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Prediction of the Spatial Pattern of Carbon Emissions Based on Simulation of Land Use Change under Different Scenarios

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  • Zhenhua Wu

    (Business School, Guilin University of Electronic Technology, Guilin 541004, China)

  • Linghui Zhou

    (Business School, Guilin University of Electronic Technology, Guilin 541004, China)

  • Yabei Wang

    (Institute of Information Technology, Guilin University of Electronic Technology, Guilin 541004, China)

Abstract

Land use is an important factor in the change of carbon emissions, and predicting the spatial pattern of carbon emissions under different land use scenarios is of great significance to respond to the “double carbon” target of China. Based on the land use data of Nanjing city, Jiangsu Province, China in 2010, 2015 and 2020, this study used the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model to simulate the land use change pattern in 2030 under multiple scenarios, and predicted the carbon emissions of each subzone based on the simulation results. It also provides a carbon balance zoning from an economic and ecological point of view and proposes strategies tailored to each district. The results show that: (1) in 2030, under the ecological conservation scenario, ecological land all shows different degrees of increase, while under the cultivated land conservation scenario, construction land only increased by 1.47%. This indicates that the ecological and cultivated land protection perspectives can effectively curb the expansion of construction land. (2) The growth rate of carbon emissions in Nanjing from 2010–2030 decreased from 16.65–3.7%. This indicates that carbon emissions continue to rise, but the trend of growth is slowing down. (3) The spatial carbon emissions in Nanjing show an overall higher level in the north and lower in the center; the large expansion of building land and the concentration of industrial industries are the main reasons for the large increase in carbon emissions. Under the ecological protection scenario, the carbon emissions of Lishui, Pukou and Qixia districts were 11.05 × 10 4 t, 19.437 × 10 4 t and 10.211 × 10 4 t lower than those under the natural growth scenario, mainly because these three districts have more ecological land and the ecological protection effect is more significant. Under the cultivated land conservation scenario, the growth rate of carbon emissions slows down significantly. This indicates that the future structure of carbon emissions in Nanjing will vary significantly, and that ecological protection and arable land conservation play an important role in reducing carbon emissions. This study shows that it is difficult to reduce emissions in a concerted manner. Therefore, for different districts, differentiated land use optimization measures should be developed according to local conditions, and ecological protection and cultivated land protection scenarios should both be taken into account.

Suggested Citation

  • Zhenhua Wu & Linghui Zhou & Yabei Wang, 2022. "Prediction of the Spatial Pattern of Carbon Emissions Based on Simulation of Land Use Change under Different Scenarios," Land, MDPI, vol. 11(10), pages 1-19, October.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1788-:d:941572
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    References listed on IDEAS

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    2. Yu-Chen Zhao & Yuan Tian & Qi-Peng Zhang & Li-Yan Jiang & Qian Wang, 2024. "Simulating the Sustainable Impact of Land Use Change on Carbon Emissions in the Upper Yellow River of Gannan: A Multi-Scenario Perspective Based on the PLUS Model," Sustainability, MDPI, vol. 16(13), pages 1-17, June.
    3. Xiang-Yi Ma & Yi-Fan Xu & Qian Sun & Wen-Jun Liu & Wei Qi, 2024. "Contributing to Carbon Neutrality Targets: A Scenario Simulation and Pattern Optimization of Land Use in Shandong Province Based on the PLUS Model," Sustainability, MDPI, vol. 16(12), pages 1-24, June.
    4. Mengyuan Guo & Hong Zhang & Yan Cui & Xiaoyu Zhang & Yong Liu, 2022. "Uncovering Stakeholders’ Participation to Better Understand Land Use Change Using Multi-Agent Modeling Approach: An Example of the Coal Mining Area of Shanxi, China," Land, MDPI, vol. 11(12), pages 1-19, December.

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