Environmental Health Criteria 214

HUMAN EXPOSURE ASSESSMENT
characterize distributions of population exposure. In this way, we
characterize total potential dose using comprehensive, simple and
possibly stochastic models to focus efforts on those exposure
pathways, media and scenarios that require more realistic assessment
of the distribution of dose within the population. This matrix allows
us to make both pathway-to-pathway and medium-specific comparisons of
total potential doses from multiple environmental media.
6.6 Probabilistic exposure models
Variability and uncertainty are two important and related
concepts in exposure modelling, but it is important to distinguish
between them. Variability arises from true heterogeneity across
people, places or time; uncertainty represents a lack of knowledge
about factors affecting exposure (or risk). Thus, variability can
affect the precision of model estimates and the degree to which they
can be generalized, whereas uncertainty can lead to inaccurate or
biased estimates (Hoffman & Hammonds, 1994). It should be noted that
variability and uncertainty can complement or confound one another.
They may also have fundamentally different manifestations. For
example, uncertainty may force decision-makers to judge how
practicable it is that exposures have been over- or underestimated for
every member of the exposed population, whereas variability forces
them to cope with the certainty that different individuals are subject
to exposures both above and below any of the exposure levels chosen as
reference points (US NRC, 1994).
Failing to distinguish between variability and uncertainty makes
it difficult to accurately characterize the population distribution of
exposure and to make informed decisions about priorities for future
research objectives. Exposure models can allow for consideration of
both variability and uncertainty.
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