Influence of salinity on the biological treatment of domestic ship sewage using an air-lift multilevel circulation membrane reactor

  • Yuhang Cai
  • Asad A. Zaidi
  • Yue ShiEmail author
  • Kun Zhang
  • Xin Li
  • Shihao Xiao
  • Aqiang Lin
Research Article


Recently, strict standards for ship domestic sewage discharge have been implemented by the International Maritime Organization (IMO). The high salinity of ship sewage was considered a key factor influencing the removal efficiency of ship sewage treatment systems. In the present study, the salinity effect on the removal of chemical oxygen demand (COD) and ammonia nitrogen (NH4+-N) from ship domestic sewage was investigated by using a novel air-lift multilevel circulation membrane reactor (AMCMBR). Enzyme activity analysis and wavelet neural network (WNN) models were built to determine the mechanisms of the process. The experimental results indicate that high salinity levels (> 21 g/L) had a negative impact on COD and NH4+-N removal efficiencies, and low saline concentrations (≤ 21 g/L) caused a negligible effect. The COD and NH4-N removal efficiencies were 84% and 97%, respectively, at a salinity of 21 g/L, which were higher than those at low salinities (i.e., 7 g/L and 14 g/L). Invertase and nitrate reductase had a close relationship with removal performance, and they can be considered important indicators reflecting the operation effort under saline environments. With high predictive accuracies, the constructed WNN models simulated the complex COD and NH4+-N removal processes well under different saline concentrations, ensuring the long-term stable operation of the AMCMBR under different salinities.


Ship sewage treatment Biodegradation Enzyme activity Wavelet neural network Numerical simulation 


Funding information

This research was financially supported by the National Key R&D Plan of China (2017YFC1404603), the Natural Science Foundation of China (Grant No. 51579049), the Natural Science Foundation of Heilongjiang Province (E2017020), and the Fundamental Research Funds for the Central Universities (HEUCFG201820).


