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Spatial Effects of Economic Modernization on Carbon Balance in China

Author

Listed:
  • Nan Huang

    (School of Economics and Management, Nanchang University, Nanchang 330031, China)

  • Chenghao Liu

    (School of Economics and Management, Nanchang University, Nanchang 330031, China)

  • Yaobin Liu

    (School of Economics and Management, Nanchang University, Nanchang 330031, China
    Key Laboratory of Poyang Lake Environment and Resource Utilization, Ministry of Education, School of Resource and Environment, Nanchang University, Nanchang 330031, China)

  • Biagio Fernando Giannetti

    (Laboratory of Production and Environment, Universidade Paulista, São Paulo 04026-002, Brazil)

  • Ling Bai

    (School of Economics and Management, Nanchang University, Nanchang 330031, China)

Abstract

Exploring the impact of economic modernization on carbon balance is an essential endeavor to achieve carbon neutrality and combat climate change. However, the spatial impact of economic modernization on carbon balance remains ambiguous. Therefore, this study aims to explore the spatial spillover effects of agricultural modernization, industrialization, and urbanization on carbon balance during the economic modernization process in China, taking 30 provinces and cities in China as examples from 2010 to 2021. This study utilizes the spatial Durbin model to derive the following results: In the past decade, the carbon balance ratio has shown a fluctuating and decreasing dynamic evolution trend. There is an increase in regions with serious carbon deficits. Further investigation into the spatial spillover effect of carbon balance unveils that for every 1% increase in the carbon balance ratio of a province, neighboring provinces experience a decrease of 0.833%. Additionally, the spatial spillover effects of the three modernizations in China on the carbon balance ratio behave differently. Agricultural modernization and urbanization demonstrate negative spatial spillover effects on the carbon balance in neighboring regions, while industrialization exerts a significant positive spatial spillover effect on the carbon balance of neighboring regions. Regarding control variables, the level of innovation solely contributes to local carbon balance realization without generating a trickle-down effect, whereas infrastructure development operates inversely. At the same time, there are differences in the spatial effects of agricultural modernization and industrialization on the carbon balance between the eastern region and the central and western regions. The study underscores the importance of economic modernization and development processes focusing on fostering synergistic growth between economic and environmental benefits within both local and neighboring areas.

Suggested Citation

  • Nan Huang & Chenghao Liu & Yaobin Liu & Biagio Fernando Giannetti & Ling Bai, 2024. "Spatial Effects of Economic Modernization on Carbon Balance in China," Land, MDPI, vol. 13(5), pages 1-21, April.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:5:p:595-:d:1385819
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    References listed on IDEAS

    as
    1. Chen, Huanyu & Yi, Jizheng & Chen, Aibin & Peng, Duanxiang & Yang, Jieqiong, 2023. "Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model," Energy Policy, Elsevier, vol. 172(C).
    2. Zhang, Yongqiang & Ge, Maosheng & Zhang, Qianwen & Xue, Shaopeng & Wei, Fuqiang & Sun, Hao, 2023. "What did irrigation modernization in China bring to the evolution of water-energy-greenhouse gas emissions?," Agricultural Water Management, Elsevier, vol. 282(C).
    3. Yaohui Liu & Wenyi Liu & Peiyuan Qiu & Jie Zhou & Linke Pang, 2023. "Spatiotemporal Evolution and Correlation Analysis of Carbon Emissions in the Nine Provinces along the Yellow River since the 21st Century Using Nighttime Light Data," Land, MDPI, vol. 12(7), pages 1-19, July.
    4. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    5. Raihan, Asif & Pavel, Monirul Islam & Muhtasim, Dewan Ahmed & Farhana, Sadia & Faruk, Omar & Paul, Arindrajit, 2023. "The role of renewable energy use, technological innovation, and forest cover toward green development: Evidence from Indonesia," Innovation and Green Development, Elsevier, vol. 2(1).
    6. Cheng, Zhonghua & Li, Lianshui & Liu, Jun, 2018. "Industrial structure, technical progress and carbon intensity in China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2935-2946.
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