IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i5p634-d1390460.html
   My bibliography  Save this article

Spatiotemporal Pattern and Spatial Convergence of Land Use Carbon Emission Efficiency in the Pan-Pearl River Delta: Based on the Difference in Land Use Carbon Budget

Author

Listed:
  • Zhenggen Fan

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

  • Wentong Xia

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

  • Hu Yu

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Ji Liu

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

  • Binghua Liu

    (College of City Construction, Jiangxi Normal University, Nanchang 330022, China)

Abstract

Research on land use carbon emission efficiency (LUCEE) in the Pan-Pearl River Delta (PPRD) can aid in formulating regional differentiated carbon reduction strategies. In this work, the inversion of carbon emissions using night-time light (NTL) data and the modified Carnegie Ames Stanford Approach (CASA) model were used to measure the net carbon emissions from land use (NCELU). On this basis, the SBM-undesirable model was used to assess the LUCEE. Additionally, the exploratory spatial data analysis (ESDA), Dagum Gini coefficient, and spatial convergence model were further introduced to analyze the spatial correlation, regional differences, and convergence trend of the LUCEE. Findings indicate that: (1) The NCELU showed an increasing fluctuation. During the period of 2006–2020, the NCELU increased from −168.58 million tons to −724.65 million tons. (2) The LUCEE exhibited a three-phase fluctuating downward trend of “decrease–rise–decrease”. The LUCEE first decreased from 0.612 in 2006 to 0.544 in 2008, then gradually increased to 0.632 in 2016, and finally decreased to 0.488 in 2020. Spatially, the LUCEE manifested a distribution characteristic of “high in the north and south, low in the middle”, with distinct spatial clustering features. (3) The overall Gini coefficient in the study period increased from 0.1819 to 0.2461. The primary contributor to the overall difference over the entire sample period was hypervariable density. (4) The PPRD and its various subregions displayed significant features of absolute and conditional β convergence. The speed of regional convergence from fastest to slowest was central > west > east, with the absolute convergence speeds of 0.0505, 0.0360, and 0.0212, respectively. Finally, policy recommendations are proposed to achieve regional carbon neutrality for the PPRD.

