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ior of multiple stressors, the interactions among them, and their contributions to
health outcomes.
The air-pollution health community has been examining the science-
readiness of a multipollutant regulatory strategy (Dominici et. al. 2010;
Greenbaum and Shaikh 2010). The challenges, opportunities, and future re-
search needs related to multipollutant approaches for the assessment of health
risks associated with exposures to air pollution were evaluated in a public work-
shop held in 2011 (Johns et al. 2012). The workshop highlighted the need for a
transdisciplinary research approach for developing more relevant tools and
methods in the fields of exposure science, human and animal toxicology, and air
pollution epidemiology. More important, it recommended collaboration among
science, engineering, and policy communities to develop practical and imple-
mentable approaches that could ultimately inform decision-making (D. Johns,
EPA, personal communication, May 9, 2012).
Related efforts to characterize toxicity of mixtures of chemicals in chemi-
cal risk assessment are under way. A key challenge is to define the universe of
possible combinations of mixtures that are representative of real-world expo-
sures. In a recent analysis, EPA researchers investigated methods from the field
of community ecology originally developed to study avian species co-
occurrence patterns and adapted them to examine chemical co-occurrence
(Tornero-Velez et al. 2012). Their findings showed that chemical co-occurrence
was not random but was highly structured and usually resulted in specific pre-
dictable combinations. Novel application of tools and approaches from a variety
of research disciplines can be used to address the complexity of mixtures, ad-
vance the scientific communities' understanding of exposures to the mixtures,
and promote the design of relevant experiments and models to assess associated
health risks.
TOOLS AND TECHNOLOGIES TO ADDRESS
CHALLENGES RELATED TO WATER QUALITY
As discussed in Chapter 2, there are several important drivers of water
quality and water-quality policies for which new technologies and approaches
can be instrumental in enhancing data-driven regulations. For the purposes of
this chapter, examples of the many areas in which new technologies will impact
water quality are divided into the following areas: remote sensing technologies
for water-quality monitoring; water modeling; and detecting microorganism and
microbial products in the environment.
Water-Quality Monitoring
Multispectral imagery has been successfully applied to water-quality moni-
toring for several decades, notably for monitoring surface temperature and concen-
trations of suspended sediments and algae (see reviews by Mertes 2002; Matthews
2011). Modern multispectral sensors—such as the moderate-resolution imaging
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