  1. Alejandro RS, Barbara MP, Miguel HM, Maria AR, Jose MP, Jesus GL (2018) Maximum influent salinity affects the diversity of mineral-precipitation-mediating bacterial communities in membrane biofilm of hybrid moving bed biofilm reactor-membrane bioreactor. Water Air Soil Pollut 229:342CrossRefGoogle Scholar
  2. Alejandro RS, Juan CLD, Barbara MP, Jose MP, Jesus GL (2019) Influence of salinity cycles in bioreactor performance and microbial community structure of membrane-based tidal-like variable salinity wastewater treatment systems. Environ Sci Pollut Res 26:514–527CrossRefGoogle Scholar
  3. APHA (2012) Standard methods for the examination of water and wastewater. American Public Health AssociationGoogle Scholar
  4. Baddam R, Reddy GB, Raczkowski C, Cyrus JS (2016) Activity of soil enzymes in constructed wetlands treated with swine wastewater. Ecol Eng 91:24–30CrossRefGoogle Scholar
  5. Bassin JP, Kleerebezem R, Muyzer G, Rosado AS, Mark CM, Loosdrecht V, Dezotti M (2012) Effect of different salt adaptation strategies on the microbial diversity, activity, and settling of nitrifying sludge in sequencing batch reactors. Appl Microbiol Biotechnol 93:1281–1294CrossRefGoogle Scholar
  6. Bella GD, Prima ND, Trapani DD, Freni G, Giustra MG, Torregrossa M, Viviani G (2015) Performance of membrane bioreactor (MBR) systems for the treatment of shipboard slops: Assessment of hydrocarbon biodegradation and biomass activity under salinity variation. J Hazard Mater 300:765–778CrossRefGoogle Scholar
  7. Buhmann AK, Waller U, Wecker B, Papenbrock J (2015) Optimization of culturing conditions and selection of species for the use of halophytes as biofilter for nutrient rich saline water. Agric. Water Manag 149:102–114CrossRefGoogle Scholar
  8. Cai H, Shen R (2005) Determination of soil protease activity with modified ninhydrin colorimetry. Acta Pedol Sin 42:306–313 (in Chinese)Google Scholar
  9. Cai YH, Li X, Zaidi AA, Shi Y, Zhang K, Sun PQ, Lu Z (2019a) Processing efficiency, simulation and enzyme activities analysis of an air-lift multilevel circulation membrane bioreactor (AMCMBR) on marine domestic sewage treatment. Period Polytech-Chem 63(3):448–458Google Scholar
  10. Cai YH, Ben T, Zaidi AA, Shi Y, Zhang K (2019b) Nitrogen removal augmentation of ship sewage by an innovative aerobic-anaerobic micro-sludge MBR technology. Process Biochem 82:123–134CrossRefGoogle Scholar
  11. Cai YH, Ben T, Zaidi AA, Shi Y, Zhang K, Lin AQ, Liu C (2019c) Effect of pH on pollutants removal of ship sewage treatment in an innovative aerobic anaerobic micro-sludge MBR system. Water Air Soil Pollut 230:163CrossRefGoogle Scholar
  12. Cai YH, Li X, Zaidi AA, Shi Y, Zhang K, Feng RZ, Lin AQ, Liu C (2019d) Effect of hydraulic retention time on pollutants removal from real ship sewage treatment via a pilot-scale air-lift multilevel circulation membrane bioreactor. Chemosphere. 236:124338CrossRefGoogle Scholar
  13. Chen ZQ, Wang HC, Chen ZB, Ren NQ, Wang AJ, Shi Y, Li XM (2011) Performance and model of a full-scale up-flow anaerobic sludge blanket (UASB) to treat the pharmaceutical wastewater containing 6-APA and amoxicillin. J Hazard Mater 185:905–913CrossRefGoogle Scholar
  14. Chen ZB, He ZW, Hu DX (2015) Effect of temperature on treating chemical synthesis-based pharmaceutical wastewater containing 7-ACA by a novel multi-stage loop membrane bioreactor. J Chem Technol Biotechnol 90:1002–1012CrossRefGoogle Scholar
  15. Cortés L, Díaz MR, Lopez CL, Peinado MS, Rodelas B, López JG (2012) Effect of salinity on enzymatic activities in a submerged fixed bed biofilm reactor for municipal sewage treatment. Bioresour Technol 121:312–319Google Scholar
  16. Corzo A, Niell FX (1991) Determination of reductase activity in Ulva rigida C. Agardh by the in situ method. J Exp Mar Ecol 146:181–191CrossRefGoogle Scholar
  17. Cristea VM, Pop C, Agachi PS (2009) Artificial neural networks modeling of PID and model predictive controlled waste water treatment plant based on the benchmark simulation model 1. Computer Aided Chemical Eng 26:1183–1188CrossRefGoogle Scholar
