Prediction of overall persistence and long-range transport potential with multimedia fate models: robustness and sensitivity of results

The hazard indicators persistence (P) and long-range transport potential (LRTP) are used in chemicals assessment to characterize chemicals with regard to the temporal and spatial extent of their environmental exposure. They are often calculated based on the results of multimedia fate models. The environmental and substance-specific input parameters of such models are subject to a range of methodological uncertainties and also influenced by natural variability. We employed probabilistic uncertainty analysis to quantify variance in P and LRTP predictions for chemicals with different partitioning and transport behavior. Variance found in the results is so large that it prevents a clear distinction between chemicals. Additionally, only small improvements are observed when evaluating the results relative to a benchmark chemical. This can be explained by the dominance of substance-specific parameters and the only small direct influence of environmental parameters on P and LRTP as model outcomes. The findings underline the importance of learning how environmental conditions cause variability in substance behavior for improved substance ranking and classification.