Effect of process parameters and optimization of photocatalytic removal of lead from wastewater over CuZn oxide nanocomposite using response surface methodology

Abstract

One major environmental challenge is effectively removing heavy metals from wastewater. This study investigates the application of CuZn oxide nanocomposite as photocatalyst for the removal of lead ion (Pb²⁺) from simulated wastewater. The influence of parameters such as pH, initial ion concentration of Pb²⁺, dosage of catalyst, and distance from the light source was evaluated to ascertain how Pb²⁺ removal would be most successful. Central Composite Design (CCD) and Response Surface Methodology (RSM) were employed for experimental design and optimization studies. With pH and Pb²⁺ initial concentration being the most significant variables, the results showed that all parameters significantly affected the photocatalytic Pb²⁺ removal process. Notable interaction effects were found among several combinations of factors, hence stressing the complex character of the photocatalytic process. The optimal conditions for maximum lead removal were found by means of process parameters optimization. Under ideal conditions, the model fairly projected a removal effectiveness of approximately 90 %. The study underlines the requirement of enhancing process parameters to boost photocatalytic performance and shows the capacity of CuZn oxide nanocomposites in effectively eliminating Pb²⁺. This work presents fresh understanding of Pb²⁺ removal and suggests a strict analytical approach to enhance complex environmental processes. Targeting a significant environmental concern, the outcomes improve the advancement of efficient and long-lasting wastewater treatment technologies.