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Polycentricity or monocentricity? A multi-scale assessment of how urban agglomeration structures influence carbon emission performance in China

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  • Zeng, Peng
  • Liang, Liying

Abstract

Global warming driven by persistent carbon emissions has made emission reduction a pressing research focus. Understanding how urban agglomeration spatial structures influence carbon emission performance is essential for developing effective mitigation strategies. This study examines 13 urban agglomerations in China from 2006 to 2020. A two-dimensional framework is proposed to capture spatial structure, encompassing both morphological and functional dimensions. A Geographically and Temporally Weighted Regression model is employed at both the city and county scales. The results indicate that: (1) Spatial morphological structures show a general trend toward monocentricity at both scales. (2) Functional structures become increasingly monocentric patterns at the city scale while remaining relatively stable at the county scale. (3) Carbon emission performance has improved overall, yet interregional disparities have widened. (4) The influence of spatial structure on carbon emission performance shows significant structure type and scale-dependent characteristics. At the city scale, the polycentricity of spatial morphological and functional structures is unstable in its direction of influence and lacks consistency. In contrast, at the county scale, morphological polycentricity continues to inhibit carbon emission performance, while functional polycentricity continues to promote performance enhancement. (5) Most control variables significantly affect carbon performance at city and county scales, but these effects' direction, strength, and temporal pattern vary across scales. These results provide new insights into the spatial mechanisms underlying low-carbon development and offer a theoretical basis for designing targeted emission reduction strategies tailored to varying spatial structures and governance contexts.

Suggested Citation

  • Zeng, Peng & Liang, Liying, 2025. "Polycentricity or monocentricity? A multi-scale assessment of how urban agglomeration structures influence carbon emission performance in China," Energy, Elsevier, vol. 335(C).
    • Handle: RePEc:eee:energy:v:335:y:2025:i:c:s0360544225035674
    DOI: 10.1016/j.energy.2025.137925
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    1. Zhang, Songlin & Miao, Xuaner & Zheng, Haoqing & Chen, Weihong & Wang, Huafeng, 2024. "Spatial functional division in urban agglomerations and carbon emission intensity: New evidence from 19 urban agglomerations in China," Energy, Elsevier, vol. 300(C).
    2. Alex Anas & Richard Arnott & Kenneth A. Small, 1998. "Urban Spatial Structure," Journal of Economic Literature, American Economic Association, vol. 36(3), pages 1426-1464, September.
    3. He, Xiaoping & Yu, Yuxuan & Jiang, Shuo, 2023. "City centrality, population density and energy efficiency," Energy Economics, Elsevier, vol. 117(C).
    4. Teng, Xiangyu & Liu, Fan-peng & Chiu, Yung-ho, 2021. "The change in energy and carbon emissions efficiency after afforestation in China by applying a modified dynamic SBM model," Energy, Elsevier, vol. 216(C).
    5. Meng, Conghui & Du, Xiaoyun & Zhu, Mengcheng & Ren, Yitian & Fang, Kai, 2023. "The static and dynamic carbon emission efficiency of transport industry in China," Energy, Elsevier, vol. 274(C).
    6. Martijn Burger & Evert Meijers, 2012. "Form Follows Function? Linking Morphological and Functional Polycentricity," Urban Studies, Urban Studies Journal Limited, vol. 49(5), pages 1127-1149, April.
    7. Yuan Zhang & Zhen Yu & Juan Zhang, 2021. "Analysis of carbon emission performance and regional differences in China’s eight economic regions: Based on the super-efficiency SBM model and the Theil index," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-21, May.
    8. Yanyan Wu & Jiadong Yuan, 2022. "Is There a Regulation in the Expansion of Urban Spatial Structure? Empirical Study from the Main Urban Area in Zhengzhou, China," Sustainability, MDPI, vol. 14(5), pages 1-17, March.
    9. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    10. Yubo Zhao & Gui Zhang & Hongwei Zhao & Anirban Chakraborti, 2021. "Spatial Network Structures of Urban Agglomeration Based on the Improved Gravity Model: A Case Study in China’s Two Urban Agglomerations," Complexity, Hindawi, vol. 2021, pages 1-17, February.
    11. Xu, Le & Fan, Meiting & Yang, Lili & Shao, Shuai, 2021. "Heterogeneous green innovations and carbon emission performance: Evidence at China's city level," Energy Economics, Elsevier, vol. 99(C).
    12. P. J. Taylor & D. M. Evans & K. Pain, 2008. "Application of the Interlocking Network Model to Mega-City-Regions: Measuring Polycentricity Within and Beyond City-Regions," Regional Studies, Taylor & Francis Journals, vol. 42(8), pages 1079-1093.
    13. Xinhua Zhu & Qianli Wang & Peifeng Zhang & Yunjiang Yu & Lingling Xie, 2021. "Optimizing the spatial structure of urban agglomeration: based on social network analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 683-705, April.
    14. Yang, Fei & Liu, Kang & Wu, Lei & Ren, Yi & Liang, Tian, 2025. "Urban geometry and energy efficiency: Evidence from 282 cities in China," Energy, Elsevier, vol. 319(C).
    15. Wu, Rongxin & Tan, Zhizhou & Lin, Boqiang, 2023. "Does carbon emission trading scheme really improve the CO2 emission efficiency? Evidence from China's iron and steel industry," Energy, Elsevier, vol. 277(C).
    16. Zhou, Anhua & Xin, Ling & Li, Jun, 2022. "Assessing the impact of the carbon market on the improvement of China's energy and carbon emission performance," Energy, Elsevier, vol. 258(C).
    17. Glaeser, Edward L., 2008. "Cities, Agglomeration, and Spatial Equilibrium," OUP Catalogue, Oxford University Press, number 9780199290444.
    18. Zhang, Hao & Song, Yan & Zhang, Ming & Duan, Ye, 2024. "Land use efficiency and energy transition in Chinese cities: A cluster-frontier super-efficiency SBM-based analytical approach," Energy, Elsevier, vol. 304(C).
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