摘要
A laboratory scale test was conducted in a combined membrane process （CMP） with a capacity of 2.91 m3/d for 240 d to treat the mixed wastewater of humidity condensate, hygiene wastewater and urine in submarine cabin during prolonged voyage. Removal performance of chemical oxygen demand （COD）, ammonia nitrogen （NH4^＋-N）, turbidity and anionic surfactants （LAS） was investigated under different conditions. It was observed that the effluent COD, NH4^＋-N, turbidity and LAS flocculated in ranges of 0.19-0.85 mg/L, 0.03-0.18 mg/L, 0.0-0.15 NTU and 0.0-0.05 mg/L, respectively in spite of considerable fluctuation in corresponding influent of 2120-5350 mg/L, 79.5-129.3 mg/L, 110-181.1NTU and 4.9-5.4 mg/L. The effluent quality of the CMP could meet the requirements of mechanical water and hygiene water according to the class I water quality standards in China （GB3838-2002）. The removal rates of COD, NH4^＋-N, turbidity and LAS removed in the MBR were more than 90%, which indicated that biodegradation is indispensable and plays a major role in the wastewater treatment and reuse. A model, built on the back propagation neural network （BPNN） theory, was developed for the simulation of CMP and produced high reliability. The average error of COD and NH4^＋-N was 5.14% and 6.20%, respectively, and the root mean squared error of turbidity and LAS was 2.76% and 1.41%, respectively. The results indicated that the model well fitted the laboratory data, and was able to simulate the removal of COD, NH4^＋-N, turbidity and LAS. It also suggested that the model proposed could reflect and manage the operation of CMP for the treatment of the mixed wastewaters in submarine.
A laboratory scale test was conducted in a combined membrane process （CMP） with a capacity of 2.91 m3/d for 240 d to treat the mixed wastewater of humidity condensate, hygiene wastewater and urine in submarine cabin during prolonged voyage. Removal performance of chemical oxygen demand （COD）, ammonia nitrogen （NH4^＋-N）, turbidity and anionic surfactants （LAS） was investigated under different conditions. It was observed that the effluent COD, NH4^＋-N, turbidity and LAS flocculated in ranges of 0.19-0.85 mg/L, 0.03-0.18 mg/L, 0.0-0.15 NTU and 0.0-0.05 mg/L, respectively in spite of considerable fluctuation in corresponding influent of 2120-5350 mg/L, 79.5-129.3 mg/L, 110-181.1NTU and 4.9-5.4 mg/L. The effluent quality of the CMP could meet the requirements of mechanical water and hygiene water according to the class I water quality standards in China （GB3838-2002）. The removal rates of COD, NH4^＋-N, turbidity and LAS removed in the MBR were more than 90%, which indicated that biodegradation is indispensable and plays a major role in the wastewater treatment and reuse. A model, built on the back propagation neural network （BPNN） theory, was developed for the simulation of CMP and produced high reliability. The average error of COD and NH4^＋-N was 5.14% and 6.20%, respectively, and the root mean squared error of turbidity and LAS was 2.76% and 1.41%, respectively. The results indicated that the model well fitted the laboratory data, and was able to simulate the removal of COD, NH4^＋-N, turbidity and LAS. It also suggested that the model proposed could reflect and manage the operation of CMP for the treatment of the mixed wastewaters in submarine.
基金
This work was supported by the Heilongjiang Natural Science Foundation(No.E2007-04)
the National Natural Science Foundation of China(No.50908062)
the State Key Laboratory of Urban Water Resource and Environment(No.HIT-QAK200808).
