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Evaluating the Variation of Dissolved Metals on a Highway Roadside Using a Generalized Additive Mixed Model (GAMM)

机译:使用广义添加剂混合模型(GAMM)评估高速公路路边的溶解金属的变化

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摘要

Assessing metal concentrations in roadside soils requires a better understanding of the extent to which they are affected by different environmental factors such as soil texture, depth, pH, runoff concentration, and precipitation. Monthly data of dissolved Cd, Ni, Cr, Pb, Cu, and Zn concentrations in three different roadside soils (sandy loam, gravel (0-32mm) and a mixture of sandy loam and gravel) were measured during a 2-year lysimeter field study at different depths. The data was used to assess the variation of trace elements and how they were affected by environmental factors. For data interpretation, generalized additive mixed models (GAMMs) were used to explore the complex behavior of metals in heterogeneous soils by detecting linear and nonlinear trends of metal concentrations in the soil solution. As a result, the modeling approach showed that Cd, Ni, Cr, Pb, Cu, and Zn concentrations are functions of different environmental variables, which have either linear or nonlinear behavior. All investigated metals showed that pH could explain their variation. With exception of precipitation, Ni and Cr variations can nearly be explained by the same environmental factors used in this study (time, pH, infiltration volume, roadside soil type, runoff concentrations, and depth). During the study period, we found that Zn variation can be explained by its nonlinear relationship with all the significant studied environmental factors. As the depth increases from the surface to 30cm of depth, the metal concentration of Cd, Ni, Cr, Pb, and Zn increases. Surprisingly, the roadside soil consisting of gravel has the lowest organic carbon and showed the lowest median concentration of Cd, Ni, Pb, Cu, and Zn at 30cm. Moreover, the model showed that the surface runoff volume has no effect on the metal variation in the soil solution.
机译:评估路边土壤中的金属浓度需要更好地了解它们受不同环境因素(例如土壤质地,深度,pH,径流浓度和降水)的影响程度。在为期2年的测渗仪田间,测量了三种不同路旁土壤(砂壤土,砾石(0-32mm)以及沙壤土和砾石的混合物)中溶解的Cd,Ni,Cr,Pb,Cu和Zn浓度的月度数据在不同的深度学习。该数据用于评估痕量元素的变化以及它们如何受到环境因素的影响。为了进行数据解释,使用广义添加剂混合模型(GAMM)通过检测土壤溶液中金属浓度的线性和非线性趋势来探索非均质土壤中金属的复杂行为。结果,建模方法表明Cd,Ni,Cr,Pb,Cu和Zn的浓度是不同环境变量的函数,这些环境变量具有线性或非线性行为。所有调查的金属均表明pH可以解释其变化。除降水外,镍和铬的变化几乎可以用本研究中使用的相同环境因素来解释(时间,pH,入渗量,路旁土壤类型,径流浓度和深度)。在研究期间,我们发现锌的变化可以用其与所有重要的环境因素之间的非线性关系来解释。随着深度从表面增加到30cm,Cd,Ni,Cr,Pb和Zn的金属浓度增加。出人意料的是,由砾石组成的路边土壤有机碳含量最低,并且在30cm处的Cd,Ni,Pb,Cu和Zn的中位浓度最低。此外,该模型表明,地表径流量对土壤溶液中的金属变化没有影响。

著录项

  • 来源
    《Water, Air, and Soil Pollution》 |2019年第4期|93.1-93.15|共15页
  • 作者单位

    Tech Univ Berlin, Dept Ecol Ecohydrol & Landscape Evaluat, Ernst Reuter Pl 1, D-10587 Berlin, Germany;

    Tech Univ Berlin, Dept Ecol Ecohydrol & Landscape Evaluat, Ernst Reuter Pl 1, D-10587 Berlin, Germany|Tech Univ Berlin, Dept Ecol, Soil Conservat, Berlin Ernst Reuter Pl 1, D-10587 Berlin, Germany;

    UPC, Dept Stat & Operat Res, Barcelona, Spain;

    Tech Univ Berlin, Dept Ecol, Soil Conservat, Berlin Ernst Reuter Pl 1, D-10587 Berlin, Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Metals; Roadside soil; Generalized additive mixed models (GAMMs); Environmental factors;

    机译:金属;路旁土壤;广义添加剂混合模型(GAMM);环境因素;

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