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Dynamic Coupling Between Atmospheric CO 2 Concentration and Land Surface Temperature in Major Urban Agglomerations in China: Insights for Sustainable Urban Development

Author

Listed:
  • Qiwen Sun

    (College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China)

  • Xuesheng Zhao

    (College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China)

  • Yiying Hua

    (College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China)

Abstract

To provide new insights into the integrated management of carbon and heat for sustainable urban development, this study systematically investigates the complex relationship between atmospheric CO 2 concentrations and land surface temperature (LST). Utilizing OCO-2 and OCO-3 satellite observations, combined with meteorological conditions, air pollutants, and spatial characteristics, a high-resolution (0.1° × 0.1°) monthly CO 2 column concentration (XCO 2 ) dataset for China spanning 2015 to 2022 was generated using the Random Forest algorithm. The study focuses on urban agglomerations, conducting centroid migration and coupling analyses of XCO 2 and LST to elucidate their spatiotemporal distribution patterns and evolution. Results reveal significant seasonal variations in XCO 2 , which has exhibited a gradual increase over the years. The spatiotemporal distributions of XCO 2 and LST in urban agglomerations show a high degree of consistency, with centroids either converging or following similar movement trajectories. Additionally, the degree of coupling and coordination between XCO 2 and LST has improved annually, indicating a closer interrelationship. These findings enhance our understanding of climate system dynamics and provide essential scientific evidence and decision-making support for addressing climate change. By clarifying the connection between atmospheric CO 2 and LST, this study contributes to the development of more effective strategies for carbon reduction and urban heat island mitigation, thereby advancing cities towards greener, lower-carbon, and more sustainable development pathways.

Suggested Citation

  • Qiwen Sun & Xuesheng Zhao & Yiying Hua, 2024. "Dynamic Coupling Between Atmospheric CO 2 Concentration and Land Surface Temperature in Major Urban Agglomerations in China: Insights for Sustainable Urban Development," Sustainability, MDPI, vol. 16(21), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9484-:d:1511466
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    References listed on IDEAS

    as
    1. Guo, Wei & Lv, Ling & Zhao, Xuesheng & Cui, Ximin & Rienow, Andreas, 2024. "Multiscale coupled development and linkage response evaluation of China's carbon neutrality and sustainable development capability–A quantitative analysis perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(C).
    2. Zixuan Tan & Jinnian Wang & Zhenyu Yu & Yiyun Luo, 2023. "Spatiotemporal Analysis of XCO 2 and Its Relationship to Urban and Green Areas of China’s Major Southern Cities from Remote Sensing and WRF-Chem Modeling Data from 2010 to 2019," Geographies, MDPI, vol. 3(2), pages 1-22, March.
    3. Xinyu Hu & Chun Dong & Yihan Wang, 2023. "Coupled and Coordinated Analysis of Urban Green Development and Ecological Civilization Construction in the Yangtze River Delta Region," Sustainability, MDPI, vol. 15(7), pages 1-26, March.
    4. Wei Wang & Junchen He & Huihui Feng & Zhili Jin, 2022. "High-Coverage Reconstruction of XCO 2 Using Multisource Satellite Remote Sensing Data in Beijing–Tianjin–Hebei Region," IJERPH, MDPI, vol. 19(17), pages 1-20, August.
    5. Zishu Sun & Zhigang Li & Jialong Zhong, 2022. "Analysis of the Impact of Landscape Patterns on Urban Heat Islands: A Case Study of Chengdu, China," IJERPH, MDPI, vol. 19(20), pages 1-15, October.
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