For optimizing the reaction conditions of 2-methyl-6-ethylaniline (MEA) degradation catalyzed by horseradish peroxidase (HRP), a response surface methodology with three factors and three levels was used in this research to establish a regression model, a ternary quadratic polynomial, in order to analyze temperature, H₂O₂ concentration and pH effects on MEA removal efficiency. The results showed that the regression model was significant (p < 0.0001), fitted well with experimental data and had a high degree of reliability and accuracy, and the data were reasonable with low errors. By analyzing interactions and solving the regression model, the maximum MEA removal efficiency was 97.90%, and the optimal conditions were defined as follows: pH 5.02, H₂O₂ concentration 13.41mM, and temperature 30.95 °C. Under the optimal conditions, the average MEA removal efficiency obtained from the experiments was 97.56%. This research can provide reference for the treatment of actual acetochlor industrial wastewater.

In order to obtain the optimal conditions for ammonia nitrogen (AN) wastewater treatment by bio filter (BF), the effects of ratio of carbon to nitrogen (C/N), pH, and hydraulic load (HL) on the AN degradation were studied by Response Surface Methodology (RSM). Central Composite Design (CCD) experiments were conducted, and the response of the AN removal rates were fitted to a second-order polynomial model. The analysis of variance showed that the model was accurate and reliable. Through model fitting, the optimal condition for AN removal was: C/N of 18.95, pH of 7.78, and HL of 1.04 d⁻¹. The maximum AN removal rate predicted by the model was 91.90%, accorded with the experimental verification value of 91.37% under the optimal condition. The research provided valuable demonstration for optimizing process parameters on AN removal in BF.