TY - JOUR
T1 - Effectual adsorptive performance of metal-based engineered nanoparticles for surface water remediation
T2 - Systematic optimization by box-behnken design
AU - Iqbal, A.
AU - Jalees, M. I.
AU - Farooq, M. U.
AU - Cevik, E.
AU - Bozkurt, A.
N1 - Publisher Copyright:
© The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University 2024.
PY - 2025/4
Y1 - 2025/4
N2 - Surface water pollution, due to various forms of organic and inorganic contaminants, is the most pressing environmental concern. Though several different approaches for water treatment have been investigated, most of them are costly or cause major health problems. To address the widespread concern of surface water pollution, the goal of the current study was to investigate the efficacy of metal-based nanoadsorbents (nickel oxide (NiO) nanoparticles and cobalt oxide (Co3O4) nanoparticles) as effective, sustainable and practical solution for the multiple removal of six different water pollutants (turbidity, total dissolved solids (TDS), chemical oxygen demand (COD), lead (Pb), cadmium (Cd), and chromium (Cr)), using the process of batch adsorption. Box-Behnken Design with Response Surface Methodology (RSM) was studied for the optimization of adsorption factors and their combined effects on pollutant removal. The following maximum removal efficiencies for chosen parameters were shown by the optimized operating conditions using NiO nanoparticles as adsorbent (pH: 8, adsorbent dose: 0.05 g, contact time: 80 min): 95.05% for turbidity, 55.05% for TDS, 58.54% for COD, and 100% for toxic meteals (Pb, Cd, and Cr). Similarly, for Co3O4 nanoparticles as adsorbent, optimized operating conditions (pH: 10, adsorbent dose: 0.0054 g, and contact time: 19.5 min) depicted 98.3% for turbidity, 66.7% for TDS, 67.6% for COD, 97.5% for Pb and 100% for Cd and Cr. Thus, this study demonstrated the exceptional ability of NiO and Co3O4 nanoparticles as efficient adsorbents for simultaneous removal of contaminates existing in water, a previously unexplored application.
AB - Surface water pollution, due to various forms of organic and inorganic contaminants, is the most pressing environmental concern. Though several different approaches for water treatment have been investigated, most of them are costly or cause major health problems. To address the widespread concern of surface water pollution, the goal of the current study was to investigate the efficacy of metal-based nanoadsorbents (nickel oxide (NiO) nanoparticles and cobalt oxide (Co3O4) nanoparticles) as effective, sustainable and practical solution for the multiple removal of six different water pollutants (turbidity, total dissolved solids (TDS), chemical oxygen demand (COD), lead (Pb), cadmium (Cd), and chromium (Cr)), using the process of batch adsorption. Box-Behnken Design with Response Surface Methodology (RSM) was studied for the optimization of adsorption factors and their combined effects on pollutant removal. The following maximum removal efficiencies for chosen parameters were shown by the optimized operating conditions using NiO nanoparticles as adsorbent (pH: 8, adsorbent dose: 0.05 g, contact time: 80 min): 95.05% for turbidity, 55.05% for TDS, 58.54% for COD, and 100% for toxic meteals (Pb, Cd, and Cr). Similarly, for Co3O4 nanoparticles as adsorbent, optimized operating conditions (pH: 10, adsorbent dose: 0.0054 g, and contact time: 19.5 min) depicted 98.3% for turbidity, 66.7% for TDS, 67.6% for COD, 97.5% for Pb and 100% for Cd and Cr. Thus, this study demonstrated the exceptional ability of NiO and Co3O4 nanoparticles as efficient adsorbents for simultaneous removal of contaminates existing in water, a previously unexplored application.
KW - Batch adsorption
KW - CoO nanoparticles
KW - NiO nanoparticles
KW - Response surface methodology
KW - Water pollutants
UR - https://www.scopus.com/pages/publications/105001080421
U2 - 10.1007/s13762-024-06075-9
DO - 10.1007/s13762-024-06075-9
M3 - Article
AN - SCOPUS:105001080421
SN - 1735-1472
VL - 22
SP - 6819
EP - 6834
JO - International Journal of Environmental Science and Technology
JF - International Journal of Environmental Science and Technology
IS - 8
M1 - 111684
ER -