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      Assessment of groundwater safety surrounding contaminated water storage sites using multivariate statistical analysis and Heckman selection model: a case study of Kazakhstan

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          Abstract

          Petrochemical enterprises in Kazakhstan discharge polluted wastewater into special recipients. Contaminants infiltrate through the soil into the groundwater, which potentially affects public health and environment safety. This paper presents the evaluation of a 7-year monitoring program from one of the factories and includes nineteen variables from nine wells during 2013–2019. Several multivariate statistical techniques were used to analyse the data: Pearson’s correlation matrix, principal component analysis and cluster analysis. The analysis made it possible to specify the contribution of each contaminant to the overall pollution and to identify the most polluted sites. The results also show that concentrations of pollutants in groundwater exceeded both the World Health Organization and Kazakhstani standards for drinking water. For example, average exceedance for total petroleum hydrocarbons was 4 times, for total dissolved solids—5 times, for chlorides—9 times, for sodium—6 times, and total hardness was more than 6 times. It is concluded that host geology and effluents from the petrochemical industrial cluster influence the groundwater quality. Heckman two-step regression analysis was applied to assess the bias of completed analysis for each pollutant, especially to determine a contribution of toxic pollutants into total contamination. The study confirms a high loading of anthropogenic contamination to groundwater from the petrochemical industry coupled with natural geochemical processes.

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                Author and article information

                Contributors
                ivan.radelyuk@tvrl.lth.se
                Journal
                Environ Geochem Health
                Environ Geochem Health
                Environmental Geochemistry and Health
                Springer Netherlands (Dordrecht )
                0269-4042
                1573-2983
                8 August 2020
                8 August 2020
                2021
                : 43
                : 2
                : 1029-1050
                Affiliations
                [1 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Department of Water Resources Engineering, , Lund University, ; Box 118, 22100 Lund, Sweden
                [2 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Center for Middle Eastern Studies, , Lund University, ; 22100 Lund, Sweden
                [3 ]GRID grid.443601.4, ISNI 0000 0004 0387 8046, Department of Chemistry and Chemical Technology, , Pavlodar State University, ; 140000 Pavlodar, Kazakhstan
                [4 ]GRID grid.171588.2, ISNI 0000 0004 0606 4849, Kazakh National Agrarian University, ; 050010 Almaty, Kazakhstan
                Author information
                http://orcid.org/0000-0002-6067-3034
                Article
                685
                10.1007/s10653-020-00685-1
                7925494
                32770289
                e460b2bf-ab45-452a-9b57-b21d232db48c
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 November 2019
                : 30 July 2020
                Categories
                Original Paper
                Custom metadata
                © Springer Nature B.V. 2021

                kazakhstan,petrochemical industry,water quality,principal component analysis,cluster analysis,heckman selection model

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