DOI: https://doi.org/10.14710/ijred.2023.52798

Modification and extension of the anaerobic model N°2 (AM2) for the simulation of anaerobic digestion of municipal solid waste

1Mohammed V University in Rabat, Higher School of Technology-Salé, Materials, Energy, and Acoustics Team (MEAT), Crown Prince Street BP 227 Salé- Médina, PO Box 11060, Morocco

2Mohammed V University in Rabat, Higher School of Technology-Salé, LASTIMI, Crown Prince Street BP 227 Salé – Médina, PO Box 11060, Morocco

Received: 2 Mar 2023; Revised: 24 Jul 2023; Accepted: 15 Aug 2023; Available online: 22 Aug 2023; Published: 1 Sep 2023.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2023 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract
Anaerobic digestion is a complex process whose understanding, optimization, and development require mathematical modeling to simulate digesters' operation under various conditions. Consequently, the present work focuses on developing a new and improved model called "AM2P" derived from the AM2 model. This new model incorporates surface-based kinetics (SBK) into the overall simulation process to transform the system into three stages: hydrolysis, acidogenesis, and methanogenesis. Experimental data from our previous work were used to identify the AM2 and AM2P models' parameters. Simulations showed that the AM2P model satisfactorily represented the effect of the hydrolysis phase on the anaerobic digestion process, since simulated values for acidogenic (X1) and methanogenic (X2) biomass production revealed an increase in their concentration as a function of particle size reduction, with a maximum concentration of the order of 5.5 g/l for X1 and 0.8 g/l for X2 recorded for the case of the smallest particle size of 0.5 cm, thus accurately representing the effect of substrate particle disintegration on biomass production dynamics and enabling the process of anaerobic digestion to be qualitatively reproduced. The AM2P model also provided a more accurate response, with less deviation from the experimental data; this was the case for the evolution of methane production, where the coefficient of determination (R2) was higher than 0.8, and the root-mean-square error (RMSE) was less than 0.02.
Fulltext View|Download
Keywords: anaerobic digestion; AM2 model; surface based kinetics; mathematical modeling; municipal solid waste

Article Metrics:

