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An alternative approach to risk rank chemicals on the threat they pose to the aquatic environment

The Science of The Total Environment 2017 134 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 50 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Andrew C. Johnson, Rachel L. Donnachie, John P. Sumpter, Monika D. Jürgens, Claudia Moeckel, M. Glória Pereira

Summary

This paper proposed an alternative approach for ranking chemicals by the threat they pose to aquatic ecosystems, integrating exposure and hazard data in a more ecologically meaningful way than standard risk quotient methods.

Study Type Environmental

This work presents a new and unbiased method of risk ranking chemicals based on the threat they pose to the aquatic environment. The study ranked 12 metals, 23 pesticides, 11 other persistent organic pollutants (POPs), 13 pharmaceuticals, 10 surfactants and similar compounds and 2 nanoparticles (total of 71) of concern against one another by comparing their median UK river water and median ecotoxicity effect concentrations. To complement this, by giving an assessment on potential wildlife impacts, risk ranking was also carried out by comparing the lowest 10th percentile of the effects data with the highest 90th percentile of the exposure data. In other words, risk was pared down to just toxicity versus exposure. Further modifications included incorporating bioconcentration factors, using only recent water measurements and excluding either lethal or sub-lethal effects. The top ten chemicals, based on the medians, which emerged as having the highest risk to organisms in UK surface waters using all the ecotoxicity data were copper, aluminium, zinc, ethinylestradiol (EE2), linear alkylbenzene sulfonate (LAS), triclosan, manganese, iron, methomyl and chlorpyrifos. By way of contrast, using current UK environmental quality standards as the comparator to median UK river water concentrations would have selected 6 different chemicals in the top ten. This approach revealed big differences in relative risk; for example, zinc presented a million times greater risk then metoprolol and LAS 550 times greater risk than nanosilver. With the exception of EE2, most pharmaceuticals were ranked as having a relatively low risk.

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