Graduation Year


Document Type




Degree Granting Department

Civil and Environmental Engineering

Major Professor

Qiong Zhang


Carbon, Light intensity, Monod model, Nitrogen,, Phosphorous,


While understanding the kinetics of algae growth plays an important role in improving algae cultivation technology, none of the existing kinetic models are able to describe algae growth when more than three growth limiting factors are involved. A model was developed in this study to describe algae growth in a photobioreactor. Two expressions were proposed based on the Monod model to relate the specific growth rate of algae to the concentration of nitrogen, phosphorus, inorganic carbon and light intensity in the culture media. Algal biomass concentration as a function of time was calculated by solving mass and energy balances around the photobioreactor. Model simulations were compared with the experimental data from the cultivation of wild type algae in a semi-continuous culture of a completely mixed photobioreactor. There were minor differences between the model results from using the two proposed expressions of the specific growth rate of algae. Biomass concentration simulated by the model followed the same pattern as the measured concentration. However, there was discrepancy between the model output and the experimental results, because of variability from environmental conditions during the experiment and some environmental factors such as temperature were not considered in the model. Also, most of the model's parameters were either derived theoretically or obtained from literature instead of being measured directly. It was found through sensitivity analysis that the maximum biomass density predicted by the model is very sensitive to the maximum specific growth rate for carbon, maximum growth yield and higher heating value of algae. Results from running the model for a continuous culture of the same photobioreactor, showed that the minimum hydraulic retention time for the growth of algae will be 30 days. Further investigations are needed to get more accurate data for sensitive parameters so algae growth can be predicted more accurately. Future work towards integrating other factors including temperature, pH, inhibition factors and decay rate in the kinetic expression, will lead to a better prediction of algae growth