LAPSE:2023.3237v1
Published Article
LAPSE:2023.3237v1
Hydrogen Production from Biomass and Organic Waste Using Dark Fermentation: An Analysis of Literature Data on the Effect of Operating Parameters on Process Performance
Rita Noelle Moussa, Najah Moussa, Davide Dionisi
February 22, 2023
Abstract
In the context of hydrogen production from biomass or organic waste with dark fermentation, this study analysed 55 studies (339 experiments) in the literature looking for the effect of operating parameters on the process performance of dark fermentation. The effect of substrate concentration, pH, temperature, and residence time on hydrogen yield, productivity, and content in the biogas was analysed. In addition, a linear regression model was developed to also account for the effect of nature and pretreatment of the substrate, inhibition of methanogenesis, and continuous or batch operating mode. The analysis showed that the hydrogen yield was mainly affected by pH and residence time, with the highest yields obtained for low pH and short residence time. High hydrogen productivity was favoured by high feed concentration, short residence time, and low pH. More modest was the effect on the hydrogen content. The mean values of hydrogen yield, productivity, and content were, respectively, 6.49% COD COD−1, 135 mg L−1 d−1, 51% v/v, while 10% of the considered experiments obtained yield, productivity, and content of or higher than 15.55% COD COD−1, 305.16 mg L−1 d−1, 64% v/v. Overall, this study provides insight into how to select the optimum operating conditions to obtain the desired hydrogen production.
Keywords
dark fermentation, Hydrogen, organic waste, regression model, statistical analysis
Suggested Citation
Moussa RN, Moussa N, Dionisi D. Hydrogen Production from Biomass and Organic Waste Using Dark Fermentation: An Analysis of Literature Data on the Effect of Operating Parameters on Process Performance. (2023). LAPSE:2023.3237v1
Author Affiliations
Moussa RN: Chemical Processes and Materials Group, School of Engineering, University of Aberdeen, Aberdeen AB24 3UE, UK
Moussa N: Department of Statistics, The Higher Institute of Applied and Economic Sciences (ISSAE-CNAM), Beirut 1103 2100, Lebanon
Dionisi D: Chemical Processes and Materials Group, School of Engineering, University of Aberdeen, Aberdeen AB24 3UE, UK
Journal Name
Processes
Volume
10
Issue
1
First Page
156
Year
2022
Publication Date
2022-01-13
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr10010156, Publication Type: Review
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LAPSE:2023.3237v1
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https://doi.org/10.3390/pr10010156
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Feb 22, 2023
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CC BY 4.0
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