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