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Nakata_Mukai_IGARSS2011.ppt
1. CHARACTERIZATION OF AEROSOLS BASED ON THE SIMULTANEOUS MEASUREMENTS M. Nakata, T. Yokomae, T. Fujito, I. Sano & Sonoyo Mukai Kinki University, Higashi-Osaka, Japan
2. Introduction Studying aerosol characteristics is an important subject especially in urban areas. In this work, we classify aerosol properties by utilizing the ground observations and investigate characterization of aerosols over Higashi-Osaka, Japan. Then the obtained results are examined for aerosol retrieval with Aqua/MODIS. aerosol properties size composition amount shape m = n - ki d V / d lnr AOT refractive index size dist function optical thickness ～ sphere
3. 1. Classification of aerosol types 2. Correlation between AOT and PM 3. Aerosol retrieval from Aqua/MODIS 4. Summary Contents
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5. size distribution for 6 aerosol categories: bi-modal (fine & coarse) lognormal fn. locations size distribution Desert dust Biomass burning Continental pollution Polluted marine Dirty pollution Rural (background)
6. Size fn. available for 6 aerosol categories is demanded in practice. r r An approximate size distribution (the parameter to characterize aerosol size is " f " alone, where f is the fraction of fine ptl.) :
7. 1. Classification of aerosol types 2. Correlation between AOT and PM 3. Aerosol retrieval from Aqua/MODIS 4. Summary Contents
8. Map of AERONET site in NASA/AERONET web page Kyoto Kobe Osaka Higashi -Osaka Nara Kinki University Campus, Higashi-Osaka, Japan 34.65°N, 135.59°E Ground measurements at Higashi-Osaka Photometry : AERONET sun/sky radiometer PM sampling: PM 2.5 & PM 10 &OBC SPM-613D NIES/LIDAR Location Ground measurements at Higashi-Osaka
9. AOT (0.675 µm) at Higashi-Osaka from 2004 to 2010 AERONET/Osaka site Photometry AERONET sun/sky radiometer
10. PM 2.5 and PM C at Higashi-Osaka from 2004 to 2010 PM C = PM 10 - PM 2.5 PM sampling PM sampling PM 2.5 & PM 10 &OBC SPM-613D
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12. Scatter diagrams as AOT (0.675 m) against (0.44/0.87 m) for three clusters of aerosols at Higashi-Osaka. Aerosol properties at Higashi-Osaka site are roughly reclassifies into 3 clusters Cluster-2: Large AOT & Large Cluster-3: Large AOT & Small Cluster-1: Small AOT
13. 1) Cluster-1,-2 (Anthropogenic) & 2) Cluster-3 (Asian dust) The correlation between AOT and PM 2.5 is improved for 2-clusters as: PM 2.5 = 62.4 AOT + 12.4 PM 2.5 = 52.8 AOT + 9.68 2hours time shift : PM 2.5 = 95.1 AOT - 18.6 Estimation of PM 2.5 from AOT ad vice versa
14. 1. Classification of aerosol types 2. Correlation between AOT and PM 3. Aerosol retrieval from Aqua/MODIS 4. Summary Contents
15. {r m , } : {0.14,1.86} {r m , } : {3.42,2.34} 【 1 】 size distribution ： represented by f 【 Retrieval Flow for dust storm 】 R sim ( ) : R obs ( ) f & m = n ( ) – k ( ) i f*, n*( ), k*( ) R ( ) ←New Radiative Transfer code ( successive scattering method* ) 【 2 】 refractive index: m = n ( ) – i ･ k ( ) 【 aerosol model 】 * available for semi-infinite atmosphere model i.e. for optically thick heavy aerosol events 0.1 0.2 0.3 0.4 0.5
16. c ) ex. Yellow dust storm on April 10 in 2006 over the Badain Jaran Desert Aqua/MODIS image AOT 4.0 Dust aerosol mass concentration with SPRINTARS
17. Retrieval of dust aerosols the Badain Jaran Desert refractive index the heavy yellow dust storm can be interpreted by the large sized aerosol model with f=0.094 and refractive index ( m ) derived from AERONET data at Dalanzadgad in the Gobi Desert ( 41N, 105E ) ( 43N, 104E )
