Abstract
Quantitative dynamics of the key intermediates, gases and carbohydrates during anaerobic digestion of different lipid rich kitchen waste and lipid rich model kitchen waste were modeled. Six batch reactors loaded with 25 g\(_\text {VS}\) l\(^{-1}\) (\(\sim\)39 \({\textrm{g}{_\text {O}}{_{2}}}\) l\(^{-1}\)) kitchen waste and model kitchen waste during a batch experiment were considered in simulation. Observed dynamics of carbohydrates, volatile organic acids and gases were described by an extended benchmark simulation model no. 2 (BSM2). In this study the extended BSM2 included a more detailed \(\beta\)-oxidation for prediction of caproic acid. Furthermore, the extensions included carbohydrate digestion with an additional intermediate before propionic acid was released. In addition, a novel simplification approach for initial pH estimation was successfully applied. For parameter estimation a Markov Chain Monte Carlo method was used to obtain parameter distributions. With the presented model it was possible even with no calibrated data to predict point of times of intermediates maxima and propionic acid with relative stable concentration over several days for kitchen waste.
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Abbreviations
- ADM1:
-
Anaerobic digestion model no. 1
- ASM1:
-
Activated sludge model no. 1
- BSM2:
-
Benchmark simulation model no. 2
- C:
-
Carbon
- C2:
-
Acetic acid
- C3:
-
Propionic acid
- C4:
-
Butyric acid
- C4i:
-
Iso-butyric acid
- C4n:
-
N-butyric acid
- C5:
-
Valeric acid
- C5i:
-
Iso-valeric acid
- C5n:
-
N-valeric acid
- C6:
-
Caproic acid
- CH\(_{4}\) :
-
Methane
- CO\(_{2}\) :
-
Carbon dioxide
- COD:
-
Chemical oxygen demand
- FOS:
-
Volatile organic acids
- GE:
-
Glucose equivalent
- H\(_{2}\) :
-
Hydrogen
- KW:
-
Kitchen waste
- LCFA:
-
Long chain fatty acid
- MCMC:
-
Markov Chain Monte Carlo
- MKW:
-
Model kitchen waste
- N:
-
Nitrogen
- TAC:
-
Total inorganic carbon
- sCOD:
-
Soluble chemical oxygen demand
- sGE:
-
Soluble glucose equivalent
- tCOD:
-
Total chemical oxygen demand
- tGE:
-
Total glucose equivalent
References
Angelidaki I, Sanders W (2004) Assessment of the anaerobic biodegradability of macropollutants. Rev Environ Sci Biotechnol Rev 3(2):117–129. https://doi.org/10.1007/s11157-004-2502-3
Boone ARKM, Lettinga G (1994) Bactericidal effect of long chain fatty acids in anaerobic digestion. Water Environ Res 66:40–49
Baker JR, Milke MW, Mihelcic JR (1999) Relationship between chemical and theoretical oxygen demand for specific classes of organic chemicals. Water Res 33(2):327–334. https://doi.org/10.1016/S0043-1354(98)00231-0
Batstone D, Keller J, Angelidaki I, Kalyuzhny S, Pavlostathis S, Rozzi A, Sanders W, Siegrist H, Vavilin V (2002a) Anaerobic digestion model No.1 (ADM1). IWA Publishing, London
Batstone D, Keller J, Angelidaki I, Kalyuzhnyi S, Pavlostathis S, Rozzi A, Sanders W, Siegrist H, Vavilin V (2002) The iwa anaerobic digestion model no 1 (adm1). Water Sci Technol 45(10):65–73. https://doi.org/10.2166/wst.2002.0292
Batstone D, Keller J, Steyer J (2006) A review of adm1 extensions, applications, and analysis: 2002–2005. Water Sci Technol 54(4):1–10. https://doi.org/10.2166/wst.2006.520
Batstone D, Tait S, Starrenburg D (2009) Estimation of hydrolysis parameters in full-scale anerobic digesters. Biotechnol Bioeng 102:1513–1520. https://doi.org/10.1002/bit.22163
