Application of Combined Chemical Coagulation and Photo-Electro-Fenton Processes for the Removal of Ammonia Nitrogen from Dairy Wastewater: RSM and ANN Modeling and Optimization

The dairy industry produces large amounts of dairy wastewater containing ammonia nitrogen (NH 3 -N). Sustainable treatment technologies are needed which can reduce the environmental pollution caused by NH 3 -N emissions from dairy wastewater. Chemical coagulation combined with the photo-electro-Fenton (PEF) treatment process has been considered a promising technology that can effectively remove NH 3 -N from dairy wastewater. In this study, Taguchi design was used first to narrow down the operating factors from five to three. The three most influential factors were then further optimized for an optimum NH 3 -N removal efficiency using response surface methodology (RSM) coupled with Box–Behnken design. Both RSM and artificial neural network (ANN) models were developed to predict the NH 3 -N removal efficiency. Under the optimal conditions of 0.51 mM Fe 2+ , 49.44 mA/cm 2 current density, and 118.60 min treatment time, removal of 92.13% NH 3 -N from dairy wastewater with 90% N 2 selectivity was achieved during validation experiments. The ANN model showed a superior predictive performance to the RSM model. The NH 3 -N degradation rate was calculated at 0.0229 min −1 based on a pseudo-first-order kinetic model. These findings demonstrate the applicability of the integrated chemical coagulation and PEF process for significantly reducing ammonia nitrogen in dairy wastewater.