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Nonlinear Influence of Land-Use Transition on Carbon Emission Transfer: A Threshold Regression Analysis of the Middle Reaches of the Yangtze River in China

Author

Listed:
  • Qiuyue Xia

    (College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China)

  • Lu Li

    (School of Public Administration and Human Geography, Hunan University of Technology and Business, Changsha 410205, China)

  • Bin Zhang

    (School of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Jie Dong

    (College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China)

Abstract

Land-use transition (LUT) refers to the change in the land-use form corresponding to the regional economic and social development. At different stages of LUT, changes in the land-use scale and structure may lead to carbon source transfer by affecting industrial transfer and carbon sinks, resulting in changes in the total carbon emission transfer (CET) from the land use in the whole region. The clarification of the relationship between LUT and CET is of great importance for the sustainable development of the regional economy and society and the realization of carbon peak and carbon neutrality. In this paper, we firstly conducted a theoretical analysis of the nonlinear relationship between LUT and CET, then took the Middle Reaches of the Yangtze River in China as an example to explore the characteristics of LUT and CET, and finally constructed a threshold regression model to verify their nonlinear relationship. The following main findings were obtained. (1) From 2000 to 2020, profound LUT had occurred in the Middle Reaches of the Yangtze River, with continuous decreases in farmland, substantial increases in construction land, and a first decrease and then increase in forest land; farmland is the main contributor to construction land and forest with a contribution rate exceeding 60%. (2) During the study period, the CET in the Middle Reaches of the Yangtze River exhibited certain regular characteristics. The phase characteristics of the carbon sink changes follow an intensification–moderation–reintensification–remoderation pattern, and those of the carbon source transfer and net carbon emissions follow an intensification–reintensification–moderation–remoderation pattern. In addition, carbon sink changes are far from enough to offset the effect of carbon source transfer. (3) The nonlinear relationship between LUT and CET was confirmed by the threshold effect at the economic development level, industrial optimization level, and technological progress level. The nonlinear relationship between the LUT and the carbon sink changes in the Middle Reaches of the Yangtze River is on the left side of the U-shaped curve and that between the LUT and the carbon source transfer or net carbon emissions is on the left side of the inverted U-shaped curve.

Suggested Citation

  • Qiuyue Xia & Lu Li & Bin Zhang & Jie Dong, 2022. "Nonlinear Influence of Land-Use Transition on Carbon Emission Transfer: A Threshold Regression Analysis of the Middle Reaches of the Yangtze River in China," Land, MDPI, vol. 11(9), pages 1-24, September.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:9:p:1531-:d:911776
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    References listed on IDEAS

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    1. Ligang Lyu & Zhoubing Gao & Hualou Long & Xiaorui Wang & Yeting Fan, 2021. "Farmland Use Transition in a Typical Farming Area: The Case of Sihong County in the Huang-Huai-Hai Plain of China," Land, MDPI, vol. 10(4), pages 1-16, March.
    2. Hualou Long & Yingnan Zhang & Li Ma & Shuangshuang Tu, 2021. "Land Use Transitions: Progress, Challenges and Prospects," Land, MDPI, vol. 10(9), pages 1-20, August.
    3. Qunyong Wang, 2015. "Fixed-effect panel threshold model using Stata," Stata Journal, StataCorp LP, vol. 15(1), pages 121-134, March.
    4. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    5. Wu, Haitao & Xu, Lina & Ren, Siyu & Hao, Yu & Yan, Guoyao, 2020. "How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model," Resources Policy, Elsevier, vol. 67(C).
    6. Huang, Junbing & Liu, Qiang & Cai, Xiaochen & Hao, Yu & Lei, Hongyan, 2018. "The effect of technological factors on China's carbon intensity: New evidence from a panel threshold model," Energy Policy, Elsevier, vol. 115(C), pages 32-42.
    7. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    8. Wyckoff, Andrew W. & Roop, Joseph M., 1994. "The embodiment of carbon in imports of manufactured products : Implications for international agreements on greenhouse gas emissions," Energy Policy, Elsevier, vol. 22(3), pages 187-194, March.
    9. Doytch, Nadia & Uctum, Merih, 2016. "Globalization and the environmental impact of sectoral FDI," Economic Systems, Elsevier, vol. 40(4), pages 582-594.
    10. Kuang, Bing & Lu, Xinhai & Zhou, Min & Chen, Danling, 2020. "Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon emissions considered," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    11. Weber, Christopher L. & Peters, Glen P. & Guan, Dabo & Hubacek, Klaus, 2008. "The contribution of Chinese exports to climate change," Energy Policy, Elsevier, vol. 36(9), pages 3572-3577, September.
    12. McGuire, Martin C., 1982. "Regulation, factor rewards, and international trade," Journal of Public Economics, Elsevier, vol. 17(3), pages 335-354, April.
    13. Haoran Yang & Hao Zheng & Hongguang Liu & Qun Wu, 2019. "NonLinear Effects of Environmental Regulation on Eco-Efficiency under the Constraint of Land Use Carbon Emissions: Evidence Based on a Bootstrapping Approach and Panel Threshold Model," IJERPH, MDPI, vol. 16(10), pages 1-20, May.
    14. Lu, Xin-hai & Jiang, Xu & Gong, Meng-qi, 2020. "How land transfer marketization influence on green total factor productivity from the approach of industrial structure? Evidence from China," Land Use Policy, Elsevier, vol. 95(C).
    15. Xia, Chuyu & Chen, Bin, 2020. "Urban land-carbon nexus based on ecological network analysis," Applied Energy, Elsevier, vol. 276(C).
    16. Wang, Han & Lu, Siying & Lu, Bo & Nie, Xin, 2021. "Overt and covert: The relationship between the transfer of land development rights and carbon emissions," Land Use Policy, Elsevier, vol. 108(C).
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