Mathematical model of dissolved microbial products in sewage treatment system

  • Xinwei Feng Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, College of Civil and Environmental, Hubei University of Technology, Ministry of Education, Wuhan 430068, Hubei, China
  • Jialei Zhang Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, College of Civil and Environmental, Hubei University of Technology, Ministry of Education, Wuhan 430068, Hubei, China
Keywords: dissolved microbial products; mathematical model; sewage treatment system; water resources
Article ID: 420

Abstract

Water is the source of life, but all kinds of water resources in the world are suffering from different degrees of pollution. Water pollution leads to a serious shortage of available fresh water resources, and sewage treatment is the main way to solve water pollution. For the sewage after biological treatment of activated sludge, the organic matter contained in the effluent is mainly the dissolved microbial products (SMPs) produced in the process of microbial metabolism. The composition of SMPs is complex, mainly including macromolecular substances such as protein, polysaccharide, humic acid and DNA and cell fragments. The mathematical model of activated sludge is a quantitative description of the mathematical relationship between substrate degradation parameters and microbial growth. Starting from the Monod equation representing the relationship between substrate consumption and microbial growth, it combines the reactor theory and microbiology theory in the chemical field. Based on the principle of conservation of materials and Monod equation, the mathematical expression of organic degradation model was determined according to the collected data and empirical values of parameters. The general idea of activated sludge model No.1 (ASM1) for activated sludge process simulation was introduced, and the influence of sludge concentration on SBR process water treatment was explored. It was found that the removal rate of COD, ammonia nitrogen, total nitrogen and total phosphorus increases with the increase of sludge concentration. When C/N=8, the removal rate of ammonia nitrogen increased from 62% to 81%, and the removal rate of total nitrogen increased from 64% to 82%, with the most obvious effect.

References

1. Shi Y, Huang J, Zeng G.Evaluation of soluble microbial products(SMP)on membrane fouling in membrane bioreactors(MBRs)at the fractional and overall level:a review. Reviews in Environmental Science and Bio/Technology,2017,17(1):1-15.

2. Zhang D Q, Eng C Y, Stuckey D C. Effects of ZnO nanoparticle exposure on wastewater treatment and soluble microbial products(SMPs) in an anoxic-aerobic membrane bioreactor. Chemosphere, 2017, 171(MAR.): 446-459.

3. Dong H, Wei D, Wei J.Qualitative and quantitative spectrometric evaluation of soluble microbial products formation in aerobic granular sludge system treating nitrate wastewater. Bioprocess&Biosystems Engineering, 2018, 41(6): 841-850.

4. Cao R,Zhou J, Chen W.Insights into membrane fouling implicated by physical adsorption of soluble microbial products onto D3520 resin. Chinese Journal of Chemical Engineering, 2020, 28(2): 429-439.

5. D Andraka, Piszczatowska I K, Dawidowicz J. Calibration of Activated Sludge Model with Scarce Data Sets. Journal of Ecological Engineering, 2018, 19(6):182-190.

6. Tian-Wei, Song, Xiao-Lin. [Nitrification and Bioaugmentation of Biological Treatment System of Sewage Treatment Plant at High Temperature in Summer]. . Huan jing ke xue=Huanjing kexue, 2019, 40(2): 768-773.

7. Feng G, Nan J, Zhang X . A dynamic modelling of nutrient metabolism in a cyclic activated sludge technology (CAST) for treating low carbon source wastewater. Environmental Science and Pollution Research, 2017, 24(20):1-15.

8. Kaur H, Sahu N, Khilnani A S.Assessment of Sewage Quality for Implementation of Decentralized Sewage Treatment System for Small Communities in Nagpur. Journal of Indian Water Works Association, 2017, 49(1): 31-35.

9. Zhu M Y, Peng S C, Tao W.Response of methane production and microbial community to the enrichment of soluble microbial products in goethite-dosed anaerobic reactors. Fuel, 2017, 191(mar.1): 495-499.

10. Teng J, Zhang M, Leung K T.A unified thermodynamic mechanism underlying fouling behaviors of soluble microbial products(SMPs)in a membrane bioreactor. Water Research, 2019, 149(FEB.1): 477-487.

