Utilization of Natural Zeolite (Scolecite) to Reduce Arsenic Contamination of Water in Relation to Machine Learning Approach
IR@CIMFR: CSIR-Central Institute of Mining and Fuel Research, Dhanbad
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| Title |
Utilization of Natural Zeolite (Scolecite) to Reduce Arsenic Contamination of Water in Relation to Machine Learning Approach
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| Creator |
Dubey, Chandra Shekhar
Usham, Arnold Luwang Raj, Seema Kaur, Dilraj Preet Bansal, Shweta Shukla , Dericks P. |
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| Subject |
Coal Characterisation
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| Description |
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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| Publisher |
Springer
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| Date |
2024-02-05
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| Type |
Article
PeerReviewed |
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| Identifier |
Dubey, Chandra Shekhar and Usham, Arnold Luwang and Raj, Seema and Kaur, Dilraj Preet and Bansal, Shweta and Shukla , Dericks P. (2024) Utilization of Natural Zeolite (Scolecite) to Reduce Arsenic Contamination of Water in Relation to Machine Learning Approach. Water, Air, & Soil Pollution, 235 (129). ISSN 0253-4126
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| Relation |
http://cimfr.csircentral.net/2684/
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