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Environ Sci Technol. 2008 Aug 1;42(15):5390-9.

Assessing the concentrations of polar organic microcontaminants from point sources in the aquatic environment: measure or model?

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  • 1Centre for Ecology and Hydrology, Wallingford, Oxfordshire OX10 8BB, UK. ajo@ceh.ac.uk

Abstract

To carry out meaningful ecotoxicity studies on novel polar organic microcontaminants, it is essential to know what concentrations wildlife may be exposed to. Traditionally these values were obtained by analytical chemistry, but in recent years GIS water quality models have been developed which may offer a quick and reliable way of getting the same information. Thus, two ways of obtaining basically the same information now exist, and an issue, therefore, arises as to which method is the most appropriate to use in which situation. To address this issue we have critically reviewed and compared measuring and modeling approaches for the determination of sewage effluent and river water concentrations of organic microcontaminants. Where model predictions and chemical measurements can be directly compared in sewage effluents, receiving waters, and across catchments, reported model mean values have all been within 1 order of magnitude of the measured values, with typically no more than a 3- or 4-fold difference. Interlaboratory chemical analysis of some organic microcontaminants in effluents in the challenging ng/L range have provided results which have varied from one another by a similar margin. No such comparison has been carried out yet for GIS water quality models to determine variation in predicted concentrations. As the level of ecotoxicological effects of many chemicals is often considerably higher than the reported measured or modeled values, such errors that might occur will often be of no consequence. But due to their extraordinary potency, much more accuracy is required with some natural and synthetic hormones. Significantly, modeling is no more complex to conduct when dealing with contaminants at ng/L compared with mg/L concentrations, but the same cannot be said for chemical analysis. A combination of modeling and measuring techniques will give the greatest confidence in risk assessment.

PMID:
18754451
[PubMed - indexed for MEDLINE]
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