Geoscience Reference
In-Depth Information
Cumulative risk assessment contains many subcategories of exposure,
health, and ecologic risk analyses, and it is important for EPA to examine its
research portfolio in this domain carefully to ensure that it is well aligned with
the ultimate decision contexts. With the increased use of LCA or life-cycle
thinking, identification of combinations of exposures associated with processes
or technologies would be increasingly common, and methods to characterize the
ecologic and human health implications of combined exposures would be valu-
able. There are potentially valuable applications of advanced biosciences for
evaluating various chemical mixtures rapidly, but they would not capture psy-
chosocial stressors and other prevalent community-scale factors that are of in-
creasing interest to the agency and various stakeholders (Nweke et al. 2011).
New epidemiologic methods or application of epidemiologic insights can start to
address those factors, but today they are limited in the number of stressors and
locations with adequate exposure data and sample size that they can accommo-
date. Advancing methods along both fronts, ideally in a coordinated and mutu-
ally reinforcing manner, would be the most fruitful approach.
As EPA concentrates increasingly on wicked problems and broad man-
dates related to sustainability, narrowly focused risk assessments that omit com-
plex interactions will be increasingly uninformative and unsupportive of effec-
tive preventive decisions. The broad challenge before the agency will involve
developing tools and approaches to characterize cumulative effects in complex
systems and harnessing insights from multistressor analyses without paralyzing
decisions because of analytic complexities or missing data.
Social, Economic, Behavioral, and Decision Sciences
Systems thinking involves acknowledgment, up front, that environmental
conditions are substantially determined by the individual and collective interac-
tions that humans have with environmental processes. As discussed in Chapter
2, the human drivers of environmental change include population growth, set-
tlement patterns, land uses, landscape patterns, the structure of the built envi-
ronment, consumption patterns, the mix and amounts of energy sources, the spa-
tial structure of production, and a host of other relevant variables. Social,
economic, behavioral, and decision sciences show that those drivers are not in-
dependent of the natural environments in which effects occur, and that there are
feedbacks, positive and negative, between human and environmental systems
(Diamond 2005; Ostrom 1990; Taylor 2009). Environmental science and engi-
neering also provide technologies for altering the relationships between humans
and the environment and tools for predicting environmental change in response
to changes in social and economic systems. That knowledge is all essential and
useful for informing environmental decisions and policies; however, additional
knowledge, skills, and expertise are needed. To make well-informed policies
and decisions that are sustainable, it is essential to integrate theories of, evidence
on, and tools for understanding how people respond to changes in the environ-
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