Suggested Citation

  • Zhenggen Fan & Wentong Xia & Hu Yu & Ji Liu & Binghua Liu, 2024. "Spatiotemporal Pattern and Spatial Convergence of Land Use Carbon Emission Efficiency in the Pan-Pearl River Delta: Based on the Difference in Land Use Carbon Budget," Land, MDPI, vol. 13(5), pages 1-27, May.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:5:p:634-:d:1390460
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/5/634/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/13/5/634/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jing Wang & Liang Feng & Paul I. Palmer & Yi Liu & Shuangxi Fang & Hartmut Bösch & Christopher W. O’Dell & Xiaoping Tang & Dongxu Yang & Lixin Liu & ChaoZong Xia, 2020. "Large Chinese land carbon sink estimated from atmospheric carbon dioxide data," Nature, Nature, vol. 586(7831), pages 720-723, October.
    2. Luc Anselin & Sanjeev Sridharan & Susan Gholston, 2007. "Using Exploratory Spatial Data Analysis to Leverage Social Indicator Databases: The Discovery of Interesting Patterns," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 82(2), pages 287-309, June.
    3. Wu, Yinyin & Wang, Ping & Liu, Xin & Chen, Jiandong & Song, Malin, 2020. "Analysis of regional carbon allocation and carbon trading based on net primary productivity in China," China Economic Review, Elsevier, vol. 60(C).
    4. Jing Wang & Liang Feng & Paul I. Palmer & Yi Liu & Shuangxi Fang & Hartmut Bösch & Christopher W. O’Dell & Xiaoping Tang & Dongxu Yang & Lixin Liu & ChaoZong Xia, 2020. "Publisher Correction: Large Chinese land carbon sink estimated from atmospheric carbon dioxide data," Nature, Nature, vol. 588(7837), pages 19-19, December.
    5. Dagum, Camilo, 1997. "A New Approach to the Decomposition of the Gini Income Inequality Ratio," Empirical Economics, Springer, vol. 22(4), pages 515-531.
    6. Liu, Xin & Wang, Ping & Song, Hang & Zeng, Xiaoying, 2021. "Determinants of net primary productivity: Low-carbon development from the perspective of carbon sequestration," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    7. Qiaowen Lin & Lu Zhang & Bingkui Qiu & Yi Zhao & Chao Wei, 2021. "Spatiotemporal Analysis of Land Use Patterns on Carbon Emissions in China," Land, MDPI, vol. 10(2), pages 1-13, February.
    8. Kun Ge & Shan Zou & Danling Chen & Xinhai Lu & Shangan Ke, 2021. "Research on the Spatial Differences and Convergence Mechanism of Urban Land Use Efficiency under the Background of Regional Integration: A Case Study of the Yangtze River Economic Zone, China," Land, MDPI, vol. 10(10), pages 1-20, October.
    9. Haoran Yang & Qun Wu, 2019. "Land Use Eco-Efficiency and Its Convergence Characteristics Under the Constraint of Carbon Emissions in China," IJERPH, MDPI, vol. 16(17), pages 1-17, August.
    10. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luyi Qiu & Kunying Niu & Wei He & Yaqi Hu, 2023. "Two Contribution Paths of Carbon Neutrality: Terrestrial Ecosystem Carbon Sinks and Anthropogenic Carbon Emission Reduction—A Case of Chongqing, China," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    2. Mengcheng Li & Haimeng Liu & Shangkun Yu & Jianshi Wang & Yi Miao & Chengxin Wang, 2022. "Estimating the Decoupling between Net Carbon Emissions and Construction Land and Its Driving Factors: Evidence from Shandong Province, China," IJERPH, MDPI, vol. 19(15), pages 1-26, July.
    3. Hui Wen & Yi Li & Zirong Li & Xiaoxue Cai & Fengxia Wang, 2022. "Spatial Differentiation of Carbon Budgets and Carbon Balance Zoning in China Based on the Land Use Perspective," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    4. Shiguang Shen & Chengcheng Wu & Zhenyu Gai & Chenjing Fan, 2023. "Analysis of the Spatiotemporal Evolution of the Net Carbon Sink Efficiency and Its Influencing Factors at the City Level in Three Major Urban Agglomerations in China," IJERPH, MDPI, vol. 20(2), pages 1-18, January.
    5. Rongtian Zhang & Jianfei Lu, 2022. "Spatial–Temporal Pattern and Convergence Characteristics of Provincial Urban Land Use Efficiency under Environmental Constraints in China," IJERPH, MDPI, vol. 19(17), pages 1-15, August.
    6. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    7. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    8. Jie Huang & Zimin Sun & Pengshu Zhong, 2022. "The Spatial Disequilibrium and Dynamic Evolution of the Net Agriculture Carbon Effect in China," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    9. Shiliang Liu & Yuhong Dong & Hua Liu & Fangfang Wang & Lu Yu, 2023. "Review of Valuation of Forest Ecosystem Services and Realization Approaches in China," Land, MDPI, vol. 12(5), pages 1-16, May.
    10. Liu, Shilei & Xia, Jun, 2021. "Forest harvesting restriction and forest restoration in China," Forest Policy and Economics, Elsevier, vol. 129(C).
    11. Yingshi Shang & Yanmin Niu & Peng Song, 2023. "Regional Differences and Influencing Factors of Green Innovation Efficiency in China’s 285 Cities," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
    12. Pan, Xunzhang & Ma, Xueqing & Zhang, Yanru & Shao, Tianming & Peng, Tianduo & Li, Xiang & Wang, Lining & Chen, Wenying, 2023. "Implications of carbon neutrality for power sector investments and stranded coal assets in China," Energy Economics, Elsevier, vol. 121(C).
    13. Zhen Shi & Huinan Huang & Yingju Wu & Yung-Ho Chiu & Shijiong Qin, 2020. "Climate Change Impacts on Agricultural Production and Crop Disaster Area in China," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    14. Xuedong Liang & Jiacheng Li & Gengxuan Guo & Sipan Li & Qunxi Gong, 2023. "Urban water resource utilization efficiency based on SBM-undesirable–Gini coefficient–kernel density in Gansu Province, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 13015-13034, November.
    15. Bishan Wu, 2024. "Low-carbon development mechanism of energy industry from the perspective of carbon neutralization," Energy & Environment, , vol. 35(2), pages 628-643, March.
    16. Zhang, Hongji & Ding, Tao & Sun, Yuge & Huang, Yuhan & He, Yuankang & Huang, Can & Li, Fangxing & Xue, Chen & Sun, Xiaoqiang, 2023. "How does load-side re-electrification help carbon neutrality in energy systems: Cost competitiveness analysis and life-cycle deduction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    17. Zhang, Qian & Cheng, Baodong & Diao, Gang & Tao, Chenlu & Wang, Can, 2023. "Does China's natural forest logging ban affect the stability of the timber import trade network?," Forest Policy and Economics, Elsevier, vol. 152(C).
    18. Wang, Lin & Zhao, Junsan & Lin, Yilin & Chen, Guoping, 2024. "Exploring ecological carbon sequestration advantage and economic responses in an ecological security pattern: A nature-based solutions perspective," Ecological Modelling, Elsevier, vol. 488(C).
    19. Longhui Li & Yue Zhang & Tianjun Zhou & Kaicun Wang & Can Wang & Tao Wang & Linwang Yuan & Kangxin An & Chenghu Zhou & Guonian Lü, 2022. "Mitigation of China’s carbon neutrality to global warming," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    20. Jiang, Jiatong & Hu, Bin & Wang, R.Z. & Deng, Na & Cao, Feng & Wang, Chi-Chuan, 2022. "A review and perspective on industry high-temperature heat pumps," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:13:y:2024:i:5:p:634-:d:1390460. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.