LAPSE:2023.36148v1
Published Article
LAPSE:2023.36148v1
Optimization of the Performances of Palm Oil Mill Effluent (POME)-Based Biogas Plants Using Comparative Analysis and Response Surface Methodology
July 4, 2023
Abstract
The rapid increase in demand for renewable energy has led to a need for more efficient and effective ways to produce biogas from palm oil mill effluent (POME), which is rich in biological and chemical oxygen demand (BOD and COD). Despite its potential as a source of biogas, POME is not always effectively utilized in biogas production due to a lack of optimization of the treatment process. This study aims to address this issue by identifying the critical parameters affecting biogas production from POME and optimizing the process for maximum biogas yield and COD removal. This study employed comparative analysis and response surface methodology to optimize the performance of palm oil mill effluent (POME)-based biogas plants in Malaysia. Historical data from three commercial POME-based biogas plants in Malaysia were analyzed to identify the most critical parameters for biogas yield and COD removal. Response surface methodology, using Box−Behnken design and Design-Expert software, was then used to optimize these parameters. Sensitivity analysis was performed to interpret the impact of parameters on biogas production, with Organic Loading Rate (OLR) found to be the most critical factor for methane yield. The results showed that the optimum conditions for maximum methane production were OLR of 1.23 kg/m3·day, inlet Total Solids (TS) of 46,370 mg/L, pH of 4.5, and temperature of 45.4 °C, resulting in a 39.6% increase in methane yield (0.335 m3 CH4/kgCODremoved) and a 1.1% increase in COD removal (93.4%).
Keywords
biogas, organic loading rate (OLR), palm oil mill effluent, response surface methodology (RSM)
Suggested Citation
Yong GTX, Chan YJ, Lau PL, Ethiraj B, Ghfar AA, Mohammed AAA, Shahid MK, Lim JW. Optimization of the Performances of Palm Oil Mill Effluent (POME)-Based Biogas Plants Using Comparative Analysis and Response Surface Methodology. (2023). LAPSE:2023.36148v1
Author Affiliations
Yong GTX: Department of Chemical and Environmental Engineering, University of Nottingham Malaysia, Broga Road, Semenyih 43500, Selangor Darul Ehsan, Malaysia
Chan YJ: Department of Chemical and Environmental Engineering, University of Nottingham Malaysia, Broga Road, Semenyih 43500, Selangor Darul Ehsan, Malaysia [ORCID]
Lau PL: Department of Chemical and Environmental Engineering, University of Nottingham Malaysia, Broga Road, Semenyih 43500, Selangor Darul Ehsan, Malaysia [ORCID]
Ethiraj B: Department of Biotechnology, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, India [ORCID]
Ghfar AA: Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia [ORCID]
Mohammed AAA: Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Shahid MK: Research Institute of Environment & Biosystem, Chungnam National University, Yuseonggu, Daejeon 34134, Republic of Korea [ORCID]
Lim JW: HICoE—Centre for Biofuel and Biochemical Research, Institute of Self-Sustainable Building, Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia [ORCID]
Journal Name
Processes
Volume
11
Issue
6
First Page
1603
Year
2023
Publication Date
2023-05-24
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr11061603, Publication Type: Journal Article
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LAPSE:2023.36148v1
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https://doi.org/10.3390/pr11061603
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Jul 4, 2023
 
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Calvin Tsay
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