首页> 外文期刊>The Science of the Total Environment >Application of exploratory and Spatial Data Analysis (SDA), singularity matrix analysis, and fractal models to delineate background of potentially toxic elements: A case study of Ahvaz, SW Iran
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Application of exploratory and Spatial Data Analysis (SDA), singularity matrix analysis, and fractal models to delineate background of potentially toxic elements: A case study of Ahvaz, SW Iran

机译:探索性和空间数据分析(SDA),奇异性矩阵分析和分形模型的应用划分潜在有毒元素背景:Ahvaz,SW伊朗的案例研究

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摘要

It is essential to study spatial distribution of Potentially Toxic Elements (PTEs) in surface soil, and separate PTEs geochemical background from their human sources, and also determine their correlation with other environmental factors in order to assess their impacts on humans, provide realistic environmental geochemical maps, and carry out soil management. For this purpose, this study was designed to investigate the surface soil in Ahvaz, Southwest of Iran. The applied methods were exploratory data analysis (EDA), including boxplot, Q-Q plot, probability plot (P-P), concentration-area (C-A), number-size (N-S) fractal model, and singularity index (SI) model. The obtained results revealed that the fractal models led to a more realistic distinction among the geochemical population compared to the EDA methods such as probability plot. Furthermore, the C-A model was found to be more effective on the separation of subpopulation compared to the N-S and P-P models. The studied elements exhibited a similar pattern implying that pollution is a function of geochemical dispersion regarding the surface soil in Ahvaz (Zn ≫ Pb > Cu > As). The studied metals-major elements plot also indicated that there was no meaningful relationship between Pb, Zn, Cu, and major elements in the study area. Plots of association of Pb. Zn, Cu, and As distinctly showed two general geogenic and anthropogenic populations. Moreover, the results of SI revealed that the highly contaminated area was consistent with the main defined hotspots and anthropogenic sources of elements as well as places affected by the contaminated area that have not been reported in previous studies. Furthermore, a combination of geochemical and geographical model comprising different statistical models was developed to more effectively separate geogenic from anthropogenic sources. Also, the geochemical background for the studied elements (Pb 180 mg/kg; Cu 200 mg/kg; Zn 90 mg/kg; As 65 mg/kg) was shown to be higher than the Iranian soil quality guideline with Pb, Zn, Cu, and As of 100,80,200, and 18 mg/kg, respectively.
机译:必须研究表面土壤中潜在有毒元素(PTE)的空间分布,并将PTES地球化学背景分离出来的人类来源,并确定其与其他环境因素的相关性,以便评估其对人类的影响,提供现实的环境地球化学地图,并进行土壤管理。为此目的,本研究旨在探讨伊朗西南部Ahvaz的表面土壤。应用方法是探索性数据分析(EDA),包括盒子,Q-Q曲线,概率图(P-P),浓度区(C-A),数尺寸(N-S)分形模型和奇异性指数(SI)模型。获得的结果表明,与诸如概率图之类的EDA方法相比,分形模型导致地球化学群体中更现实的区别。此外,与N-S和P-P型号相比,发现C-A模型更有效地对亚泊素的分离。所研究的元件表现出类似的模式,暗示污染是一种具有关于AHVAZ(Zn + Pb> Cu> As)的地表土壤化合理分散体的函数。研究的金属主要元素图也表明,研究区中的PB,Zn,Cu和主要元素之间没有有意义的关系。 PB关联的情节。 Zn,Cu,并且明显地显示出两种遗传造林和人为群体。此外,Si的结果显示,高度污染的区域与主要明确的热点和人为元素来源以及受污染区域影响的地方一致,尚未在以前的研究中尚未报告。此外,开发了包括不同统计模型的地球化学和地理模型的组合,以更有效地将胎生源与人体源分开。此外,所研究的元件的地球化学背景(Pb 180mg / kg; Cu 200 mg / kg; Zn 90mg / kg; Zn90mg / kg; Zn90mg / kg; Zn90mg / kg; Zn90mg / kg)被证明高于伊朗土壤质量指南与Pb,Zn, Cu,以及100,80,200和18毫克/千克。

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