  18. Cristian F (2008) Insights into the role and structure of plant ureases. Phytochemistry 69:18–28CrossRefGoogle Scholar
  19. Cui F, Park S, Kim M (2014) Characteristics of aerobic granulation at mesophilic temperatures in wastewater treatment. Bioresour Technol 151:78–84CrossRefGoogle Scholar
  20. Cunha A, Almeida A, Coelho FJRC, Gomes NCM, Oliveira V, Santos AL (2010) Bacterial extracellular enzymatic activity in globally changing aquatic ecosystems. In: current research, technology and education topics in applied microbiology and microbial biotechnology. In: Mendez-Vilas A (ed) Formatex microbiology series, vol 1. Badajoz, Spain, pp 124–135Google Scholar
  21. Doucoure B, Agbossou K, Cardenas A (2016) Time series prediction using artificial wavelet neural network and multi-resolution analysis: application to wind speed data. Renew Energy 92:202–211CrossRefGoogle Scholar
  22. Forstner U (1998) Water pollution: wasterwater. Integrated Pollution Co Ntrol 197-238.Google Scholar
  23. Gao F, Nan J, Li SN, Wang YR (2018) Modeling and simulation of a biological process for treating different COD:N ratio wastewater using an extended ASM1 model. Chem Eng J 332:671–681CrossRefGoogle Scholar
  24. Guo QJ, Qi XN, Zheng W, Yin Q, Sun P, Guo PJ, Liu JC (2019) Modeling and characteristic analysis of fouling in a wet cooling tower based on wavelet neural networks. Appl Therm Eng 152:907–916CrossRefGoogle Scholar
  25. Huang B, Wang HC, Cui D, Zhang B, Chen ZB, Wang AJ (2018) Treatment of pharmaceutical wastewater containing β-lactams antibiotics by a pilot-scale anaerobic membrane bioreactor (AnMBR). Chem Eng J 341:238–247CrossRefGoogle Scholar
  26. Hülsen T, Hsieh K, Batstone DJ (2019) Saline wastewater treatment with purple phototrophic bacteria. Water Res 160:259–267CrossRefGoogle Scholar
  27. IMO-MEPC (2006) Revised guidelines on implementation of effluent standards and performance tests for sewage treatment plants. In: Committee MEP, editor. 159(55). MEPC 55/23 Annex 26.Google Scholar
  28. IMO-MEPC (2010) Revised guidelines on implementation of effluent standards and performance tests for sewage treatment plants. In: Committee MEP, editor. 227(64). MEPC 64/23 Annex 22.Google Scholar
  29. Jammazi R, Aloui C (2012) Crude oil forecasting: experimental evidence from wavelet decomposition and neural network modeling. Energy Econ 34:828–841CrossRefGoogle Scholar
  30. Jang D, Wang Y, Shin H, Lee W (2013) Effects of salinity on the characteristics of biomass and membrane fouling in membrane bioreactors. Bioresour Technol 141:50–56CrossRefGoogle Scholar
  31. Jiang XQ, Lin AQ, Ma HL, Li XY, Li YY (2020) Minimizing the thermal bridge through the columns in a refrigeration room. Appl Therm Eng. 165:114565Google Scholar
  32. Johir MAH, Vigneswaran S, Kandasamy J, BenAim R, Grasmick A (2013) Effect of salt concentration on membrane bioreactor (MBR) performances: detailed organic characterization. Desalination 322:13–20CrossRefGoogle Scholar
  33. Karim SAA, Kamarudin MG, Karim BA, Hasan MK, Sulaiman J (2011) Wavelet transform and fast Fourier transform for signal compression: a comparative study. Int Conf Electr Dev 280–285Google Scholar
  34. Kumar VBA, Mohan TCK, Murugan K (2008) Purification and kinetic characterization of polyphenol oxidase from Barbados cherry (Malpighia glabraL.). Food Chem 110:328–333CrossRefGoogle Scholar
  35. Lay WCL, Liu Y, Fane AG (2010) Impacts of salinity on the performance of high retention membrane bioreactors for water reclamation: a review. Water Res 44:21–40CrossRefGoogle Scholar
  36. Li R, Wang Y, Ling J, Liao X (2017) Effects of high pressure processing on activity and structure of soluble acid invertase in mango pulp, crude extract, purified form and model systems. Food Chem 231:96–104CrossRefGoogle Scholar
  37. Li M, Liang ZL, Callier MD, Emmanuelle R, Sun GX, Ma XN, Li X, Wang SK, Liu Y, Song XF (2018) Nutrients removal and substrate enzyme activities in vertical subsurface flow constructed wetlands for mariculture wastewater treatment: effects of ammonia nitrogen loading rates and salinity levels. Mar Pollut Bull 131:142–150CrossRefGoogle Scholar
