Separation of uncertainty and interindividual variability in human exposure modeling

Abstract

The NORMTOX model predicts the lifetime-averaged exposure to contaminants through multiple environmental media, that is, food, air, soil, drinking and surface water. The model was developed to test the coherence of Dutch environmental quality objectives (EQOs). A set of EQOs is called coherent if simultaneous exposure to different environmental media that are all polluted up to their respective EQOs does not result in exceeding the acceptable or tolerable daily intake (ADI or TDI). Aim of the present study is to separate the impact of uncertainty and interindividual variability in coherence predictions with the NORMTOX model. The method is illustrated in a case study for chlorfenvinphos, mercury and nitrate. First, ANOVA was used to calculate interindividual variability in input parameters. Second, nested Monte Carlo simulation was used to propagate uncertainty and interindividual variability separately. Lifetime-averaged exposure to chlorfenvinphos, mercury and nitrate was modeled for the Dutch population. Output distributions specified the population fraction at risk, due to a particular exposure, and the reliability of this risk. From the case study, it was obtained that at lifelong exposure to all media polluted up to their standard, 100% of the Dutch population exceeds the ADI for chlorfenvinphos, 15% for mercury and 0% for nitrate. Variance in exposure to chlorfenvinphos, mercury and nitrate is mostly caused by interindividual variability instead of true uncertainty. It is concluded that the likelihood that ADIs of chlorfenvinphos and mercury will be exceeded should be further explored. If exceeding is likely, decision makers should focus on identification of high-risk subpopulations, rather than on additional research to obtain more accurate estimates for particular parameters.

Exposure of the Irish population to PBDEs in food: consideration of parameter uncertainty and variability for risk assessment

“…To date, there are only few exposure studies that have attempted to consider parameter uncertainty and separate it from population variability (Ragas et al 2009) and, to the best of our knowledge, this is the first study using this approach for human exposure to PBDEs from food. We used 2D-MCS to evaluate the extensive Irish database on PBDE concentrations in food (Fernandes et al 2009) along with food consumption data for the Irish adult population (IUNA 2001).…”

Uncertainty in environmental health impact assessment: Quantitative methods and perspectives

“…Of the 51 articles identified by the search strategy outlined above, 19 met the inclusion criteria (Fehr et al 2003;Pelekis et al 2003;Li et al 2007Li et al , 2008Tainio et al 2007Tainio et al , 2010Vicari et al 2007;Hauck et al 2008;Liu et al 2008;Ragas et al 2008;Vardoulakis et al 2008;Kuo et al 2009;Orru et al 2009;Roberts and Martin 2009;Schram-Bijkerk et al 2009;van der Voet et al 2009;Vlachokostas et al 2009;Ö zkaynak et al 2009;Koornneef et al 2010). Most were excluded since they did not have an explicit quantitative uncertainty characterisation component.…”

Probabilistic Risk Assessment for Six Vapour Intrusion Algorithms

“…The interpretation of results by decision makers might not always be straightforward as there is no rule-of-thumb to decide on the acceptance of the variation in predicted air concentrations in relation to uncertainty and variability of input parameters" (van der Sluijs et al, 2004;EPA, 1997;Morgan & Henrion, 1990;Saltelli, Tarantola, Campolongo, & Ratto, 2004;Burmaster & Anderson, 1994). Another limitation of the Monte Carlo approach is that the contribution of uncertainty and variability, however distinct phenomena with different interpretation and implications, are mixed in one output distribution (Ragas et al, 2009) unless a 2D simulation is performed in which the contribution from uncertainty and variability are dealt with separately in the calculations.…”