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M. Schaap , A. Apituley, R. Koelemeijer, R. Timmermans, G. de Leeuw

Mapping the PM2.5 distribution in the Netherlands using MODIS AOD. M. Schaap , A. Apituley, R. Koelemeijer, R. Timmermans, G. de Leeuw. Introduction. Satellite derived AOD may be used to gain insight in the regional PM2.5 distribution

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M. Schaap , A. Apituley, R. Koelemeijer, R. Timmermans, G. de Leeuw

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  1. Mapping the PM2.5 distribution in the Netherlands using MODIS AOD M. Schaap, A. Apituley, R. Koelemeijer, R. Timmermans, G. de Leeuw

  2. Introduction • Satellite derived AOD may be used to gain insight in the regional PM2.5 distribution • Goal: To assess the relationship between AOD and PM2.5 in the Netherlands. • Can we use AOD data at all? • If yes, what is the relation? • When does it apply? • Can we extrapolate the relation at Cabauw to the Netherlands and estimate PM2.5 concentrations from satellite data? Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  3. Cabauw The combination of the instrumentation at Cabauw provides an unique opportunity to study the AOD-PM2.5 relationship in the Netherlands. Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  4. Instruments used in this study • AOD: Sun-photometer (CIMEL) AERONET Level 1.5 • PM2.5: TEOM-FDMS • Backscatter profile: aerosol LIDAR • Clouds: combination of Cabauw instrumentation Period: 1 August 2006 – 31 May 2007 Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  5. AOD and PM2.5: Timeseries 2006 2007 Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  6. Typical vertical profile in periods with good correlation • Stable nice weather conditions typical for smog conditions • Continental airmasses • Cloud free • Well mixed boundary layer Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  7. Typical vertical profile in periods with bad correlation AOD meas. A need for improved cloud detection! Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  8. Cloud detection using the LIDAR and Angstrom coef. Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  9. Influence of cloud screening Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  10. Time of day Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  11. Air mass origin Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  12. Application to MODIS data… MODIS validation MODIS AOD-PM2.5 Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  13. Estimated PM2.5 distribution over the Netherlands There appear to be unrealisitc gradients in the AOD distribution within the Netherlands Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  14. Conclusions • First inspection of the AERONET (L1.5) AOD and PM2.5 data yields a low correlation between the two properties • AOD correlates well with PM2.5 under stable fair weather conditions with continental air masses • AERONET L1.5 contains significant cloud contamination • Improved cloud detection using LIDAR eliminates many “outliers” • Comparison to L2.0 provides confidence in our cloud-screening method and that of AERONET • Strength of correlation increases when focusing around noon. • Mapping of the regional PM2.5 distribution yields concentrations that are about 45% higher than the long term average • The uncertainty associated with the AOD data may be higher or of similar magnitude as the spatial variability within the country. • The good temporal correlation shows that AOD can be used for monitoring PM2.5 changes in time Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

  15. Comparison to L2.0 provides confidence in our cloud-screening method and that of AERONET Mapping the PM2.5 distribution in the Netherlands using MODIS AOD

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