Solar photocatalytic treatment of wastewater contaminated with pesticides: Application of artificial neural network modelling

Homogeneous and heterogeneous photocatalysis systems were used to treat water contaminated with three pesticides, atrazine (ATZ), diazinon (DIZ), and alachlor (ALC).A pilot-scale plant powered by solar energy, consisting of compound parabolic collectors (CPCs), was used.The effect of H 2 O 2 concentration from 200 to 2400 mg/L, Fe +2 from 5 to 30 mg/L, and TiO 2 from 100 to 500 mg/L was studied to find their effects on the degradation efficiency.The concentrations of the parent pollutants rapidly declined to zero for ALC and DIZ in the initial stages of the experiment and were converted into intermediate products.The chemical oxygen demand (COD) removal efficiency for the homogeneous photocatalytic process at the optimal dosage was 45%, 74%, and 80% for ATZ, ALC, and DIZ, respectively.In comparison, the heterogeneous photocatalytic system showed removal efficiencies of 43%, 73%, and 76% for the same compounds.The single, binary, and ternary pesticide mixtures were tested in a homogeneous system.The results show that ATZ reduces oxidation of the mixture when combined with other pesticides.An artificial neural network was employed to predict the experimental results.The model demonstrated a good fit with the experimental results.