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Probabilistic approaches in the effect assessment of toxic chemicals

What are the benefits and limitations?


There is an ongoing discussion whether in the environmental risk assessment for chemicals the so called ‘deterministic’ approach using point estimates of exposure and effect concentrations is still appropriate. Instead, the more detailed and scientifically sounder probabilistic methods that have been developed over the last years are widely recommended. Here, we present the results of a probabilistic effect assessment for the aquatic environment performed for the pesticide methyl parathion and compare them with the results obtained with the common deterministic approach as described in the EU Technical Guidance Document. Methyl parathion was chosen because a sufficient data set (acute toxicity data for about 70 species) was available. The assumptions underlying the probabilistic effect assessment are discussed in the light of the results obtained for methyl parathion. Two important assumptions made by many studies are: (i) a sufficient number of ecologically relevant toxicity data is available, (ii) the toxicity data follow a certain distribution such as log-normal. Considering the scarcity of data for many industrial chemicals, we conclude that these assumptions would not be fulfilled in many cases if the probabilistic assessment was applied to the majority of industrial chemicals. Therefore, despite the well-known limitations of the deterministic approach, it should not be replaced by probabilistic methods unless the assumptions of these methods are carefully checked in each individual case, which would significantly increase the effort for the assessment procedure.

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Correspondence to Martin Scheringer.

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Scheringer, M., Steinbach, D., Escher, B. et al. Probabilistic approaches in the effect assessment of toxic chemicals. Environ Sci & Pollut Res 9, 307 (2002). https://doi.org/10.1007/BF02987572

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  • Aquatic toxicity
  • deterministic risk assessment
  • effect assessment
  • logit
  • methyl parathion
  • probabilistic risk assessment
  • probit