Development of toxicological risk assessment models for acute and chronic exposure to pollutants

Date published

2016-08-31

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MDPI

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Article

ISSN

2072-6651

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Citation

Elke S. Reichwaldt, Daniel Stone, Dani J. Barrington, Som C. Sinang and Anas Ghadouani. Development of toxicological risk assessment models for acute and chronic exposure to pollutants. Toxins, 2016, Volume 8, Issue 9, Article number 251

Abstract

Alert level frameworks advise agencies on a sequence of monitoring and management actions, and are implemented so as to reduce the risk of the public coming into contact with hazardous substances. Their effectiveness relies on the detection of the hazard, but with many systems not receiving any regular monitoring, pollution events often go undetected. We developed toxicological risk assessment models for acute and chronic exposure to pollutants that incorporate the probabilities that the public will come into contact with undetected pollution events, to identify the level of risk a system poses in regards to the pollutant. As a proof of concept, we successfully demonstrated that the models could be applied to determine probabilities of acute and chronic illness types related to recreational activities in waterbodies containing cyanotoxins. Using the acute model, we identified lakes that present a ‘high’ risk to develop Day Away From Work illness, and lakes that present a ‘low’ or ‘medium’ risk to develop First Aid Cases when used for swimming. The developed risk models succeeded in categorising lakes according to their risk level to the public in an objective way. Modelling by how much the probability of public exposure has to decrease to lower the risks to acceptable levels will enable authorities to identify suitable control measures and monitoring strategies. We suggest broadening the application of these models to other contaminants.

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Github

Keywords

environmental risk assessment, pollutant, cyanobacteria, chronic risk, acute risk, microcystins, probability of exposure

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Attribution 4.0 International

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