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Model development for the growth of microalgae: A review

Darvehei, P., Bahri, P.A. and Moheimani, N.R. (2018) Model development for the growth of microalgae: A review. Renewable and Sustainable Energy Reviews, 97 . pp. 233-258.

Link to Published Version: https://doi.org/10.1016/j.rser.2018.08.027
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Abstract

Despite attracting many attentions in the past decades, microalgal cultivation still faces many challenges for industrialisation. Growth, as one of the most crucial characteristics of a microalgal cultivation system, has been a significant subject for modelling. This paper presents a review of available models in the literature regarding the effect of process parameters such as light, temperature, nutrients, oxygen accumulation, salinity, and pH and carbon, on the growth rate of microalgal cells to understand their application in large-scale microalgal production. The existing models are classified based on the process conditions or parameters they considered in the formulation, and where multiple parameters were included the model was broken into separate functions, and each function was presented in the associated section. The most prominent result of this review is the huge gap between models and their validity for outdoor systems. It seems that to find suitable models for a real condition application, a new pathway is needed where models are developed based on the behaviour of the outdoor cultures in long-term. There are some effects such as adaptation which are difficult to model in short-term modelling while if the long-term approach is used these effects can be considered negligible. These characteristics of outdoor cultivation help in simplification of the models and less struggle in their validation. Moreover, using saline water is an effective way to improve the viability of algal production which requires understanding the relationship between growth and salinity of the medium. Such models are missing in the literature.

Publication Type: Journal Article
Murdoch Affiliation: School of Engineering and Information Technology
Publisher: Elsevier
Copyright: © 2018 Elsevier Ltd.
URI: http://researchrepository.murdoch.edu.au/id/eprint/41985
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