Effectual adsorptive performance of metal-based engineered nanoparticles for surface water remediation: Systematic optimization by box-behnken design

Abstract

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.