Journal article
Satellite Remote Sensing for Developing Time and Space Resolved Estimates of Ambient Particulate in Cleveland, OH
Aerosol science and technology, Vol.45(9), pp.1090-1108
09/01/2011
DOI: 10.1080/02786826.2011.581256
PMCID: PMC3253537
PMID: 22238503
Abstract
This article empirically demonstrates the use of fine resolution satellite-based aerosol optical depth (AOD) to develop time and space resolved estimates of ambient particulate matter (PM) ≤2.5 μm and ≤10 μm in aerodynamic diameters (PM
2.5
and PM
10
, respectively). AOD was computed at three different spatial resolutions, i.e., 2 km (means 2 km × 2 km area at nadir), 5 km, and 10 km, by using the data from MODerate Resolution Imaging Spectroradiometer (MODIS), aboard the Terra and Aqua satellites. Multiresolution AOD from MODIS (AOD
MODIS
) was compared with the in situ measurements of AOD by NASA's AErosol RObotic NETwork (AERONET) sunphotometer (AOD
AERONET
) at Bondville, IL, to demonstrate the advantages of the fine resolution AOD
MODIS
over the 10-km AOD
MODIS
, especially for air quality prediction. An instrumental regression that corrects AOD
MODIS
for meteorological conditions was used for developing a PM predictive model.
The 2-km AOD
MODIS
aggregated within 0.025° and 15-min intervals shows the best association with the in situ measurements of AOD
AERONET
. The 2-km AOD
MODIS
seems more promising to estimate time and space resolved estimates of ambient PM than the 10-km AOD
MODIS
, because of better location precision and a significantly greater number of data points across geographic space and time. Utilizing the collocated AOD
MODIS
and PM data in Cleveland, OH, a regression model was developed for predicting PM for all AOD
MODIS
data points. Our analysis suggests that the slope of the 2-km AOD
MODIS
(instrumented on meteorological conditions) is close to unity with the PM monitored on the ground. These results should be interpreted with caution, because the slope of AOD
MODIS
ranges from 0.52 to 1.72 in the site-specific models. In the cross validation of the overall model, the root mean square error (RMSE) of PM
10
was smaller (2.04 μg/m
3
in overall model) than that of PM
2.5
(2.5 μg/m
3
). The predicted PM in the AOD
MODIS
data (∼2.34 million data points) was utilized to develop a systematic grid of daily PM at 5-km spatial resolution with the aid of spatiotemporal Kriging.
Details
- Title: Subtitle
- Satellite Remote Sensing for Developing Time and Space Resolved Estimates of Ambient Particulate in Cleveland, OH
- Creators
- Naresh Kumar - Department of Geography , University of IowaAllen D Chu - Goddard Space Flight Center , National Aeronautics and Space Administration (NASA)Andrew D Foster - Brown UniversityThomas Peters - Department of Occupation and Environmental Health , University of IowaRobert Willis - Environmental Protection Agency
- Resource Type
- Journal article
- Publication Details
- Aerosol science and technology, Vol.45(9), pp.1090-1108
- DOI
- 10.1080/02786826.2011.581256
- PMID
- 22238503
- PMCID
- PMC3253537
- NLM abbreviation
- Aerosol Sci Technol
- ISSN
- 0278-6826
- eISSN
- 1521-7388
- Publisher
- Taylor & Francis Group
- Language
- English
- Date published
- 09/01/2011
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Occupational and Environmental Health
- Record Identifier
- 9983997343502771
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