Integral microalgae-bacteria model (BIO_ALGAE): Application to wastewater high rate algal ponds

Area of Science:

• Environmental Engineering
• Microbial Ecology
• Bioprocess Engineering

Background:

• Mixed algal-bacterial systems are crucial for wastewater treatment.
• Understanding their complex interactions is key for optimizing performance.
• Existing models often lack detailed mechanistic descriptions of these interactions.

Purpose of the Study:

• To develop an integral mechanistic model (BIO_ALGAE) for mixed algal-bacterial systems in wastewater.
• To incorporate key physical, chemical, and biokinetic processes affecting microalgae and bacteria.
• To validate the model using experimental data from pilot high-rate algal ponds (HRAPs).

Main Methods:

• Developed the BIO_ALGAE model based on activated sludge models (ASM) framework.
• Implemented the model using COMSOL Multiphysics™.
• Calibrated and validated the model with pilot-scale HRAP data treating real wastewater.

Main Results:

• The model accurately simulated pond dynamics and predicted microalgae (58-68% TSS) and bacteria (30-20% TSS) proportions.
• Microalgae growth was significantly influenced by light availability (fL(I)), reducing concentrations by 40-60%.
• Reducing influent organic matter by 50-70% increased microalgae production (8.7 to 13.5 g TSS m⁻² d⁻¹).

Conclusions:

• The BIO_ALGAE model provides a robust tool for simulating and understanding algal-bacterial interactions in wastewater.
• It can accurately predict microalgae production and the impact of operational parameters.
• The model aids in the design and optimization of high-rate algal ponds (HRAPs).