Kinetic Modelling of Microbial Fuel Cell Voltage Data From Market Fruit Wastes In Nairobi, Kenya

Authors

  • Imwene K. O  University of Nairobi, Faculty of Science and Technology, Department of Chemistry, P.O. BOX 30197, 00100, Nairobi, Kenya
  • Mbui D. N  University of Nairobi, Faculty of Science and Technology, Department of Chemistry, P.O. BOX 30197, 00100, Nairobi, Kenya
  • Mbugua J.K  University of Nairobi, Faculty of Science and Technology, Department of Chemistry, P.O. BOX 30197, 00100, Nairobi, Kenya
  • Kinyua A. P  University of Jyvaskyla, Department of Biological and Environmental Science, P.O. Box 35, FI-40014, University of Jyvaskyla, Finland
  • Kairigo P. K  University of Nairobi, Faculty of Science and Technology, Department of Chemistry, P.O. BOX 30197, 00100, Nairobi, Kenya

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  • Onyatta J. O  

Keywords:

Fruit Waste, Inhibitor, Microorganism, Treatment, Segregation, Kinetic Models

Abstract

Indiscriminate dumping of organic waste is a global problem rapidly being recognized as a health hazard since it attracts rodents and pests that risk human life. As a result, investigation of ways to manage it, which, among other things, involves investigation of the kinetics of its degradation by microorganisms, is crucial. Generally, mathematical and computational models assist in building a connection between input and output variables. This study examines the use of Monod, Haldane, and Han-Levenspiel models to model growth curves obtained from electricity obtained from microbial fuel cells (MFCs) loaded with fruit waste from Kenyan markets. The accuracy of the fitted model was assessed using JMP statistical analysis to provide a test of significance for each market fruit waste collected for the study. Kinetic constants of each model were determined as follows: the constant for the Monod model ranged from 99.57mgL^(-1)to 99.63mgL^(-1), the constant for the Andrew Haldane model ranged from 50.09mgL^(-1)to 50.18mgL^(-1) and that of Han-Levenspiel model ranged from 91.09mgL^(-1)to 100.75mgL^(-1). Multivariate data analysis of market fruit waste (treatment) against both Voltage and current indicated a significant difference in fruit waste mixture and the banana waste, while fruit waste versus Power showed no statistical significant difference in output (P?0.05) in all the treatments. The findings show that extensive use of mathematical models can give a new understanding of how degradation inhibits the bacterium's electricity production, thus leading to new insights into predicting the progress of organic waste reduction in bioremediation analyses. The current study suggests that bacteria consortia have great potential in biodegrading market fruit waste in a fuel cell hence generating electricity. As a result, a successful scale-up process should include material and design optimization that allows for a cost and energy-efficient technology, more lab-based and field-based research work to develop this technique for large-scale applications.

