IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i11p4586-d1404027.html
   My bibliography  Save this article

Study on Driving Factors and Spatiotemporal Differentiation of Eco-Environmental Quality in Jianghuai River Basin of China

Author

Listed:
  • Hong Cai

    (Anhui Cultural Tourism Innovative Development Research Institute, Anhui Jianzhu University, Hefei 203106, China
    School of Public Policy & Management, Anhui Jianzhu University, Hefei 203106, China)

  • Xueqing Ma

    (Social Innovation Design Research Center, Anhui University, Hefei 203106, China)

  • Pengyu Chen

    (Social Innovation Design Research Center, Anhui University, Hefei 203106, China)

  • Yanlong Guo

    (Social Innovation Design Research Center, Anhui University, Hefei 203106, China)

Abstract

For an in-depth analysis of the ecosystems of the Jianghuai Valley, this study utilized municipal data from 2017 to 2021. In addition, this study established an index scale evaluation system for the quality of the ecological environment in the Jianghuai Valley. This system encompasses five critical dimensions: drivers, pressures, states, impacts, and responses, in accordance with the DPSIR model. The entropy-weighted TOPSIS method combined with the gray correlation method was used to assess the ecological status of each region of the Jianghuai Valley at different time periods and the driving factors affecting the ecological quality of the Jianghuai Valley. Our study yields several key conclusions. First, it was observed that the ecological environment within the Jianghuai Valley showed a continuous upward bias in inter-annual variability. Second, there exists variation in ecological environment quality among the eleven urban areas within the Jianghuai Valley, highlighting regional disparities. Third, among the eleven urban areas in the Jianghuai Valley, Anqing has the best ecological quality, and Huainan has the worst ecological performance. Fourth, the ecological environment quality within the Jianghuai Valley demonstrates an aggregated pattern. From west to east, this pattern is delineated by distinct areas: one marked by excellent ecological environment quality, another exhibiting average ecological environment quality, followed by a zone characterized by good ecological environment quality, and finally, an area with poor ecological environment. Fifth, our analysis reveals that Q9 (indicating the percentage of excellent air days) and Q13 (denoting the annual average temperature) have a pronounced correlation with the Jianghuai Valley’s ecological quality. Conversely, Q3, which pertains to the rate of natural population growth, had the lowest relevance to the ecological quality of the Jianghuai Valley.

Suggested Citation

  • Hong Cai & Xueqing Ma & Pengyu Chen & Yanlong Guo, 2024. "Study on Driving Factors and Spatiotemporal Differentiation of Eco-Environmental Quality in Jianghuai River Basin of China," Sustainability, MDPI, vol. 16(11), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4586-:d:1404027
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/11/4586/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/11/4586/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiao-Jun Wang & Jian-Yun Zhang & Shamsuddin Shahid & Wei Xie & Chao-Yang Du & Xiao-Chuan Shang & Xu Zhang, 2018. "Modeling domestic water demand in Huaihe River Basin of China under climate change and population dynamics," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(2), pages 911-924, April.
    2. Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & Shou-hai Bi & Amgad Elmahdi & Chuan-hua Liao & You-de Li, 2018. "Forecasting industrial water demand in Huaihe River Basin due to environmental changes," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(4), pages 469-483, April.
    3. Jiamei Zhang & Guijian Liu & Zijiao Yuan & Ruwei Wang, 2014. "Levels and distributions of polycyclic aromatic hydrocarbons (PAHs) in middle reach of Huaihe River, China: anthropogenic influences and ecological risks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 705-716, November.
    4. Afnan Agramont & Nora van Cauwenbergh & Ann van Griesven & Marc Craps, 2022. "Integrating spatial and social characteristics in the DPSIR framework for the sustainable management of river basins: case study of the Katari River Basin, Bolivia," Water International, Taylor & Francis Journals, vol. 47(1), pages 8-29, January.
    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. Jun Liu & Yuyan Zhou & Lihua Chen & Lichuan Wang, 2023. "Assessing the Impact of Climate Change on Water Usage in Typical Industrial Enterprises," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    2. Xiaohang Zhai & Zhe Chen & Chunlan Tan & Guangliang Li, 2023. "Heterogeneity Analysis of Industrial Structure Upgrading on Eco-Environmental Quality from a Spatial Perspective: Evidence from 11 Coastal Provinces in China," Sustainability, MDPI, vol. 15(21), pages 1-22, October.
    3. Selvin Antonio Saravia-Maldonado & Luis Francisco Fernández-Pozo & Beatriz Ramírez-Rosario & María Ángeles Rodríguez-González, 2024. "Analysis of Deforestation and Water Quality in the Talgua River Watershed (Honduras): Ecosystem Approach Based on the DPSIR Model," Sustainability, MDPI, vol. 16(12), pages 1-22, June.
    4. Wencong Yue & Zhongqi Liu & Meirong Su & Meng Xu & Qiangqiang Rong & Chao Xu & Zhenkun Tan & Xuming Jiang & Zhixin Su & Yanpeng Cai, 2022. "Inclusion of Ecological Water Requirements in Optimization of Water Resource Allocation Under Changing Climatic Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 551-570, January.
    5. Shaokun He & Shenglian Guo & Guang Yang & Kebing Chen & Dedi Liu & Yanlai Zhou, 2020. "Optimizing Operation Rules of Cascade Reservoirs for Adapting Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(1), pages 101-120, January.

    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:16:y:2024:i:11:p:4586-:d:1404027. 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.