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Spatial and Temporal Variability Characteristics of Future Carbon Stocks in Anhui Province under Different SSP Scenarios Based on PLUS and InVEST Models

Author

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  • Shuaijun Yue

    (College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
    Henan Engineering Research Center of Land Consolidation and Ecological Restoration, Zhengzhou 450046, China)

  • Guangxing Ji

    (College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
    Henan Engineering Research Center of Land Consolidation and Ecological Restoration, Zhengzhou 450046, China)

  • Weiqiang Chen

    (College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
    Henan Engineering Research Center of Land Consolidation and Ecological Restoration, Zhengzhou 450046, China)

  • Junchang Huang

    (College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
    Henan Engineering Research Center of Land Consolidation and Ecological Restoration, Zhengzhou 450046, China)

  • Yulong Guo

    (College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
    Henan Engineering Research Center of Land Consolidation and Ecological Restoration, Zhengzhou 450046, China)

  • Mingyue Cheng

    (College of Resources and Environment, Henan Agricultural University, Zhengzhou 450046, China
    Henan Engineering Research Center of Land Consolidation and Ecological Restoration, Zhengzhou 450046, China)

Abstract

With the rapid development of the social economy, human activities have had a severe impact on the environment. The global climate issue caused by CO 2 emissions has attracted the attention of various countries around the world, and reducing CO 2 emissions is urgent. This article simulates the changes in carbon storage in Anhui Province from 2030 to 2070 based on SSP1-2.5, SSP2-4.5, and SSP5-5.8 scenarios. First, based on the land use data of Anhui Province in 2010, the PLUS model was used to simulate the land use data of 2015, and the accuracy of the simulation results was verified against real data. Then, the land use data of Anhui Province were simulated in the future period from 2030 to 2070 under different SSP scenarios. Finally, based on the InVEST model, the spatiotemporal changes in future carbon storage were calculated. The research showed that, during the period of 2030 to 2070, the spatial distribution of carbon storage in Anhui Province under three scenario simulations generally showed a distribution pattern of high carbon storage in the north and south, and low carbon storage in the central region. Under the SSP1-2.6 scenario, Anhui Province’s carbon storage decreased by 0.33 million tons, a decrease of 0.029%. Under the SSP2-4.5 scenario, carbon storage increased by 0.25 million tons, an increase of 0.021%. Under the SSP5-8.5 scenario, carbon storage decreased by 1.54 million tons, a decrease of 0.133%. The reasons for the changes in carbon storage were related to the areas of arable land, forest land, and grassland. This study can provide a reference for future low-carbon land use planning.

Suggested Citation

  • Shuaijun Yue & Guangxing Ji & Weiqiang Chen & Junchang Huang & Yulong Guo & Mingyue Cheng, 2023. "Spatial and Temporal Variability Characteristics of Future Carbon Stocks in Anhui Province under Different SSP Scenarios Based on PLUS and InVEST Models," Land, MDPI, vol. 12(9), pages 1-17, August.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1668-:d:1225446
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    References listed on IDEAS

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    1. Linfeng Xu & Xuan Liu & De Tong & Zhixin Liu & Lirong Yin & Wenfeng Zheng, 2022. "Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model," Land, MDPI, vol. 11(5), pages 1-16, April.
    2. Opelele Omeno Michel & Ying Yu & Wenyi Fan & Tolerant Lubalega & Chen Chen & Claude Kachaka Sudi Kaiko, 2022. "Impact of Land Use Change on Tree Diversity and Aboveground Carbon Storage in the Mayombe Tropical Forest of the Democratic Republic of Congo," Land, MDPI, vol. 11(6), pages 1-19, May.
    3. Lyndré Nel & Ana Flávia Boeni & Viola Judit Prohászka & Alfréd Szilágyi & Eszter Tormáné Kovács & László Pásztor & Csaba Centeri, 2022. "InVEST Soil Carbon Stock Modelling of Agricultural Landscapes as an Ecosystem Service Indicator," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
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    1. Lin Tang & Jing Wang & Luo Xu & Heng Lu, 2024. "Exploring New Avenues in Sustainable Urban Development: Ecological Carbon Dynamics of Park City in Chengdu," Sustainability, MDPI, vol. 16(15), pages 1-21, July.

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