1. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 1 PM MAPPER®: An air quality monitoring system from MODIS data NGUYEN Thi Nhat Thanh 1,3, BOTTONI Maurizio 2, MANTOVANI Simone 1,2 1 MEEO SRL. Via Saragat 9, 44122 Ferrara, Italy 2 SISTEMA GmbH, Dr. Karl Lueger Platz 5, A-1010 Wien, Austria 3 University of Ferrara, Via Giuseppe Saragat 1, 44122 Ferrara, Italy

2. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 22 Outline OVERVIEW VALIDATION CONCLUSION

3. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 3 PM MAPPER® Overview

4. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 4 PM MAPPER® FeaturesPM MAPPER® InputMODIS – Moderate Resolution Imaging Spectroradiometer Output dataAerosol Optical Thickness Map PM 2.5/10 Concentration Map Air Quality Index Map Land cover information Output Resolution 3 x 3 km 2 Orbit: 705km, sun-synchronous, near-polar, circular 10:30 a.m. descending node (Terra) or 1:30 p.m. ascending node (Aqua) 2330 km (cross track) by 10 km (along track at nadir) Spectrum region from 0.41 to 14.235 µm Spatial resolution (250m (band 1 - 2), 500m (band 3- 7), 1km (band 8- 36))

5. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 5 PM MAPPER® vs. MODIS product FeaturesPM MAPPER® InputMODIS – Moderate Resolution Imaging Spectroradiometer Output dataAOT Map PM Concentration Map Air Quality Index Map Integrated surface information Output Resolution 3 x 3 km 2 MODIS product MODIS – Moderate Resolution Imaging Spectroradiometer AOT map 10 x 10 km 2 Modules[Modis_Flatfile] SOIL MAPPER® - [Modified Modis_Aerosol] [PM MAPPER] [Modis_Flatfile] [Modis_CloudMask] [Modis_CloudTop] [Modis_Profiles] [Modis_Aerosol]

6. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 6 System Overview AQI Map at 3x3 km 2 Aerosol Optical Thickness retrieval (MODIS algorithm) Particulate Matter (PM) and Air Quality Index (AQI) retrieval Aerosol Over Ocean Algorithm Aerosol Over Land Algorithm (Dense dark vegetation algorithm) PM 2.5 & AOT relationship * US EPA 2006 health quality criteria Ancillary data Coefficient data PM Map at 3x3 km 2 Land/Water/Cloud Classification Preprocessing Flatfile Extraction SOIL MAPPER® MODIS data Lookup tables * Gupta et al., 2006

7. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 77 MODIS data 56 classes AOT over Ocean AOT over Land AQI map PM 2.5 map Integrated AOT

8. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 8 MODIS AOT vs. PM MAPPER® AOT

9. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 9 Land Cover Integration

10. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 10 PM MAPPER® Validation

11. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 11 Validation Objectives –Assess the quality of PM MAPPER® product at 3x3 km 2 spatial resolutions –Assess the performance of PM MAPPER® over different land backgrounds Comparison: MODIS products Data set –Over Italy –6 months (January 2008 – June 2008) –Selection of 15 images (out of the 180 available) Validation Factors –Correlation Coefficient –Number of Retrieved Pixels

12. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 12 PM MAPPER® with 3x3 km 2 resolution Average Correlation Coefficient over Land & Ocean: 0.88 Deviation: 0.78 – 0.95

13. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 13 PM MAPPER® with 3x3 km 2 resolution

14. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 14 PM MAPPER® over different backgrounds Group 1, group 2 : poor statistics on dataset and low correlation Group 3 : bright and dense classes Group 4 : dark, large number of retrieval pixels, and high correlation GroupClasses NumberLabelDarknessAOT PixelsAOT Correlation 114Bright Weak Vegetation000 116Bright Strong Shrub Rangeland000 117Dark Strong Shrub Rangeland000 120Strong Herbaceous Rangeland000 136Dark Barren Land 2000 223Bright Barren Land 10.9894090.38683900 231Average Barren Land 111,4500.53916040 235Dark Barren Land 111020.55672200 228Strong Barren Land 20.9822,7750.67422529 238Dark Barren Land 411910.70847186 27Dark Peat Bogs1990.70906600 227Strong Barren Land 114850.73638586 211Bright Strong Vegetation1760.75544625 215Dark Weak Vegetation0.9891100.83535935 324Bright Barren Land 20.163105,7650.62656844 326Bright Barren Land 40.431345,9170.80878480

15. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 15 PM MAPPER® over different backgrounds GroupClasses NumberLabelDarknessAOT PixelsAOT Correlation 421Average Herbaceous Rangeland117,9850.74601631 432Average Barren Land 20.9996,4360.74735650 450Dark Range Land183,2880.76368429 410Dark Strong Vegetation187,3930.76461758 49Bright Peat Bogs0.9983,8060.78243092 444Wet land0.99613,8290.78631986 441Shadow Barren Land0.9788,9140.79855887 419Dark Average Shrub Rangeland150,5570.80909021 429Strong Barren Land 3152,5050.81401573 440Shadow Vegetation0.92176,1240.81550220 418Bright Average Shrub Rangeland0.999697,6780.81552407 430Strong Barren Land 40.999190,4920.81709721 437Dark Barren Land 31129,0720.82782053 449Strong Barren Land 50.99748,3740.83077167 425Bright Barren Land 30.90841,5690.83334107 448Very Bright Average Vegetation 20.998976,4420.83837347 434Average Barren Land 41206,5570.83893550 48Mid tone Peat Bogs15,2250.84086842 412Bright Average Vegetation11,133,1620.85488120 447Very Bright Average Vegetation 11392,3990.85551107 439Bright Rangeland0.999231,6690.85601407 413Dark Average Vegetation0.999308,4500.86284347 422Mid tone Rangeland1386,8600.87782180 433Average Barren Land 31326,1970.87997400

16. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 16 Conclusion and Future Work

17. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 17 Conclusion PM MAPPER® characteristics –Input: MODIS data –Output: AOT, PM 2.5, PM 10, AQI, Land Cover information –Consistent with MODIS standard products Advantages –Finer spatial resolution –Increase the number of retrieval pixels –Remove the coastline effects –Land cover classes integration

18. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 18 Future works Improve AOT quality on some bright and dark surfaces by statistic approach (data-driven model) Validate PM MAPPER® products in the comparison with ground-based sensors Continue to increase spatial resolution up to 1x1 km 2 Apply our approach for other existing satellite sensors (AATSR) Extend PM MAPPER® to future mission like Sentinel 3

19. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 19 Thank you for your attention

20. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 20 CONTACTS Via Saragat, 9. I-44122, Ferrara, Italy Tel.: +39-0532-1861501 Fax: +39-0532-1861637 info@meeo.itinfo@meeo.it www.meeo.it

21. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 21 MODIS 10 x 10 km 2 PM MAPPER® 3 x 3 km 2 PM MAPPER® with 3 x 3 km 2 resolution Effectively monitoring air pollution at the finer scale (i.e. over urban areas where surface and pollution field are complex). Providing detailed AOT distribution maps to identify emission sources.

22. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 22 Background map Aerosol map Providing background information useful to analyze potential factors affecting the AOT retrieval algorithm. Providing the assessment of AOT retrieval algorithms on different backgrounds, which is valuable for algorithms’ analysis and improvements. PM MAPPER® with background information

23. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 23 MODIS MODerate resolution Imaging Spectroradiometer (MODIS) sensors –On Polar-orbiting satellite: Terra, Aqua –700km altitude, 2330km swath –Measure spectrum region from 0.41 – 14.235 µm MODIS data for PMMAPPER® –8 Bands (depend on characteristics of Aerosol Retrieval Algorithms) –Data Size 1km resolution (1354 x 2030 pixels), 500m resolution, and 250m resolution –Calibration data: Level 1B (L1B)

24. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 24 Aerosol Algorithm over Ocean - Principles Measured radiance = path radiance + ocean surface reflection Physical Factors –Ocean surface reflection Glitter (glitter angle) Foam reflection: –Independent with visible channels –Decrease to 0.8, 0.5, and 0.25 at 1.24, 1.64, and 2.13µm Lambertian Reflectance (Water-leaving radiance): –Affect much on reflectance of 0.47, 0.55, 0.66 µm –Almost un-affected on reflectance of other bands –Atmosphere factors: Cloud contamination: 0.55 µm Dust: 0.47, 0.66 µm Cloudy: 0.47 µm Cirrus cloud: 1.38, 1.24 µm Ocean surface reflection is almost un-affected on some special bands Choosing special bands to eliminate atmosphere factors

25. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 25 Aerosol Algorithm over Ocean - Principles Define Aerosol models –Bi-modal log-normal distribution Present Radiance is detected by satellite Estimate Aerosol models to minimize the quantity Small model Large model Where is single-mode log-normal distribution function

26. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 26 Aerosol Algorithm over Ocean AOT Masking pixel by pixel -Reflectance -Averaged reflectance for the box -Solar zenith angle -Lookup reflectance -Scattering angle Interpolate and calculate associated parameters LUT Associated parameters Aerosol Model Parameters Model Contribution Parameters Optical Thickness -Spatial variability (0.55) -Dust call back (0.47, 0.66) -Cloudy (0.47) -IR test -Cirrus cloud test (1.38, 1.24) -Sediment mask Discard brightest 25% & darkest 25% (0.86) Enough good pixels & condition? 0.47, 0.55, 0.66, 0.86, 1.24, 1.38, 1.64, 2.13µm Derive the optical thickness Estimate Aerosol model (small and large size distribution)

27. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 27 Aerosol Algorithm over Land - Principles Separate path radiance from measured radiance of satellite Conditions –Contribution of ρ * from path radiance is large Shorter wavelengths Low values of surface reflectance (ρ <0.06) –Small uncertainty of path radiance From +-0.005 to +- 0.01 Measured radiancePath radiance Reflection radiance from surface

28. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 28 Aerosol Algorithm over Land - Principles Physical Factors –The scattering & absorption effect dominates to surface reflection on the dark surface (surface reflectance ρ <0.06) –Surface reflectance is correlated to some extent Soil: 0.47, 0.66, 2.1, and 3.8 µm Vegetation: visible channels and IR channels Wet soil: visible channels and 2.1 and 3.8 µm Dark pixels is located by mid-IR (2.1 or 3.8 µm) –Aerosol effect is much smaller in the mid-IR (2.1 µm) than in the visible bands Dark pixels are used to derive Aerosol Red & blue bands are used to AOT derivation

29. This document is proprietary. Any dispatch or disclosure of content is authorized only after written authorization by MEEO S.r.l. 29 Aerosol Algorithm over Land AOT LUT Average Land Reflectance -Detect and delete cloud pixels -Identify dark pixels (2.1µm) -Remove 50% brightest & 20% darkest pixels (0.66µm) 0.47, 0.66, 2.12, 3.8 µm Determine the aerosol model Compute and interpolate the associated parameters Derive non-cloudy AOT from MODIS measured radiances -Continental aerosol -Biomass burning -Industrial/urban aerosol -Dust aerosol Fail 1, change cloud threshold Fail 2 Success LUT -Scattering angle -Lookup Reflectance -Path radiance, slope, error If (dark pixels > 10%), calculate the average reflectance -Spatial variability