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Spatio-Temporal Correlation and Optimization of Urban Development Characteristics and Carbon Balance in Counties: A Case Study of the Anhui Province, China

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  • Yuling Wu

    (School of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Hongyun Kan

    (School of Public Administration, Central China Normal University, Wuhan 430079, China)

  • Aili Deng

    (School of Public Administration, Central China Normal University, Wuhan 430079, China)

Abstract

Exploring the carbon balance pattern from the perspective of urban spatial development pattern is an effective way to solve the urban carbon emissions reduction problem, promote high-quality economic development, and synergize the development of the regional “nature–economy” dual system. Taking 105 counties (districts) in Anhui Province as an example, based on the calculation of regional carbon balance and urban development characteristics in 2001, 2010, and 2019, we used the spatio-temporal leap model to analyze urban development characteristics and combined the GWTR model and geodetic probes to explore the spatial and temporal correlation between the carbon balance and urban development characteristics, as well as their influence mechanisms. The results of the study show that: (1) The carbon balance of the 105 counties in Anhui Province shows a general decline in the time axis, with a small recovery, and the spatial sequence decreases and then increases from the north to the south. (2) The urban structure of southeast Anhui Province and central Anhui Province is stable, and the development status is good, but the carbon balance is out of balance, the carbon emissions are much higher than the carbon sinks, and the urban structure of the mountainous areas of west Anhui Province and north Anhui Province is dynamic and coordinated, with the carbon balance in harmony. (3) The spatial development characteristics of the cities in Anhui Province have a negative impact on the carbon balance at the scale-area level and a positive impact at the functional structure level. Among them, the area of urban built-up area and the number of the largest urban patches have strong explanatory power for the carbon balance, and the number of the largest urban patches is the main driver of spatial heterogeneity in the carbon balance. (4) The carbon budget of Anhui Province under the influence of urban spatial development characteristics can be divided into four regions: the economic development–carbon balance lopsided area, the ecological protection–carbon balance surplus area, the urban agglomeration–carbon balance adjustment area, and the potential enhancement–carbon balance equilibrium area. Based on the results, urban development needs to strengthen the construction of urban functional zones, and when formulating low-carbon policies in provinces with uneven development, it is necessary to comprehensively analyze the differences in development between cities and build cities according to local conditions.

Suggested Citation

  • Yuling Wu & Hongyun Kan & Aili Deng, 2024. "Spatio-Temporal Correlation and Optimization of Urban Development Characteristics and Carbon Balance in Counties: A Case Study of the Anhui Province, China," Land, MDPI, vol. 13(6), pages 1-26, June.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:6:p:810-:d:1410159
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    References listed on IDEAS

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    1. Chang, Ching-Chih, 2010. "A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China," Applied Energy, Elsevier, vol. 87(11), pages 3533-3537, November.
    2. Jiang, Weiguo & Deng, Yue & Tang, Zhenghong & Lei, Xuan & Chen, Zheng, 2017. "Modelling the potential impacts of urban ecosystem changes on carbon storage under different scenarios by linking the CLUE-S and the InVEST models," Ecological Modelling, Elsevier, vol. 345(C), pages 30-40.
    3. Myles R. Allen & David J. Frame & Chris Huntingford & Chris D. Jones & Jason A. Lowe & Malte Meinshausen & Nicolai Meinshausen, 2009. "Warming caused by cumulative carbon emissions towards the trillionth tonne," Nature, Nature, vol. 458(7242), pages 1163-1166, April.
    4. Cai, Bofeng & Cui, Can & Zhang, Da & Cao, Libin & Wu, Pengcheng & Pang, Lingyun & Zhang, Jihong & Dai, Chunyan, 2019. "China city-level greenhouse gas emissions inventory in 2015 and uncertainty analysis," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
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    1. Mulin Sun & Yuhao Fu & Mingyao Sun & Run Huang & Yun Teng, 2025. "Study on Key Influencing Factors of Carbon Emissions from Farmland Resource Utilization in Northeast China Under the Background of Energy Conservation and Emission Reduction," Energies, MDPI, vol. 18(2), pages 1-22, January.
    2. Chunzhu Wei & Xufeng Liu & Wei Chen & Lupan Zhang & Ruixia Chao & Wei Wei, 2024. "How Do Temporal and Geographical Kernels Differ in Reflecting Regional Disparities? Insights from a Case Study in China," Land, MDPI, vol. 14(1), pages 1-25, December.

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