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Multivariate statistics on groundwater geochemical data to identify arsenic release mechanism and related microenvironments: a case study from West Bengal, India

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Abstract

The distribution of arsenic and other parameters in groundwater of 302 tube-wells in Nakashipara and Tehatta blocks of Nadia district, West Bengal, India is analysed. The arsenic contents of 255 tube-wells out of 302 are above permissible limit of 10 μg/L and thus contaminated. As per the spatial buffer analysis, the contaminated tube-wells are found to be within 500 m distance from waterbodies, abandoned and palaeo-channels; interior of which, in presence of fresh organic carbon and arsenic bearing fines, the reductive dissolution and desorption processes occur. Among the identified three types of aquifers (1, 2, 2A), the semi to leaky-confined aquifer of Type-2 is presumably more susceptible to create arsenic release environments from sediment to groundwater. This is due to the elevated organic carbon content in the clay layer of Type-2 that boosts bacteriogenic reductive dissolution processes. The principal component analysis performed on 23 parameters of 302 water samples has identified five physico-chemical principal components responsible for arsenic release to aqueous systems from sediment. The hierarchical agglomerative cluster analysis on these five principal components using ‘Euclidean distances’ as a measure of similarity has classified the tube-wells into three distinct clusters (I, II, III). It is concluded that they actually represent the different stages of reductive dissolution of arsenic in an order of cluster II → cluster I → cluster III, indicating less reducing to higher reducing aquifer conditions. These stages mimic probable microenvironments within a broad realm of reducing environments of arsenic release. These microenvironments change rapidly within small areal range.

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Acknowledgements

The work has been carried out under FSP Code: M3CSDB/NC/CHQ//2019/26849; M3CSDB/NC/CHQ//2019/30102 of Geological Survey of India, Government of India, for the field seasons 2019-2020 and 2020-2021 respectively. The authors are thankful to Prof. Olaf Kolditz, Editor-in-Chief; and three anonymous reviewers for giving thoughtful insights which have significantly improved the presentation, scientific and technical contents of the paper. The authors are indebted to Dr. Saju Varghese, Senior Geologist, Marine and Coastal Survey Division, Geological Survey of India, Mangalore, India for carrying out the PCA and HACA analyses on the groundwater data, whose results are one of the backbones of this paper.

Funding

The work is funded under FSP Code: M3CSDB/NC/CHQ//2019/26849; M3CSDB/NC/CHQ//2019/30102 by Geological Survey of India, Government of India, for the field seasons 2019–2020 and 2020–2021, respectively.

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  1. Map and Cartography Division, Geological Survey of India, 29 J. L. Nehru Road, Kolkata, 700016, India

    Diptansu Sengupta, Pradip Kumar Mukherjee & Sudeep Manish Toppo

  2. Marine and Coastal Survey Division, Geological Survey of India, Mangladevi Road, Pandeshwar, Mangalore, 575001, India

    Basab Mukhopadhyay

  3. Geochemical Mapping Division, Geological Survey of India, Sector 12, Gandhinagar, Gujarat, 382016, India

    Jimmykumar Mahendrakumar Patel

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  1. Diptansu Sengupta
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D. S., P. K. M., and B. M. conceived the idea; B. M. and D. S. wrote the manuscript and subsequently improved with inputs from all authors. All the authors contributed during analyzing & interpreting field data, and final editing of the paper.

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Correspondence to Basab Mukhopadhyay.

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Sengupta, D., Mukherjee, P.K., Mukhopadhyay, B. et al. Multivariate statistics on groundwater geochemical data to identify arsenic release mechanism and related microenvironments: a case study from West Bengal, India. Environ Earth Sci 81, 439 (2022). https://doi.org/10.1007/s12665-022-10571-x

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