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Examining the Overall and Heterogeneous Impacts of Urban Spatial Structure on Carbon Emissions: A Case Study of Guangdong Province, China

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  • Ke Luo

    (Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
    Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China
    These authors contributed equally to this work.)

  • Shuo Chen

    (School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China
    These authors contributed equally to this work.)

  • Shixi Cui

    (School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China)

  • Yuantao Liao

    (Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
    Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China)

  • Yu He

    (Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
    Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China)

  • Chunshan Zhou

    (School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China)

  • Shaojian Wang

    (School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China)

Abstract

The variation in the urban spatial structure (USS) has profound impacts on carbon emissions. Studying the relationship between the two can provide guidance for carbon neutrality strategies and the construction of low-carbon cities in China. However, there is currently a lack of comparative research on the different regions within a province. In this paper, the spatiotemporal evolution of the USS and carbon emissions, at five-year intervals from 2000 to 2020, is investigated in 21 prefecture-level cities in Guangdong Province, China, and the overall relationship of the USS to carbon emissions and their spatiotemporal variations are analyzed by using a two-way fixed-effects model and a geographically and temporally weighted regression model, respectively. The results show that, first, over the past twenty years, the scale of cities has continued to expand, with increasing continuity and aggregation in the built-up areas, while the complexity and fragmentation of their shapes have gradually decreased. Second, the gap in carbon emissions between the Pearl River Delta and other regions in Guangdong shows a trend of first decreasing and then increasing, with high values concentrated in the Pearl River Delta region and the city of Shantou in the east. Third, compared to socio-economic factors, the USS has a more direct and pronounced impact on carbon emissions. Urban expansion and the increased complexity of land patches promote carbon emissions, whereas improving urban spatial continuity and compactness can reduce carbon emissions. Fourth, the dominant spatial structure indicators of carbon emissions differ among the regions of eastern, western, and northern Guangdong and the Pearl River Delta. This study proposes spatial optimization strategies for the low-carbon development of cities in Guangdong Province, providing a new perspective for integrating urban layout and emission reduction policies.

Suggested Citation

  • Ke Luo & Shuo Chen & Shixi Cui & Yuantao Liao & Yu He & Chunshan Zhou & Shaojian Wang, 2023. "Examining the Overall and Heterogeneous Impacts of Urban Spatial Structure on Carbon Emissions: A Case Study of Guangdong Province, China," Land, MDPI, vol. 12(9), pages 1-19, September.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1806-:d:1243266
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    References listed on IDEAS

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    1. He, Xiaoping & Yu, Yuxuan & Jiang, Shuo, 2023. "City centrality, population density and energy efficiency," Energy Economics, Elsevier, vol. 117(C).
    2. Gudipudi, Ramana & Fluschnik, Till & Ros, Anselmo García Cantú & Walther, Carsten & Kropp, Jürgen P., 2016. "City density and CO2 efficiency," Energy Policy, Elsevier, vol. 91(C), pages 352-361.
    3. Yanchun Yi & Yajun Wang & Yaqin Li & Ji Qi, 2021. "Impact of urban density on carbon emissions in China," Applied Economics, Taylor & Francis Journals, vol. 53(53), pages 6153-6165, November.
    4. Guiliang Tian & Suwan Yu & Zheng Wu & Qing Xia, 2022. "Study on the Emission Reduction Effect and Spatial Difference of Carbon Emission Trading Policy in China," Energies, MDPI, vol. 15(5), pages 1-20, March.
    5. Wang, Jieyu & Wang, Shaojian & Li, Shijie & Feng, Kuishuang, 2019. "Coupling analysis of urbanization and energy-environment efficiency: Evidence from Guangdong province," Applied Energy, Elsevier, vol. 254(C).
    6. Zhou, Yang & Liu, Yansui, 2016. "Does population have a larger impact on carbon dioxide emissions than income? Evidence from a cross-regional panel analysis in China," Applied Energy, Elsevier, vol. 180(C), pages 800-809.
    7. Kai Zhu & Manya Tu & Yingcheng Li, 2022. "Did Polycentric and Compact Structure Reduce Carbon Emissions? A Spatial Panel Data Analysis of 286 Chinese Cities from 2002 to 2019," Land, MDPI, vol. 11(2), pages 1-15, January.
    8. Changlong Sun & Yongli Zhang & Wenwen Ma & Rong Wu & Shaojian Wang, 2022. "The Impacts of Urban Form on Carbon Emissions: A Comprehensive Review," Land, MDPI, vol. 11(9), pages 1-20, August.
    9. Wang, Shaojian & Liu, Xiaoping & Zhou, Chunshan & Hu, Jincan & Ou, Jinpei, 2017. "Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities," Applied Energy, Elsevier, vol. 185(P1), pages 189-200.
    10. Fang, Chuanglin & Wang, Shaojian & Li, Guangdong, 2015. "Changing urban forms and carbon dioxide emissions in China: A case study of 30 provincial capital cities," Applied Energy, Elsevier, vol. 158(C), pages 519-531.
    11. Yanru Pu & Yuyi Wang & Peng Wang, 2022. "Driving effects of urbanization on city-level carbon dioxide emissions: from multiple perspectives of urbanization," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 26(1), pages 108-128, January.
    12. Shi, Kaifang & Chen, Yun & Li, Linyi & Huang, Chang, 2018. "Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective," Applied Energy, Elsevier, vol. 211(C), pages 218-229.
    13. Shu, Hui & Xiong, Ping-ping, 2019. "Reallocation planning of urban industrial land for structure optimization and emission reduction: A practical analysis of urban agglomeration in China’s Yangtze River Delta," Land Use Policy, Elsevier, vol. 81(C), pages 604-623.
    14. Martin Herold & Joseph Scepan & Keith C Clarke, 2002. "The Use of Remote Sensing and Landscape Metrics to Describe Structures and Changes in Urban Land Uses," Environment and Planning A, , vol. 34(8), pages 1443-1458, August.
    15. Jaehyeok Kim & Hyungwoo Lim & Ha-Hyun Jo, 2020. "Do Aging and Low Fertility Reduce Carbon Emissions in Korea? Evidence from IPAT Augmented EKC Analysis," IJERPH, MDPI, vol. 17(8), pages 1-15, April.
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