Application of Inductively Coupled Plasma Spectrometric Techniques and Multivariate Statistical Analysis in the Hydrogeochemical Profiling of Caves—Case Study Cloșani, Romania

The aim of the study was to develop the hydrogeochemical profiling of caves based on the elemental composition of water and silty soil samples and a multivariate statistical analysis. Major and trace elements, including rare earths, were determined in the water and soil samples. The general characte...

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Published in:Molecules (Basel, Switzerland) Vol. 26; no. 22; p. 6788
Main Authors: Torok, Anamaria Iulia, Levei, Erika Andrea, Constantin, Silviu, Moldovan, Oana Teodora, Senila, Marin, Cadar, Oana, Casoni, Dorina, Angyus, Simion Bogdan, Tanaselia, Claudiu, Covaci, Eniko, Frentiu, Tiberiu
Format: Journal Article
Language:English
Published: Basel MDPI AG 10-11-2021
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Summary:The aim of the study was to develop the hydrogeochemical profiling of caves based on the elemental composition of water and silty soil samples and a multivariate statistical analysis. Major and trace elements, including rare earths, were determined in the water and soil samples. The general characteristics of water, anions content, inorganic and organic carbon fractions and nitrogen species (NO3− and NH4+) were also considered. The ANOVA—principal component analysis (PCA) and two-way joining analysis were applied on samples collected from Cloșani Cave, Romania. The ANOVA-PCA revealed that the hydrogeochemical characteristics of Ca2+-HCO3− water facies were described by five factors, the strongest being associated with water-carbonate rock interactions and the occurrence of Ca, Mg and HCO3− (43.4%). Although organic carbon fractions have a lower influence (20.1%) than inorganic ones on water characteristics, they are involved in the chemical processes of nitrogen and of the elements involved in redox processes (Fe, Mn, Cr and Sn). The seasonal variability of water characteristics, especially during the spring, was observed. The variability of silty soil samples was described by four principal components, the strongest influence being attributed to rare earth elements (52.2%). The ANOVA-PCA provided deeper information compared to Gibbs and Piper diagrams and the correlation analysis.
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ISSN:1420-3049
1420-3049
DOI:10.3390/molecules26226788