A comprehensive simulation approach for pollutant bio-transformation in the gravity sewer

  • Nan Zhao
  • Huu Hao Ngo
  • Yuyou Li
  • Xiaochang Wang
  • Lei Yang
  • Pengkang JinEmail author
  • Guangxi Sun
Research Article


Presently, several activated sludge models (ASMs) have been developed to describe a few biochemical processes. However, the commonly used ASM neither clearly describe the migratory transformation characteristics of fermentation nor depict the relationship between the carbon source and biochemical reactions. In addition, these models also do not describe both ammonification and the integrated metabolic processes in sewage transportation. In view of these limitations, we developed a new and comprehensive model that introduces anaerobic fermentation into the ASM and simulates the process of sulfate reduction, ammonification, hydrolysis, acidogenesis and methanogenesis in a gravity sewer. The model correctly predicts the transformation of organics including proteins, lipids, polysaccharides, etc. The simulation results show that the degradation of organics easily generates acetic acid in the sewer system and the high yield of acetic acid is closely linked to methanogenic metabolism. Moreover, propionic acid is the crucial substrate for sulfate reduction and ammonification tends to be affected by the concentration of amino acids. Our model provides a promising tool for simulating and predicting outcomes in response to variations in wastewater quality in sewers.


Gravity sewer Modeling Pollutant transformation Biochemical reaction process 



This work was financially supported by the National Key Project of Water Pollution Control and Management (Grant No. 2012ZX07313-001), the New Century Excellent Talents Award Program from Education Ministry of China (Grant No. NCET-12-1043), and the Program for Innovative Research Team in Shaanxi Province (Grant No. 2013KCT-13).

