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Analysis of Spatiotemporal Predictions and Drivers of Carbon Storage in the Pearl River Delta Urban Agglomeration via the PLUS-InVEST-GeoDetector Model

Author

Listed:
  • Jinghang Cai

    (Department of Ocean Engineering and Energy, Guangdong Ocean University, Zhanjiang 524088, China)

  • Hui Chi

    (Department of Ocean Engineering and Energy, Guangdong Ocean University, Zhanjiang 524088, China)

  • Nan Lu

    (Department of Ocean Engineering and Energy, Guangdong Ocean University, Zhanjiang 524088, China)

  • Jin Bian

    (Department of Ocean Engineering and Energy, Guangdong Ocean University, Zhanjiang 524088, China)

  • Hanqing Chen

    (Department of Ocean Engineering and Energy, Guangdong Ocean University, Zhanjiang 524088, China)

  • Junkeng Yu

    (Department of Ocean Engineering and Energy, Guangdong Ocean University, Zhanjiang 524088, China)

  • Suqin Yang

    (Guangdong Yuehai Water Investment Co., Ltd., Zhanjiang 524088, China)

Abstract

Land use and land cover change (LUCC) significantly influences the dynamics of carbon storage in thin terrestrial ecosystems. Investigating the interplay between land use alterations and carbon sequestration is crucial for refining regional land use configurations, sustaining the regional carbon balance, and augmenting regional carbon storage. Using land use data from the Pearl River Delta Urban Agglomeration (PRDUA) from 2010 to 2020, this study employed PLUS-InVEST models to analyze the spatiotemporal dynamics of land use and carbon storage. Projections for the years 2030, 2040, and 2050 were performed under three distinct developmental scenarios, namely, natural development (ND), city priority development (CPD), and ecological protection development (EPD), to forecast changes in land use and carbon storage. The geographic detector model was leveraged to dissect the determinants of the spatial and temporal variability of carbon storage, offering pertinent recommendations. The results showed that (1) during 2010–2020, the carbon storage in the PRDUA showed a decreasing trend, with a total decrease of 9.52 × 10 6 Mg, and the spatial distribution of carbon density in the urban agglomeration was imbalanced and showed an overall trend in increasing from the center to the periphery. (2) Clear differences in carbon storage were observed among the three development scenarios of the PRDUA between 2030 and 2050. Only the EPD scenario achieved an increase in carbon storage of 1.10 × 10 6 Mg, and it was the scenario with the greatest potential for carbon sequestration. (3) Among the drivers of the evolution of spatial land use patterns, population, the normalized difference vegetation index (NDVI), and distance to the railway had the greatest influence on LUCC. (4) The annual average temperature, annual average rainfall, and GDP exerted a significant influence on the spatiotemporal dynamics of carbon storage in the PRDUA, and the interactions between the 15 drivers and changes in carbon storage predominantly manifested as nonlinear and double-factor enhancements. The results provide a theoretical basis for future spatial planning and achieving carbon neutrality in the PRDUA.

Suggested Citation

  • Jinghang Cai & Hui Chi & Nan Lu & Jin Bian & Hanqing Chen & Junkeng Yu & Suqin Yang, 2024. "Analysis of Spatiotemporal Predictions and Drivers of Carbon Storage in the Pearl River Delta Urban Agglomeration via the PLUS-InVEST-GeoDetector Model," Energies, MDPI, vol. 17(20), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5093-:d:1498008
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    References listed on IDEAS

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    1. Li, Jiasheng & Guo, Xiaomin & Chuai, Xiaowei & Xie, Fangjian & Yang, Feng & Gao, Runyi & Ji, Xuepeng, 2021. "Reexamine China’s terrestrial ecosystem carbon balance under land use-type and climate change," Land Use Policy, Elsevier, vol. 102(C).
    2. Huang, Daquan & Huang, Jing & Liu, Tao, 2019. "Delimiting urban growth boundaries using the CLUE-S model with village administrative boundaries," Land Use Policy, Elsevier, vol. 82(C), pages 422-435.
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