Geoinformation for Disaster and Risk Management - ISPRS

Daily PM2.5 concentrations from April 2006 were
used to identify areas in New Mexico that had high
potential for dust-related health issues (Figure 5). At
left in the figure, the measure is the proportion of
days that 24-hour average DUST2.5 was greater than
15ug/m3. This concentration was used because it is
the Federal USA guideline. At right the measure is
the proportion of days that exceeded a 24-hour
maximum of 35ug/m³. Up to one-third of the days
were forecasted to exceed a level considered to be
“unhealthy.”
Outlook
Satellite sensing in dry environments is critical for
early warning of imminent dust storms to reduce
risk of exposure to individuals and populations.
Satellite data sets assimilated into models improve
identification of active dust sources, and thus,
enhance forecasts of dust generation, entrainment,
and downwind dispersal and deposition. Products
designed specifically with end users in mind are
being evaluated by health authorities having
operational health and air quality responsibilities.
These products are being modified through
continuing research, and in time will foster adoption
by public health services.
Technologies for making air quality measurements
continue to improve, but the data and observations
themselves are not systematically stored for retrieval
and medical research. Science, technology, and policy
communities face huge challenges in: gathering,
storing, modeling, interpreting, and disseminating
air quality data for tracking health outcomes in
populations. Biogeochemical and dynamical
processes of airborne pathogens and pollutants must
be researched further so that epidemiologists can
understand the medical consequences of air masses
traversing their regions.
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Figure 5: (left), All but the lightest color exceeded the standard daily average concentration of 15
µg/m³ for PM2.5 dust in the USA; (right), the darkest three colors exceeded the 24-hr daily maximum
concentration of 35 µg/m³ (from Myers, personal communication).
Long-term archives of global air quality data and
information are needed for longitudinal studies
based on sentinel or cohort populations. The grand
challenge is to add health professionals into efforts
that merge environmental surveillance with human
health syndromes.
Acknowledgements
The system described here was funded by NASA
under agreement NNS04AA19A titled Public Health
Applications in Remote Sensing (PHAiRS). Thanks
are due to all team members who participated in this
five year effort. Special thanks are extended to
William Sprigg, Dazhong Yin, Brian Barbaris, Patrick
Shaw, and Slobodan Nickovic (all from the University
of Arizona, Department of Atmospheric Sciences; to
Karl Benedict, Thomas Budge, William Hudspeth
Alan Zelicoff and Orrin Myers (all at the University of
New Mexico, Earth Data Analysis Center and UNM
Health Sciences Center).