Optimization of the O3/H2O2 process with response surface methodology for pretreatment of mother liquor of gas field wastewater

? Real ML-GFW with high salinity and high organics was degraded by O₃/H₂O₂ process. ? Successful optimization of operation conditions was attained using RSM based on CCD. ? Single-factor experiments in advance ensured optimal experimental conditions. ? The satisfactory removal efficiency of TOC was achieved in spite of high salinity. ? The initial pH plays the most significant role in the degradation of ML-GFW. The present study reports the use of the O₃/H₂O₂ process in the pretreatment of the mother liquor of gas field wastewater (ML-GFW), obtained from the multi-effect distillation treatment of the gas field wastewater. The range of optimal operation conditions was obtained by single-factor experiments. Response surface methodology (RSM) based on the central composite design (CCD) was used for the optimization procedure. A regression model with Total organic carbon (TOC) removal efficiency as the response value was established (R² = 0.9865). The three key factors were arranged according to their significance as: pH>H₂O₂ dosage>ozone flow rate. The model predicted that the best operation conditions could be obtained at a pH of 10.9, an ozone flow rate of 0.8 L/min, and H₂O₂ dosage of 6.2 mL. The dosing ratio of ozone was calculated to be 9.84 mg O₃/mg TOC. The maximum removal efficiency predicted was 75.9%, while the measured value was 72.3%. The relative deviation was found to be in an acceptable range. The ozone utilization and free radical quenching experiments showed that the addition of H₂O₂ promoted the decomposition of ozone to produce hydroxyl radicals (·OH). This also improved the ozone utilization efficiency. Gas chromatography-mass spectrometry (GC-MS) analysis showed that most of the organic matters in ML-GFW were degraded, while some residuals needed further treatment. This study provided the data and the necessary technical supports for further research on the treatment of ML-GFW.