IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i21p15477-d1271508.html
   My bibliography  Save this article

Spatiotemporal Pattern and Driving Factors of Carbon Emissions in Guangxi Based on Geographic Detectors

Author

Listed:
  • Qianru Guo

    (Guangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, College of Environment and Resources, Guangxi Normal University, Guilin 541000, China)

  • Xiuting Lai

    (Guangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, College of Environment and Resources, Guangxi Normal University, Guilin 541000, China)

  • Yanhong Jia

    (Guangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, College of Environment and Resources, Guangxi Normal University, Guilin 541000, China)

  • Feili Wei

    (Guangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions, College of Environment and Resources, Guangxi Normal University, Guilin 541000, China)

Abstract

Analysis of the spatiotemporal distribution pattern and driving factors of carbon emissions has been a focus of research in recent years. However, at the county level, analyses of the driving factors of carbon emissions are still relatively few. This study selected the Guangxi Zhuang Autonomous Region as the research subject, selecting the normalized difference vegetation index (NDVI), nighttime light index (NLI), gross domestic product (GDP), and population density (POP) as driving factors. Based on the geographic detector method, the spatiotemporal distribution pattern and driving factors of carbon emissions at the county level in Guangxi were investigated. The results show the following: (1) There are significant regional differences in the degree of change in carbon emissions. From 2005 to 2020, the total carbon emissions in Guangxi show an upward trend, presenting a “high in the south and low in the north” distribution characteristic, gradually forming a high-level region in the capital city of Nanning, the city of Liuzhou, and some coastal cities (such as the cities of Qinzhou, Beihai, and Fangchenggang) as the core of carbon emissions; (2) NDVI, NLI, GDP, and POP have a relatively high impact on the carbon emission pattern in Guangxi, and the impact of human activity intensity on carbon emissions is higher than that of the influencing factors of NDVI; (3) The interaction between NDVI, NLI, GDP, and POP has a significant impact on the carbon emission pattern. The aforementioned results can provide decision-making suggestions for the social and economic development of Guangxi, as well as the formulation of carbon sequestration policies.

Suggested Citation

  • Qianru Guo & Xiuting Lai & Yanhong Jia & Feili Wei, 2023. "Spatiotemporal Pattern and Driving Factors of Carbon Emissions in Guangxi Based on Geographic Detectors," Sustainability, MDPI, vol. 15(21), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15477-:d:1271508
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/21/15477/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/21/15477/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Feipeng Guo & Linji Zhang & Zifan Wang & Shaobo Ji, 2022. "Research on Determining the Critical Influencing Factors of Carbon Emission Integrating GRA with an Improved STIRPAT Model: Taking the Yangtze River Delta as an Example," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    2. Fan, Jingjing & Wang, Jianliang & Qiu, Jixiang & Li, Nu, 2023. "Stage effects of energy consumption and carbon emissions in the process of urbanization: Evidence from 30 provinces in China," Energy, Elsevier, vol. 276(C).
    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. Jia Peng & Xianli Hu & Xinyue Fan & Kai Wang & Hao Gong, 2023. "The Impact of the Green Economy on Carbon Emission Intensity: Comparisons, Challenges, and Mitigating Strategies," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    2. Xuemei Jia & Qing Liu & Jiahao Feng & Yuru Li & Lijun Zhang, 2023. "The Induced Effects of Carbon Emissions for China’s Industry Digital Transformation," Sustainability, MDPI, vol. 15(16), pages 1-20, August.
    3. Hongqiang Wang & Wenyi Xu & Yingjie Zhang, 2023. "Research on Provincial Carbon Emission Reduction Path Based on LMDI-SD-Tapio Decoupling Model: The Case of Guizhou, China," Sustainability, MDPI, vol. 15(17), pages 1-20, September.
    4. Xi Wang & Xiangli Wu & Nanchen Chu & Yilin Zhang & Limin Wang, 2024. "Coupling Relationship between Urbanization and Green Total Factor Productivity in the Context of Population Shrinkage: Evidence from the Rust Belt Region of China," Sustainability, MDPI, vol. 16(3), pages 1-22, February.
    5. Kerong Zhang & Liangyu Jiang & Yanzhi Jin & Wuyi Liu, 2022. "The Carbon Emission Characteristics and Reduction Potential in Developing Areas: Case Study from Anhui Province, China," IJERPH, MDPI, vol. 19(24), pages 1-28, December.
    6. Mingchen Yang & Lei Wang & Hang Hu, 2024. "Analysis of Factors Influencing the Spatial and Temporal Variability of Carbon Intensity in Western China," Sustainability, MDPI, vol. 16(8), pages 1-19, April.
    7. Dong Xue & Tongyang Liu & Xiaomin Li & Xiaolei Zhao, 2023. "Can the Digital Economy Accelerate “Carbon Neutrality”?—An Empirical Analysis Based on Provincial Data in China," Sustainability, MDPI, vol. 15(14), pages 1-26, July.

    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:jsusta:v:15:y:2023:i:21:p:15477-:d:1271508. 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.