Environmental Engineering Reference
In-Depth Information
known, these models often do not perform too badly for certain substance
classes. New analytical technologies (e.g., time of flight technologies) also
provide a powerful tool to identify and semi-quantify emerging contaminants
in real environmental systems. By using the information on potential inputs to
a system, it should be possible to focus the analysis on the emerging contamin-
ants of most interest. We also have a number of tools available for estimating
the effects of a substance, including read across techniques, QSARs and expert
systems. By using exposure models and effects prediction approaches in com-
bination, we can begin to home in on those substances that are likely to pose
the greatest risk in a particular situation. The main problem is that for many
classes of emerging contaminants, the predictive models are inappropriate. For
example, exposure models do not yet exist for assessing the fate of engineered
nanoparticles, and good quality QSARs are not always available for predicting
ecotoxicity of some chemical classes. However, as REACh begins to have an
impact, this situation is likely to improve. Our understanding of risks of ECs
would also improve through more sharing of data (e.g., between scientists
working in the area and industry), including negative data that may never find
its way into a scientific publication.
Previous horizon scanning studies for emerging contaminants
A number of previous studies have been performed to identify priority
emerging environmental pollutants (e.g., Boxall et al.
2003b
; Sanderson et al.
2003
; Thomas & Hilton
2003
; Capelton et al.
2006
; Sinclair et al.
2006
). These
have considered a range of classes (veterinary and human medicines and
degradates), different exposure pathways and have been aimed at different
protection goals (
Table 5.3
). An outline of the different studies and the outputs
are described in more detail below.
A UK Environment Agency funded study identified human pharmaceuticals
of most concern to the environment (Thomas & Hilton
2003
). Data were
obtained from manufacturers on the amounts of all active ingredients used
in the UK on a yearly basis. These data were then used to estimate exposure
concentrations in the aquatic environment. The relative risk to the environ-
ment was then determined by comparing exposure concentrations to either
ecotoxicity predictions obtained using QSARs or to the therapeutic dose of the
active ingredient. Two priority lists were then developed: one based on the
therapeutic dose approach and the other on QSAR predictions. Active ingredi-
ents identified as highest priority using both approaches are given in
Table 5.4
.
Sanderson et al.(
2003
) ranked approximately 3000 pharmaceuticals in terms
of their hazard to algae, daphnids and fish. Modifying additives were the most
toxic class, while cardiovascular, gastrointestinal, antiviral, anxiolytic seda-
tives, hypnotics, antipsychotics, corticosteroid and thyroid pharmaceuticals
were identified as the hazardous therapeutic classes.
