Methods for Characterizing Fine Particulate Matter Using Satellite Remote-Sensing Data and Ground Observations : Potential Use for Environmental Public Health Surveillance
- Quattrochi, Dale A.
- Physical Description:
- 1 electronic document
- Additional Creators:
- Crosson, William L., Rickman, Douglas L., Qualters, Judith R., Limaye, Ashutosh S., Tolsma, Dennis D., Estes, Maurice G., Al-Hamdan, Mohammad Z., Niskar, Amanda S., Sinclair, Amber H., and Adeniyi, Kafayat A.
- Restrictions on Access:
- Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
- This study describes and demonstrates different techniques for surfacing daily environmental / hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5) for the purpose of integrating respiratory health and environmental data for the Centers for Disease Control and Prevention (CDC s) pilot study of Health and Environment Linked for Information Exchange (HELIX)-Atlanta. It described a methodology for estimating ground-level continuous PM2.5 concentrations using B-Spline and inverse distance weighting (IDW) surfacing techniques and leveraging National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectrometer (MODIS) data to complement The Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM2.5 from the EPA database for the year 2003 as well as PM2.5 estimates derived from NASA s satellite data. Hazard data have been processed to derive the surrogate exposure PM2.5 estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM2.5 not only provides a more complete daily representation of PM2.5 than either data set alone would allow, but it also reduces the errors in the PM2.5 estimated surfaces. The results of this paper have shown that the daily IDW PM2.5 surfaces had smaller errors, with respect to observations, than those of the B-Spline surfaces in the year studied. However the IDW mean annual composite surface had more numerical artifacts, which could be due to the interpolating nature of the IDW that assumes that the maxima and minima can occur only at the observation points. Finally, the methods discussed in this paper improve temporal and spatial resolutions and establish a foundation for environmental public health linkage and association studies for which determining the concentrations of an environmental hazard such as PM2.5 with good accuracy levels is critical.
- Other Subject(s):
- NASA Technical Reports Server (NTRS) Collection.
- Document ID: 20070013994.
- Copyright, Distribution as joint owner in the copyright.
View MARC record | catkey: 16002471