The evaluation of biogas production from sewage sludge in industrial sewage treatment plant / Mohd Faizan Jamaluddin

By: Material type: TextTextPublisher: Kuantan, Pahang : UMP, 2021Copyright date: © 2021Description: xiii, 194 pages : illustrations (some color) ; 30 cm. + 1 CD-ROMContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • THE0009245(Local)
Subject(s): Dissertation note: Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2021 Abstract: Anaerobic digestion (AD) of sewage sludge has become favoured technology in wastewater treatment system due to its efficiency and its potential in renewable energy sector. However, the digestion process is so delicate and easy to be interrupted or even hindered due to microbe availability. The process troubleshoots in industrial scale required scrupulous procedure to avoid extra process which required an increase cost. In this study, the real scale digester was scale down to pilot scale unit with the assistance of IWK to prevent major error in large scale troubleshooting. The 40-l pilot digester was built using stainless steel 304SS with factor of 13,000 based on IWK digester design. The novelty of this study is the using of statistical approach in pilot scale study to improve and troubleshoot the digestion performance. At first, the utilized sludge in treatment plant was investigated to trace the abnormality in sludge characteristic. The inlet sludge was found to be performing better than digestate in several test even with lower characteristic value. The biogas production was measured and analysed using gas chromatography (GC) equipment. The statistical approach to improve the process was then applied to analyse the parameter effects in two treatment plants. The factorial analysis was applied in both Pantai 1 and Bunus plant to investigate the parameter effects on the process. Central composite design was later used in process optimization. Parameter values from the study showing that the main and interaction effects could contribute to the digestion performance. The pH, TS and FR contribution effect towards biogas production in Pantai 1 were recorded at 38%, 16.7% and 13.45% respectively. Interaction factor between pH and TS also contribute towards biogas production with 15.35%. At Bunus, five factors such as pH, TS, FR, IP and HRT was screened with contribution effects of 13%, 8%, 1%, 5%, 15% respectively. The interaction factors between FR and IP found to be the most influential factors with 20% percentage contribution. Then, the optimum condition for biogas production was found at pH 7.0 and HRT at 15.9 days. But, the most feasible option for optimum process were proposed at pH 7.0 and HRT 10.7 due to shorter retention time. The process performance for baseline study and improved condition was monitored in both treatment plants to probe the optimization effect. The biogas yield increased up to 70% compared with the baseline study in Pantai 1. Higher yield was obtained in Bunus with more than 15% increment compared to Pantai 1. The models acquired from both sites were obtained in lab scale found to be good predictor and applicable for pilot unit with error less than 10%. At the end of the study, four dominant bacteria samples were isolated from sludge in optimum condition and identified based on their colony and cell morphological. All samples found to be methanogens with strain A is Methanosarcina barkeri CM1, B is Methanosarcina Mazei Strain 3, followed by C and D as Methanobrevibacter curvatus strain DSM11111 and Methanobrevibacter filiformis DSM 11501, respectively. The finding proof that microorganism play an important role in biogas production and aligned with other researches. The statistical approach applied in the study also suggest that the tool is applicable for AD improvement in both small and large scale which could facilitate the cost of troubleshooting in real world issue.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode
Restricted Collection Restricted Collection UMPLIB PEKAN Reference CD 12986 (Browse shelf(Opens below)) 1 Not for loan (Restricted access) T000001641
Restricted Collection Restricted Collection UMPLIB PEKAN Reference Reference KK .F35 2021 r Thesis (Browse shelf(Opens below)) 1 Not for loan (Restricted access) T000001640

College of Engineering

Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2021

Includes bibliographical references

Anaerobic digestion (AD) of sewage sludge has become favoured technology in wastewater treatment system due to its efficiency and its potential in renewable energy sector. However, the digestion process is so delicate and easy to be interrupted or even hindered due to microbe availability. The process troubleshoots in industrial scale required scrupulous procedure to avoid extra process which required an increase cost. In this study, the real scale digester was scale down to pilot scale unit with the assistance of IWK to prevent major error in large scale troubleshooting. The 40-l pilot digester was built using stainless steel 304SS with factor of 13,000 based on IWK digester design. The novelty of this study is the using of statistical approach in pilot scale study to improve and troubleshoot the digestion performance. At first, the utilized sludge in treatment plant was investigated to trace the abnormality in sludge characteristic. The inlet sludge was found to be performing better than digestate in several test even with lower characteristic value. The biogas production was measured and analysed using gas chromatography (GC) equipment. The statistical approach to improve the process was then applied to analyse the parameter effects in two treatment plants. The factorial analysis was applied in both Pantai 1 and Bunus plant to investigate the parameter effects on the process. Central composite design was later used in process optimization. Parameter values from the study showing that the main and interaction effects could contribute to the digestion performance. The pH, TS and FR contribution effect towards biogas production in Pantai 1 were recorded at 38%, 16.7% and 13.45% respectively. Interaction factor between pH and TS also contribute towards biogas production with 15.35%. At Bunus, five factors such as pH, TS, FR, IP and HRT was screened with contribution effects of 13%, 8%, 1%, 5%, 15% respectively. The interaction factors between FR and IP found to be the most influential factors with 20% percentage contribution. Then, the optimum condition for biogas production was found at pH 7.0 and HRT at 15.9 days. But, the most feasible option for optimum process were proposed at pH 7.0 and HRT 10.7 due to shorter retention time. The process performance for baseline study and improved condition was monitored in both treatment plants to probe the optimization effect. The biogas yield increased up to 70% compared with the baseline study in Pantai 1. Higher yield was obtained in Bunus with more than 15% increment compared to Pantai 1. The models acquired from both sites were obtained in lab scale found to be good predictor and applicable for pilot unit with error less than 10%. At the end of the study, four dominant bacteria samples were isolated from sludge in optimum condition and identified based on their colony and cell morphological. All samples found to be methanogens with strain A is Methanosarcina barkeri CM1, B is Methanosarcina Mazei Strain 3, followed by C and D as Methanobrevibacter curvatus strain DSM11111 and Methanobrevibacter filiformis DSM 11501, respectively. The finding proof that microorganism play an important role in biogas production and aligned with other researches. The statistical approach applied in the study also suggest that the tool is applicable for AD improvement in both small and large scale which could facilitate the cost of troubleshooting in real world issue.

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