Application of Response Surface Methodology in the Photocatalytic Removal of Pollutants–A Systematic Review: Characteristics, Common Mistakes, and Qualitative Evaluation of Articles Publisher



Nabizadeh Nodehi R¹ ; Sheikhi R¹ ; Gholami M² Show Affiliations
Source: Results in Chemistry Published:2024

Abstract

In the last decade, the use of response surface methodology (RSM) as an advanced technique for designing empirical tests has been developing. Investigations show that RSM is sometimes not used correctly in designing experiments, developing models, and optimizing various physicochemical processes to remove water and wastewater pollutants. Making serious mistakes can lead to misleading conclusions, and questions the validity of scientific research. In this study, the characteristics and mistakes of RSM application in the last decade have been systematically investigated. For the first time, a checklist has been designed to check the correct implementation of the RSM. Using this checklist, the quality of articles on photocatalytic removal of physicochemical pollutants from aqueous environments using TiO2 catalyst and UV light has been investigated, based on the correct implementation of RSM. According to our results, many mistakes were observed in using RSM in the included studies; 41% of the articles did not report the lack of fit value for their works. In 19% of the articles, the P-value of the equation's main terms was insignificant. Higher than 20% and 61% of those studies did not perform the optimization of photocatalytic removal of pollutants and the confirmatory experiments after optimization, respectively. Contrary to expectation, the final score of the articles included in this evaluation had no proportion to the CiteScore of the respective journals. The trend of the average scores over time showed that the authors’ attention to the correct implementation of RSM requirements has not changed in a decade. The present study has a crucial role in advancing knowledge related to RSM and preventing potential common mistakes in this field. It also makes researchers pay more attention to the correct use of RSM. The checklist proposed can be used by researchers and reviewers who use RSM. © 2024 The Author(s)