期刊
ALGAL RESEARCH-BIOMASS BIOFUELS AND BIOPRODUCTS
卷 41, 期 -, 页码 -出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.algal.2019.101515
关键词
Cylindrical photobioreactor; Microalgae; Predictive model; Biomass; Temperature; Light
资金
- scholarship of China Scholarship Council [201706745010]
- 'Yuanzhi' project of School of Biotechnology of East China University of Science and Technology
- Science and Industry Endowment Fund (John Stocker Postdoctoral Fellowship) [PF16-087]
Advancing microalgae biotechnologies requires the design of high efficiency, large scale outdoor photobioreactor systems. Here we present a predictive biomass productivity model to define system design parameters yielding high biomass productivities for a facility encompassing arrays of cylindrical photobioreactors (PBRs) in a sub-tropical location (Brisbane, Australia). The model analyses the temperature and the light distributed through the culture medium as a function of PBR height, diameter, spacing distance between reactors, biomass concentration and cultivation regime (continuous vs. batch; fixed vs. capped temperature control). Temporal changes in light and temperature were used to predict volumetric and areal productivities (P-vol and P-areal respectively) for three Chlorella strains (C. vulgaris, C. sp. 11_H5 and C. pyrenoidosa). A simple empirical relationship was derived to rapidly predict P-vol in PBR arrays based on the ratio of spacing distance and reactor height (L/H) if the P-vol of a single, unshaded PBR was known. For C. vulgaris under a continuous operation and variable temperature (within its maximum growth threshold), the highest P-vol in the range analysed was obtained at the smallest diameter (0.1 m), highest biomass concentration (1.5 g L-1) and largest L/H, (P-vol similar to 0.3 g L-1 d(-1)). In contrast, the highest P-areal (similar to 50 t ha(-1) yr(-1)) was found at higher diameters (0.15 and 0.3 m), a lower biomass concentration (0.3 g L-1) and low L/H (0.2-0.4); this was attributed to a higher overall culture volume per PBR and per area. Our predictions, based on light and temperature effects on productivity, suggest that attaining a high P-vol could reduce costs, energy and materials associated with water usage, harvest loads and PBRs; whereas attaining a P-areal toward its maxima could reduce costs associated with land. The model supports effective PBR array design and process optimisation to help minimise production cost.
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