Batstone DJ, Pind PF, Angelidaki I (2003) Kinetics of thermophilic, anaerobic oxidation of straight and branched chain butyrate and valerate. Biotechnol Bioeng 84(2):195–204. https://doi.org/10.1002/bit.10753
Batstone DJ, Puyol D, Flores-Alsina X, Rodríguez J (2015) Mathematical modelling of anaerobic digestion processes: applications and future needs. Rev Environ Sci Biotechnol 14(4):595–613. https://doi.org/10.1007/s11157-015-9376-4
Browne JD, Murphy JD (2013) Assessment of the resource associated with biomethane from food waste. Appl Energy 104:170–177. https://doi.org/10.1016/j.apenergy.2012.11.017
Cirne D, Paloumet X, Björnsson L, Alves M, Mattiasson B (2007) Anaerobic digestion of lipid-rich waste - effects of lipid concentration. Renewable Energy 32(6):965–975. https://doi.org/10.1016/j.renene.2006.04.003
Clegg KM (1956) The application of the anthrone reagent to the estimation of starch in cereals. J Sci Food Agric 7(1):40–44. https://doi.org/10.1002/jsfa.2740070108
Donoso-Bravo A, Mailier J, Martin C, Rodríguez J, Aceves-Lara CA, Wouwer AV (2011) Model selection, identification and validation in anaerobic digestion: A review. Water Res 45(17):5347–5364. https://doi.org/10.1016/j.watres.2011.08.059
Flotats X, Ahring BK, Angelidaki I (2003) Parameter identification of thermophilic anaerobic degradation of valerate. Appl Biochem Biotechnol 109(1):47–62. https://doi.org/10.1385/ABAB:109:1-3:47
Gallert C, Winter J (2008) Propionic acid accumulation and degradation during restart of a full-scale anaerobic biowaste digester. Bioresour Technol 99(1):170–178. https://doi.org/10.1016/j.biortech.2006.11.014
Goswami V, Srivastava A (2000) Fed-batch propionic acid production by propionibacterium acidipropionici. Biochem Eng J 4(2):121–128. https://doi.org/10.1016/S1369-703X(99)00042-X
Haario H, Laine M, Mira A, Saksman E (2006) Dram: Efficient adaptive mcmc. Stat Comput 16(4):339–354. https://doi.org/10.1007/s11222-006-9438-0
Hanaki K, Matsuo T, Nagase M (1981) Mechanism of inhibition caused by long-chain fatty acids in anaerobic digestion process. Biotechnol Bioeng 23(7):1591–1610. https://doi.org/10.1002/bit.260230717
Henze M, Jr G, CPL, Gujer W, Marais G, Matsuo T (1987) Activated sludge model no.1. Tech. Rep. 1, IAWQ Scientific and Technical Report
Hinken L, Huber M, Weichgrebe D, Rosenwinkel KH (2014) Modified ADM1 for modelling an UASB reactor laboratory plant treating starch wastewater and synthetic substrate load tests. Water Res 64:82–93. https://doi.org/10.1016/j.watres.2014.06.044
Inanc B, Matsui S, Ide S (1996) Propionic acid accumulation and controlling factors in anaerobic treatment of carbohydrate: effects of h2 and ph. Water Sci Technol 34(5–6):317–325. https://doi.org/10.1016/0273-1223(96)00661-0
Jeppsson U, Rosen C, Alex J, Copp J, K VG, Pons MN, Vanrolleghem P, (2006) Towards a benchmark simulation model for plant-wide control strategy performance evaluation of wwtps. Water Sci Technol 54(1):287–295. https://doi.org/10.2166/wst.2006.031
Kalfas H, Skiadas I, Gavala H, Stamatelatou K, Lyberatos G (2006) Application of adm1 for the simulation of anaerobic digestion of olive pulp under mesophilic and thermophilic conditions. Water Sci Technol 54(4):149–156. https://doi.org/10.2166/wst.2006.536
Kim M, Nakhla G, Keleman M (2019) Modeling the impact of food wastes on wastewater treatment plants. J Environ Manage 237:344–358. https://doi.org/10.1016/j.jenvman.2019.02.065
Kleerebezem R, Van Loosdrecht M (2006) Waste characterization for implementation in adm1. Water Sci Technol 54(4):167–174. https://doi.org/10.2166/wst.2006.538
