iSTREEM®: An approach for broad-scale in-stream exposure assessment of 'down-the-drain' chemicals.

Autor: Kapo, Katherine E, DeLeo, Paul C, Vamshi, Raghu, Holmes, Christopher M, Ferrer, Darci, Dyer, Scott D, Wang, Xinhao, White‐Hull, Charlotte
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Zdroj: Integrated Environmental Assessment & Management; Oct2016, Vol. 12 Issue 4, p782-792, 11p
Abstrakt: ABSTRACT The 'in-stream exposure model' iSTREEM®, a Web-based model made freely available to the public by the American Cleaning Institute, provides a means to estimate concentrations of 'down-the-drain' chemicals in effluent, receiving waters, and drinking water intakes across national and regional scales under mean annual and low-flow conditions. We provide an overview of the evolution and utility of the iSTREEM model as a screening-level risk assessment tool relevant for down-the-drain products. The spatial nature of the model, integrating point locations of facilities along a hydrologic network, provides a powerful framework to assess environmental exposure and risk in a spatial context. A case study compared national distributions of modeled concentrations of the fragrance 1,3,4,6,7,8-Hexahydro-4,6,6,7,8,8,-hexamethylcyclopenta-γ-2-benzopyran (HHCB) and the insect repellent N,N-Diethyl- m-toluamide (DEET) to available monitoring data at comparable flow conditions. The iSTREEM low-flow model results yielded a conservative distribution of values, whereas the mean-flow model results more closely resembled the concentration distribution of monitoring data. We demonstrate how model results can be used to construct a conservative estimation of the distribution of chemical concentrations for effluents and streams leading to the derivation of a predicted environmental concentration (PEC) using the high end of the concentration distribution (e.g., 90th percentile). Data requirements, assumptions, and applications of iSTREEM are discussed in the context of other down-the-drain modeling approaches to enhance understanding of comparative advantages and uncertainties for prospective users interested in exposure modeling for ecological risk assessment. Integr Environ Assess Manag 2016;12:782-792. © 2016 SETAC [ABSTRACT FROM AUTHOR]
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