(668e) Microalgal Fuels and Chemicals Production Using Kinetic Modeling and Scaled-up Experimental Studies | AIChE

(668e) Microalgal Fuels and Chemicals Production Using Kinetic Modeling and Scaled-up Experimental Studies


Bekirogullari, M. - Presenter, The University of MAnchester
Microalgal Fuels and Chemicals Production using Kinetic Modeling and Scaled-up Experimental Studies
Mesut Bekirogullaria,b,c, Jon K. Pittmanc and Constantinos Theodoropoulosa,b,*

aSchool of Chemical Engineering and Analytical Science, University of Manchester, M13 9PL, UK

bCentre for Process Integration, University of Manchester, M13 9PL, UK

cFaculty of Life Sciences, University of Manchester, M13 9PL, UK

Cultivation of microalgae for the production of biomass and lipid oils is a promising candidate in the field of renewable fuels [1,2]. The price of the microalgal biodiesel production is currently too high to compete with the fossil diesel production. Nevertheless, optimization and scaled-up control of the microalgae growth process can improve the competitiveness and sustainability of microalgal-derived biodiesel industry [3].

The aim of this work is the development of a detailed kinetic model which will be used in conjunction with in-house obtained experimental data to enable the optimization and the control of the microalgae growth in bench-scale batch systems. The proposed integrated framework will be employed to analyse the performance of microalgae growth, manifested by nutrient and environmental parameters such as substrate, nitrogen, light, temperature and pH. Successful control and optimization of such a system can lead to the utilisation of reduced excess/uncontrolled carbon, nutrient and water sources, and also to the production of high oil bodies.

A detailed ODE-based kinetic model is constructed here and it is used for the simultaneous simulation of the carbon substrate, the nitrogen, the light intensity and the pH in the system [4,5]. High fidelity experiments were conducted at a range of operating conditions to analyse the effect of substrate and nitrogen on the lipid oil production, and to complement the computational study in order to enable the estimation of system kinetic parameters of crucial importance. The constructed model is validated and it is utilised to define the optimal growth conditions, which lead to highest oil accumulation and biomass growth.

Furthermore, experiments were carried out in open raceway ponds under the obtained optimal growth conditions and they were used for kinetic model validation at a scale-up level. We believe that scaled-up process simulations using such a detailed modelling framework will enable the system industrial applicability and commercialization.

Keywords: microalgae, bench scale, raceway pond, multi-parameter quantification.


  1. Driver, T., Bajhaiya, A. & Pitmann, J. K. 2014. Potential of Bioenergy Production from Microalgae. Current Sustainable/Renewable Energy Reports, 1, 94-103.
  2. Y. Chisti, 2007; Biotechnology Advances, 25, 294-306.
  3. Bechet, Q., Shilton, A. & Guieysse, B. 2013. Modeling the effects of light and temperature on algae growth: State of the art and critical assessment for productivity prediction during outdoor cultivation. Biotechnology Advances, 31, 1648-1663.
  4. M. Bekirogullari, J. Pittman and C. Theodoropoulos, 2015; Computer Aided Chemical Engineering, 37, 2393-2398.
  5. M. Bekirogullari, I.S. Fragkopoulos, J.K.Pittman and C. Theodoropoulos, 2016; Algal Research, Submitted

* Corresponding author, e-mail: k.theodoropoulos@manchester.ac.uk

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