Biophysical modeling of microalgal cultivation in open ponds

Bunushree Behera, Nazimdhine Aly and Balasubramanian P.

Ecological Modelling, 2018, vol. 388, issue C, 61-71

Abstract: Microalgal biomass is currently recognized as a promising sustainable source for biofuel production and carbon dioxide (CO2) sequestration. Utilization of biophysical models are emerging to access the real-time feasibility of microalgal technology. In this present work, a comprehensive mathematical model based on the site-specific meteorological variables is formulated using MATLAB ODE 45 s solver to estimate the microalgal productivity. The predictive model framework utilized material balance equations with basic laws of physics, known constants and conservative assumptions to evaluate the water temperature that influences the microalgal viability. The dynamic behaviour of algal ponds considering the operating variables like light intensity (including the effects of photoinhibition), water temperature, and design criteria like pond depth, microalgal concentration, was used to estimate the performance of T. pseudonana in open ponds. Maximum growth was projected in September accounting to the biomass and lipid productivity of 170.28 kg (dry mass) ha−1 d−1 and 39.42 l ha−1 d−1 respectively with a CO2 capture potential of 224.77 kg (CO2) ha−1 d−1 based on the influence of water temperature. Optimal pond depth and operational conditions to achieve the desired productivity for the specific site were estimated. The maximum annual areal productivity dropped by 19% from 62.18 tons (dry mass) ha−1 yr−1 due to photoinhibition. The simulated biophysical model as a tool could be used to evaluate the biokinetic processes affecting the algal pond performance for further facilitation of effective decision making on scaling up of microalgae cultivation.

Keywords: Mathematical modeling; Microalgae; Biomass productivity; Carbon sequestration; Feasibility analysis; Photoinhibition (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:388:y:2018:i:c:p:61-71

DOI: 10.1016/j.ecolmodel.2018.09.024

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