Results from the multi-species benchmark problem (BM3) using one-dimensional models

Area of Science:

• Environmental Microbiology
• Biochemical Engineering
• Water Treatment Technologies

Background:

• Biofilms are complex microbial communities crucial in environmental and industrial processes.
• Understanding the coexistence of multiple species (heterotrophic bacteria, nitrifying bacteria, inert biomass) within biofilms is essential for process optimization.
• The International Water Association (IWA) Biofilm Modeling Task Group established a benchmark problem to evaluate different modeling approaches.

Purpose of the Study:

• To compare nine different one-dimensional biofilm models used to simulate a multi-species system.
• To identify key distinctions in model structures and their impact on simulation outcomes.
• To assess how different biomass distribution strategies affect model predictions.

Main Methods:

• Development of a multi-species benchmark problem involving heterotrophic bacteria, nitrifying bacteria, and inert biomass.
• Submission and analysis of solutions from nine distinct one-dimensional biofilm models.
• Categorization of models based on numerical solution methods (full numerical vs. spreadsheet) and biomass distribution assumptions.

Main Results:

• Models protecting slow-growing species (nitrifiers) by positioning them away from the biofilm surface led to increased nitrifier and inert coverage but decreased heterotroph coverage.
• Heterotroph coverage and chemical oxygen demand (COD) removal were significantly influenced by the dilution effect of nitrifiers and inerts near the biofilm surface.
• Models preventing significant dilution of heterotrophs in the outer layer predicted higher COD removal rates.

Conclusions:

• The selection of a biofilm model depends on the specific application and the relative importance placed on protecting slow-growing species versus accounting for dilution effects on fast-growing species.
• Model structure, particularly biomass distribution, critically influences predictions of biofilm performance and microbial dynamics.
• These findings aid in selecting appropriate biofilm models for wastewater treatment and other relevant applications.