School of Public Health, Columbia University, New York, NY, 10032, USA

    Pengyue Dou

  4. State Key Laboratory of Numerical Modelling for Atmosphere Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Liang Zhao

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  1. Kuiying Gu
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  2. Min Yan
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  3. Pengyue Dou
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  4. Liang Zhao
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Contributions

Kuiying Gu initiated the study. Kuiying Gu, Min Yan and Pengyue Dou performed the statistical analysis. Kuiying Gu drafted the paper. Kuiying Gu, Min Yan, Pengyue Dou and Liang Zhao revised the paper. All authors read the final version of the manuscript and approved the submission.

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Correspondence to Kuiying Gu.

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Appendix

Appendix

Table 2

Table 2 Industry consolidation comparison table
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Table 3

Table 3 Conversion factors of energy carbon emissions
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Table 4

Table 4 Decomposition of driving factors of carbon dioxide emission of sub industries in Xinjiang from 1997 to 2002 Unit: MT
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Table 5

Table 5 Decomposition of driving factors of carbon dioxide emission of sub industries in Xinjiang from 2002 to 2007 Unit: MT
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Table 6

Table 6 Decomposition of driving factors of carbon dioxide emission of sub industries in Xinjiang from 2007 to 2012 Unit: MT
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Table 7

Table 7 Decomposition of change factors of carbon dioxide emission of sub industries in Xinjiang from 2012 to 2017 Unit: MT
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Gu, K., Yan, M., Dou, P. et al. Who drives carbon emissions and what emission reduction potential in the resource curse agglomeration: a case of Xinjiang. Environ Sci Pollut Res 30, 100403–100430 (2023). https://doi.org/10.1007/s11356-023-29247-5

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