Language of response surface methodology as an experimental strategy for electrochemical wastewater treatment process optimization

Abstract

The availability and accessibility to safe and secure water resources are the key technological and scientific concerns of global significance. As a result of water scarcity worldwide, wastewater treatment and reuse are considered viable options to replace freshwater resources in agricultural irrigation and domestic and industrial purposes. A significant need for clean water has promoted the invention and/or enhancement of several electrochemical wastewater treatment (EWT) processes. Optimization of the process variables plays a crucial role in wastewater treatment to enhance technology performance, considering removal efficiency, operating cost, and environmental impacts. These processes are fundamentally complex multivariable, and the optimization through conventional methods is unreliable, inflexible, and time- and material-consuming. In this perspective, response surface methodology (RSM) appears to be a beneficial statistical experimental strategy for the performance optimization of the EWT process. This model could be utilized for the optimization and analysis of the individual and/or combined effects of operational variables on the treatment process to improve the system performance. Furthermore, this model provides a number of information from a slight number of experimental trials. In this chapter, a summary and a discussion are presented on the RSM model used in the electrochemical wastewater treatment processes to overcome process crucial challenges toward the optimization and modeling of process parameters. It provides a potential model to enhance the various types of wastewater treatment process performance with effective optimization. Overall, it is described that the RSM model can be used in EWT processes to find the optimum conditions. © 2022 Elsevier B.V., All rights reserved.