Predictive modelling is very important for water pollution management. In this study, based on an electromagnetic field-enhanced vertical flow artificial wetland and using the actual measured data as inputs to the model, the ammonia nitrogen (NH₄⁺-N) effluent concentration of this wetland system was analyzed by Pearson’s correlation analysis to be related to six key factors, which were the NH⁺-N raw water concentration, the chemical oxygen demand (COD) raw water concentration, the treatment time, the magnetic field strength, the aeration time, and the electric field strength. Then, different artificial neural network models were constructed for comparison and the constructed models were evaluated based on statistical parameters. The results show that the PSO algorithm can improve the prediction effect of the BP neural network, but the prediction accuracy of the CNN model is better compared to the others. The prediction accuracy of the RF model is the highest compared to the others, and the evaluation parameters of R2, RMSE, and MAE of the test set are (0.9446, 2.4328, and 3.0943), respectively. The prediction error of this model is the smallest, and the model can predict the concentration of electric and magnetic fields in a wetland system with high accuracy compared to other models. This model can more accurately predict the NH₄⁺-N effluent concentration of the magnetic field-enhanced wetland system, which can provide a certain basis for the study of the management of water pollution.

The addition of physical field enhancement measures to improve the purification effect of vertical flow artificial wetlands has gradually become popular. In this study, a vertical flow artificial wetland system reinforced by electric and magnetic fields was constructed. These fields were first optimized using finite element 3D simulation software to obtain the optimal electric and magnetic field parameters. Then, the pollutant removal effects and changes in microbial community structure were comparatively analyzed. The optimal electromagnetic field parameters (applied voltage of 15 V and applied magnetic field of 20 mT) resulted in significantly enhanced removal rates of chemical oxygen demand (COD), nitrate nitrogen (NH₄⁺-N), total phosphorus (TP), and orthophosphorus (PO₄³⁻-P) in wastewater, with rates of 74.47%, 45.44%, 89.85%, and 90.04%, respectively. These rates were notably higher than those observed in the vertical flow artificial wetland system. The microbial community structure analysis revealed that the vertical flow constructed wetland with enhanced electric and magnetic fields exhibited (EM-VFCW) a more diverse and complex microbial community structure. Notably, the abundance of bacteria capable of removing NH₄⁺-N and COD, including Aspergillus, Fusarium, and Actinobacteria, was significantly elevated.

Electrochemical oxidation combined with reagents of O₃, H₂O₂ and FeCl₂ was conducted in this study to treat the wastewater from wet fermentation of Yunnan arabica coffee. In addition, the effect of oxidants on the efficiency of wastewater treatment, the binding capacities of the oxidants to proteins, the degradation of organic pollutants in the wastewater, and the formation of oxidized organic components were systematically investigated. The results reveal better performance of O₃-combined electrochemical oxidation (63.60% COD removal efficiency) for treatment of organic species in coffee wastewater than that of the electrochemical processes with H₂O₂ (47.70% COD removal efficiency) and FeCl₂ (34.48% COD removal efficiency). The synergy of the electrooxidation/O₃ process (0.0133 A/cm², 20 mg/L–2 L/min) could not only raise the pH value (3.70~4.20, 5.14~5.44) of the wastewater and reduce the NaOH dosage of 2.80~3.7 g/L, but also effectively degrade the proteins, lipids, unsaturated hydrocarbons, and carbohydrates, with a total chemical oxygen demand (COD) value above 20,000 mg/L. After the oxidation treatment, some organic components remained in the wastewater, including 31.94% of S-containing organics, lignin, condensed aromatic compounds, and aromatic structural compounds, which are difficult to be utilized by microorganisms. In addition, it was found that OH⁻ could bind to proteins and affect the required amount of NaOH addition, whereas the protein binding energy of O₃ is higher than that of H₂O₂, indicating a stronger ability of O₃ to oxidize proteins. Therefore, the combination of O₃ and electrochemical oxidation can be considered as an effective method to treat organic pollutants in the wastewater from wet fermentation of Yunnan arabica coffee.