Toxicity End Points Based on Body Burdens for
Toxicity end points based on body burdens for ecological receptors received a
score of 3 for high magnitude of uncertainty. Data are available for nonpolar
organics, but fewer data are available for metals.
The relationship between toxicity end points and body burdens is complicated
when the contaminant is metabolized by the organism. Some organisms can
metabolize contaminants to more or less toxic forms, but prediction of how a
particular chemical will be metabolized by a particular organism is difficult.
Also, since most metabolites are not detected by conventional analytical
methods, exposure of animals may be underestimated.
Dose-Response Models for Human Receptors
Dose-response models for human receptors received a score of 3 for high
magnitude of uncertainty. This uncertainty encompasses both the shape of the
dose-response curve as well as the uncertainties encountered when extrapolating
from animal to human studies. A national scientific commission recently
reviewed problems associated with such extrapolations (Presidential/
Congressional Commission on Risk Assessment and Risk Management 1997).
To extrapolate from animal toxicity data to an "acceptable" concentration or dose
in humans, USEPA applies uncertainty factors that range from 10 to 10,000. The
Presidential/Congressional Commission on Risk Assessment and Risk
Management made practical recommendations for future animal studies to
minimize these uncertainties.
Toxicity of Complex Mixtures
The toxicity of complex mixtures is not well understood for humans or
ecological receptors. Approaches are being developed to address this uncertainty
(Swartz et al. 1995; van Wezel and Opperhuizen 1995; and Giesy, Ludwig, and
Tillitt 1994) and should be pursued within the dredged material management
program. Prediction of human health impacts from chemical mixtures is equally
if not more problematic, because there is such a small database for chemical
mixture toxicity data for such mixtures as tobacco smoke and diesel exhaust.
Alternatively, researchers often must rely on models (e.g., toxicity equivalency
factors for dioxinlike compounds). To enlarge the toxicity database for chemical
mixtures, coordinated research efforts are needed among epidemiologists and
Chapter 6 Preliminary Ranking and Recommendations