# Chlorobenzene Removal Using DBD Coupled with CuO/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) Catalyst
## 3 Results and Discussion
### RSM Analysis  
The regression model was used in this study to analyze the removal efficiency and CO\({}_{2}\) selectivity of chlorobenzene in the DBD reactor packed with CuO/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) catalyst. Figures 9 and 10 show the chosen process parameters and corresponding results of chlorobenzene degradation. The removal efficiency of chlorobenzene by plasma catalysis varied between 51.5% and 97.4%, and CO\({}_{2}\) selectivity varied between 21.3% and 33.3%. The fitted models of removal efficiency and CO\({}_{2}\) selectivity in terms of standardized input parameters are given as:  
Removal efficiency:  
\[\text{Y}_{1}=80.8-7.35\text{x}_{1}+11.49\text{x}_{2}-0.0668^{\text{*}}\text{x} _{1}{}^{2}+2.66\text{x}_{1}\text{x}_{2}-1.35\text{x}_{2}{}^{2}\]  
CO\({}_{2}\) selectivity:  
\[\text{Y}_{2}=26.1-2.18\text{x}_{1}-2.62\text{x}_{2}+0.337^{\text{*}}\text{x}_{ 1}{}^{2}-0.410\text{x}_{1}\text{x}_{2}+0.562\text{x}_{2}{}^{2}\]  
Table 3 shows the analysis of variance for the fitted models. The results show that the response of the model is significant because the F values of Y\({}_{1}\) and Y\({}_{2}\) are 62.23 and 82.25; for comparison, the critical value of this model is 6.61. Moreover, the ultimate low \(p\)-value (<0.01) supports the hypothesis that the goodness-of-fit is high (confidence level >95%). It is generally certified that most of the variation in the response can be explained by the fitted model with F-value higher than the critical value and a \(p\)-value lower than 0.01. The root means square errors of Y\({}_{1}\) and Y\({}_{2}\) were 2.632 and 1.016, respectively, which were comparably smaller than the predicted values. The regression correction (R\({}^{2}\)) coefficients (Y\({}_{1}\) = 0.9766, Y\({}_{2}\) = 0.9466, close to 1) also indicates that the regression model fits the experimental results well. The coefficient of variation (C.V.), the ratio of the standard error of the estimated value to the average value of the response, can serve as the index judging the reproducibility of the model. For this experiment, the C.V. value of Y\({}_{1}\) (<10%) and Y\({}_{2}\) (<10%) suggests that the reliability and reproducibility of the model are acceptable [51].  
Figure 10: Effect of flow rate and discharge power on CO\({}_{2}\) selectivity of chlorobenzene in the Cu/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) reactor.  
Figure 9: Effect of flow rate and discharge power on efficiency of chlorobenzene in the Cu/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\) reactor.  
In general, the fitted model could reflect the changes in chlorobenzene degradation efficiency and CO2 selectivity under different flow rates and discharge power. The effect of flow rate and discharge power on the removal efficiency of chlorobenzene is plotted in Figure 9. The effect of chosen process parameters on the performance of the reactor is in agreement with the analysis of Sections 3.2 and 3.3: the removal efficiency of chlorobenzene will increase with discharge power since more active substances can be produced. Moreover, the improved effect of discharge power is more significant for large flow rates since the removal efficiency gradient is not uniform, which indicates that the interactions between discharge power and flow rate are not negligible. Moreover, the ultimate low \(p\)-value of the term x1x2 (<0.01) also supports this conclusion.  
The effect of flow rate and discharge power on the CO2 selectivity of chlorobenzene is plotted in Figure 10. The chosen process parameter exhibits a similar effect on the process performance as discussed in Sections 3.2 and 3.3. Moreover, the interactions between the two terms on the reaction performance are insignificant as the CO2 selectivity gradient is almost uniform. The \(p\)-value of x1x2 (>0.05) also supports this conclusion.