Journal
JOURNAL OF GEOCHEMICAL EXPLORATION
Volume 212, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.gexplo.2020.106508
Keywords
Uranium; Thorium; Potassium; Soil; Compositional analysis; Geochemical mapping
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Funding
- Istituto Zooprofilattico Sperimentale del Mezzogiorno (IZSM) [497/2013, n.585]
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Uranium, thorium and potassium are distinguished in different compartments of the environmental media according to the inputs, the fate and the distribution patterns that occur in the ecosystems. Thus, an understanding of the sources patterns and behaviours of these elements in soils, their rock-soil relationships and potential toxicity or deficiency problems associated with them is nowadays a relevant concern for environmental protection and human health. A robust compositional computation analysis coupled with frequency spatial-method (Fractal model) is applied on 3 selected elements (U, Th and K), based on a large dataset of 7134 topsoil samples over the whole Campania region, and investigated elements concentrations were analysed (after aqua regia extraction) by inductively coupled plasma mass spectrometry (ICP-MS). In this survey, U concentrations ranged from 0.05 to 43.2 mg kg(-1) with a mean value of 3.35 mg kg(-1), Th concentrations ranged from 0.3 to 64.30 mg kg(-1) with a mean values of 11.95 mg kg(-1) and K concentrations ranged from 0.03 to 5.97% with a mean value of 0.68%. The mean values for U and Th are slightly above the mean crustal abundances, while K is slightly below them. Fractal mapping of Centred-log transformed (clr) data of investigated elements show that the U, Th and K geochemical anomalies can be ascribed to geology-related volcanic sources. Indeed, the highest values in soils were assessed in the surveyed alkaline magmatic areas in the central-western part of the region characterized by volcanic rocks, whereas lowest values are found in areas characterized by silico-clastic and carbonate deposits, occurring mostly in the southern and eastern part of the region. Evidence from this study showed that compositional data transformations such as clr transformation could help to avoid artefacts, prior to statistical computations.
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