北京耕地土壤重金属空间自回归模型及影响因素

    Spatial autogression model for heavy metals in cultivated soils of Beijing

    • 摘要: 为了揭示土壤重金属含量与其影响因素间的作用关系,为土壤重金属的污染控制和治理提供参考,该研究以北京市耕作土壤重金属元素为例,采用传统线性回归模型和空间自回归模型分析和比较了土壤重金属含量及其影响因素间的相关关系。结果表明:Cr、Ni、Zn、Hg空间自回归模型的拟合度较传统线性回归模型好,并且残差的空间自相关性消失。因此,空间自回归模型能够很好地解释重金属含量与其影响因素间的相关关系。结果表明:Cr、Ni含量的影响因素主要为土壤母质和土地利用强度,Zn、Hg含量的主要影响因素为道路、工矿企业和土壤母质。

       

      Abstract: In order to effectively reveal the effect of influencing factors on heavy metals and provide scientific basis for controlling heavy metals pollution, conventional linear regression model and spatial autogression model were applied to analyze the relationship between heavy metals and their influencing factors in Beijing cultivated soils. The results showed that the spatial autogression model for Cr, Ni, Zn, and Hg had a better goodness-of-fit than conventional linear regression model, and yielded residuals without spatial autocorrelation, indicating that the spatial autogression model could explain the relationship between heavy metals and their influencing factors excellently. Results showed that the important influencing factors for Cr and Ni were soil parent materials and land use intensity, and the main influencing factors for Zn and Hg were mining establishments, road and oil parent materials.

       

    /

    返回文章
    返回