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Satellite Remote Sensing of Particulate Matter
•Introduction•MODIS AOT and PM2.5•Mesoscale modeling•Summary
sundar@nsstc.uah.edu
MODIS AQUA
Sundar A. ChristopherAssociate ProfessorDepartment of Atmos. SciencesUniversity of Alabama-HuntsvilleNSSTCCollaboratorsDick McNider, UAHU. Nair, UAHElaine Prins, NOAA/NESDISJeff Reid, NRLJim Szykman, EPAJun Wang, UAH
Introduction
Main focus: Can satellite data provide assessment of air quality?Recent work with MODIS: Wang and Christopher, GRL, 2003; Chu et al., JGR(2003); Englen-Cox et al., AE (2004); Hutchinson, AE(2003).Premise : Satellite derived column AOT related with PM2.5 ground measurements and could be a cost effective way for monitoring air pollution and forecast.
MODIS AOD captures spatial extent of large scale aerosol events during cloud free conditionsFig. courtesy, J. Szykman
Surface
Aerosol
Rayleigh Scattering
Water vapor + other gases (absorption)
Ozone
10km
Aqua Satellite
Sun
ColumnSatelliteMeasurement
PointMeasurementPM2.5 mass
TEOMAOT = ∑ Extinction X dz
Particle sizeCompositionWater uptakeVertical Distribution
Aerosol Optical Thickness:Basis
Satellite retrieval issues - inversion (e.g. aerosol model, background).
r
Seven MODIS Seven MODIS bandsbandsare utilized to are utilized to derivederiveaerosol aerosol propertiesproperties
0.47, 0.47, 0.55, 0.55, 0.65, 0.65, 0.86, 0.86, 1.24, 1.24, 1.64, 1.64, and and 2.13 2.13 µµmm10X10 10X10 kmkm22
Res.Res.
4 day sequence showingtransport of regional
pollution event. Posts showEPA PM2.5 ground-based
measuring site. Color contoursare MODIS aerosol optical depth
0.0 0.2 0.4 0.6 0.8 1.0 0 10 20 30 40 50 60 70 0 15.5 40.5 65.5 150.5
Aerosol Optical Depth Cloud Optical Thickness PM2.5 (ug/m3)
Sept 9 Sept 10
Sept 11 Sept 12
No EPA sitesMODIS fills in
MODIS AOD vs. PM2.5 : Texas
Time Series shows agreement of hourly PM2.5 Concentrations (Surface Monitor) and Aerosol Optical Depth in Coincident MODIS pixel. Correlation Coefficient > 0.88.
Fig. Courtesy, J. Szykman, (EPA), A. Chu, NASA
Study area. Circles: PM2.5 observation stations. Triangles: power plants.
Wang and Christopher, GRL, 2003.
ResultsJefferson County, Alabama, 2002
Hourly PM2.5 correlated well withMODIS Terra and Aqua AOT
Evaluation of MODIS AOD/PM2.5:Chicago
MODIS AOD shows strongcorrelations withPM2.5 mass concentrations duringlarge scale aerosol events(US EPA, 2003 and Engel-Cox, J. et. al. 2004).
MODIS AOD estimate correct AQI level >90% (regional AL study)(Wang, J., S. Christopher, 2003).
Fig. courtesy, J. Szykman
AOT and PM2.5
MODIS AOT captures the intra-annual variations of AOT (as indicated by sun photometer) and PM2.5 data.
Jefferson County, Alabama, 2002
MODIS AOT vs. AQI
Wang and Christopher, GRL, 2003.
Daily PM2.5 and AOT relationship usedto obtain AQI categories from MODIS
Excellent correlation between 24-hr PM2.5 and MODIS AOT
Sensitive groups should avoid all physical activity outdoors; everyone else should avoid prolonged or heavy exertion
Sensitive groups should avoid prolonged or heavy exertion; everyone else should reduce prolonged or heavy exertion
Sensitive groups should reduce prolonged or heavy exertion
Unusually sensitive people should consider reducing prolonged or heavy exertion
None
Cautionary Statements
201-300
151-200
101-150
51-1000-50
IndexValues
PM10
(ug/m3)
PM2.5
(ug/m3)Category
355-424
255-354
155-254
55-154
0-54
150.5-250.4
65.5-150.4
40.5-65.4
15.5-40.4
0-15.4Good
Very Unhealthy
Unhealthy
Unhealthy for Sensitive Groups
Moderate
Jefferson County, Alabama, 2002
MODIS vs. PM2.5: Other sites
Texas
•Hong Kong•Delhi•China•Spain•Switzerland•Australia
Hong Kong
Delhi, India
Radiative Forcing
Wm
-2
•WF_ABBA Fires •FLAMBE smoke emission•RAMS model•SCAR-B aerosol•NCAR/NCEP fields•Four-stream RT mode•Online RT calculations
Modeling Strategy
Preliminary Results
Modeled AOT (d) MODIS/Terra AOT
Measured PM2.5 vs. Modeled Smoke Mass(a) Surface Smoke Mass Concentration
AOT after the assimilation
SummaryGood correlation between MODIS column AOT and PM2.5 mass – especially 24-hr. averages.
Current satellite data has tremendous potential for air quality applications –world wide!
AOT data can be used to develop AQI categories, However….
Further research needed to examine vertical distribution of aerosols, hygroscopiscity and chemical composition. Ground and space-borne lidarsneeded.
Satellite data can be used where PM2.5 measurements are not available. However cloud cover is a problem for satellites.
Assimilation of satellite-derived smoke emission and AOT data in provides information to forecast pollution when sources are from outside the U.S.
Combination of satellite and regional models will be successful for forecasting pollution.
sundar@nsstc.uah.edu
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