Lide DR (ed) (2009) CRC handbook of chemistry and physics. CRC Press/Taylor and Francis, Boca Raton
Liu JS (2004) Monte carlo strategies in scientific computing. Springer, New York
Marchaim U, Krause C (1993) Propionic to acetic acid ratios in overloaded anaerobic digestion. Bioresour Technol 43(3):195–203. https://doi.org/10.1016/0960-8524(93)90031-6
Mawson A, Earle R, Larsen V (1991) Degradation of acetic and propionic acids in the methane fermentation. Water Res 25(12):1549–1554. https://doi.org/10.1016/0043-1354(91)90187-U
Neves L, Gonc E, Oliveira R, Alves M (2008) Influence of composition on the biomethanation potential of restaurant waste at mesophilic temperatures. Waste Manage 28:965–972. https://doi.org/10.1016/j.wasman.2007.03.031
Palatsi J, Illa J, Prenafeta-Boldú F, Laureni M, Fernandez B, Angelidaki I, Flotats X (2010) Long-chain fatty acids inhibition and adaptation process in anaerobic thermophilic digestion: Batch tests, microbial community structure and mathematical modelling. Bioresour Technol 101(7):2243–2251. https://doi.org/10.1016/j.biortech.2009.11.069
Ramirez I, Volcke EI, Rajinikanth R, Steyer JP (2009) Modeling microbial diversity in anaerobic digestion through an extended ADM1 model. Water Res 43(11):2787–2800. https://doi.org/10.1016/j.watres.2009.03.034
Rosen C, Vrecko D, Gernaey K, Pons M, Jeppsson U (2006) Implementing adm1 for plant-wide benchmark simulations in matlab/simulink. Water Sci Technol 54(4):11–19. https://doi.org/10.2166/wst.2006.521
Sobel R, Versic R, Gaonkar AG (2014) Chapter 1 - introduction to microencapsulation and controlled delivery in foods. In: Gaonkar AG, Vasisht N, Khare AR, Sobel R (eds) Microencapsulation in the food industry. Academic Press, San Diego, pp 3–12. https://doi.org/10.1016/B978-0-12-404568-2.00001-7
Swick RW (1962) Propionic acid metabolism: Mechanism of the methylmalonyl isomerase reaction and the reduction of acrylyl coenzyme a to propionyl coenzyme a in propionibacteria. Proc Natl Acad Sci USA 48(2):288–293. https://doi.org/10.1073/pnas.48.2.288
Vavilin V, Fernandez B, Palatsi J, Flotats X (2008) Hydrolysis kinetics in anaerobic degradation of particulate organic material: An overview. Waste Manage 28(6):939–951. https://doi.org/10.1016/j.wasman.2007.03.028
Weber S (2023) Lipid rich kitchen waste: analytic characterization, anaerobic digestion, and mass balances. Biomass Conv Bioref. https://doi.org/10.1007/s13399-023-04466-5
Zaher U, Rodríguez J, Franco A, Vanrolleghem PA (2003) Application of the iwa adm1 model to simulate anaerobic digester dynamics using a concise set of practical measurements. In: IWA Conference on Enviromental Biotechnology
Zaher U, Buffiere P, Steyer JP, Chen S (2009) A procedure to estimate proximate analysis of mixed organic wastes. Water Environ Res 81(4):407–415. https://doi.org/10.2175/106143008X370548
Acknowledgements
Many thanks to Mrs. Buch for constructive discussions. Additional, the author thanks syndicate Minett-Kompost for supporting this work. The author acknowledge the use of resources of University of Luxembourg.
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Weber, S. Modeling key intermediates during anaerobic digestion of lipid rich kitchen waste with an extended ADM1. Biodegradation (2024). https://doi.org/10.1007/s10532-024-10072-7
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DOI: https://doi.org/10.1007/s10532-024-10072-7