IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i7p1317-d1683997.html
   My bibliography  Save this article

Can the Coordinated Development of Land Urbanization and Population Urbanization Promote Carbon Emission Efficiency? A Multi-Scale Heterogeneity Analysis in China

Author

Listed:
  • Hanlong Gu

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
    National Engineering Research Center for Efficient Use of Soil and Fertilizer, Shenyang 110866, China)

  • Qi Liu

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
    National Engineering Research Center for Efficient Use of Soil and Fertilizer, Shenyang 110866, China)

  • Ming Cheng

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
    National Engineering Research Center for Efficient Use of Soil and Fertilizer, Shenyang 110866, China)

  • Chongyang Huan

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
    National Engineering Research Center for Efficient Use of Soil and Fertilizer, Shenyang 110866, China)

  • Bingyi Wang

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
    National Engineering Research Center for Efficient Use of Soil and Fertilizer, Shenyang 110866, China)

  • Jiaqian Wu

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
    National Engineering Research Center for Efficient Use of Soil and Fertilizer, Shenyang 110866, China)

Abstract

Coordinating development of land urbanization and population urbanization (CDLUPU) to enhance carbon emission efficiency ( CEE ) is a critical challenge for developing countries experiencing accelerated urbanization. The coupled coordination model and super efficiency SBM are employed to estimate the levels of CDLUPU and CEE across 276 prefecture-level cities from 2010 to 2021. Furthermore, we utilize kernel density estimation and Spatial Durbin Model (SDM) to explore the spatio-temporal distribution characteristics and spatial effects. The results indicate that CDLUPU levels exhibited a sustained upward trend with diminishing regional disparities, whereas CEE displayed a pattern of initial growth followed by decline. Spatial analyses revealed a consistent gradient structure for both CDLUPU and CEE , characterized by radiation decay from southeastern coastal hubs toward interior hinterlands. CDLUPU exerts a significant positive direct impact and spatial spillover effect and indicates that the spillover effects on peripheral regions are substantially stronger than local effects. Regional heterogeneity analysis reveals that CDLUPU negatively affects CEE in eastern China, the Yangtze River Delta (YRD) is more pronounced, but it positively impacts central and western China, as well as Beijing–Tianjin–Hebei (BTH) and Chengdu–Chongqing (CY). Regarding indirect effects, eastern China shows significant positive impact on CEE , and similarly in the YRD. However, central China exhibits a negative effect, whereas BTH shows the opposite trend. Western China and CY show statistically insignificant results. This study offers policy insights for China to coordinate new urbanization strategy and achieve the “dual carbon goal”.

