湖北农业科学 ›› 2024, Vol. 63 ›› Issue (9): 68-72.doi: 10.14088/j.cnki.issn0439-8114.2024.09.012

• 资源·环境 • 上一篇    下一篇

甘肃省土地利用碳排放的时序特征及影响因素

张园园, 渠丽萍   

  1. 中国地质大学(武汉)公共管理学院,武汉 430074
  • 收稿日期:2024-05-30 出版日期:2024-09-25 发布日期:2024-09-30
  • 通讯作者: 渠丽萍(1973-),女,山西晋中人,副教授,主要从事土地利用与国土空间规划研究,(电话)18602765272(电子信箱)lp_qu@163.com。
  • 作者简介:张园园(1996-),女,山西太原人,硕士,主要从事土地调查与评价研究,(电话)15536524260(电子信箱)1134112639@qq.com。
  • 基金资助:
    国家自然科学基金面上项目(42071254)

Temporal characteristics and influencing factors of carbon emissions from land use in Gansu Province

ZHANG Yuan-yuan, QU Li-ping   

  1. School of Public Administration,China University of Geosciences(Wuhan),Wuhan 430074,China
  • Received:2024-05-30 Published:2024-09-25 Online:2024-09-30

摘要: 以甘肃省为研究区,在测算甘肃省2000—2020年土地利用碳排放量的基础上,采用Tapio脱钩模型和LMDI模型分析土地利用碳排放影响因素。结果表明,2000—2020年,甘肃省土地利用碳排放的贡献值为3 755.78万t,但是增长率呈明显的下降趋势。土地利用碳排放与经济发展间呈弱脱钩状态,虽然经济发展导致的土地利用碳排放量不断增加,但这种增速要低于经济增长的速度,且脱钩指数持续下降,逐渐接近于强脱钩状态。经济发展是造成甘肃省土地利用碳排放增加的主要原因,土地利用结构对其产生负向影响,而土地碳排放密度、经济发展、能源利用和人口规模则对其产生正向影响。

关键词: 土地利用, 碳排放, Tapio脱钩分析, 时序特征, LMDI模型, 甘肃省

Abstract: Taking Gansu Province as the research area, based on the calculation of land use carbon emissions in Gansu Province from 2000 to 2020, the Tapio decoupling model and LMDI model were used to analyze the influencing factors of land use carbon emissions. The results showed that from 2000 to 2020, the contribution value of land use carbon emissions in Gansu Province was 37.557 8 million tons, but the growth rate showed a significant downward trend. There was a weak decoupling between carbon emissions from land use and economic development,although the carbon emissions from land use caused by economic development continued to increase, this growth rate was slower than the economic growth rate, and the decoupling index continued to decline, gradually approaching a strong decoupling state.Economic development was the main reason for the increase in carbon emissions from land use in Gansu Province. Land use structure had a negative impact on it, while land carbon emissions density, economic development, energy utilization, and population size had a positive impact.

Key words: land use, carbon emissions, Tapio decoupling analysis, temporal characteristics, LMDI model, Gansu Province

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