By the same authors

From the same journal

Highly time-variable exposure to chemicals: toward an assessment strategy

Research output: Contribution to journalArticle

Author(s)

Department/unit(s)

Publication details

JournalIntegrated Environmental Assessment and Management
DateE-pub ahead of print - 25 Jun 2013
DatePublished (current) - Jul 2013
Issue number3
Volume9
Number of pages7
Pages (from-to)e27-e33
Early online date25/06/13
Original languageEnglish

Abstract

Organisms in the environment experience fluctuating, pulsed or intermittent exposure to pollutants. Accounting for effects of such exposures is an important challenge for environmental risk assessment, particularly given the simplified design of standard ecotoxicity tests. Dynamic simulation using toxicokinetic-toxicodynamic (TK-TD) models describes the processes that link exposure with effects in an organism and provides a basis for extrapolation to a range of exposure scenarios. In so doing, TK-TD modelling makes the risk assessment more robust and aids use and interpretation of experimental data. TK-TD models are well developed for predicting survival of individual organisms and are increasingly applied to sub-lethal endpoints. In the latter case particularly, linkage to individual-based models (IBMs) allows extrapolation to population level as well as accounting for differences in effects of toxicant exposure at different stages in the life cycle. Extrapolation between species remains an important constraint because there is currently no systematic understanding of species traits that cause differences in the relevant processes. TK-TD models allow interrogation of exposure profiles to determine intrinsic toxicity potential rather than using absolute maximum concentrations or time-weighted averages as surrogates. A decision scheme is proposed to guide selection of risk assessment approaches using dose extrapolation based on Haber’s Law, TK-TD models and/or IBM’s depending on the nature of toxic effect and timing in relation to life history.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations