Removal of acetaminophen (ACT) from aqueous solution by using nanosilica adsorbent: experimental study, kinetic and isotherm modeling

Abstract

Purpose A nanosilica adsorbent was prepared and characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD) and BET. Design/methodology/approach The optimum conditions for the highest adsorption performance were determined by kinetic modeling. The adsorbent was used for the adsorption of acetaminophen (ACT), and the parameters affecting the adsorption were discussed like pH, initial concentration, contact time and adsorbent dosage. The adsorbent have been characterized by SEM, XRD and BET analysis. The kinetic models including pseudo-first-order and pseudo-second-order with Langmuir and Freundlich isotherm models were applied to investigate the kinetic and isotherms parameters. Findings The adsorption of ACT increased to around 95% with the increase of nanosilica concentration to 30 g/L. Moreover, the adsorption process of ACT follows the pseudo-second-order kinetics and the Langmuir isotherm with the maximum adsorption capacity of 609 mg/g. Practical implications This study provided a simple and effective way to prepare of nanoadsorbents. This way was conductive to protect environmental and subsequent application for removal of emerging pollutants from aqueous solutions. Originality/value The novelty of the study is synthesizing the morphological and structural properties of nanosilica-based adsorbent (specific surface area, pore volume and size, shape and capability) and improving its removal rate through optimizing the synthesis method; and studying the capability of synthesis of nanosilica-based adsorbent for removal of ACT as a main emerging pharmaceutical water contaminant.

ZnO-based nanocomposites for removal of lead (Pb2+) from water/wastewater: a review

“…1.3.1.4 Contact time. The effect of contact time is an important parameter in determining the operating costs in the adsorption process (Eslami et al, 2018;Eslami et al, 2020). It also helps identify the reaction time of binding for the removal of hazardous pollutants (Khashij et al, 2016).…”