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High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance
Thesis (MEng)--Stellenbosch University, 2022.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2022
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| _version_ | 1867613805944504320 |
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| access_status_str | Open Access |
| author | Van der Berg, David John |
| author2 | Gorgens, Johann F.
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| author_browse | Gorgens, Johann F.
Van der Berg, David John |
| author_facet | Gorgens, Johann F.
Van der Berg, David John |
| author_sort | Van der Berg, David John |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2022. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/124843 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:41:59.323Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/124843 High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance Van der Berg, David John Gorgens, Johann F. Van Rensburg, Eugene Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering. Sewage -- Purification -- Anaerobic treatment Biomethane potential Gas power plants UCTD Thesis (MEng)--Stellenbosch University, 2022. ENGLISH SUMMARY: Under steady-state conditions, full-scale anaerobic digestion (AD) plants generate methane gas by utilising industrial organic wastes such as food and beverage processing wastes. The selection and monitoring of operating parameters of AD provides insight into the process dynamics of the system, which presents opportunities to enhance the digester’s performance. However, predicting full-scale performance comes with several challenges, including the limitations of using bench-/lab-scale AD tests to accurately estimate industrial-scale AD performance, the impacts of environmental effects on biogas plant operations and the differences in process conditions between AD test scales. Bench-scale tests such as biomethane potential (BMP) assay tests are used to estimate the methane potential and degradability of a particular feedstock. BMP tests serve as indicators of AD performance and the basis of designing full-scale plants according to an expected biogas output. However, these methods are not always reliable due to the differences in bench- and full-scale AD process conditions, for example different reactor feeding modes. Furthermore, there is a lack of standardisation in BMP test protocols which impacts the reproducibility of BMP results. Very few studies have attempted to predict performance parameters of full-scale AD plants based on bench-scale AD experimental data. Performance parameters such as biogas and methane yields have been estimated for full-scale processes, but not over long durations of time where variations in feedstock compositions are accounted for. This study aimed to utilize bench-scale BMP tests that was efficient in estimating the performance of full-scale AD plants over an operational period spanning three years. The term “high-throughput BMP tests” pertains to the performing of numerous BMP tests simultaneously. Three full-scale AD plants were included in this study, namely a co-digestion plant of 3200 m3 working volume treating mixed food and agricultural wastes (Plant 1), a full-scale plant of 60 m3 working volume treating tomato wastes (Plant 2) and a liquid-based plant of 2200 m3 working volume treating distillery wastes (Plant 3). BMP tests (500 mL) were performed using a defined standardised BMP protocol on feedstock samples collected over a period of 6 to 8 months. Pilot-scale studies (50 L) were performed under operating conditions replicating those at full-scale AD to assess whether pilot-scale data could predict full-scale performance parameters more accurately than BMP tests. Full-scale performance was predicted using two methods identified from literature: (1) an extrapolation method and a (2) continuous-stirred tank dynamic model. Estimated full-scale performance parameters were then compared to real-time full-scale data to assess the deviation between ideal, bench-scale conditions and full-scale conditions. These deviations were defined as “scale factors” throughout this dissertation, defined as the ratio between real-time and estimated full-scale performance parameters. The three full-scale AD plants encountered various process disturbances, for example, variations in feedstock composition, which were observed from their full-scale operational datasets. It was found that BMP tests could be used to estimate the performance of full-scale AD processes using the two aforementioned methods identified from literature. Pilot-scale data could not be used to estimate full-scale AD process performance due to errors encountered during experimental procedures. For biogas production and yield estimations, the extrapolation method reflected scale factors of 0.42 for Plant 1 (mixed food wastes), a factor of 1.05 for Plant 2 (TW) and a factor of 0.69 for Plant 3. The dynamic model provided more accurate estimations of full-scale performance, where scale factors of 0.86, 3.10 and 0.92 were calculated for Plant 1, Plant 2 and Plant 3, respectively. These scale factors have the potential to estimate the energy production potentials of downstream power units for full-scale AD plant by accounting for changes in feedstock composition. Recommendations for this study included obtaining more reliable datasets of full-scale operational data by ensuring sufficient process monitoring instrumentation (e.g. gas flow meters) is installed at the plant, obtaining operational period spanning a longer time frame (Plants 1 and 2) and by ensuring the design of pilot-scale AD reactors better suit the conditions of full-scale AD plants, e.g. establish the same feeding mode. "Geen opsomming beskikbaar." Masters 2022-03-09T11:15:02Z 2022-04-29T09:36:27Z 2022-03-09T11:15:02Z 2022-04-29T09:36:27Z 2022-04 Thesis http://hdl.handle.net/10019.1/124843 en_ZA Stellenbosch University xviii, 170 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Sewage -- Purification -- Anaerobic treatment Biomethane potential Gas power plants UCTD Van der Berg, David John High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance |
| title | High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance |
| title_full | High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance |
| title_fullStr | High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance |
| title_full_unstemmed | High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance |
| title_short | High-throughput biomethane potential (BMP) tests as predictors for commercial-scale anaerobic digester performance |
| title_sort | high throughput biomethane potential bmp tests as predictors for commercial scale anaerobic digester performance |
| topic | Sewage -- Purification -- Anaerobic treatment Biomethane potential Gas power plants UCTD |
| url | http://hdl.handle.net/10019.1/124843 |
| work_keys_str_mv | AT vanderbergdavidjohn highthroughputbiomethanepotentialbmptestsaspredictorsforcommercialscaleanaerobicdigesterperformance |