Micropollutant concentration fluctuations in combined sewer overflows require short sampling intervals

Area of Science:

• Environmental Science
• Water Quality
• Urban Hydrology

Background:

• Combined sewer overflows (CSOs) are a significant urban pathway for organic micropollutants entering water bodies.
• Current understanding of micropollutant dynamics during CSOs is limited due to reliance on grab samples or event mean concentrations (EMCs).
• High temporal resolution data is needed to accurately characterize micropollutant behavior during CSO events.

Purpose of the Study:

• To investigate the temporal dynamics of polar organic micropollutants in CSOs from urban catchments of varying sizes.
• To differentiate micropollutant behavior based on source (municipal wastewater vs. urban surface runoff) and catchment characteristics.
• To evaluate the accuracy of different time-proportional sampling strategies for estimating EMCs.

Main Methods:

• Conducted high temporal resolution (3-minute intervals) measurements of 33 wastewater and 13 urban runoff micropollutants in CSOs from small (2,700 P) and large (159,000 P) catchments.
• Analyzed concentration variations of different micropollutant categories over time.
• Simulated various time-proportional sampling strategies to assess errors in EMC estimation.

Main Results:

• Micropollutant concentration dynamics in CSOs varied significantly based on substance source and catchment size.
• Indoor-originating substances (e.g., pharmaceuticals) in small catchments exhibited high temporal variability (1-2 orders of magnitude change within 9 minutes).
• Outdoor substances in small catchments and all substances in the large catchment showed less dynamic concentration fluctuations.

Conclusions:

• High temporal resolution sampling is essential for accurately capturing micropollutant dynamics in CSOs, particularly for indoor substances in small urban catchments.
• A sampling interval of 3 minutes is recommended for small catchments to accurately monitor indoor micropollutants.
• Understanding these dynamics improves CSO monitoring, management, and the design of urban wet-weather treatment systems, minimizing errors in EMC estimation.