Article Info
Section: Original Research Article
Language : EN
Recent articles
Numerical assessment of meshless method for studying nanofluid natural convection in a corrugated wall square cavity Evaluating the EEMD-LSTM model for short-term forecasting of industrial power load: A case study in Vietnam Computational prediction of green fuels from crude palm oil in fluid catalytic cracking riser More recent articles
Most cited articles
Biohydrogen Production by Reusing Immobilized Mixed Culture in Batch System Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm. (On-Line Harmonics Estimation Application) Potency of Solar Energy Applications in Indonesia Promotion of Renewable Energy Sources in the European Union Performance Evaluation of PV Panel Under Dusty Condition More cited articles
  1. Arzate, J.A., Kirstein, M., Ertem, F.C., Kielhorn, E., Ramirez Malule, H., Neubauer, P., Cruz-Bournazou, M.N. and Junne, S. (2017). Anaerobic Digestion Model (AM2) for the Description of Biogas Processes at Dynamic Feedstock Loading Rates. Chemie Ingenieur Technik, 89: 686-695. https://doi.org/10.1002/cite.201600176
  2. Atallah NM., El-Fadel, M., Ghanimeh, S., Saikaly P., Abou-Najm M. (2014), Performance optimization and validation of ADM1 simulations under anaerobic thermophilic conditions, Bioresource Technology, 174, 243-25 https://doi.org/10.1016/j.biortech.2014.09.143
  3. Bandgar, P.S., Jain, S., Panwar, N.L. (2022). A comprehensive review on optimization of anaerobic digestion technologies for lignocellulosic biomass available in India, Biomass and Bioenergy, 161,106479. https://doi.org/10.1016/j.biombioe.2022.106479
  4. Batstone, D, J., Keller, J., (2003). Industrial applications of the IWA anaerobic digestion model No. 1 (ADM1), Water Science and Technology, 47(12):199-206. PMID: 12926689. https://doi.org/10.2166/wst.2003.0647
  5. Batstone, D,J., Keller, J., Angelidaki I, Kalyuzhnyi, SV., Pavlostathis, SG., Rozzi A., Sanders, WT., Siegrist H., Vavilin, VA., (2002). The IWA Anaerobic Digestion Model No 1 (ADM1), Water Science and Technology; 45(10), 65-73. PMID: 12188579. https://doi.org/10.2166/wst.2002.0292
  6. Benyahia, B., Sari, T., Cherki, B., Harmand, J., (2010). Sur le modèle AM2 de digestion anaérobie, In CARI’10, Yamoussoukrou, Côte d’ivoire
  7. Benyahia, B., Sari, T., Cherki, B., Harmand, J., (2013). Anaerobic membrane bioreactor modeling in the presence of Soluble Microbial Products (SMP) – the Anaerobic Model AM2b, Chemical Engineering Journal, 228, 1011-1022. https://doi.org/10.1016/j.cej.2013.05.073
  8. Benyahia, B., (2012). Modélisation et observation des bioprocédés à membranes : application à la digestion anaérobie, Doctoral thesis, In Algeria, University of Tlemcen
  9. Benyahia, B., Sari, T., Cherki, B., Harmand, J., (2013). Anaerobic membrane bioreactor modeling in the presence of Soluble Microbial Products (SMP) – the Anaerobic Model AM2b. Chemical Engineering Journal., 228, 1011-1022 https://doi.org/10.1016/j.cej.2013.05.073
  10. Bernard, O., Hadj-Sadok, Z., Dochain, D., Genovesi, A., Steyer, J.P., (2001). Dynamical model development and parametric identificatin for an anaerobic wastewater treatment process, Biotechnology and Bioengineering, 75(4), 424–438. https://doi.org/10.1002/bit.10036
  11. Campos, R, A.; Zárate-Navarro, M.A.; Aguilar-Garnica, E.; Alcaraz-González, V.; García-Sandoval, J.P, (2022). Study of the Behavior of Alkalinities Predicted by the AM2 Model. Water, 14, 1634. https://doi.org/10.3390/w14101634
  12. Cano, R., Nielfa, A., Fdz-Polanco, M. (2014), Thermal hydrolysis integration in the anaerobic digestion process of different solid wastes: energy and economic feasibility study. Bioresource Technology ;168:14–22. https://doi.org/10.1016/j.biortech.2014.02.007
  13. Capson-Tojo G., Astals S., Robles A. (2021), Considering syntrophic acetate oxidation and ionic strength improves the performance of models for food waste anaerobic digestion, Bioresource Technology, 341, 125802. https://doi.org/10.1016/j.biortech.2021.125802
  14. D’Silva, T C., Isha, A., Chandra, R., Vijay, V K., Subbarao, P M V., Kumar, R., Chaudhary, V P., Singh, H., Khan, A A., Tyagi, V K., Kovács, K L. (2021), Enhancing methane production in anaerobic digestion through hydrogen assisted pathways – A state-of-the-art review, Renewable and Sustainable Energy Reviews, 151, 111536. https://doi.org/10.1016/j.rser.2021.111536
  15. Dimock, R., Morgenroth, E., (2006). The influence of particle size on microbial hydrolysis of protein particles in activated sludge, WATER RESEARCH 40(10), 2064– 2074. https://doi.org/10.1016/j.watres.2006.03.011
  16. Emebu, S., Pecha,J., Janáčová, D. (2022), Review on anaerobic digestion models: Model classification & elaboration of process phenomena, Renewable and Sustainable Energy Reviews, 160, 112288. https://doi.org/10.1016/j.rser.2022.112288
  17. Esposito, G., Frunzo, L., Panico, A., d’Antonio, G., (2008). Mathematical modelling of disintegration-limited co-digestion of OFMSW and sewage sludge. Water Science and Technology. 58(7), 1513e1519. https://doi.org/10.2166/wst.2008.509
  18. Fekih Salem, R., (2013). Modèles Mathématiques pour la compétition et la coexistence des espèces microbiennes dans un chémostat, Doctoral thesis, In France, University of Montpellier2
  19. Fezzani,B., Ben Cheikh, R., (2008). Implementation of iwa anaerobic digestion model no. 1 (ADM1) for simulating the thermophilic anaerobic co-digestion of olive mill wastewater with olive mill solid waste in a semi-continuous tubular digester, Chemical Engineering Journal, 141,1–3, 75-88. https://doi.org/10.1016/j.cej.2007.10.024
