Fuzzy-based fugacity model for propagating uncertainty in assessing swimmer exposures to disinfection byproducts

Aleatory and epistemic uncertainty are widely accepted as unavoidable components of human health risk assessment. Model uncertainty and variability in exposure factors contribute to the overall uncertainty in the assessed risk. Probabilistic methods are commonly used to characterize these uncertainties. Exposures to disinfection byproducts have been linked to cancer as well as reproductive and respiratory health effects. Swimmers are exposed to disinfection byproducts mainly through inhalation and dermal contact and to a lesser extent through ingestion. A fugacity model has previously been used to estimate inhalation, dermal contact and ingestion exposures for swimmers. There is no consensus in literature regarding the most applicable models to use to estimate these parameters. Uncertainties related to differences between these models have been addressed here using fuzzy set theory. Possibilistic treatment of these uncertainties provides a helpful alternative to arbitrarily chosen models or probability distributions. A case study using disinfection byproduct concentrations from Italian swimming pools is presented.