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Opinion: Use Pollution Models to Support Stream Sampling

Modeling gives insight to the critical role of streamflow conditions when assessing the concentrations of endocrine disrupting compounds.  

Jul 11, 2017
Jacelyn Rice, Paul Westerhoff

ISTOCK, WOODYUPSTATEEndocrine disrupting compounds (EDCs) are a class of emerging contaminants that potentially pose a threat to aquatic life by mimicking hormones. Steroidal estrogens found in treated municipal wastewaters are of higher concern to aquatic wildlife, and amongst these 17β-estradiol(E2), estrone(E1), and 17α-ethinylestradiol (EE2) have shown to be some of the most potent, with several studies displaying their potential to exert effects at low and environmentally relevant concentrations. 

In our recent Nature Geoscience article, we calculated the proportion of stream flow that derives from upstream, publicly owned treatment works and used that to estimate estrogenic compound concentrations during average and low-flow conditions. For this study, we utilized a spatially explicit watershed-scale hydrologic model consisting of more than 14,000 sites in the U.S. where treated wastewater discharges to rivers or lakes to estimate the dilution factor (the ratio of total flow in the stream to the flow of wastewater discharge).  We then assessed potential threats to aquatic life by estimating the receiving streams’ abilities to meet or exceed the dilution factor required to meet the hazard quotient (HQ), including a tenfold factor of safety.

We find that lower dilution factors naturally equate to higher contaminant concentrations and higher potential ecological threat, yet such a national estimate had not previously been conducted. While treated wastewater contains low levels of EDCs, the discharge water itself is critical to sustaining streamflow of many rivers. Without the wastewater in the river, the flows could be 50 percent lower, or less, especially in smaller streams. Across the entire U.S., out of 15,837 wastewater treatment plants the 25th, 50th, and 75th percentiles for dilution factors (river water to wastewater flows) are 8:1, 43:1, and 287:1 for all receiving streams under average streamflow conditions, respectively.

For a subset of the locations (N=1,049) we were able to assess the influence of variable streamflows. In dry years, when the streamflows are low (we applied a standard low-flow index, Q95, when streamflow is exceeded 95 percent of the time), the median dilution factors decreased from 43:1 to 14:1. The hazard quotients associated with the estrogenic compounds under low-flow conditions indicate that more than half the streams (635 of the 1,049) exceeded the safety threshold for concentrations of one EDC; in roughly a third of the streams, the threshold was exceeded for two estrogenic compounds.

The results indicate the vulnerability of streams to EDCs under low-flow conditions. Additionally, the dependence of contaminant concentrations on streamflow conditions highlights the role that streamflow conditions can play when analyzing surface water samples for EDCs and other wastewater contaminants.

Prior studies have created sampling plans to capture diurnal and seasonal patterns in streamflow. However, obtaining enough samples to fully represent temporal variations in contaminant concentrations can still prove to be time consuming and expensive. Estrogenic impacts to fish can occur on a short time scale, and can also be reversed when higher dilution of wastewater returns after drought periods. For this reason, modeling efforts such as the one performed in our study can serve as a good accompaniment to environmental sampling. Our model can be used to identify stream locations where contaminants are expected to be high, signaling where further chemical analysis is warranted. Additionally, after samples are collected, the model can be used to adjust measured environmental concentrations and estimate contaminant concentrations under a range of streamflow conditions.

Jacelyn Rice is an assistant professor in the Department of Engineering Technology and Construction Management at the University of North Carolina, Charlotte, and Paul Westerhoff is a regents professor in the School of Sustainable Engineering and the Built Environment at Arizona State University. Their study was partially supported by the Arizona State University Decision Center for a Desert City (NSF Award No. 0951366) and Central Arizona-Phoenix Long Term Ecological Research (BCS-1026865 & DEB-1637590).

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