In the current work, the hybrid process potential of ultrasound (US) and electro-Fenton (EF), named sono-electro-Fenton (SEF), was fully investigated for sulfadiazine (SDZ) degradation. The decontamination in the integration approach was revealed to be greater than in individual procedures, i.e., EF process (roughly 66%) and US process (roughly 15%). The key operating process factors (i.e., applied voltage, H2O2 content, pH, initial concentration of SDZ, and reaction time) affecting SDZ removal were evaluated and optimized using Box-Behnken Design (BBD). In addition, an adaptive neuro-fuzzy inference system (ANFIS) as an efficient predictive model was applied to forecast the decontamination efficiency of SDZ through the SEF process based on the same findings produced from BBD. The results revealed that the predictability of SDZ elimination by the ANFIS and BBD approaches exhibited an excellent agreement (a greater R2 of 0.99%) among the both models. Density functional theory was also employed to forecast the plausible decomposition elucidation by the bond-breaking mechanism of organic substances. Plus, the main side products of SDZ degradation during the SEF process were tracked. Eventually, the non-carcinogenic risk assessment of different samples of natural water containing SDZ that was treated by adopting US, EF, and SEF processes was examined for the first time. The findings indicated that the non-carcinogenic risk (HQ) values of all the purified water sources were computed in the permissible range.
Keywords: Adaptive neuro-fuzzy interference system; Non-carcinogenic risk assessment; Sono-electro-Fenton; Sulfadiazine.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.