Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil

Author:

Raza Md Basit12ORCID,Datta Siba Prasad1,Golui Debasis13ORCID,Barman Mandira1,Das Tapas Kumar4,Sahoo Rabi Narayan5,Upadhyay Devi1,Rahman Mohammad Mahmudur67ORCID,Behera Biswaranjan8,Naveenkumar A1

Affiliation:

1. Division of Soil Science and Agricultural Chemistry, ICAR-Indian Agricultural Research Institute, New Delhi 110012, India

2. ICAR-Indian Institute of Soil and Water Conservation, RC Koraput, Odisha 763002, India

3. Department of Civil, Construction and Environmental Engineering, North Dakota State University, Fargo, ND 58102, USA

4. Division of Agronomy, ICAR-Indian Agricultural Research Institute, New Delhi 110012, India

5. Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi 110012, India

6. Global Centre for Environmental Remediation (GCER), College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia

7. Department of General Educational Development, Faculty of Science & Information Technology, Daffodil International University, Ashulia, Savar, Dhaka 1207, Bangladesh

8. ICAR-Indian Institute of Water Management, Bhubaneswar 751023, India

Abstract

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 (qe or qt) 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 (qmax) 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.

Publisher

MDPI AG

Subject

Chemistry (miscellaneous),Analytical Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Molecular Medicine,Drug Discovery,Pharmaceutical Science

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