## 3 Results and Discussion
### Desorption Studies
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Column Models/Parameters**} & \multicolumn{3}{c}{**Flow Rate (cm\({}^{3}\) min\({}^{-1}\))**} \\ \cline{3-5} \multicolumn{2}{c}{} & **0.5** & **1.0** & **1.5** \\ \hline \multicolumn{5}{c}{As(V)} \\ \hline \multirow{3}{*}{B–A} & \(\text{K}_{\text{BA}}\) (dm\({}^{3}\) mg\({}^{-1}\) min\({}^{-1}\)) & 0.082 \(\pm\) 0.002 & 0.155 \(\pm\) 0.003 & 0.224 \(\pm\) 0.007 \\ \cline{2-5}  & \(\text{N}_{0}\) (mg dm\({}^{-3}\)) & 41.62 \(\pm\) 0.236 & 36.86 \(\pm\) 0.248 & 32.24 \(\pm\) 0.313 \\ \cline{2-5}  & \(\text{R}^{2}\) & 0.998 & 0.998 & 0.996 \\ \hline \multirow{3}{*}{Y–N} & \(\text{K}_{\text{YN}}\) (min\({}^{-1}\)) & 0.788 \(\pm\) 0.017 & 0.748 \(\pm\) 0.017 & 0.755 \(\pm\) 0.022 \\ \cline{2-5}  & \(\text{\theta}\) (min) & 5.558 \(\pm\) 0.031 & 4.923 \(\pm\) 0.033 & 4.305 \(\pm\) 0.042 \\ \cline{2-5}  & \(\text{R}^{2}\) & 0.998 & 0.998 & 0.996 \\ \hline \multirow{3}{*}{Thomas} & \(\text{K}_{\text{TH}}\) (dm\({}^{3}\) mg\({}^{-1}\) min\({}^{-1}\)) & 0.163 \(\pm\) 0.004 & 0.155 \(\pm\) 0.003 & 0.156 \(\pm\) 0.004 \\ \cline{2-5}  & \(\text{q}_{0}\) (mg g\({}^{-1}\)) & 41.62 \(\pm\) 0.236 & 36.86 \(\pm\) 0.248 & 32.24 \(\pm\) 0.312 \\ \cline{2-5}  & \(\text{R}^{2}\) & 0.998 & 0.998 & 0.996 \\ \hline \multicolumn{5}{c}{Iprodione} \\ \hline \multirow{3}{*}{B–A} & \(\text{K}_{\text{BA}}\) (dm\({}^{3}\) mg\({}^{-1}\) min\({}^{-1}\)) & 0.060 \(\pm\) 0.001 & 0.123 \(\pm\) 0.001 & 0.201 \(\pm\) 0.002 \\ \cline{2-5}  & \(\text{N}_{0}\) (mg dm\({}^{-3}\)) & 89.81 \(\pm\) 0.293 & 80.06 \(\pm\) 0.172 & 70.51 \(\pm\) 0.148 \\ \cline{2-5}  & \(\text{R}^{2}\) & 0.998 & 0.999 & 0.999 \\ \hline \multirow{3}{*}{Y–N} & \(\text{K}_{\text{YN}}\) (min\({}^{-1}\)) & 0.594 \(\pm\) 0.012 & 0.603 \(\pm\) 0.007 & 0.657 \(\pm\) 0.007 \\ \cline{2-5}  & \(\text{\theta}\) (min) & 11.80 \(\pm\) 0.038 & 10.52 \(\pm\) 0.023 & 9.266 \(\pm\) 0.020 \\ \cline{2-5}  & \(\text{R}^{2}\) & 0.998 & 0.999 & 0.999 \\ \hline \multirow{3}{*}{Thomas} & \(\text{K}_{\text{TH}}\) (dm\({}^{3}\) mg\({}^{-1}\) min\({}^{-1}\)) & 0.121 \(\pm\) 0.002 & 0.123 \(\pm\) 0.001 & 0.134 \(\pm\) 0.001 \\ \cline{2-5}  & \(\text{q}_{0}\) (mg g\({}^{-1}\)) & 89.73 \(\pm\) 0.292 & 80.00 \(\pm\) 0.172 & 70.45 \(\pm\) 0.148 \\ \cline{1-1} \cline{2-5}  & \(\text{R}^{2}\) & 0.998 & 0.999 & 0.999 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Bohart–Adams, [PERSON]–Nelson, and [PERSON] models’ parameters for adsorption of As(V) and Iprodione onto ESősAPTES-GT hybrid material in a fixed-bed column. efficiency decrease (higher for app. 15% in comparison to the results given in Figure 7, as an example, 32% of \(q_{\text{e}}\) was decreased for As(V) removal after the fifth cycle) and, thus, a decrease in the adsorbent usage period is obvious. The best desorption system was found to be sodium hydrogen carbonate (NaHCO\({}_{3}\), 4%) or sodium chloride (NaCl, 4%) for Iprodione, while a NaOH (2%)/NaCl (2%) mixture for arsenate desorption. Fungicide desorption increases with both a pH and ionic strength increase (0.001, 0.01, and 0.1 mol dm\({}^{-3}\) KNO\({}_{3}\)), which indicates a physisorption mechanism. For the adsorption capacity of EGS@APTES-GT, before and after the regeneration step, qi and q(i + 1) were further used for the calculation of the regeneration efficiency (RE, %) in the following operational conditions: an adsorbent mass of 10 mg and 10 mL of a pollutant solution, all at a concentration of 5 mg dm\({}^{-3}\) and pH 7. The regeneration efficiency was calculated according to Equation (1):  
\[RE=\frac{\text{q}_{(i+1)}}{\text{q}_{\text{i}}}\times 100 \tag{1}\]  
The obtained results (Figure 7) for As(V) and Iprodione showed a small decrease in the adsorption efficiency of 17% and 14%, respectively, after the fifth reuse cycle, which ensures good EGS@APTES-GT adsorbent efficiency in an industrial-scale application and meets the requirement for a real application at optimal operational conditions.