IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i6p810-d1410159.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/6/810/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/6/810/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    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. Fankhauser, Samuel & Hepburn, Cameron, 2010. "Designing carbon markets. Part I: Carbon markets in time," Energy Policy, Elsevier, vol. 38(8), pages 4363-4370, August.
    2. Z Fang & D Ding & C Guan, 2024. "Does Methodology Matter? Revisiting the Energy-growth Nexus in Asia Pacific Economies," Economic Issues Journal Articles, Economic Issues, vol. 29(1), pages 5-34, March.
    3. Omri, Anis, 2014. "An international literature survey on energy-economic growth nexus: Evidence from country-specific studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 951-959.
    4. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    5. Sun, Lu & Liu, Wenjing & Li, Zhaoling & Cai, Bofeng & Fujii, Minoru & Luo, Xiao & Chen, Wei & Geng, Yong & Fujita, Tsuyoshi & Le, Yiping, 2021. "Spatial and structural characteristics of CO2 emissions in East Asian megacities and its indication for low-carbon city development," Applied Energy, Elsevier, vol. 284(C).
    6. Cui, Can & Wang, Zhen & Cai, Bofeng & Peng, Sha & Wang, Yang & Xu, Chengdong, 2021. "Evolution-based CO2 emission baseline scenarios of Chinese cities in 2025," Applied Energy, Elsevier, vol. 281(C).
    7. Dietz, Simon & Gollier, Christian & Kessler, Louise, 2018. "The climate beta," Journal of Environmental Economics and Management, Elsevier, vol. 87(C), pages 258-274.
    8. van der Ploeg, Frederick & Rezai, Armon, 2017. "Cumulative emissions, unburnable fossil fuel, and the optimal carbon tax," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 216-222.
    9. Hermann Held, 2019. "Cost Risk Analysis: Dynamically Consistent Decision-Making under Climate Targets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 247-261, January.
    10. Valero, Antonio & Agudelo, Andrés & Valero, Alicia, 2011. "The crepuscular planet. A model for the exhausted atmosphere and hydrosphere," Energy, Elsevier, vol. 36(6), pages 3745-3753.
    11. Juan Luo & Chong Xu & Boyu Yang & Xiaoyu Chen & Yinyin Wu, 2022. "Quantitative Analysis of China’s Carbon Emissions Trading Policies: Perspectives of Policy Content Validity and Carbon Emissions Reduction Effect," Energies, MDPI, vol. 15(14), pages 1-20, July.
    12. Manal Ayyad Dhif Alshammry & Saqib Muneer, 2023. "The influence of economic development, capital formation, and internet use on environmental degradation in Saudi Arabia," Future Business Journal, Springer, vol. 9(1), pages 1-16, December.
    13. Hoel, Michael, 2016. "Optimal control theory with applications to resource and environmental economics," Memorandum 08/2016, Oslo University, Department of Economics.
    14. Qing Liu & Dongdong Yang & Lei Cao & Bruce Anderson, 2022. "Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Tropics: A Case Study of Hainan Island, China," Land, MDPI, vol. 11(2), pages 1-24, February.
    15. Marques, António Cardoso & Fuinhas, José Alberto & Neves, Sónia Almeida, 2018. "Ordinary and Special Regimes of electricity generation in Spain: How they interact with economic activity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1226-1240.
    16. Malik Curuk & Suphi Sen, 2023. "Climate Policy and Resource Extraction with Variable Markups and Imperfect Substitutes," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 10(4), pages 1091-1120.
    17. Ouyang, Xiaoling & Lin, Boqiang, 2015. "An analysis of the driving forces of energy-related carbon dioxide emissions in China’s industrial sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 838-849.
    18. Zhiyuan Ma & Xuejun Duan & Lei Wang & Yazhu Wang & Jiayu Kang & Ruxian Yun, 2023. "A Scenario Simulation Study on the Impact of Urban Expansion on Terrestrial Carbon Storage in the Yangtze River Delta, China," Land, MDPI, vol. 12(2), pages 1-16, January.
    19. Gustav Engström & Johan Gars, 2016. "Climatic Tipping Points and Optimal Fossil-Fuel Use," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(3), pages 541-571, November.
    20. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.

    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:6:p:810-:d:1410159. 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.