LAPSE:2023.28944
Published Article
LAPSE:2023.28944
Modeling the Methane Production Kinetics of Anaerobic Co-Digestion of Agricultural Wastes Using Sigmoidal Functions
April 12, 2023
The modified sigmoidal bacteria growth functions (the modified Gompertz, logistic, and Richards) were used to evaluate the methane production process kinetics of agricultural wastes. The mesophilic anaerobic co-digestion experiments were conducted with various agricultural wastes as feedstocks, including cow manure, corn straw, grape leaves, vines, wine residue, strawberry leaves, and tomato leaves. The results showed that anaerobic co-digestion of cow manure and other agricultural wastes increased the methane yields while it prolonged the lag phase time. Compared with the modified Gompertz and logistic models, the modified Richards model obtained higher correlation coefficients and was able to fit experimental data better. The results of this study were expected to determine a suitable model to simulate and study the kinetic process of anaerobic co-digestion with mixed agricultural wastes as feedstocks.
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Keywords
agricultural wastes, anaerobic digestion, kinetic study, modified Gompertz model, modified logistic model, modified Richards model
Suggested Citation
Zhang H, An D, Cao Y, Tian Y, He J. Modeling the Methane Production Kinetics of Anaerobic Co-Digestion of Agricultural Wastes Using Sigmoidal Functions. (2023). LAPSE:2023.28944
Author Affiliations
Zhang H: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China [ORCID]
An D: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
Cao Y: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
Tian Y: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
He J: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
An D: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
Cao Y: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
Tian Y: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
He J: Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
Journal Name
Energies
Volume
14
Issue
2
Article Number
en14020258
Year
2021
Publication Date
2021-01-06
Published Version
ISSN
1996-1073
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PII: en14020258, Publication Type: Journal Article
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LAPSE:2023.28944
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doi:10.3390/en14020258
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Apr 12, 2023
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