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Simulation and Prediction of Land Use Change and Carbon Emission under Multiple Development Scenarios at the City Level: A Case Study of Xi’an, China

Author

Listed:
  • Rui Bian

    (School of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Anzhou Zhao

    (School of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Lidong Zou

    (School of Artificial Intelligence, Shenzhen Polytechnic University, Shenzhen 518055, China)

  • Xianfeng Liu

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China)

  • Ruihao Xu

    (School of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

  • Ziyang Li

    (School of Mining and Geomatics, Hebei University of Engineering, Handan 056038, China)

Abstract

Studying urban land use and its impact on carbon emissions is crucial for achieving China’s dual carbon goals. This research utilized the Shared Socio-economic Pathways (SSPs) scenarios 126, 245, and 585 from the Sixth International Coupled Model Intercomparison Project (CMIP6), along with a coupled System Dynamics (SD) and Patch-generating Land Use Simulation (PLUS) model and a carbon emission coefficient method to simulate and predict Xi’an’s land use carbon emissions from 2020 to 2040. The results indicate the following: (1) Cultivated and forest lands are the predominant land use types in Xi’an, with cultivated and grassland areas projected to decline under all three SSP scenarios by 2040. The most significant expansion of construction land, primarily at the expense of farmland, is projected under the SSP585 scenario, with an increase of 515.92 km 2 by 2040. (2) Land use carbon emissions increased from 414.15 × 10 4 t in 2000 to 2376.10 × 10 4 t in 2020, with construction land being the primary source of emissions and forest land serving as the main carbon sink. However, the carbon sink capacity remained low at only 21.38 × 10 4 t in 2020. (3) Carbon emissions are expected to continue increasing under all scenarios through 2030 and 2040, though at a decreasing rate. The SSP126 scenario predicts the lowest emissions, reaching 9186.00 × 10 4 t by 2040, while SSP585 predicts the highest at 14,935.00 × 10 4 t. The findings of this study provide theoretical support for future low-carbon and high-quality urban development strategies.

Suggested Citation

  • Rui Bian & Anzhou Zhao & Lidong Zou & Xianfeng Liu & Ruihao Xu & Ziyang Li, 2024. "Simulation and Prediction of Land Use Change and Carbon Emission under Multiple Development Scenarios at the City Level: A Case Study of Xi’an, China," Land, MDPI, vol. 13(7), pages 1-18, July.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:7:p:1079-:d:1437214
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    References listed on IDEAS

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    1. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    2. Yangfei Huang & Xiaomin Jiang & Yong Chen, 2023. "Analysis of the Spatial-Temporal Evolution of Urbanization Quality in Zhejiang Province, China," IJERPH, MDPI, vol. 20(5), pages 1-15, February.
    3. Wenli Yang & Langang Feng & Zuogong Wang & Xiangbo Fan, 2023. "Carbon Emissions and National Sustainable Development Goals Coupling Coordination Degree Study from a Global Perspective: Characteristics, Heterogeneity, and Spatial Effects," Sustainability, MDPI, vol. 15(11), pages 1-23, June.
    4. Dingrao Feng & Wenkai Bao & Meichen Fu & Min Zhang & Yiyu Sun, 2021. "Current and Future Land Use Characters of a National Central City in Eco-Fragile Region—A Case Study in Xi’an City Based on FLUS Model," Land, MDPI, vol. 10(3), pages 1-25, March.
    5. Luo, Haizhi & Li, Yingyue & Gao, Xinyu & Meng, Xiangzhao & Yang, Xiaohu & Yan, Jinyue, 2023. "Carbon emission prediction model of prefecture-level administrative region: A land-use-based case study of Xi'an city, China," Applied Energy, Elsevier, vol. 348(C).
    6. Alexiadis, Alessio, 2007. "Global warming and human activity: A model for studying the potential instability of the carbon dioxide/temperature feedback mechanism," Ecological Modelling, Elsevier, vol. 203(3), pages 243-256.
    7. Yabo Zhao & Shifa Ma & Jianhong Fan & Yunnan Cai, 2021. "Examining the Effects of Land Use on Carbon Emissions: Evidence from Pearl River Delta," IJERPH, MDPI, vol. 18(7), pages 1-19, March.
    8. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
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