Differences by Selection Method for Exposure Factor Input Distribution for Use in Probabilistic Consumer Exposure Assessment

Abstract

Probabilistic exposure assessment can be used for exposure and risk assessment associated with consumer products (CPs).It is important to select input variables carefully to obtain good outcomes. The first step of a probabilistic exposure assessment is to characterize input parameters as distribution functions.Among the various methods used to assess distribution, testing the fit of a theoretical distribution to an empirical data set is a typical statistical approach. 1) Goodness-of-fit (GOF) tests can be used to obtain exposure factor distributions by selecting probabilistic models and estimating the related parameters. 2) In the second step, the distribution is combined with a mathematical simulation (e.g., using the Monte Carlo method) to obtain exposure assessment results.There are many statistical approaches for testing GOF,