References

  1. Laszlo Koók, Ákos Szabó, Péter Bakonyi, Gábor Tóth, Katalin Bélafi-Bakó, Nándor Nemestóthy . Process simulation of integrated biohydrogen production: hydrogen recovery by Membrane separation. Journal of Agricultural Informatics, 5(2): 45?54. 2014.
  2. Nath, K., Das, D.: Biohydrogen production as a potential energy resource-present state-of-art. Journal of Scientific and Industrial Research, 63:729-738. 2004.
  3. Yoshida, A., Nishimura, T., Kawaguchi, H., Inui, M., Yukawa, H.: Enhanced hydrogen production from glucose using ldh-and frd-inactivated Escherichia coli strains. Applied Microbiology and biotechnology, 73(1): 67-72. 2006.
  4. Siddharth Y. Electricity Production by Microbial Fuel Cell, Department of Farm Power Machinery and Energy, Kerala Agricultural University, 2014.
  5. Gajda I., Stinchcombe A., Merino-Jimenez I., Pasternak G., Sanchez-Herranz D., Greenman J., Ieropoulos I.A. Miniaturized ceramic-based microbial fuel cell for efficient power generation from urine and stack development, Front. Energy Res. 6:084, 2018.
  6. Gajda, I., Greenman, J., Santoro, C., Serov, A., Atanassov, P., Melhuish, C., & Ieropoulos, I. A. Multi?functional microbial fuel cells for power, treatment and electro?osmotic purification of urine. Journal of Chemical Technology & Biotechnology, 94(7), 2098-2106. 2019.
  7. Manhart, M., Adkar, B. V., & Shakhnovich, E. I. Trade-offs between microbial growth phases lead to frequency-dependent and non-transitive selection. Proceedings of the Royal Society B: Biological Sciences, 285(1872), 20172459. 2018.
  8. Koch, C., Kuchenbuch, A., Kretzschmar, J., Wedwitschka, H., Liebetrau, J., Müller, S., & Harnisch, F. Coupling electric energy and biogas production in anaerobic digesters–impacts on the microbiome. RSC Advances, 5(40): 31329-31340, 2015.
  9. Yates, G. T., & Smotzer, T. On the lag phase and initial decline of microbial growth curves. Journal of Theoretical Biology, 244(3), 511-517. 2007.
  10. Song Zhimin. Characterization of kinetics and performance in a microbial fuel cell with synthetic landfill leachate. Open Access Master's Thesis, Michigan Technology University. 2017.
  11. Lee, H. S., Torres, C. I., & Rittmann, B. E. Effects of substrate diffusion and anode potential on kinetic parameters for anode-respiring bacteria. Environmental science & technology, 43(19), 7571-7577. 2009.
  12. Liu, H., & Logan, B. E. Electricity generation using an air-cathode single chamber microbial Fuel cell in the presence and absence of a proton exchange membrane. Environmental science & technology, 38(14), 4040-4046. 2004.
  13. Liu, H., Cheng, S., & Logan, B. E. Production of electricity from acetate or butyrate using A single-chamber microbial fuel cell. Environmental science & technology, 39(2), 658-662. 2005.
  14. Jia, J., Tang, Y., Liu, B., Wu, D., Ren, N. and Xing, D. Electricity Generation from Food Wastes and Microbial Community Structure in Microbial Fuel Cells. Bioresource Technology, 144, 94-99. 2013.
  15. El-Chakhtoura, J., El-Fadel, M., Rao, H. A., Li, D., Ghanimeh, S., & Saikaly, P. E. Electricity generation and microbial community structure of air-cathode microbial fuel cells powered with the organic fraction of municipal solid waste and inoculated with different seeds. Biomass and bioenergy, 67, 24-31. 2014.
  16. Benoit Chezeau, Christophe Vial. Modeling and simulation of Bio-hydrogen production Process, Bio-hydrogen-Second Edition. (445-483). 2019,
  17. Revetta, R. P., Pemberton, A., Lamendella, R., Iker, B., & Santo Domingo, J. W. Identification of bacterial populations in drinking water using 16S rRNA-based sequence analyses. Water Research, 44(5), 1353-1360. 2010.
  18. Esser, D. S., Leveau, J. H., & Meyer, K. M. Modeling microbial growth and dynamics. Applied microbiology and biotechnology, 99(21), 8831-8846. 2015.
  19. Nasrollahzadeh, H. S., Najafpour, G. D., Pazouki, M., Younesi, H., Zinatizadeh, A. A., & Mohammadi, M. Biodegradation of phenanthrene in an anaerobic batch reactor: Growth kinetics. Chemical Industry and Chemical Engineering Quarterly/CICEQ, 16(2), 157-165. 2010.
  20. Gharasoo, M., Centler, F., Van Cappellen, P., Wick, L. Y., & Thullner, M. Kinetics of substrate biodegradation under the cumulative effects of bioavailability and self-inhibition. Environmental science & technology, 49(9), 5529-5537. 2015.
  21. Chai, A., Wong, Y. S., Ong, S. A., Lutpi, N. A., Sam, S. T., Kee, W. C., & Ng, H. H. Haldane-Andrews substrate inhibition kinetics for pilot-scale thermophilic anaerobic degradation of sugarcane vinasse. Bioresource Technology, 125319. 2021.
  22. Vijay, A., Chhabra, M., & Vincent, T. Microbial community modulates electrochemical performance and denitrification rate in a biocathodic autotrophic and heterotrophic denitrifying microbial fuel cell. Bioresource technology, 272, 217-225. 2019.
  23. Seluy, L.G., Isla, M.A. A process to treat high-strength brewery wastewater via ethanol recovery and vinasse fermentation. Ind. Eng. Chem. Res. 53 (44), 17043–17050. 2014.
  24. Zhang Jiqiang., Ping Zhang., Meng Zhang., Hiu Chen., Tingting Chen., Zuofu Xie., Jing Cai, and Ghulam Abbs. Kinetics of substrate degradation and electricity generation in anodic denitrification microbial fuel cell (AD-MFC). Bioresource Technology, 149: 44-50. 2013.
  25. Wang J and W. Wan. "The effect of substrate concentration on bio-hydrogen production by using kinetic models," Science in China B, 51(11), 1110–1117. 2008.
  26. Mullai, P., Rene, E. R., and Sridevi, K. Biohydrogen production and kinetic modeling using sediment microorganisms of pichavaram mangroves, India. Bio-Med research international, 2013. 2013.
  27. Zhao, Y., Hou, Y., Tang, G., Cai, E., Liu, S., Yang, H., Wang, S. Optimization of ultrasonic extraction of phenolic compounds from Epimedium brevicornum maxim using response surface methodology and evaluating its antioxidant activities in vitro. Journal of Analytical Methods in Chemistry, 2014, 864654. 2014.

International Journal of Scientific Research in Chemistry

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Published

2021-10-31

Issue

Volume 6, Issue 5, September-October-2021

Section

Research Articles

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How to Cite

[1]
Imwene K. O, Mbui D. N, Mbugua J.K, Kinyua A. P, Kairigo P. K, Onyatta J. O, " Kinetic Modelling of Microbial Fuel Cell Voltage Data From Market Fruit Wastes In Nairobi, Kenya, International Journal of Scientific Research in Chemistry(IJSRCH), ISSN : 2456-8457, Volume 6, Issue 5, pp.25-37, September-October-2021.