Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface Methodology
Bioflocculants can be used for cost-effective harvesting of microalgae biomass on an industrial scale. This study investigates the flocculation-based harvesting approach to recovering <i>Chlorella vulgaris</i> microalgae biomass using chitosan biopolymer. Response surface methodology (RS...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Separations |
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| Online Access: | https://www.mdpi.com/2297-8739/10/9/507 |
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| author | Harun Elcik Dogan Karadag Ayse Irem Kara Mehmet Cakmakci |
| author_facet | Harun Elcik Dogan Karadag Ayse Irem Kara Mehmet Cakmakci |
| author_sort | Harun Elcik |
| collection | DOAJ |
| description | Bioflocculants can be used for cost-effective harvesting of microalgae biomass on an industrial scale. This study investigates the flocculation-based harvesting approach to recovering <i>Chlorella vulgaris</i> microalgae biomass using chitosan biopolymer. Response surface methodology (RSM) was used to design the experiments and optimize the critical operating parameters. Box-Behnken Design (BBD) was employed at three levels, and 17 experimental runs were conducted to determine the optimal conditions and the relationship between operating parameters. The highest biomass recovery of 99.10% was achieved at the following optimized conditions: pH of 5, flocculation time of 45 min, and chitosan concentration of 10 mg/L. Both experimental results and model outputs indicated that pH significantly impacts microalgae harvesting and that process performance is less dependent on chitosan concentration and flocculation time. The quadratic model has shown the best fit with the experimental results. The results could be applied to large-scale microalgae harvesting applications to promote microalgae biomass recovery and reduce operating costs. |
| first_indexed | 2024-03-10T22:00:28Z |
| format | Article |
| id | doaj.art-7374ba10fe8d4d858daa98b7ae8a7164 |
| institution | Directory Open Access Journal |
| issn | 2297-8739 |
| language | English |
| last_indexed | 2024-03-10T22:00:28Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Separations |
| spelling | doaj.art-7374ba10fe8d4d858daa98b7ae8a71642023-11-19T12:58:07ZengMDPI AGSeparations2297-87392023-09-0110950710.3390/separations10090507Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface MethodologyHarun Elcik0Dogan Karadag1Ayse Irem Kara2Mehmet Cakmakci3Department of Environmental Engineering, Yildiz Technical University, Istanbul 34220, TurkeyDepartment of Environmental Engineering, Yildiz Technical University, Istanbul 34220, TurkeyDepartment of Environmental Engineering, Yildiz Technical University, Istanbul 34220, TurkeyDepartment of Environmental Engineering, Yildiz Technical University, Istanbul 34220, TurkeyBioflocculants can be used for cost-effective harvesting of microalgae biomass on an industrial scale. This study investigates the flocculation-based harvesting approach to recovering <i>Chlorella vulgaris</i> microalgae biomass using chitosan biopolymer. Response surface methodology (RSM) was used to design the experiments and optimize the critical operating parameters. Box-Behnken Design (BBD) was employed at three levels, and 17 experimental runs were conducted to determine the optimal conditions and the relationship between operating parameters. The highest biomass recovery of 99.10% was achieved at the following optimized conditions: pH of 5, flocculation time of 45 min, and chitosan concentration of 10 mg/L. Both experimental results and model outputs indicated that pH significantly impacts microalgae harvesting and that process performance is less dependent on chitosan concentration and flocculation time. The quadratic model has shown the best fit with the experimental results. The results could be applied to large-scale microalgae harvesting applications to promote microalgae biomass recovery and reduce operating costs.https://www.mdpi.com/2297-8739/10/9/507microalgaesustainabilitybiotechnologyharvestingbiomassprocess optimization |
| spellingShingle | Harun Elcik Dogan Karadag Ayse Irem Kara Mehmet Cakmakci Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface Methodology Separations microalgae sustainability biotechnology harvesting biomass process optimization |
| title | Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface Methodology |
| title_full | Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface Methodology |
| title_fullStr | Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface Methodology |
| title_full_unstemmed | Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface Methodology |
| title_short | Microalgae Biomass Harvesting Using Chitosan Flocculant: Optimization of Operating Parameters by Response Surface Methodology |
| title_sort | microalgae biomass harvesting using chitosan flocculant optimization of operating parameters by response surface methodology |
| topic | microalgae sustainability biotechnology harvesting biomass process optimization |
| url | https://www.mdpi.com/2297-8739/10/9/507 |
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