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Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil
Groundwater arsenic (As) pollution is a naturally occurring phenomenon posing serious threats to human health. To mitigate this issue, we synthesized a novel bentonite-based engineered nano zero-valent iron (nZVI-Bento) material to remove As from contaminated soil and water. Sorption isotherm and ki...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10004430/ https://www.ncbi.nlm.nih.gov/pubmed/36903414 http://dx.doi.org/10.3390/molecules28052168 |
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author | Raza, Md Basit Datta, Siba Prasad Golui, Debasis Barman, Mandira Das, Tapas Kumar Sahoo, Rabi Narayan Upadhyay, Devi Rahman, Mohammad Mahmudur Behera, Biswaranjan Naveenkumar, A |
author_facet | Raza, Md Basit Datta, Siba Prasad Golui, Debasis Barman, Mandira Das, Tapas Kumar Sahoo, Rabi Narayan Upadhyay, Devi Rahman, Mohammad Mahmudur Behera, Biswaranjan Naveenkumar, A |
author_sort | Raza, Md Basit |
collection | PubMed |
description | Groundwater arsenic (As) pollution is a naturally occurring phenomenon posing serious threats to human health. To mitigate this issue, we synthesized a novel bentonite-based engineered nano zero-valent iron (nZVI-Bento) material to remove As from contaminated soil and water. Sorption isotherm and kinetics models were employed to understand the mechanisms governing As removal. Experimental and model predicted values of adsorption capacity (q(e) or q(t)) were compared to evaluate the adequacy of the models, substantiated by error function analysis, and the best-fit model was selected based on corrected Akaike Information Criterion (AICc). The non-linear regression fitting of both adsorption isotherm and kinetic models revealed lower values of error and lower AICc values than the linear regression models. The pseudo-second-order (non-linear) fit was the best fit among kinetic models with the lowest AICc values, at 57.5 (nZVI-Bare) and 71.9 (nZVI-Bento), while the Freundlich equation was the best fit among the isotherm models, showing the lowest AICc values, at 105.5 (nZVI-Bare) and 105.1 (nZVI-Bento). The adsorption maxima (q(max)) predicted by the non-linear Langmuir adsorption isotherm were 354.3 and 198.5 mg g(−1) for nZVI-Bare and nZVI-Bento, respectively. The nZVI-Bento successfully reduced As in water (initial As concentration = 5 mg L(−1); adsorbent dose = 0.5 g L(−1)) to below permissible limits for drinking water (10 µg L(−1)). The nZVI-Bento @ 1% (w/w) could stabilize As in soils by increasing the amorphous Fe bound fraction and significantly diminish the non-specific and specifically bound fraction of As in soil. Considering the enhanced stability of the novel nZVI-Bento (upto 60 days) as compared to the unmodified product, it is envisaged that the synthesized product could be effectively used for removing As from water to make it safe for human consumption. |
format | Online Article Text |
id | pubmed-10004430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100044302023-03-11 Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil Raza, Md Basit Datta, Siba Prasad Golui, Debasis Barman, Mandira Das, Tapas Kumar Sahoo, Rabi Narayan Upadhyay, Devi Rahman, Mohammad Mahmudur Behera, Biswaranjan Naveenkumar, A Molecules Article Groundwater arsenic (As) pollution is a naturally occurring phenomenon posing serious threats to human health. To mitigate this issue, we synthesized a novel bentonite-based engineered nano zero-valent iron (nZVI-Bento) material to remove As from contaminated soil and water. Sorption isotherm and kinetics models were employed to understand the mechanisms governing As removal. Experimental and model predicted values of adsorption capacity (q(e) or q(t)) were compared to evaluate the adequacy of the models, substantiated by error function analysis, and the best-fit model was selected based on corrected Akaike Information Criterion (AICc). The non-linear regression fitting of both adsorption isotherm and kinetic models revealed lower values of error and lower AICc values than the linear regression models. The pseudo-second-order (non-linear) fit was the best fit among kinetic models with the lowest AICc values, at 57.5 (nZVI-Bare) and 71.9 (nZVI-Bento), while the Freundlich equation was the best fit among the isotherm models, showing the lowest AICc values, at 105.5 (nZVI-Bare) and 105.1 (nZVI-Bento). The adsorption maxima (q(max)) predicted by the non-linear Langmuir adsorption isotherm were 354.3 and 198.5 mg g(−1) for nZVI-Bare and nZVI-Bento, respectively. The nZVI-Bento successfully reduced As in water (initial As concentration = 5 mg L(−1); adsorbent dose = 0.5 g L(−1)) to below permissible limits for drinking water (10 µg L(−1)). The nZVI-Bento @ 1% (w/w) could stabilize As in soils by increasing the amorphous Fe bound fraction and significantly diminish the non-specific and specifically bound fraction of As in soil. Considering the enhanced stability of the novel nZVI-Bento (upto 60 days) as compared to the unmodified product, it is envisaged that the synthesized product could be effectively used for removing As from water to make it safe for human consumption. MDPI 2023-02-25 /pmc/articles/PMC10004430/ /pubmed/36903414 http://dx.doi.org/10.3390/molecules28052168 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Raza, Md Basit Datta, Siba Prasad Golui, Debasis Barman, Mandira Das, Tapas Kumar Sahoo, Rabi Narayan Upadhyay, Devi Rahman, Mohammad Mahmudur Behera, Biswaranjan Naveenkumar, A Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil |
title | Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil |
title_full | Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil |
title_fullStr | Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil |
title_full_unstemmed | Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil |
title_short | Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil |
title_sort | synthesis and performance evaluation of novel bentonite-supported nanoscale zero valent iron for remediation of arsenic contaminated water and soil |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10004430/ https://www.ncbi.nlm.nih.gov/pubmed/36903414 http://dx.doi.org/10.3390/molecules28052168 |
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