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Prediction and Trend Analysis of Regional Industrial Carbon Emission in China: A Study of Nanjing City

Author

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  • Zhicong Zhang

    (School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing 210023, China)

  • Hao Xie

    (School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing 210023, China
    Zhenjiang Institute for Innovation and Development, Nanjing Normal University, Zhenjiang 212016, China)

  • Jubing Zhang

    (School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing 210023, China)

  • Xinye Wang

    (School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing 210023, China
    Zhenjiang Institute for Innovation and Development, Nanjing Normal University, Zhenjiang 212016, China)

  • Jiayu Wei

    (School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing 210023, China)

  • Xibin Quan

    (School of Energy and Mechanical Engineering, Nanjing Normal University, Nanjing 210023, China)

Abstract

Based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the impact factors of industrial carbon emission in Nanjing were considered as total population, industrial output value, labor productivity, industrialization rate, energy intensity, research and development (R&D) intensity, and energy structure. Among them, the total population, industrial output value, labor productivity, and industrial energy structure played a role in promoting the increase of industrial carbon emissions in Nanjing, and the degree of influence weakened in turn. For every 1% change in these four factors, carbon emissions increased by 0.52%, 0.49%, 0.17% and 0.12%, respectively. The industrialization rate, R&D intensity, and energy intensity inhibited the increase of industrial carbon emissions, and the inhibiting effect weakened in turn. Every 1% change in these three factors inhibited the increase of industrial carbon emissions in Nanjing by 0.03%, 0.07%, and 0.02%, respectively. Then, taking the relevant data of industrial carbon emissions in Nanjing from 2006 to 2020 as a sample, the gray rolling prediction model with one variable and one first-order equation (GRPM (1,1)) forecast and scenario analysis is used to predict the industrial carbon emission in Nanjing under the influence of the pandemic from 2021 to 2030, and the three development scenarios were established as three levels of high-carbon, benchmark and low-carbon, It was concluded that Nanjing’s industrial carbon emissions in 2030 would be 229.95 million tons under the high-carbon development scenario, 226.92 million tons under the benchmark development scenario, and 220.91 million tons under the low-carbon development scenario. It can not only provide data reference for controlling industrial carbon emissions in the future but also provide policy suggestions and development routes for urban planning decision-makers. Finally, it is hoped that this provides a reference for other cities with similar development as Nanjing.

Suggested Citation

  • Zhicong Zhang & Hao Xie & Jubing Zhang & Xinye Wang & Jiayu Wei & Xibin Quan, 2022. "Prediction and Trend Analysis of Regional Industrial Carbon Emission in China: A Study of Nanjing City," IJERPH, MDPI, vol. 19(12), pages 1-23, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7165-:d:836408
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    1. Ran Wang & Hui Ci & Ting Zhang & Yuxin Tang & Jinyuan Wei & Hui Yang & Gefei Feng & Zhaojin Yan, 2023. "Spatial-Temporal Evolution Characteristics of Industrial Carbon Emissions in China’s Most Developed Provinces from 1998–2013: The Case of Guangdong," Energies, MDPI, vol. 16(5), pages 1-21, February.
    2. Ting Zhang & Longqian Chen & Ziqi Yu & Jinyu Zang & Long Li, 2022. "Spatiotemporal Evolution Characteristics of Carbon Emissions from Industrial Land in Anhui Province, China," Land, MDPI, vol. 11(11), pages 1-18, November.
    3. Yong Xiao & Cheng Yong & Wei Hu & Hanyun Wang, 2023. "Factors Influencing Carbon Emissions in High Carbon Industries in the Zhejiang Province and Decoupling Effect Analysis," Sustainability, MDPI, vol. 15(22), pages 1-22, November.
    4. Jiang Zhu & Xiang Li & Huiming Huang & Xiangdong Yin & Jiangchun Yao & Tao Liu & Jiexuan Wu & Zhangcheng Chen, 2023. "Spatiotemporal Evolution of Carbon Emissions According to Major Function-Oriented Zones: A Case Study of Guangdong Province, China," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
    5. Yuan Yuan & Ping Xu & Hui Zhang, 2023. "Spatial Zoning of Carbon Dioxide Emissions at the Intra-City Level: A Case Study of Nanjing, China," IJERPH, MDPI, vol. 20(5), pages 1-19, February.

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