Stormwater biofilter treatment model (MPiRe) for selected micro-pollutants

Area of Science:

• Environmental Engineering
• Water Quality Management
• Hydrology

Background:

• Biofiltration systems (rain gardens, bioretentions) are crucial for stormwater treatment.
• Accurate predictive models are needed to optimize biofilter design and performance.
• Existing models often lack the complexity to capture diverse micro-pollutant behaviors.

Purpose of the Study:

• To present a novel model for simulating the removal of various micro-pollutants in biofiltration systems.
• To enhance the understanding of pollutant transport and fate within these systems.
• To provide a tool for improved design and validation of biofilters for stormwater harvesting.

Main Methods:

• Utilized a bucket approach for water flow simulation.
• Employed advection/dispersion transport equations for pollutant dynamics, including non-equilibrium sorption, decay, and volatilization.
• Calibrated and validated the model using field data from two distinct biofilters under varied operational conditions and micro-pollutants (triazines, glyphosate, chloroform).

Main Results:

• The model accurately simulated water flow, with minor deviations during prolonged dry periods.
• Good agreement was observed between simulated and measured pollutographs for most micro-pollutants.
• Model parameters aligned with existing literature, indicating robustness for predicting other micro-pollutants like PAHs and phthalates.

Conclusions:

• The developed model effectively simulates micro-pollutant removal in biofiltration systems.
• It offers a valuable tool for practical applications such as biofilter sizing and monitoring for stormwater harvesting.
• The model's ability to handle complex conditions suggests broader applicability for various stormwater contaminants.