## 3 Results and Discussion
### Model Parameter Determination and Statistical Analysis
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multicolumn{6}{c}{**Values of Kinetic Parameter (\(\pm\)95\% Confidence Interval)**} \\ \hline
**Model** & \(V_{m}\) (h\({}^{-1}\)) & \(K_{i}\) (mgL\({}^{-1}\)) & \(K_{s}\) (mgL\({}^{-1}\)) & \(n\) (-) & \(\mathbf{R^{2}}\) & **Variance** \\ \hline Rate law & & & & & & \\ \(-\frac{dC_{s}}{dt}=r=K_{i}C_{a}^{n}\) & - & 3.33 \(\times\) 10\({}^{-5}\) & - & 2.65 & 0.92 & 0.05 \\ Haldane & & & & & & \\ \(\frac{dC_{s}}{dt}=\frac{V_{m}C_{c}}{C_{s}+\frac{C_{s}^{2}}{K_{s}}}\) & 0.36 & 11.36 & - & - & 0.95 & 365.43 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Estimated values of kinetic parameters for the models for CN\({}^{-}\) degradation. Figure 2: Parity plots of predicted values versus experimental values. Assimilations of the model data into NH\({}_{4}\)N degradation experimental data (Rate law, [PERSON], and Andrew). Figure 3: Parity plots of predicted values versus experimental values. Assimilations of the model data into CN- degradation experimental data (Rate law, [PERSON], and Andrews). Overall, the models used and reported in this research also fitted the CN\({}^{-}\) degradation data well (Figure 3). The models that gave a better fit were the rate law (R\({}^{2}\) = 0.92, Adj R\({}^{2}\) = 0.90, variance = 0.052 and standard deviation = 0.076) and [PERSON] model (R\({}^{2}\) = 0.95, adj R\({}^{2}\) = 0.94, variance = 0.034 and standard deviation= 0.061)--see Table 3. [PERSON] models' had a poor prediction of CN\({}^{-}\) degradation with (R\({}^{2}\) = -0.99, adj R\({}^{2}\) = -2.31, variance = 1.75, and standard deviation = 0.38). This indicated that CN\({}^{-}\) degradation was not inhibited by the presence of NH\({}_{4}\)-N, as some organism would rather alternatively use the less inhibitory pollutant; although, inhibitory compound biodegradation might be a favorable alternative. [PERSON]'s model was developed to predict substrate utilization in systems with substrate inhibition, thus the models' inability to model CN\({}^{-}\) removal. [PERSON] et al. [19] studied the kinetics of SNaD under high phenol concentrations using bacterial strains capable of phenol degradation, heterotrophic nitrification, and aerobic denitrification. Additionally, [PERSON] et al. [20] also studied the kinetics of denitrification with nitrate inhibition. Additionally, [PERSON] et al. [21] also determined that the [PERSON] model predicted CN\({}^{-}\) well with R\({}^{2}\) being 0.99 These studies indicated the feasibility of SNaD, even under inhibitory pollutant loading. Moreover, the kinetic parameters obtained were comparable to those obtained for this study (Table 3). Overall, the variance and standard deviation of the model showed that all three models predicted NH\({}_{4}\)-N degradation better as opposed to CN\({}^{-}\) degradation. This was shown with the higher variances and standard deviation of CN\({}^{-}\) degradation than those of NH\({}_{4}\)-N degradation. Although, all three models adequately represented NH\({}_{4}\)-N removal with high R\({}^{2}\) and adj R\({}^{2}\), the rate law and Andrews models had higher average standard deviation and variance for predicted rate of CN\({}^{-}\) degradation in comparison to actual experimental data (Figure 3); thus rendering unusable as candidate prediction models for removal systems with multiple nitrogenous pollutants. Moreover, [PERSON] model was selected as a better predictor of NH\({}_{4}\)-N removal under CN\({}^{-}\) conditions. This decision was based on its standard deviation and the variance being the lowest for both NH\({}_{4}\)-N and CN\({}^{-}\) degradation, indicating that the predicted rate of NH\({}_{4}\)-N and CN\({}^{-}\) by [PERSON] had a minute deviation from the experimental data thus qualifying it as a better model to be used for multiple nitrogenous pollutants systems, especially, SNaD. The result obtained it this study were consistent with those that were previously reported by [PERSON] et al.