Model-based analysis on growth of activated sludge in a sequencing batch reactor

Area of Science:

• Environmental microbiology
• Wastewater treatment engineering
• Bioprocess modeling

Background:

• Activated sludge systems are crucial for biological wastewater treatment.
• Understanding microbial dynamics, including heterotrophs and autotrophs, is key to optimizing these systems.
• Existing models may not fully capture the complex interactions and biomass composition.

Purpose of the Study:

• To develop and validate a mathematical model for simulating the growth of multiple microbial species in activated sludge.
• To evaluate the model's ability to predict key performance indicators like chemical oxygen demand and biomass characteristics.
• To analyze the impact of sludge retention time (SRT) on microbial community dynamics and reactor stability.

Main Methods:

• Development of a mathematical model incorporating heterotrophic and autotrophic microbial growth.
• Experimental validation using a lab-scale sequencing batch reactor with a storage process.
• Model simulations to assess the influence of varying sludge retention times (SRT).

Main Results:

• The model accurately predicts the fate of chemical oxygen demand, storage polymers (X(STO)), volatile suspended solids (VSS), ammonia, and oxygen uptake rate (OUR).
• Biomass components require 1-4 times the SRT to reach steady-state conditions.
• At an SRT of 20 days, active bacteria (autotrophs and heterotrophs) comprise approximately 57% of the VSS.

Conclusions:

• The established mathematical model effectively simulates activated sludge reactor performance.
• The model provides valuable insights into autotrophic and heterotrophic growth dynamics in complex microbial environments.
• This modeling approach can aid in optimizing wastewater treatment processes by predicting microbial behavior under different operational conditions.