Supplementary material


  1. Abdul-Talib S, Hvitved-Jacobsen T, Vollertsen J, Ujang Z (2002). Half saturation constants for nitrate and nitrite by in-sewer anoxic transformations of wastewater organic matter. Water Science and Technology, 46(9): 185–192Google Scholar
  2. Barrera E L, Spanjers H, Solon K, Amerlinck Y, Nopens I, Dewulf J (2015). Modeling the anaerobic digestion of cane-molasses vinasse: Extension of the Anaerobic Digestion Model No. 1 (ADM1) with sulfate reduction for a very high strength and sulfate rich wastewater. Water Research, 71: 42–54Google Scholar
  3. Bentler P M, Bonett D G (1980). Significance tests and goodness of fit in the analysis of covariance structure. Psychological Bulletin, 88(3): 588–606Google Scholar
  4. Cravo-Laureau C, Labat C, Joulian C, Matheron R, Hirschler-Réa A (2007). Desulfatiferula olefinivorans gen. nov., sp. nov., a long-chain n-alkene-degrading, sulfate-reducing bacterium. International Journal of Systematic and Evolutionary Microbiology, 57(11): 2699–2702Google Scholar
  5. Fedorovich V, Lens P, Kalyuzhnyi S (2003). Extension of Anaerobic Digestion Model No. 1 with processes of sulfate reduction. Applied Biochemistry and Biotechnology, 109(1–3): 33–46Google Scholar
  6. Fu G, Makropoulos C, Butler D (2010). Simulation of urban wastewater systems using artificial neural networks: Embedding urban areas in integrated catchment modelling. Journal of Hydroinformatics, 12(2): 140–149Google Scholar
  7. Garsdal H, Mark O, Dorge J, Jepsen S (1995). Mousetrap: Modelling of water quality processes and the interaction of sediments and pollutants in sewers. Water Science and Technology, 31(7): 33–41Google Scholar
  8. Guisasola A, Sharma K R, Keller J, Yuan Z (2009). Development of a model for assessing methane formation in rising main sewers. Water Research, 43(11): 2874–2884Google Scholar
  9. Higashioka Y, Kojima H, Nakagawa T, Sato S, Fukui M (2009). A novel n-alkane-degrading bacterium as a minor member of p-xylene-degrading sulfate-reducing consortium. Biodegradation, 20(3): 383–390Google Scholar
  10. Huisman J L, Gujer W (2002). Modelling wastewater transformation in sewers based on ASM3. Water Science and Technology, 45(6): 51–60Google Scholar
  11. Hvitved-Jacobsen T, Vollertsen J, Nielsen P H (1998). A process and model concept for microbial wastewater transformations in gravity sewers. Water Science and Technology, 37(1): 233–241Google Scholar
  12. Jiang F, Leung D H, Li S, Chen G H, Okabe S, van Loosdrecht M C (2009). A biofilm model for prediction of pollutant transformation in sewers. Water Research, 43(13): 3187–3198Google Scholar
  13. Jiang F, Leung H W, Li S Y, Lin G S, Chen G H (2007). A new method for determination of parameters in sewer pollutant transformation process model. Environmental Technology, 28(11): 1217–1225Google Scholar
  14. Jie W, Peng Y, Ren N, Li B (2014). Volatile fatty acids (VFAs) accumulation and microbial community structure of excess sludge (ES) at different pHs. Bioresource Technology, 152: 124–129Google Scholar
  15. Jin P, Shi X, Sun G, Yang L, Cai Y, Wang X C (2018). Co-variation between distribution of microbial communities and biological metabolization of organics in urban sewer systems. Environmental Science & Technology, 52(3): 1270–1279Google Scholar
  16. Jin P, Wang B, Jiao D, Sun G, Wang B, Wang X C (2015). Characterization of microflora and transformation of organic matters in urban sewer system. Water Research, 84: 112–119Google Scholar
  17. Jing Z, Hu Y, Niu Q, Liu Y, Li Y Y, Wang X C (2013). UASB performance and electron competition between methane-producing archaea and sulfate-reducing bacteria in treating sulfate-rich waste-water containing ethanol and acetate. Bioresource Technology, 137: 349–357Google Scholar
  18. Kreisberg R A, Siegal A M, Owen W C (1971). Glucose-lactate interrelationships: Effect of ethanol. Journal of clinical investigation, 50(1): 175–185Google Scholar
  19. Li H, Song Y, Li Q, He J, Song Y (2014). Effective microbial calcite precipitation by a new mutant and precipitating regulation of extracellular urease. Bioresource Technology, 167: 269–275Google Scholar
  20. Li Y F, Wei S, Yu Z (2013). Feedstocks affect the diversity and distribution of propionate CoA-transferase genes (pct) in anaerobic digesters. Microbial Ecology, 66(2): 351–362Google Scholar
  21. Liu H, Yu T, Liu Y (2015). Sulfate reducing bacteria and their activities in oil sands process-affected water biofilm. The Science of the total environment, 536: 116–122Google Scholar
  22. Liu Y, Boone D R (1991). Effects of salinity on methanogenic decomposition. Bioresource Technology, 35(3): 271–273Google Scholar
  23. Mackey H R, Rey Morito G, Hao T, Chen G H (2016). Pursuit of urine nitrifying granular sludge for decentralised nitrite production and sewer gas control. Chemical Engineering Journal, 289: 17–27Google Scholar
  24. Nie Y Q, Liu H, Du G C, Chen J (2007). Enhancement of acetate production by a novel coupled syntrophic acetogenesis with homoacetogenesis process. Process Biochemistry, 42(4): 599–605Google Scholar
