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The Spatiotemporal Evolution and Prediction of Carbon Storage: A Case Study of Urban Agglomeration in China’s Beijing-Tianjin-Hebei Region

Author

Listed:
  • Yingting He

    (School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China)

  • Chuyu Xia

    (Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China)

  • Zhuang Shao

    (School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China)

  • Jing Zhao

    (School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China)

Abstract

Due to rapid urban expansion, urban agglomerations face enormous challenges on their way to carbon neutrality. Regarding China’s urban agglomerations, 25% of the land contains 75% of the population, and all types of land are used efficiently and intensively. However, few studies have explored the spatiotemporal link between changes in land use and land cover (LULC) and carbon storage. In this work, the carbon storage changes from 1990 to 2020 were estimated using the InVEST model in China’s Beijing–Tianjin–Hebei (BTH) region. By coupling the Future Land Use Simulation (FLUS) model and InVEST model, the LULC and carbon storage changes in the BTH region in 2035 and 2050 under the natural evolution scenario (NES), economic priority scenario (EPS), ecological conservation scenario (ECS), and coordinated development scenario (CDS). Finally, the spatial autocorrelation analysis of regional carbon storage was developed for future zoning management. The results revealed the following: (1) the carbon storage in the BTH region exhibited a cumulative loss of 3.5 × 10 7 Mg from 1990 to 2020, and the carbon loss was serious between 2000 and 2010 due to rapid urbanization. (2) Excluding the ECS, the other three scenarios showed continued expansion of construction land. Under the EPS, the carbon storage was found to have the lowest value, which decreased to 16.05 × 10 8 Mg in 2035 and only 15.38 × 10 8 Mg in 2050; under the ECS, the carbon storage was predicted to reach the highest value, 18.22 × 10 8 Mg and 19.00 × 10 8 Mg, respectively; the CDS exhibited a similar trend as the NES, but the carbon storage was found to increase. (3) The carbon storage under the four scenarios was found to have a certain degree of similarity in terms of its spatial distribution; the high-value areas were found to be clustered in the northwestern part of Beijing and the northern and western parts of Hebei. As for the number of areas with high carbon storage, the ECS was found to be the most abundant, followed by the CDS, and the EPS was found to be the least. The findings of this study can help the BTH region implement the “dual carbon” target and provide a leading example for other urban agglomerations.

Suggested Citation

  • Yingting He & Chuyu Xia & Zhuang Shao & Jing Zhao, 2022. "The Spatiotemporal Evolution and Prediction of Carbon Storage: A Case Study of Urban Agglomeration in China’s Beijing-Tianjin-Hebei Region," Land, MDPI, vol. 11(6), pages 1-25, June.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:6:p:858-:d:832999
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    References listed on IDEAS

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    1. Wenbo Cai & Wanting Peng, 2021. "Exploring Spatiotemporal Variation of Carbon Storage Driven by Land Use Policy in the Yangtze River Delta Region," Land, MDPI, vol. 10(11), pages 1-12, October.
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    5. 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.
    6. Mingruo Chu & Jiayi Lu & Dongqi Sun, 2022. "Influence of Urban Agglomeration Expansion on Fragmentation of Green Space: A Case Study of Beijing-Tianjin-Hebei Urban Agglomeration," Land, MDPI, vol. 11(2), pages 1-19, February.
    7. 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.
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