Assessing the effects of field-relevant pesticide mixtures for their compliance with the concentration addition model – An experimental approach with Daphnia magna
| Autor: | Jochen P. Zubrod, Theresa Schell, Alexander Feckler, Ralf Schulz, Simon Lüderwald, Willem Goedkoop, Mirco Bundschuh |
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| Rok vydání: | 2018 |
| Předmět: |
Environmental Engineering
Model prediction Daphnia magna 0211 other engineering and technologies 02 engineering and technology Complex Mixtures 010501 environmental sciences Risk Assessment 01 natural sciences Daphnia Chemical mixtures Animals Environmental Chemistry Standard test Pesticides Waste Management and Disposal 0105 earth and related environmental sciences Environmental risk assessment 021110 strategic defence & security studies biology Agriculture Pesticide biology.organism_classification Pollution Environmental chemistry Environmental science Risk assessment Water Pollutants Chemical |
| Zdroj: | Science of The Total Environment. 644:342-349 |
| ISSN: | 0048-9697 |
| DOI: | 10.1016/j.scitotenv.2018.06.334 |
| Popis: | The environmental risk assessment of pesticides is mainly performed on individual active ingredients. In surface waters within the agricultural landscape, however, contamination is usually characterized by complex pesticide mixtures. To estimate the joint effects caused by these complex mixtures, mathematical models have been proposed. Among these, the model of concentration addition (CA) is suggested as default model for the risk assessment of chemical mixtures as it is considered protective for mixtures composed of similar and dissimilar acting substances. Here we assessed the suitability of CA predictions for seven field relevant pesticide mixtures using acute (immobility) and chronic (reproduction) responses of the standard test species Daphnia magna. Pesticide mixtures indicated largely additive or less than additive effects when using CA model predictions as a reference. Moreover, we revealed that deviations from CA predictions are lower for chronic (up to 3.2-fold) relative to acute (up to 7.2-fold) response variables. Additionally, CA predictions were in general more accurate for complex mixtures relative to those composed of only a few pesticides. Thus, this study suggests CA models as largely protective for the risk assessment of pesticide mixtures justifying its use as default model. At the same time, extrapolating conclusions about the joint effects of pesticides from acute to chronic responses is uncertain, due to partly large discrepancies with regards to the deviation of model prediction and observed effects between exposure scenarios. |
| Databáze: | OpenAIRE |
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