A novel metabolic-ASM model for full-scale biological nutrient removal systems

Area of Science:

• Environmental Microbiology
• Biochemical Engineering
• Water Treatment Technologies

Background:

• Existing enhanced biological phosphorus removal (EBPR) models have limitations in describing key microbial processes and require extensive calibration.
• Understanding the competition between polyphosphate-accumulating organisms (PAOs) and glycogen-accumulating organisms (GAOs) is crucial for optimizing nutrient removal.

Purpose of the Study:

• To introduce META-ASM, an integrated metabolic activated sludge model for biological nutrient removal (BNR) systems.
• To demonstrate META-ASM's capability to describe key organisms and processes with a robust set of default parameters, overcoming shortcomings of existing EBPR models.

Main Methods:

• Model validation against 34 datasets from laboratory cultures and full-scale water resource recovery facilities (WRRFs).
• Testing on two process configurations: three-stage Phoredox (A2/O) and adapted Biodenitro™ with return sludge sidestream hydrolysis (RSS).
• Analysis of operational conditions influencing PAO/GAO competition, denitrification, metabolic shifts, and polymer roles.

Main Results:

• META-ASM demonstrated good correlations between predicted and measured EBPR profiles across diverse datasets.
• The model accurately describes microbial and chemical transformations in BNR systems with minimal parameter adjustments.
• Comparison revealed existing models require extensive parameter changes and possess limited long-term predictive power.

Conclusions:

• META-ASM provides a robust platform for describing BNR systems, reducing calibration efforts and improving predictive capabilities.
• The model is a powerful tool for predicting and mitigating EBPR upsets, optimizing performance, and evaluating new process designs.
• META-ASM advances the understanding and application of microbial processes in wastewater treatment.