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Related Experiment Videos

Multipopulation model of membrane-aerated biofilms.

John W Shanahan1, Michael J Semmens

  • 1Department of Civil Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA.

Environmental Science & Technology
|July 1, 2004
PubMed
Summary

A new multipopulation biofilm model accurately predicts wastewater treatment performance. This model, unlike single-population models, accounts for diverse microbial communities, improving predictions for chemical oxygen demand (COD) and inorganic nitrogen removal.

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Area of Science:

  • Environmental microbiology
  • Biotechnology
  • Wastewater treatment engineering

Background:

  • Membrane-supported biofilms exhibit unique growth due to counter-diffusing nutrients (oxygen from membrane, substrates from water).
  • Previous computer models for these biofilms focused on single aerobic bacterial populations, limiting their applicability to complex wastewater environments.

Purpose of the Study:

  • To develop and validate a multipopulation biofilm model for predicting simultaneous removal of chemical oxygen demand (COD) and inorganic nitrogen.
  • To compare the predictive capabilities of a multipopulation model against existing single-population models.

Main Methods:

  • Construction of a multipopulation biofilm model using Aquasim software.
  • Inclusion of key microbial groups: aerobic heterotrophs, nitrifiers, denitrifiers, and acetoclastic methanogens.

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  • Validation of model predictions against experimental data on COD and inorganic nitrogen removal.

    • Main Results:

    • The multipopulation model successfully predicts the simultaneous removal of COD and inorganic nitrogen in membrane-supported biofilms.
    • Model predictions align with previously observed experimental behaviors in laboratory studies.
    • Comparison highlights the limitations of single-population models for mixed microbial communities.

    Conclusions:

    • A multipopulation biofilm model provides a more accurate representation of biofilm processes in wastewater treatment.
    • This model enhances understanding and prediction of nutrient removal in complex microbial consortia.
    • The developed model shows significant potential for optimizing wastewater treatment applications.