Identification of influential parameters and conditions in heavy metals adsorption onto Cal-LDH-PC using optimization...

Adsorption process plays an important role in the remediation of heavy metals (HMs) from wastewater. A laboratory trial was conducted to investigate effective parameters for improving the bio-adsorption removal of HMs. SEM, EDX, BET, and FTIR techniques were applied to characterize the calcined layer double hydroxide (Cal-LDH), pectin (PC), and Cal-LDH-PC composite prepared from Licorice pomace. The adsorption of zinc (Zn) cadmium, nickel (Ni) and lead (Pb) onto the most efficient sorbent was investigated using RSM methodology with operational factors such as concentration, reaction time, sorbent dose, and pH. The results related to FTIR showed that Cal-LDH-PC had the highest number of functional groups. Based on the SEM results Cal-LDH had a low surface area (9.36 m² g^-1) and a small pore size (9.22 nm). After the modification process (Cal-LDH-PC), the values of surface area and pore size increased by 13-fold (120 m² g^-1) and 1.5-fold (18 nm), respectively. Cal-LDH had high adsorption performance, more cavities, stability, various functional groups, and excessive carbon and oxygen content, which make it efficient and powerful in removing HMs from wastewater. The optimal condition for achieving the removal efficiency (RE%) values of metals was determined to be 80.79 mg L^-1, 100 min, 0.167 g L^-1, and 9 for concentration, reaction time, sorbent dose, and pH, respectively. Maximum adsorption capacity and RE (%) were 300 mg g^-1 and 99% for Zn. According to the results concentration had a major impact on RE% (except for Ni), while for Ni, adsorbent dose had the most significant impact. The present study introduced Cal-LDH-PC prepared from Licorice pomace as a capable, useful and economical sorbent for HMs removal from polluted environments. Taguchi's statistical method is distinguished as an economic method with easier interpretation, while the RSM approach is more accurate, and it can also check the interaction of parameters.