Geoscience Reference
In-Depth Information
The three questions posed in this section may be similarly applied to any
emerging material to identify concerns surrounding new hazards, exposure
routes, and material tracking. The case of nanotechnology is an example of how
EPA will need to approach many emerging tools, technologies, and challenges
in general in the future. In order to have the capacity to address those tools,
technologies, and challenges, it will need to have enough internal expertise to
identify and collaborate with the expertise of all of its stakeholders in order to
ask the right questions; determine what existing tools and strategies can be ap-
plied to answer those questions; determine the needs for new tools and strate-
gies; develop, apply, and refine the new tools and strategies; and use the science
to make recommendations based on hazards, exposures, and monitoring.
TOOLS AND TECHNOLOGIES TO ADDRESS CHALLENGES
RELATED TO AIR POLLUTION AND CLIMATE CHANGE
As discussed in Chapter 2, EPA's first goal in its 2011-2015 strategic plan
is “taking action on climate change and improving air quality” (EPA 2010). Im-
proved modeling capabilities are integral to attaining that goal inasmuch as
models are needed to test the understanding of sources, environmental proc-
esses, fate, and effects of airborne contaminants and to investigate the effects of
potential mitigation measures. Examples of the many areas in which new tech-
nologies will impact air quality and climate change are discussed in the follow-
ing sections on air-pollution modeling; carbon-cycle modeling, greenhouse-gas
emissions, and sinks; and air-quality monitoring.
Air-Pollution Modeling
EPA has a strong history of leadership in air-quality modeling. Its Com-
munity Multi-scale Air Quality (CMAQ) model is used both domestically and
internationally as a premier platform for “one atmosphere” modeling of the
chemistry and transport of ground-level ozone, particulate matter, reactive nitro-
gen, mercury, and dozens of other materials. In recent years, EPA researchers
have worked with other government and university scientists to develop capa-
bilities to run the CMAQ model in a real-time forecast mode (Eder et al. 2009);
to couple the CMAQ model to an advanced meteorologic model, the Weather
Research and Forecasting system (Appel et al. 2010); and to build advanced
sensitivity analysis and inverse modeling capabilities (Napelenok et al. 2008;
Tian et al. 2010).
In coming years, investments in modeling efforts will advance the under-
standing of sources and environmental processes that contribute to particulate-
matter loadings and health and environmental effects. Modeling efforts will also
improve the understanding of interactions between climate change and air qual-
ity with a special focus on relatively short-lived greenhouse agents, such as
ozone, black carbon, and other constituents of particulate matter. Improved
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