Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling Approach
In the quest for improved anaerobic digestion (AD) efficiency and stability, iron-based additives and drinking water treatment sludge (DWTS) have emerged as promising components. This study explores the kinetics of methane production during AD of dairy manure under various concentrations of iron sha...
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Shahid Bahonar University of Kerman
2024-06-01
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| Series: | Biomechanism and Bioenergy Research |
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| Online Access: | https://bbr.uk.ac.ir/article_4274_a204d1fd096cfb5d917356e08bcd3b4a.pdf |
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| author | Javad Rezaeifar Abbas Rohani Mohammadali Ebrahimi-Nik |
| author_facet | Javad Rezaeifar Abbas Rohani Mohammadali Ebrahimi-Nik |
| author_sort | Javad Rezaeifar |
| collection | DOAJ |
| description | In the quest for improved anaerobic digestion (AD) efficiency and stability, iron-based additives and drinking water treatment sludge (DWTS) have emerged as promising components. This study explores the kinetics of methane production during AD of dairy manure under various concentrations of iron shavings (IS) and Fe3O4 (10, 20, and 30 mg/L) and DWTS (6, 12, and 18 mg/L). The experimental data were employed to assess the suitability of the Michaelis-Menten model as a non-linear regression (NLR) equation for evaluating the kinetics of dairy manure AD with these additives. The results demonstrate that the Michaelis-Menten model exhibits sufficient predictive capability for estimating cumulative methane production during the digestion process. The model was then utilized to compare the average cumulative methane production across the investigated treatments using the least significant difference (LSD) method, as well as to calculate the quantity of methane production at 25%, 50%, 75%, and 90% of the final methane yield. Notably, the findings revealed a significant difference (P > 0.05) in biomethane production among the different levels of DWTS, IS, and Fe3O4. Additionally, treatments containing varying levels of DWTS exhibited significantly shorter time durations to achieve 25% and 50% of their maximum methane yield compared to treatments containing Fe3O4. The most pronounced changes in these parameters were observed between distinct levels of IS. |
| format | Article |
| id | doaj-art-10249b2629684b22916288c975390b8d |
| institution | Kabale University |
| issn | 2821-1855 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Shahid Bahonar University of Kerman |
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| series | Biomechanism and Bioenergy Research |
| spelling | doaj-art-10249b2629684b22916288c975390b8d2025-01-11T18:55:35ZengShahid Bahonar University of KermanBiomechanism and Bioenergy Research2821-18552024-06-0131465510.22103/bbr.2024.22854.10764274Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling ApproachJavad Rezaeifar0Abbas Rohani1Mohammadali Ebrahimi-Nik2Department of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran.Department of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran.Department of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran.In the quest for improved anaerobic digestion (AD) efficiency and stability, iron-based additives and drinking water treatment sludge (DWTS) have emerged as promising components. This study explores the kinetics of methane production during AD of dairy manure under various concentrations of iron shavings (IS) and Fe3O4 (10, 20, and 30 mg/L) and DWTS (6, 12, and 18 mg/L). The experimental data were employed to assess the suitability of the Michaelis-Menten model as a non-linear regression (NLR) equation for evaluating the kinetics of dairy manure AD with these additives. The results demonstrate that the Michaelis-Menten model exhibits sufficient predictive capability for estimating cumulative methane production during the digestion process. The model was then utilized to compare the average cumulative methane production across the investigated treatments using the least significant difference (LSD) method, as well as to calculate the quantity of methane production at 25%, 50%, 75%, and 90% of the final methane yield. Notably, the findings revealed a significant difference (P > 0.05) in biomethane production among the different levels of DWTS, IS, and Fe3O4. Additionally, treatments containing varying levels of DWTS exhibited significantly shorter time durations to achieve 25% and 50% of their maximum methane yield compared to treatments containing Fe3O4. The most pronounced changes in these parameters were observed between distinct levels of IS.https://bbr.uk.ac.ir/article_4274_a204d1fd096cfb5d917356e08bcd3b4a.pdfanaerobic digestionmichaelis-menten modeldairy manureiron-based additives |
| spellingShingle | Javad Rezaeifar Abbas Rohani Mohammadali Ebrahimi-Nik Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling Approach Biomechanism and Bioenergy Research anaerobic digestion michaelis-menten model dairy manure iron-based additives |
| title | Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling Approach |
| title_full | Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling Approach |
| title_fullStr | Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling Approach |
| title_full_unstemmed | Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling Approach |
| title_short | Unleashing Dairy Manure's Biogas Potential: A Michaelis-Menten Modeling Approach |
| title_sort | unleashing dairy manure s biogas potential a michaelis menten modeling approach |
| topic | anaerobic digestion michaelis-menten model dairy manure iron-based additives |
| url | https://bbr.uk.ac.ir/article_4274_a204d1fd096cfb5d917356e08bcd3b4a.pdf |
| work_keys_str_mv | AT javadrezaeifar unleashingdairymanuresbiogaspotentialamichaelismentenmodelingapproach AT abbasrohani unleashingdairymanuresbiogaspotentialamichaelismentenmodelingapproach AT mohammadaliebrahiminik unleashingdairymanuresbiogaspotentialamichaelismentenmodelingapproach |