Suggested Citation

  • Hanlong Gu & Qi Liu & Ming Cheng & Chongyang Huan & Bingyi Wang & Jiaqian Wu, 2025. "Can the Coordinated Development of Land Urbanization and Population Urbanization Promote Carbon Emission Efficiency? A Multi-Scale Heterogeneity Analysis in China," Land, MDPI, vol. 14(7), pages 1-26, June.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:7:p:1317-:d:1683997
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/14/7/1317/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/14/7/1317/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liangen Zeng & Haiyan Lu & Yenping Liu & Yang Zhou & Haoyu Hu, 2019. "Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015," Energies, MDPI, vol. 12(16), pages 1-21, August.
    2. Tone, Kaoru & Sahoo, Biresh K., 2004. "Degree of scale economies and congestion: A unified DEA approach," European Journal of Operational Research, Elsevier, vol. 158(3), pages 755-772, November.
    3. Sun, J. W., 2005. "The decrease of CO2 emission intensity is decarbonization at national and global levels," Energy Policy, Elsevier, vol. 33(8), pages 975-978, May.
    4. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    5. Wang, Yuan & Li, Li & Kubota, Jumpei & Han, Rong & Zhu, Xiaodong & Lu, Genfa, 2016. "Does urbanization lead to more carbon emission? Evidence from a panel of BRICS countries," Applied Energy, Elsevier, vol. 168(C), pages 375-380.
    6. Huang, Jing & Han, Wenjing & Zhang, Zhengfeng & Ning, Shanshan & Zhang, Xiaoling, 2024. "The decoupling relationship between land use efficiency and carbon emissions in China: An analysis using the Socio-Ecological Systems (SES) framework," Land Use Policy, Elsevier, vol. 138(C).
    7. Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
    8. Xing, Peixue & Wang, Yanan & Ye, Tao & Sun, Ying & Li, Qiao & Li, Xiaoyan & Li, Meng & Chen, Wei, 2024. "Carbon emission efficiency of 284 cities in China based on machine learning approach: Driving factors and regional heterogeneity," Energy Economics, Elsevier, vol. 129(C).
    9. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
    10. Hanlong Gu & Yiying Liu & Fengkui Qian & Qiubing Wang & Xiuru Dong, 2021. "An Empirical Analysis of the Factors Affecting Farmer Satisfaction Under the China Link Policy," SAGE Open, , vol. 11(2), pages 21582440211, June.
    11. Lianshui Li & Yang Cai & Liang Liu, 2019. "Research on the Effect of Urbanization on China’s Carbon Emission Efficiency," Sustainability, MDPI, vol. 12(1), pages 1-16, December.
    12. Quah, Danny T, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," Journal of Economic Growth, Springer, vol. 2(1), pages 27-59, March.
    13. Zhou, Di & Huang, Qing & Chong, Zhaohui, 2022. "Analysis on the effect and mechanism of land misallocation on carbon emissions efficiency: Evidence from China," Land Use Policy, Elsevier, vol. 121(C).
    14. 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. 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.
    2. Xian’En Wang & Shimeng Wang & Xipan Wang & Wenbo Li & Junnian Song & Haiyan Duan & Shuo Wang, 2019. "The Assessment of Carbon Performance under the Region-Sector Perspective based on the Nonparametric Estimation: A Case Study of the Northern Province in China," Sustainability, MDPI, vol. 11(21), pages 1-23, October.
    3. Zhang, Wei & Liu, Xuemeng & Wang, Die & Zhou, Jianping, 2022. "Digital economy and carbon emission performance: Evidence at China's city level," Energy Policy, Elsevier, vol. 165(C).
    4. Silu Wang & Shunyi Li, 2025. "Spatiotemporal Evolution and Driving Factors of Coupling Coordination Between Carbon Emission Efficiency and Carbon Balance in the Yellow River Basin," Sustainability, MDPI, vol. 17(13), pages 1-33, June.
    5. Haiyan Luo & Xiaoe Qu, 2022. "Spatiotemporal Evolution Trends of Urban Total Factor Carbon Efficiency under the Dual-Carbon Background," Land, MDPI, vol. 12(1), pages 1-19, December.
    6. Fan, Di & Peng, Bo & Wu, Jianxin & Zhang, ZhongXiang, 2024. "The convergence of total-factor energy efficiency across Chinese cities: A distribution dynamics approach," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 406-416.
    7. Shen, Neng & Peng, Hui & Wang, Qunwei, 2021. "Spatial dependence, agglomeration externalities and the convergence of carbon productivity," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    8. Shi, Xunpeng & Yu, Jian & Cheong, Tsun Se, 2020. "Convergence and distribution dynamics of energy consumption among China's households," Energy Policy, Elsevier, vol. 142(C).
    9. Minyoung Yang & Jinsoo Kim, 2022. "A Critical Review of the Definition and Estimation of Carbon Efficiency," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    10. Jie Zhang & Zhencheng Xing & Jigan Wang, 2016. "Analysis of CO 2 Emission Performance and Abatement Potential for Municipal Industrial Sectors in Jiangsu, China," Sustainability, MDPI, vol. 8(7), pages 1-15, July.
    11. Kounetas, Konstantinos & Zervopoulos, Panagiotis D., 2019. "A cross-country evaluation of environmental performance: Is there a convergence-divergence pattern in technology gaps?," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1136-1148.
    12. Ling, Yantao & Xia, Senmao & Cao, Mengqiu & He, Kerun & Lim, Ming K. & Sukumar, Arun & Yi, Huiyong & Qian, Xiaoduo, 2021. "Carbon emissions in China's thermal electricity and heating industry: an input-output structural decomposition analysis," LSE Research Online Documents on Economics 112930, London School of Economics and Political Science, LSE Library.
    13. Feng Dong & Chang Qin & Xiaoyun Zhang & Xu Zhao & Yuling Pan & Yujin Gao & Jiao Zhu & Yangfan Li, 2021. "Towards Carbon Neutrality: The Impact of Renewable Energy Development on Carbon Emission Efficiency," IJERPH, MDPI, vol. 18(24), pages 1-23, December.
    14. You, Jianmin & Zhang, Wei, 2022. "How heterogeneous technological progress promotes industrial structure upgrading and industrial carbon efficiency? Evidence from China's industries," Energy, Elsevier, vol. 247(C).
    15. Kounetas, Kostas & Zervopoulos, Panagiotis, 2017. "Annex I and non-Annex I countries’productive performance revisited using a generalized directional distance function under a metafrontier framework: Is there any convergence-divergence pattern for tec," MPRA Paper 80904, University Library of Munich, Germany.
    16. Juanjuan Tian & Xiaoqian Song & Jinsuo Zhang, 2022. "Spatial-Temporal Pattern and Driving Factors of Carbon Efficiency in China: Evidence from Panel Data of Urban Governance," Energies, MDPI, vol. 15(7), pages 1-24, March.
    17. Jianxin Wu & Chunbo Ma, 2019. "The Convergence of China’s Marginal Abatement Cost of CO2: An Emission-Weighted Continuous State Space Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(4), pages 1099-1119, April.
    18. Chenxu Liu & Ruien Tang & Yaqi Guo & Yuhan Sun & Xinyi Liu, 2022. "Research on the Structure of Carbon Emission Efficiency and Influencing Factors in the Yangtze River Delta Urban Agglomeration," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    19. Li-Ming Xue & Zhi-Xue Zheng & Shuo Meng & Mingjun Li & Huaqing Li & Ji-Ming Chen, 2022. "Carbon emission efficiency and spatio-temporal dynamic evolution of the cities in Beijing-Tianjin-Hebei Region, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 7640-7664, June.
    20. Gianfranco DI VAIO & Michele BATTISTI, 2010. "A Spatially-Filtered Mixture of Beta-Convergence Regression for EU Regions, 1980-2002," Regional and Urban Modeling 284100013, EcoMod.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:14:y:2025:i:7:p:1317-:d:1683997. 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.