Using predictive models unravel the potential of titanium oxide-loaded activated carbon for the removal of leachate ammoniacal nitrogen.

The TiO nanocomposite efficiency was determined under optimized conditions with activated carbon to remove ammoniacal nitrogen (NH-N) from the leachate sample. In this work, the facile impregnation and pyrolysis synthesis method was employed to prepare the nanocomposite, and their formation was confirmed using the FESEM, FTIR, XRD, and Raman studies. In contrast, Raman phonon mode intensity ratio I/I increases from 2.094 to 2.311, indicating the increase of electronic conductivity and defects with the loading of TiO nanoparticles. The experimental optimal conditions for achieving maximum NH-N removal of 75.8% were found to be a pH of 7, an adsorbent mass of 1.75 mg/L, and a temperature of 30 °C, with a corresponding time of 160 min. The experimental data were effectively fitted with several isotherms (Freundlich, Hill, Khan, Redlich-Peterson, Toth, and Koble-Corrigan). The notably elevated R value of 0.99 and a lower ARE % of 14.61 strongly support the assertion that the pseudo-second-order model compromises a superior depiction of the NH-N reduction process. Furthermore, an effective central composite design (CCD) of response surface methodology (RSM) was employed, and the lower RMSE value, precisely 0.45, demonstrated minimal disparity between the experimentally determined NH-N removal percentages and those predicted by the model. The subsequent utilization of the desirability function allowed us to attain actual variable experimental conditions.