title: Pollutants removal and simulation model of combined membrane process for wastewater treatment and reuse in submarine cabin for long voyage.
abstract: 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 (NH(4+)-N), turbidity and anionic surfactants (LAS) was investigated under different conditions. It was observed that the effluent COD, NH(4+)-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, NH(4+)-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 NH(4+)-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, NH(4+)-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.
authors.affiliation: State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China. czbhdx@163.com
authors.forename: Zhaobo
authors.initials: Z
authors.lastname: Chen
authors.forename: Aijuan
authors.initials: A
authors.lastname: Zhou
authors.forename: Nanqi
authors.initials: N
authors.lastname: Ren
authors.forename: Yu
authors.initials: Y
authors.lastname: Tian
authors.forename: Dongxue
authors.initials: D
authors.lastname: Hu
mesh_terms: D003198:Computer Simulation; D018504:Ecological Systems, Closed; D008567:Membranes, Artificial; D009391:Nephelometry and Turbidimetry; D016571:Neural Networks, Computer; D009584:Nitrogen / Q000737:chemistry*; D012767:Ships; D013501:Surface-Active Agents / Q000737:chemistry*; D014874:Water Pollutants, Chemical / Q000737:chemistry*
chemical_list: D008567:Membranes, Artificial; D013501:Surface-Active Agents; D014874:Water Pollutants, Chemical; D009584:Nitrogen