## 3 Results and Discussion
### Taguchi Methods Results  
The statistical processing of the results with the Taguchi method can quantify the effect of each variable on the parameter under consideration. This is achieved by applying the technique of Analysis of Variance (ANOVA). More precisely, \"One-Way Analysis of Variance\" (or One-Factor Analysis of Variance, or ANOVA-One for short) is applied. Figure 11: Photocatalytic kinetics under visible light irradiation for (**a**) Rhodamine B, (**b**) Methylene Blue, and (**c**) Brilliant Green. In this study, One-Factor Variance Analysis is chosen, because the experimental data are distinguished by only one characteristic: the achieved rate of degradation. Table 3 summarizes the (%) effect of each parameter (factor) on the photocatalysis process. It is observed that the choice of pollutant plays the most important role in the photocatalytic tests, since it affects photocatalysis at a rate of 52.21%. Therefore, to investigate the catalyst's action in photocatalysis, it is necessary to choose the proper type of pollutant, which will be stable and not degrade easily. The amount of catalyst used, while expected to be the main affecting factor, comes in second, by approximately 30%. The other two factors, cell distance from the radiation source and total radiation time, are almost at the same effect levels of approximately 10%. From the Minitab software, graphs which actively illustrate the qualitative effect of the variables and their levels on the measured parameter are also extracted. Figure 12 shows the level of each variable and to which photocatalytic degradation (C/C\({}_{0}\)) they lead. The Taguchi method is a solidly built experimental design that aims to derive the best combination set of factors/levels together with the lowest economical solution, in order to satisfy a product's quality specifications [56]. It is applied in the catalysis field for optimizing the synthesis of NPs and TiO\({}_{2}\). Most of these studies investigate 3-5 different factors with 3-4 levels each, which is in correspondence with this study. For example, TiO\({}_{2}\) NPs synthesis is optimized by researching the factors that lead to a low crystallite size [28] and the ZnO-TiO\({}_{2}\) composite catalyst is optimized taking into account its photocatalytic activity in MB under visible light irradiation for 120 min duration and 30 min time interval [57]. Similar studies are found on other NPs, including optimizing the synthesis of ZnO doped with various metals (Al, Fe, Cr) regarding the photocatalytic  
Figure 12: Qualitative effect of each factor on the final degradation of C/Co, where A is the amount of catalyst/pollutant (g/L), B is the pollutant, C is the distance from the light source and, D is the time protocol. \begin{table}
\begin{tabular}{c c} \hline \hline
**Factor** & **Effect \%** \\ \hline A-Photocatalyst/pollutant (g/L) & 28.78 \\ B-Pollutant & 52.21 \\ C-Distance from light source (cm) & 10.95 \\ D-Irradiation time (total min/measuring gap time) & 8.07 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Percentage of effect of each factor on the final degradation according to Taguchi method. degradation on MB under visible light [58]. The present study takes the application of the Taguchi methods to the next level, investigating the photocatalytic process on N-TiO\({}_{2}\) NPs. When evaluating the statistical results of a Taguchi experiment, there is a philosophy of \"the larger the better\", \"the smaller the better\", or \"the on-target, minimum-variation\" [30]. In this study, it is preferable to choose the level that leads to higher C/C\({}_{0}\) for all the factors, ensuring that the choice is simultaneously low cost. It should also be noted that the inclination of each graph indicates the degree of influence of each variable on the final degradation. The higher the inclination of the graph, the greater the influence of the variable.