Optimization of biofiltration for odor control: model calibration, validation, and applications

Area of Science:

• Environmental Engineering
• Biotechnology
• Air Pollution Control

Background:

• Wastewater treatment plants generate air emissions containing hydrogen sulfide (H2S).
• Biofiltration is a viable technology for H2S removal, but dynamic modeling is needed for effective design and operation.
• Accurate prediction of H2S removal efficiency under varying conditions is crucial.

Purpose of the Study:

• To develop and validate a dynamic model for H2S biofiltration from wastewater treatment plant air emissions.
• To assess the model's predictive capability using pilot- and full-scale biofilter data.
• To identify key operational parameters influencing H2S removal efficiency.

Main Methods:

• A dynamic biofiltration model was developed.
• The model was calibrated and validated using data from pilot- and full-scale biofilters.
• Model performance was evaluated by comparing predicted effluent concentrations with measured data.

Main Results:

• The model accurately predicted dynamic effluent H2S concentrations, with measured data within 58-80% of model outputs.
• The model successfully predicted trends in field data, even with changing input concentrations and low effluent levels (<1 ppmv).
• Simulations indicated that increased gas residence time and temperature, and decreased influent H2S concentration, reduce effluent concentration.

Conclusions:

• The dynamic biofiltration model is a reliable tool for predicting H2S removal.
• Biofilter design should consider maximum influent H2S concentrations to manage dynamic loading increases.
• The model provides valuable insights for optimizing the design and operation of biofilters for H2S emission control.