Evaluation of the effects of input variables on the growth of two microalgae classes during wastewater treatment

Wastewater treatment carried out by microalgae is usually affected by the type of algal strain and the combination of cultivation parameters provided during the process. Every microalga strain has a different tolerance level towards cultivation parameters, including temperature, pH, light intensity, CO2 content, initial inoculum level, pretreatment method, reactor type and nutrient concentration in wastewater. Therefore, it is vital to supply the right combination of cultivation parameters to increase the wastewater treatment efficiency and biomass productivity of different microalgae classes. In the current investigation, the decision tree was used to analyse the dataset of class Trebouxiophyceae and Chlorophyceae. Various combinations of cultivation parameters were determined to enhance their performance in wastewater treatment. Nine combinations of cultivation parameters leading to high biomass production and eleven combinations each for high nitrogen removal efficiency and high phosphorus removal efficiency for class Trebouxiophyceae were detected by decision tree models. Similarly, eleven combinations for high biomass production, nine for high nitrogen removal efficiency, and eight for high phosphorus removal efficiency were detected for class Chlorophyceae. The results obtained through decision tree analysis can provide the optimum conditions of cultivation parameters, saving time in designing new experiments for treating wastewater at a large scale.

Automated summary

The wastewater treatment efficiency and biomass productivity of microalgae in wastewater treatment are influenced by the algal strain and cultivation parameters. This study used decision tree models to analyze the data of Trebouxiophyceae and Chlorophyceae classes, and identified suitable combinations of cultivation parameters to enhance their performance.