Affiliations 

  • 1 Aquatic Ecology and Ecosystem Studies, School of Civil, Environmental and Mining Engineering, The University of Western Australia, 35 Stirling Highway, M015, Crawley WA 6009, Western Australia, Australia. elke.reichwaldt@uwa.edu.au
  • 2 Aquatic Ecology and Ecosystem Studies, School of Civil, Environmental and Mining Engineering, The University of Western Australia, 35 Stirling Highway, M015, Crawley WA 6009, Western Australia, Australia. 20514707@student.uwa.edu.au
  • 3 International Water Centre, Department of Marketing, Monash University, School of Public Health, The University of Queensland, Level 16, 333 Ann Street, Brisbane QLD 4000, Queensland, Australia. dani.barrington@monash.edu
  • 4 Faculty of Science and Mathematics, Sultan Idris Education University, Tanjong Malim 35900, Perak, Malaysia. somcit@fsmt.upsi.edu.my
  • 5 Aquatic Ecology and Ecosystem Studies, School of Civil, Environmental and Mining Engineering, The University of Western Australia, 35 Stirling Highway, M015, Crawley WA 6009, Western Australia, Australia. anas.ghadouani@uwa.edu.au
Toxins (Basel), 2016 08 31;8(9).
PMID: 27589798 DOI: 10.3390/toxins8090251

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.