  20. Gavala, H, N., Angelidaki, I., Ahring B,K., (2003). Kinetics and Modeling of Anaerobic Digestion Process, Advances in Biochemical Engineering/Biotechnology ;81:57-93. https://doi.org/10.1007/3-540-45839-5_3
  21. Giovanni, E., Frunzo, L., Panico, A., Pirozzi, F., (2011). Modelling the effect of the OLR and OFMSW particle size on the performances of an anaerobic co-digestion reactor", Process Biochemistry, 46(2), 557-565. https://doi.org/10.1016/j.procbio.2010.10.010
  22. Hajji, A., Rhachi, M., (2013). The Influence of Particle Size on the Performance of Anaerobic Digestion of Municipal Solid Waste, Energy Procedia, 36, 515-520. https://doi.org/10.1016/j.egypro.2013.07.059
  23. Hajji, A., Rhachi, M., (2022). The effect of thermochemical pretreatment on anaerobic digestion efficiency of municipal solid waste under mesophilic conditions, Scientific African, 16, e01198. https://doi.org/10.1016/j.sciaf.2022.e01198
  24. Harshad Vijay Kulkarni, (2010). Sensitivity Analysis of Variables Related to Bacterial Hydrolysis : A Study to Help Optimize Anaerobic Digestion of Recalcitrant Wastes. Project Report, SPRING
  25. Hassam, S., Ficara,E., Leva, A., Harmand, J., (2015). A generic and systematic procedure to derive a simplified model from the anaerobic digestion model No. 1 (ADM1), Biochemical Engineering Journal, 99, 193-203, https://doi.org/10.1016/j.bej.2015.03.007
  26. Hess, J., (2007). Modélisation de la qualité du biogaz produit par un fermenteur méthanogène et stratégie de régulation en vue de sa valorisation, Doctoral thesis, In France, University of Nice
  27. Houngue, C,F,C., Hounganq,K,T., Adjovi,C,E., (2015). Contribution à la régulation de la température au sein d’un digesteur de type batch utilisant un système de chauffage de type solaire, Afrique Science 11(3) 10–20. https://www.ajol.info/index.php/afsci/article/view/118691
  28. Kythreotou, N., Florides, G., Tassou, S A. (2014), A review of simple to scientific models for anaerobic digestion, Renewable Energy, 71, 701-714. https://doi.org/10.1016/j.renene.2014.05.055
  29. Lauwers,J., Appels, L.,, Thompson, L P., Degrève, J., Van Impe, J F., Dewil, R. (2013), Mathematical modelling of anaerobic digestion of biomass and waste: Power and limitations, Progress in Energy and Combustion Science, 39(4), 383-402. https://doi.org/10.1016/j.pecs.2013.03.003
  30. Li,Y., Chen,Y., Wu,J. (2019), Enhancement of methane production in anaerobic digestion process: A review, Applied Energy, 240, 20-137. https://doi.org/10.1016/j.apenergy.2019.01.243
  31. Noykova, N., Thorsten G. M, Gyllenberg, M., Timmer, J., (2002). Quantitative Analyses of Anaerobic Wastewater Treatment Processes: Identifiability and Parameter Estimation, Biotechnology and Bioengineering, 78, 89-103. https://doi.org/10.1002/bit.10179
  32. Panico, A., Giuseppe,A., Giovanni, E., Frunzo, L., Iodice,P., Pirozzi,F., (2014). The Effect of Substrate-Bulk Interaction on Hydrolysis Modeling in Anaerobic Digestion Process, Sustainability, 6(12), 8348-8363. https://doi.org/10.3390/su6128348
  33. Pessoa, R.W.S., Mendes, F., Oliveira, T.R., Oliveira-Esquerre, K., Krstic, M (2019).Numerical optimization based on generalized extremum seeking for fast methane production by a modified ADM1, Journal of Process Control, 84, 56-69. https://doi.org/10.1016/j.jprocont.2019.09.006
  34. Rakotoniaina, V, A., (2012). co-methanisation des dechets fermiers et alimentaires : experimentation et modelisation, Doctoral thesis, In France, University of La Réunion
  35. Rozzi, A., Sanders, W.T.M, Siegriest, H., Vavilin, V.A, (2002). Anaerobic Digestion Model N°1 (ADM1).International Water Association Scientific and Technical Report n°13, London, UK, IWA Publishing, p 68
  36. Sanders WT, Geerink M, Zeeman G, Lettinga G, (2000). Anaerobic hydrolysis kinetics of particulate substrates. Water Science and Technology, 41(3),17-24. https://doi.org/10.2166/wst.2000.0051
  37. Sun, H., Yang, Z., Zhao.Q, Kurbonova,M., Zhang,R, Liu,G., Wang,W. (2020), Modification and extension of anaerobic digestion model No.1 (ADM1) for syngas biomethanation simulation: From lab-scale to pilot-scale, Chemical Engineering Journal, 403. https://doi.org/10.1016/j.cej.2020.126177
  38. Vavilin, V.A., Fernandez, B., Palatsi, J., Flotats, X., (2008). Hydrolysis kinetics in anaerobic degradation of particulate organic material: An overview, Waste Management, 28(6), 939-951. https://doi.org/10.1016/j.wasman.2007.03.028
  39. Wang,P., Wang,P., Qiu,Y., Ren,L., Jiang,B. (2018), Microbial characteristics in anaerobic digestion process of food waste for methane production–A review, Bioresource Technology, 248, 29-36, https://doi.org/10.1016/j.biortech.2017.06.152
  40. wen-der, L, chi-yuan, L., (2007). Practical identification analysis of haldane kinetic parameters describing phenol biodegradation in batch operations, Journal of Environmental Engineering and Management, 17(1), 71-80 http://ntour.ntou.edu.tw:8080/handle/987654321/24170
  41. Xu, F., Li,Y., Wang,Z W. (2015), Mathematical modeling of solid-state anaerobic digestion, Progress in Energy and Combustion Science, 51, 49-66. https://doi.org/10.1016/j.pecs.2015.09.001
  42. Zaatri, A., Chaouche, K,N., Karaali, M., (2011). Étude de bioréacteurs anaérobies expérimentaux pour la production de méthane, Revue des Énergies Renouvelables , 14 (2), 291 – 300
  43. Zaatri, A. dan Kelaiaia, R., (2020). Analysis and Simulation of AM2 Model for Anaerobic Digesters, Banat′s Journal of Biotechnology, XI (22). https://doi.org/10.7904/2068–4738–XI(22)–30

Last update:

No citation recorded.

Last update: 2024-05-02 12:13:04

No citation recorded.