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2022, 01, v.52 21-31
基于县域尺度土地利用碳排放的时空分异及影响因素研究
基金项目(Foundation): 国家自然科学基金资助项目(41971271,41871185)
邮箱(Email): chw@nwu.edu.cn;
DOI: 10.16152/j.cnki.xdxbzr.2022-01-003
摘要:

基于县域尺度研究土地利用变化导致的碳排放变化、空间异质性及影响因素,对推动土地利用方式向低碳化转变及制定合理有效的政策意义重大。该文以陕西省为例,估算县域1990—2015年土地利用导致的碳排放,探索时空变化的同时分析了不同县域的碳排放风险及其影响因素。结果表明,陕西省土地利用碳排放呈不断增加趋势,年均增长率为13.20%,其中建设用地是主要碳源,耕地的碳源作用不断减弱,林地是主要的碳汇,草地发挥着弱碳汇作用;1990—2015年各县域碳排放总量均出现不同程度的增加,且不同县域碳排放增量和碳排放风险差异显著,其中,市辖区的变化最为明显;GDP、城市化水平、高程、政策是影响陕西省县域土地利用碳排放的主要因素,且城市化水平对碳排放量的解释作用最大。

Abstract:

Research on the changes in carbon emissions, spatial heterogeneity and influencing factors caused by land use changes based on the county scale is of great significance for promoting the transformation of land use to low-carbon mode and formulating reasonable and effective policies. Taking Shaanxi Province as an example, this paper estimated the carbon emissions caused by land use in counties from 1990 to 2015, explored temporal and spatial changes, and analyzed the carbon emission risks and influencing factors of different counties. The results showed that, the carbon emissions from land use in Shaanxi Province were increasing, with an average annual growth rate of 13.20%, of which construction land was the main carbon source, and the role of arable land was continuously weakening; forest land was the main carbon sink, and grassland played a role of weak carbon sink; from 1990 to 2015, the total carbon emissions of all counties had increased to varying degrees, and the increase in carbon emissions and carbon emissions risks of different counties were significantly different. Among them, the changes in the municipal districts were the most obvious; GDP, urbanization level, elevation, and policies were the main factors affecting carbon emissions from county land use in Shaanxi Province, and the level of urbanization had the greatest explanatory effect on carbon emissions.

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基本信息:

DOI:10.16152/j.cnki.xdxbzr.2022-01-003

中图分类号:X321;F301.24

引用信息:

[1]张杰,陈海,刘迪等.基于县域尺度土地利用碳排放的时空分异及影响因素研究[J].西北大学学报(自然科学版),2022,52(01):21-31.DOI:10.16152/j.cnki.xdxbzr.2022-01-003.

基金信息:

国家自然科学基金资助项目(41971271,41871185)

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