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首页> 外文期刊>Journal of Geochemical Exploration: Journal of the Association of Exploration Geochemists >Soil geochemical follow-up in the Cilento World Heritage Park (Campania, Italy) through exploratory compositional data analysis and C-A fractal model
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Soil geochemical follow-up in the Cilento World Heritage Park (Campania, Italy) through exploratory compositional data analysis and C-A fractal model

机译:Cilento World Heritage Park(意大利Campania,意大利)土壤地球化学后续通过探索性的组成数据分析和C-A分形模型

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Campania Region (southern Italy) is characterized by several elemental soil anomalies both geogenic and anthropogenic. Parts of these anomalies occur into the World Heritage Territory known as "National Park of the Cilento and Vallo di Diano", where this follow-up study has been carried out. In this paper, a methodology based on compositional data analysis (CoDA) and factor score C-A fractal model was applied on geochemical data from the above study in order to identify geochemical signatures associated anomalies. Eighty-one top soil samples were collected over an area of 98 km(2), and analyzed by ICP-MS after aqua regia digestion. Frequency based method (edaplots, classical and robust compositional biplot) and frequency space-method (factor score maps) were applied to visualize the correlation between variables and their main features into the survey areas. The different geochemical patterns were distinguished by a multivariate analysis combined with Concentration-Area (C-A) fractal method. Results show that geochemical data should be transformed under a compositional perspective to avoid artefacts, prior to statistical computations. Indeed, ilr-transformed data show a distinct bimodal distribution for several elements. This type of distribution appears masked considering raw and lognormal data. A "robustification" of the variables dataset permits to found a more clear relationship between variables. Factor score maps based on ilr-transformed variables and C-A plot cut off threshold displayed different geochemical patterns. In our survey area soil alteration phenomena could mask the nature of parental rock. The factor scores maps highlight an antithetic behaviour of many elements. Elements characterized by elevated geochemical mobility, such as Ca and Mg, are negatively correlated with Chemical Alteration Index values. Instead, Sn, Th, Be, Al are characterized by elevated geochemical stability; for this reason they are found where high-weathered soils occurs. The presence of elements such as Co, Cu Fe, Ni, Cr, Zn, K, Mn is mainly controlled by terrigenous flysch deposition. As, Pb (exceeding the CSC) and Sb association mainly occur in correspondence of urban areas and where traffic jams are frequent.
机译:Campania地区(意大利南部)的特征在于几种元素的土壤异常,造成了造环和人为。这些异常的部分发生在世界遗产领域被称为“Cilento和Vallo di Diano国家公园”,这项后续研究已经开展。本文基于组合数据分析(CODA)和因子评分C-A分形模型的方法在来自上述研究的地球化学数据上应用了一种方法,以鉴定地球化学签名相关的异常。收集八十一体土壤样品在98公里(2)的面积上收集,并在Aqua Regia消化后由ICP-MS进行分析。应用基于频率的方法(edaplots,经典和鲁棒成分化学方法)和频率空间方法(因子评分图)以可视化变量与其主要特征之间的相关性在调查区域。通过与浓度区(C-A)分形法相结合的多变量分析来区分不同的地球化学图案。结果表明,在统计计算之前,应在组合角度下改变地球化学数据以避免人工制品。实际上,ILR转换的数据显示了几个元素的不同双峰分布。考虑到原始和逻辑数据,此类分布出现屏蔽。变量数据集的“稳定化”允许在变量之间找到更明确的关系。基于ILR变换变量的因子评分映射和C-A曲线图截止阈值显示了不同的地球化学模式。在我们的调查区域中,土壤改变现象可能会掩盖父母岩石的性质。因子分数映射突出了许多元素的反向行为。特征在于地球化学迁移率升高的元件,例如Ca和Mg,与化学改变指标值呈负相关。相反,Sn,Th,是,Al的特征在于地球化学稳定性升高;出于这个原因,它们被发现发生高风化的土壤。诸如CO,Cu Fe,Ni,Cr,Zn,K,Mn的元素的存在主要由土刺氏沉积控制。 AS,PB(超过CSC)和SB协会主要发生在城市地区的对应关系中,交通拥堵频繁。

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