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首页> 外文期刊>Journal of Geochemical Exploration: Journal of the Association of Exploration Geochemists >Exploring topsoil geochemistry from the CoDA (Compositional Data Analysis) perspective: The multi-element data archive of the Campania Region (Southern Italy)
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Exploring topsoil geochemistry from the CoDA (Compositional Data Analysis) perspective: The multi-element data archive of the Campania Region (Southern Italy)

机译:从CoDA(组成数据分析)角度探索表土地球化学:Campania地区(意大利南部)的多元素数据档案库

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Soil geochemistry is often investigated by considering a large number of variables, including major, minor and trace elements. Some of the variables are usually highly correlated due to coherent geochemical behaviour, but the effect of anthropic factors tends to increase data variability, sometimes obscuring natural relationships governing their distributions. In this framework it may be difficult to identify geochemical features linked to natural phenomena as well as to separate geogenic anomaly from the anthropogenic ones. Consequently the identification of background/baseline values may be seriously compromised. However, knowledge about these reference terms is fundamental to manage and protect natural resources on different scales. Moreover, adequate estimations of background/baseline values are possible only if a sufficient number of chemical analyses are stored in complex repositories. In this contribution the multi-element data archive of the Campania Region (Southern Italy) was explored from the CoDA (Compositional Data Analysis) multivariate perspective to characterise its structure. The archive contains abundance data of Al, As, B, Ba, Ca, Co, Cr, Cu, Fe, K, La, Mg, Mn, Mo, Na, Ni, P, Pb, Sr, Th, Ti, V and Zn (mg/kg) determined in 3535 new topsoils as well as information on coordinates, geology and land cover. Under CoDA the proportionality features of abundance data are fully taken into account enhancing their relative multivariate behaviour in the correct sample space.
机译:通常通过考虑大量变量(包括主要,次要和微量元素)来研究土壤地球化学。由于连贯的地球化学行为,某些变量通常高度相关,但是人为因素的影响往往会增加数据的可变性,有时会掩盖控制其分布的自然关系。在这种框架下,可能难以确定与自然现象相关的地球化学特征,也难以区分人为的地球成因异常。因此,可能会严重损害背景/基线值的识别。但是,有关这些参考术语的知识对于管理和保护不同规模的自然资源至关重要。此外,只有在复杂的存储库中存储了足够数量的化学分析后,才能对背景/基线值进行适当的估计。在这项贡献中,从CoDA(组成数据分析)多元视角探索了坎帕尼亚地区(意大利南部)的多元素数据档案库,以表征其结构。档案中包含Al,As,B,Ba,Ca,Co,Cr,Cu,Fe,K,La,Mg,Mn,Mo,Na,Ni,P,Pb,Sr,Th,Ti,V和在3535种新表土中测定的锌(mg / kg)以及坐标,地质和土地覆盖的信息。在CoDA下,充分考虑了丰度数据的比例特征,从而增强了它们在正确样本空间中的相对多元行为。

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