EAWAG, Swiss Federal Institute of Aquatic Science and Technology, Switzerland
At the higher tiers of chemical risk assessment, regulatory guidance typically recommends the performance of simulation-type transformation studies to identify major transformation products (TPs). However, most risk assessment guidelines fall short of providing guidance on how the risk of identified TPs should ultimately be assessed.
In this presentation two possible approaches to identify risk-relevant TPs were presented and contrasted in terms of their advantages and disadvantages. This was based on earlier published work (Escher and Fenner, 2011). The default approach recommended in most regulatory risk assessment frameworks is exposure-driven, i.e. chemical-analytical identification of major TPs followed up by their synthesis and subsequent effect testing. Recent approaches to speed up TP structure identification (see Helbling et al, 2010) such as high-resolution mass spectrometry combined with high-throughput data analysis tools were discussed in this context. An effect-driven approach based on toxicity to the bacteria Escherichia coli was presented as an alternative, potentially more direct way of identifying toxicologically relevant TPs. In this approach, samples from simulation studies are not only subjected to chemical analysis, but are also analysed with one or more bioassays to follow the development of toxicity over the course of the experiment. Comparison of parent compound concentration and toxicity development over time then indicates whether any toxicologically relevant TPs are formed.
Both of the above-mentioned experimental approaches are quite labour- and time-intensive suggesting that there is a role of models for prioritisation of TPs for further investigation. A model to estimate relative concentrations of pesticide (trichlosane) TPs in surface waters was presented and its performance assessed relative to measured field data. Further, a model for estimating plausible ranges of toxic effects of TPs relative to their parent compounds was discussed. A combination of such models could potentially help to estimate the contribution of TPs to overall environmental risk caused by the release of a given parent compound.