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Bivariate probability plots: A method for delineating different populations in soil geochemical data

机译:双变量概率图:一种在土壤地球化学数据中描绘不同种群的方法

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Bivariate probability plots (BPP) have been developed as an extension to univariate probability plots (UPP) to characterize and separate geochemical populations. The two approaches have been applied to Pb, Zn, As and Cd in soils collected from the vicinity of the Irankuh Pb and Zn mines to compare their capacity to separate geogenic patterns from anthropogenic contamination in nearby agricultural land. Separating populations by UPP and comparing thresholds with the Iranian regulatory limits for metal concentrations in agricultural land indicates that the mining operations and adjacent open ground areas are heavily contaminated. Separating the samples into different populations using BPP, based on typical element associations of Pb with Zn and As with Cd, demonstrates the extent of anthropogenic contamination is relatively higher for Pb and Zn than the other two elements. This is attributed to dispersion of dust from the mining site. Outside this area elevated metal concentrations appear related to geogenic factors, and which is attributed to weathering and erosion of underlying mineralized lithologies. (C) 2019 Published by Elsevier B.V.
机译:已经开发了双变量概率图(BPP)作为单变量概率图(UPP)的扩展,以表征和分离地球化学种群。这两种方法已应用于从伊朗核铅矿和锌矿附近收集的土壤中的铅,锌,砷和镉,以比较它们从附近农田的人为污染中分离出地质类型的能力。通过UPP将人口分开,并将阈值与伊朗有关农田中金属浓度的监管限值进行比较,表明采矿作业和邻近的露天场地受到严重污染。基于铅和锌以及砷和镉的典型元素关联,使用BPP将样品分为不同的种群,证明人为污染的程度比其他两种元素高。这归因于来自采矿现场的灰尘散布。在该区域之外,金属浓度升高似乎与成矿因素有关,这归因于风化作用和潜在矿化岩性的侵蚀。 (C)2019由Elsevier B.V.发布

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