The Grey–Taguchi Method, a Statistical Tool to Optimize the Photo-Fenton Process: A Review

Abstract

Currently there is a growing concern about the presence of emerging contaminants (EC) in water bodies and their potential ecotoxicological effects. Pharmaceuticals, a type of EC, are widely distributed in the environment and their main entry is through wastewater from treatment plants, since these systems are not designed to remove EC. In this sense, the photo-Fenton process, an advanced oxidation process, has proven to be highly efficient in degrading new potentially harmful contaminants. However, this process is affected by multiple factors, which makes it necessary to implement a methodological strategy to optimize the photo-Fenton process. Within these, the Taguchi method provides robust and low-cost solutions with the least number of experiments, providing knowledge of the contribution of each of the factors studied to the response variable. In addition to the above, the Taguchi method can be coupled to a Grey relational analysis (Grey–Taguchi method), which will allow the optimization of more than one response variable at the same time. This paper discusses the parameters that affect the photo-Fenton process and the application of designs of experiments to optimize the process.