An empirical process model to predict microalgal carbon fixation rates in photobioreactors
- Publication Type:
- Journal Article
- Citation:
- Algal Research, 2018, 31 pp. 334 - 346
- Issue Date:
- 2018-04-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 1-s2.0-S2211926417305490-main (1).pdf | Accepted Manuscript Version | 1.46 MB |
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© 2018 Elsevier B.V. An empirical process model was developed to infer the instantaneous net photosynthesis and carbon fixation rates from continuous pH and dissolved oxygen measurements during microalgal cultivation in photobioreactors. The model is based on the physical and chemical processes that govern the relationship between inorganic carbon supplied to a microalgal culture and the organic carbon fixed into microalgal biomass, with a particular focus on carbonate chemistry and mass transfer. Bayesian statistics were used to estimate the uncertainty in state variables, such as pH, net photosynthesis rate, and bicarbonate ion concentration, based on the constraints imposed by prior knowledge about these variables. The model was verified by batch-culturing the chlorophyte microalga Chlorella vulgaris in a photobioreactor under both bicarbonate-replete and bicarbonate-limiting conditions in order to test its predictive ability under different operational settings. The replicate photobioreactors were set up to simulate a scaled-down vertical cross-section of a typical raceway pond. This model could be used to test the activity and efficiency of carbon concentrating mechanisms in different microalgal species. It also provides a detailed understanding of how the rate of photosynthesis depends on dissolved inorganic carbon concentration, which could lead to better management of carbon supply in large-scale microalgal cultivation facilities.
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