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Analysis and assessment of heavy metal contamination in the vicinity of Lake Atamanskoe (Rostov region, Russia) using multivariate statistical methods

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Abstract

Assessment of spatial patterns of potentially toxic metals is one of the most urgent tasks in soil chemistry. In this study, descriptive statistics and three methods of multivariate statistical analysis, such as the hierarchical cluster analysis (HCA), correlation analysis, and conditional inference tree (CIT), were used to identify patterns and potential sources of heavy metals (Co, Ni, Cu, Cr, Pb, MnO, and Zn). The investigation was carried out on 81 sample points, using 20 testing parameters. A strong positive correlation found among Ni, Cu, Zn, and HCA results has confirmed the common origin of the elements from waste discharge. Hierarchical CA divided the 81 test sites into 5 classes based on the soil quality and HMs contamination similarity. Regression trees for Cr, Pb, Zn, and Cu were verified by the splitting factor including HMs content and soil chemistry factors. The CIT has revealed that the elements (Cr, Pb, Zn, and Cu) concentration values are split at the first level by some other metal, indicating common anthropogenic impact resulting from industrial waste discharges. The factors at the next hierarchical level of splitting, in addition to the HMs, include compounds belonging to soil chemistry variables (SiO2, Al2O3, and K2O). The CIT nonlinear regression model is in good agreement with the data: R2 values for log-transformed concentrations of Cr, Pb, Zn, and Cu are equal to 0.775; 0.774; 0.775; 0.804, respectively.

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Acknowledgements

This research was financially supported by the Ministry of Science and Higher Education of the Russian Federation (No. 0852-2020-0029), the Russian Foundation for Basic Research (Grant No.19-34-60041) and budget theme 0137-2019-0008 (GEOKHI RAS).

Funding

This research was sponsored by the Ministry of Science and Higher Education of the Russian Federation (No. 0852-2020-0029), the Russian Foundation for Basic Research (Grant No.19-34-60041) and budget theme 0137-2019-0008 (GEOKHI RAS).

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Authors and Affiliations

  1. Institute of Geochemistry and Analytical Chemistry, Russian Academy of Sciences, Moscow, 119991, Russian Federation

    Vitaly G. Linnik

  2. Institute of Environmental Sciences, Kazan Federal University, Kazan, 420097, Russian Federation

    Anatoly A. Saveliev

  3. Federal Research Centre the Southern Scientific Centre of the Russian Academy of Sciences, Rostov-on-Don, 344006, Russian Federation

    Tatiana V. Bauer

  4. Southern Federal University, 194/1 prosp. Stachki ave, Rostov-on-Don, 344006, Russian Federation

    Tatiana M. Minkina & Saglara S. Mandzhieva

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  1. Vitaly G. Linnik
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  2. Anatoly A. Saveliev
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  3. Tatiana V. Bauer
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  4. Tatiana M. Minkina
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  5. Saglara S. Mandzhieva
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Contributions

Vitaly Linnik was involved in methodology, original draft preparation, writing—review & editing. Anatoly Saveliev helped in software and formal analysis, writing—review & editing. Tatiana Bauer contributed to formal analysis, investigation, writing—review & editing. Tatiana Minkina was involved in conceptualization, supervision, writing—review & editing. Saglara Mandzhieva helped in investigation, data curation, formal analysis, supervision.

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Correspondence to Saglara S. Mandzhieva.

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Linnik, V.G., Saveliev, A.A., Bauer, T.V. et al. Analysis and assessment of heavy metal contamination in the vicinity of Lake Atamanskoe (Rostov region, Russia) using multivariate statistical methods. Environ Geochem Health 44, 511–526 (2022). https://doi.org/10.1007/s10653-021-00853-x

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