利用PLUS和InVEST模型评估呼和浩特市土地利用和碳储量变化:多情景模拟

IF 5.4 Q1 ENVIRONMENTAL SCIENCES
Jiaping Zhang , Penghui Cao , Ruhizal Roosli
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引用次数: 0

摘要

在全球气候变化和快速城市化的背景下,土地利用变化对区域碳封存的影响是一个至关重要的问题。利用斑块生成土地利用模拟(PLUS)模型和生态系统服务与权衡综合评价(InVEST)模型对呼和浩特市土地利用格局进行了预测。利用历史土地利用数据和15个影响因子对不同情景下的碳储量动态进行了评价。从2000年到2020年,呼和浩特市碳储量净损失158万吨,主要是由于耕地和草地转化为发达土地。到2030年,自然发展情景下的碳储量预计达到14767万吨,生态保护情景下的碳储量预计达到14846万吨,经济增长情景下的碳储量预计达到14733万吨。在生态保护情景下,预计碳储量最高,突出了环境法规在减少碳损失和促进可持续发展方面的重要性。本研究提出了一种可复制的方法,将情景建模与政策导向干预相结合,为快速城市化地区的土地利用规划和碳管理提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing land use and carbon storage changes using PLUS and InVEST models: A multi-scenario simulation in Hohhot
The impact of land-use change on regional carbon sequestration is a crucial concern in the context of global climate change and rapid urbanization. This study utilized the Patch-Generating Land-Use Simulation (PLUS) model and the Integrated Valuation of Ecosystem Services and Trade -offs (InVEST) model to predict land-use patterns in Hohhot, China. The dynamics of carbon stocks under various scenarios were evaluated using historical land-use data and 15 influencing factors. From 2000 to 2020, Hohhot City experienced a net loss of 1.58 million tonnes of carbon storage, mainly due to the conversion of arable land and grassland into developed land. By 2030, carbon storage is projected to reach 147.67 million tonnes in the natural-development scenario, 148.46 million tonnes in the ecological-protection scenario, and 147.33 million tonnes in the economic-growth scenario. The highest carbon storage was expected under the ecological-protection scenario, highlighting the importance of environmental regulations in reducing carbon loss and promoting sustainable development. This study presents a replicable methodology that integrates scenario-modeling with policy-oriented interventions, providing valuable insights for land-use planning and carbon management in rapidly urbanizing regions.
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来源期刊
Environmental and Sustainability Indicators
Environmental and Sustainability Indicators Environmental Science-Environmental Science (miscellaneous)
CiteScore
7.80
自引率
2.30%
发文量
49
审稿时长
57 days
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