  38. Lin AQ, Sun YG, Zhang H, Lin X, Yang L, Zheng Q (2018) Fluctuating characteristics of air-mist mixture flow with conjugate wall-film motion in a compressor of gas turbine. Appl Therm Eng 142: 779–792Google Scholar
  39. Mannina G, Cosenza A, Trapani DD, Capodici M, Viviani G (2016) Membrane bioreactors for treatment of saline wastewater contaminated by hydrocarbons (diesel fuel): an experimental pilot plant case study. Chem Eng J 291:269–278CrossRefGoogle Scholar
  40. Muhammad A, Amine C, Jeonghwan K (2019) Membrane scouring to control fouling under fluidization of non-adsorbing media for wastewater treatment. Environ Sci Pollut Res 26:1061–1071CrossRefGoogle Scholar
  41. Panapakidis PI, Dagoumas AS (2017) Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model. Energy 118:231–245CrossRefGoogle Scholar
  42. Panswad T, Anan C (1999) Impact of high chloride wastewater on an anerobic/anoxic/aerobic process with and without inoculation of chloride acclimated seeds. Water Res 33:1165–1172CrossRefGoogle Scholar
  43. Reid E, Liu XR, Judd SJ (2006) Effect of high salinity on activated sludge characteristics and membrane permeability in an immersed membrane bioreactor. J Membr Sci 1–2(283):164–171CrossRefGoogle Scholar
  44. Serra WC, Houot S, Barriuso E (1995) Soil enzymatic response to addition of municipal solid-waste compost. Biol Fertil Soils 20:226–236CrossRefGoogle Scholar
  45. Shi Y, Zhao XT, Zhang YM, Ren NQ (2009) Back propagation neural network (BPNN) prediction model and control strategies of methanogen phase reactor treating traditional Chinese medicine wastewater (TCMW). J Biotechnol 144:70–74CrossRefGoogle Scholar
  46. Tan S, Cui C, Chen X, Li W (2017) Effect of bioflocculation on fouling-related biofoulants in a membrane bioreactor during saline wastewater treatments. Bioresour Technol 224:285–291CrossRefGoogle Scholar
  47. Urszula GD, Szymanowska U, Baraniak B (2007) Characterization of polyphenol oxidase from broccoli (Brassica oleracea var. botrytis italica) florets. Food Chem 105:1047–1053CrossRefGoogle Scholar
  48. Vendramel S, Dezotti M, Sant’Anna GL Jr (2011) Nitrification of an industrial wastewater in a moving-bed biofilm reactor: effect of salt concentration. Environ Technol 32(8):837–846CrossRefGoogle Scholar
  49. Vieira A, Marques R, Galinha C, Povoa P, Carvalho G, Oehmen A (2019) Nitrous oxide emissions from a full-scale biological aerated filter (BAF) subject to seawater infiltration. Environ Sci Pollut Res 26:20939–20948CrossRefGoogle Scholar
  50. Whiffin VS, Paassen VLA, Harkes MP (2007) Microbial carbonate precipitation as a soil improvement technique. Geomicrobiol J 24(5):417–423CrossRefGoogle Scholar
  51. Yogalakshmi KN, Joseph K (2010) Effect of transient sodium chloride shock loads on the performance of submerged membrane bioreactor. Bioresour Technol 101:7054–7061CrossRefGoogle Scholar
  52. Yun MA, Yeon KM, Park JS, Lee CH, Chun J, Lim DJ (2006) Characterization of biofilm structure and its effect on membrane permeability in MBR for dye wastewater treatment. Water Res 1(40):45–52CrossRefGoogle Scholar
  53. Zhang GN, Chen ZH, Zhang AM, Chen LJ, Wu ZJ (2013) Nitrogen and phosphorus related hydrolytic enzyme activities influenced by N deposition under semiarid grassland soil. In: Advanced Materials Research. Trans Tech Publ, pp 3847–3854Google Scholar
  54. Zheng MS, Lin JJ, Zhou SD, Zhong JL, Li YH, Xu NJ (2019) Salinity mediates the effects of nitrogen enrichment on the growth, photosynthesis, and biochemical composition of Ulva prolifera. Environ Sci Pollut Res 26:19982–19990CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Yuhang Cai
    • 1
  • Asad A. Zaidi
    • 2
  • Yue Shi
    • 1
    Email author
  • Kun Zhang
    • 1
  • Xin Li
    • 3
  • Shihao Xiao
    • 1
  • Aqiang Lin
    • 1
  1. 1.College of Power and Energy EngineeringHarbin Engineering UniversityHarbinPR China
  2. 2.Department of Engineering Sciences, PN Engineering CollegeNational University of Sciences and TechnologyKarachiPakistan
  3. 3.China Aviation Development InstituteShenyang CityChina

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