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Utilization of Natural Zeolite (Scolecite) to Reduce Arsenic Contamination of Water in Relation to Machine Learning Approach

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Abstract

Among heavy metals, arsenic contamination in water resources is a major concern due to its harmful effects on human health as slow poison behaviour affecting many states of India and at global level. The present study is about efficiency of Scolecite (CaAl2Si3O10.3H2O), a natural zeolite mineral, to remove arsenic contamination from water. The arsenic-contaminated water samples were collected from both industrial areas and non-industrial areas which include Singrauli industrial sites of Madhya Pradesh/Uttar Pradesh, Jalangi Block and various thermal power station areas of West Bengal, Kaudikasa-Rajnandgaon district of Chhattisgarh and Kakching area of Manipur. After conducting rigorous experimental studies, it was observed that the collected water samples had been reduced up to below 10 ppb within the permissible limit of WHO in 7 days with different quantities of scolecite (as 0.5 g/50 ml, 2.5 g/50 ml, 5 g/50 ml and 10 g/100 ml). The reduction of arsenic and the absorbing properties were identified as negative charge developed on the crystal face of Si3Al3 in scolecite. The XRD analysis of filtrate, which remained after filtration of samples prior to chemical analysis for arsenic concentration, is that specific hkl faces (i.e. 111, 040, 132, 400 and 240) are more affected in increase of pH in scolecite-treated water samples and hence play a major role in arsenic removal. The adsorption efficiency of arsenic (As) from water samples was predicted in the present study using an artificial neural network (ANN) model and perceived that the smallest quantity of scolecite may reduce higher amount of As in proportionate water samples.

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Acknowledgements

The authors thanks and acknowledge the support received from the leadership of K.R. Mangalam University, Gurugram, Haryana, India, and Director, CSIR-Central Institute of Mining and Fuel Research, Dhanbad, India, for inspiring and motivating to publish the paper.

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Conceptualization: Chandra Shekhar Dubey, Arnold Luwang Usham, Seema Raj, Dilraj Preet Kaur, Shweta Bansal and Dericks P. Shukla. Methodology: Chandra Shekhar Dubey and Arnold Luwang Usham. Formal analysis and investigation: Chandra Shekhar Dubey, Arnold Luwang Usham, Seema Raj, Dilraj Preet Kaur, Shweta Bansal and Dericks P. Shukla. Writing—original draft preparation: Chandra Shekhar Dubey, Arnold Luwang Usham, Seema Raj, Dilraj Preet Kaur, Shweta Bansal and Dericks P. Shukla. Writing—review and editing: Chandra Shekhar Dubey, Arnold Luwang Usham, Seema Raj, Dilraj Preet Kaur, Shweta Bansal and Dericks P. Shukla. Resources: Chandra Shekhar Dubey and Arnold Luwang Usham and Dericks P. Shukla. Supervision: Chandra Shekhar Dubey.

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Correspondence to Seema Raj.

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Dubey, C.S., Usham, A.L., Raj, S. et al. Utilization of Natural Zeolite (Scolecite) to Reduce Arsenic Contamination of Water in Relation to Machine Learning Approach. Water Air Soil Pollut 235, 129 (2024). https://doi.org/10.1007/s11270-024-06946-4

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  • DOI: https://doi.org/10.1007/s11270-024-06946-4

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