11. Villain-Gambier M, Bourven I, Guibaud G. Influence of proteins and humic-like substances from soluble microbial products on membrane bioreactor fouling under normal and stress conditions. Process Biochemistry, 2019, 78(MAR.):140-147.

12. Qian J, Zhou J, Pei X.Bioactivities and formation/utilization of soluble microbial products(SMP) in the biological sulfate reduction under different conditions. Chemosphere, 2019,221(APR.): 37-44.

13. Peng L, Ngo H H, Song S. Heterotrophic denitrifiers growing on soluble microbial products contribute to nitrous oxide production in anammox biofilm:Model evaluation. Journal of Environmental Management, 2019, 242(JUL.15): 309-314.

14. Wu M, Liang Y, Zhang Y. The effects of biodegradation on the characteristics and disinfection by-products formation of soluble microbial products chemical fractions. Environmental Pollution, 2019, 253(Oct.):1047-1055.

15. Kang L, Liu SF, Yi DW, Wang K, Du HL, Huang HQ, Chen P. Renewable conversion of coal gangue to 13-X molecular sieve for Cd2+-containing wastewater adsorption performance. Rare Metals, 2024, 43(2):702-710.

16. Marwan Ghanem. Natural Ecological and Environmental Protection Strategies Based on Biotechnology Analysis. Nature Environmental Protection, 2020, 1(3): 1-9.

17. Hong S, Tang X C, Wu N X. Leakage of soluble microbial products from biological activated carbon filtration in drinking water treatment plants and its influence on health risks. Chemosphere, 2018, 202(JUL.): 626-636.

18. Herath B S, Torres A,Sathasivan A. Effects of feed water NOM variation on chloramine demand from chloramine-decaying soluble microbial products during rechloramination. Chemosphere, 2018, 212(DEC.): 744-754.

19. Wu J, Ye J, Peng H. Solar photolysis of soluble microbial products as precursors of disinfection by-products in surface water. Chemosphere, 2018,201(jun.): 66-76.

20. Su X, Su R, Zhang Z.Fouling mechanisms of soluble microbial products and biomacromolecules extracted from membrane bioreactors during early filtration stages. Desalination and water treatment, 2017, 86(AUG.): 19-27.

21. Liu F, Li W, Guo X. Characteristics of soluble microbial products during BCOR-MBR treating brine wastewater. Chinese Journal of Environmental Engineering, 2017, 11(6): 3914-3921.

22. Dong H, Wei D,Wang S.Production of soluble microbial products in aerobic granular sludge system under the stress of toxic 4-chlorophenol. Environmental Technology, 2017, 38(21-24): 3192-3200.

23. Dan,Yang, Dong-Fang. [Characterization Composition of Soluble Microbial Products in an Aerobic Granular Sludge System]. . Huan jing ke xue=Huanjing kexue, 2017, 39(3):1325-1332.

24. Hu H,Y Shi,Liao K.Effect of temperature on the characterization of soluble microbial products in activated sludge system with special emphasis on dissolved organic nitrogen.Water Research,2019,162(OCT.1):87-94.

25. Dan, Yang, Dong-Fang. [Characterization Composition of Soluble Microbial Products in an Aerobic Granular Sludge System]..Huan jing ke xue=Huanjing kexue,2017,39(3):1325-1332.

26. Mankee Jeon. Construction of Sewage Treatment System Integrating Boosting and Bagging Algorithms and Artificial Intelligence. Water Pollution Prevention and Control Project, 2022, 3(2):41-49.

27. Grzegorz Gembalczyk. Construction of Water Pollution Prevention and Control Project of Urban Sewage System Based on Feature Selection Algorithm and Machine Learning. Water Pollution Prevention and Control Project, 2020, 1(3): 1-10.

Published
2024-11-05
How to Cite
Feng, X., & Zhang, J. (2024). Mathematical model of dissolved microbial products in sewage treatment system. Molecular & Cellular Biomechanics, 21(2), 420. https://doi.org/10.62617/mcb.v21i2.420
Section
Article