Abstract

There is growing interest in the ability of high rate algal ponds (HRAP) to treat wastewater. This method reduces the costs of algal production while treating the wastewater quicker and more efficiently than standard lagoon practices. Two parallel HRAPs were used in this study to treat secondary effluent. Nitrogen levels were significantly reduced with a mean reduction of 71% for ammonia and 64% for total nitrogen. The use of the HRAPs significantly increased the algal biomass levels compared to the algal growth in the storage lagoons, with a mean increase of 274%. Beneficial use of algae can be used to reduce treatment costs; so being able to predict and optimise the amount of algal biomass produced in HRAPs is vital. However, most models are complicated and require specific, detailed information. In this study, a predictive microalgal growth model was developed for HRAP by adapting two previously established models: the Steele and Monod models. The model could predict algal growth based on temperatures and solar radiation and account for limiting ammonia concentrations in an elevated pH environment with natural variations in the algal community. This model used experimental data that would be readily available to any established HRAP study.

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