  25. Onifade A A, Al-Sane N A, Al-Musallam A A, Al-Zarban S (1998). A review: Potentials for biotechnological applications of keratin-degrading microorganisms and their enzymes for nutritional improvement of feathers and other keratins as livestock feed resources. Bioresource Technology, 66(1): 1–11Google Scholar
  26. Pandey S K, Kim K H, Kwon E E, Kim Y H (2016). Hazardous and odorous pollutants released from sewer manholes and stormwater catch basins in urban areas. Environmental Research, 146: 235–244Google Scholar
  27. Pereyra L P, Hiibel S R, Prieto Riquelme M V, Reardon K F, Pruden A (2010). Detection and quantification of functional genes of cellulose-degrading, fermentative, and sulfate-reducing bacteria and methanogenic archaea. Applied and Environmental Microbiology, 76(7): 2192–2202Google Scholar
  28. Rahman A, Kumashiro M, Ishihara T (2011). Direct synthesis of formic acid by partial oxidation of methane on H-ZSM-5 solid acid catalyst. Catalysis Communications, 12(13): 1198–1200Google Scholar
  29. Rajagopal R, Massé D I, Singh G (2013). A critical review on inhibition of anaerobic digestion process by excess ammonia. Bioresource Technology, 143: 632–641Google Scholar
  30. Ramsing N B, Kühl M, Jørgensen B B (1993). Distribution of sulfate-reducing bacteria, O2, and H2S in photosynthetic biofilms determined by oligonucleotide probes and microelectrodes. Applied and Environmental Microbiology, 59(11): 3840–3849Google Scholar
  31. Rawsthorne H, Dock C N, Jaykus L A (2009). PCR-based method using propidium monoazide to distinguish viable from nonviable Bacillus subtilis spores. Applied and Environmental Microbiology, 75(9): 2936–2939Google Scholar
  32. Ren N, Wang B, Huang J C (1997). Ethanol-type fermentation from carbohydrate in high rate acidogenic reactor. Biotechnology and Bioengineering, 54(5): 428–433Google Scholar
  33. Ren N, Wang Q, Wang Q, Huang H, Wang X (2017). Upgrading to urban water system 3.0 through sponge city construction. Frontiers of Environmental Science & Engineering, 11(4): 9Google Scholar
  34. Ross T (1996). Indices for performance evaluation of predictive models in food microbiology. The Journal of applied bacteriology, 81(5): 501–508Google Scholar
  35. Rudelle E, Vollertsen J, Hvitved-Jacobsen T, Nielsen A H (2011). Anaerobic transformations of organic matter in collection systems. Water Environment Research A: Research Publication of the Water Environment Federation, 83(6): 532–540Google Scholar
  36. Schmitt F, Seyfried C F (1992). Sulfate reduction in sewer sediments. Water Science and Technology, 25(8): 83–90Google Scholar
  37. Sepers A B J (1981). Diversity of ammonifying bacteria. Hydrobiologia, 83(2): 343–350Google Scholar
  38. Sharma K, Derlon N, Hu S, Yuan Z (2014). Modeling the pH effect on sulfidogenesis in anaerobic sewer biofilm. Water Research, 49: 175–185Google Scholar
  39. Sharma K, Ganigue R, Yuan Z (2013). pH dynamics in sewers and its modeling. Water Research, 47(16): 6086–6096Google Scholar
  40. Song X, Zhang Z (2011). Notice of Retraction Sulfate Reducing Rate of SRB with Acetic, Propionic, n-Butyric Acids as Carbon Sources. In: The 5th International Conference on Bioinformatics and Biomedical Engineering, Wuhan. New York: Curran Associates, 1–4Google Scholar
  41. Steinberg L M, Regan J M (2009). mcrA-targeted real-time quantitative PCR method to examine methanogen communities. Applied and Environmental Microbiology, 75(13): 4435–4442Google Scholar
  42. Sun Y, Zhao J, Chen L, Liu Y, Zuo J (2018). Methanogenic community structure in simultaneous methanogenesis and denitrification granular sludge. Frontiers of Environmental Science & Engineering, 12(4): 10Google Scholar
  43. Taconi K A, Zappi M E, Todd French W, Brown L R (2008). Methanogenesis under acidic pH conditions in a semi-continuous reactor system. Bioresource Technology, 99(17): 8075–8081Google Scholar
  44. Uggetti E, Sialve B, Latrille E, Steyer J P (2014). Anaerobic digestate as substrate for microalgae culture: the role of ammonium concentration on the microalgae productivity. Bioresource Technology, 152(152): 437–443Google Scholar
  45. Vavilin V A (2002). The IWA Anaerobic Digestion Model No. 1. London: IWA PublishingGoogle Scholar
  46. Widdel F, Pfennig N (1977). A new anaerobic, sporing, acetate-oxidizing, sulfate-reducing bacterium, Desulfotomaculum (emend.) acetoxidans. Archives of Microbiology, 112(1): 119–122Google Scholar
  47. Yuan D, Rao K, Relue P, Varanasi S (2011). Fermentation of biomass sugars to ethanol using native industrial yeast strains. Bioresource Technology, 102(3): 3246–3253Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Nan Zhao
    • 1
  • Huu Hao Ngo
    • 2
  • Yuyou Li
    • 3
  • Xiaochang Wang
    • 1
  • Lei Yang
    • 1
  • Pengkang Jin
    • 1
    Email author
  • Guangxi Sun
    • 4
  1. 1.School of Environmental and Municipal EngineeringXi’an University of Architecture and TechnologyXi’anChina
  2. 2.Centre for Technology in Water and Wastewater, School of Civil and Environmental EngineeringUniversity of TechnologySydneyAustralia
  3. 3.Department of Civil and Environmental EngineeringTohoku UniversitySendai, MiyagiJapan
  4. 4.Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijingChina

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