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Collection 6 Aerosol Products Becoming Available C6 Aerosol Product Includes: MYD04_L2 Dark Target AOD at 10 km 2 Deep Blue AOD at 10 km 2 Deep-Dark Merged.

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Presentation on theme: "Collection 6 Aerosol Products Becoming Available C6 Aerosol Product Includes: MYD04_L2 Dark Target AOD at 10 km 2 Deep Blue AOD at 10 km 2 Deep-Dark Merged."— Presentation transcript:

1 Collection 6 Aerosol Products Becoming Available C6 Aerosol Product Includes: MYD04_L2 Dark Target AOD at 10 km 2 Deep Blue AOD at 10 km 2 Deep-Dark Merged AOD MYD04_3K Dark Target AOD at 3 km 2

2 Air Quality Applied Sciences Team 6th Semi-Annual Meeting (AQAST 6) January 15-17, 2014 Pawan Gupta 1,2, Rob Levy 2, Shana Mattoo 2,3, and Leigh Munchak 2,3

3 Motivation: Why Urban? PM2.5 pollution levels in many mega cities exceeds the WHO standards by 5 to 10 times. Satellite observed aerosol information has been increasingly in use for air quality monitoring efforts at local to regional to global scales. MODIS Dark Target AOD validation studies have shown a bias over urban areas due to surface assumptions (Oo et al., 2010; Castanho et al., 2007, Munchak et al., 2013, Gupta et al., 2013) Urban areas comprise 0.5% of the Earths surface, but will contain 2/3 of the Earths population by 2025, thus addressing urban bias in AOD is critical for obtaining accurate air quality information from space.

4 City Center Appears as HOT SPOT in MODIS DT AOD New Delhi, India Gupta et al., 2012 Distance (deg) MODIS AOD

5 Mega cities appeared as hot-spots in MODIS AOD images with high gradient from center to outside the city area. Aerosol and Pollution in Mega Cities

6 Land identified as urban by MODIS land cover product at 500 m resolution Percent of pixels identified as urban in same 15 km box around AERONET station Mean bias (MODIS 3 km - AERONET) averaged over the campaign duration at each AERONET location Munchak et al., 2013

7 Levy et al., 2007, 2013 MDT assumes a relationship between the visible (VIS) and shortwave-IR (SWIR) surface reflectance, based on statistics of dark-target (primarily vegetated) surfaces. Surface Characterization in MODIS Dark Target (MDT) Retrieval R VIS = f (R SWIR, Angles, NDVI SWIR ) Over brighter and more variable surfaces (e.g. urban), the assumed VIS/SWIR relationship breaks down (Oo et al., 2010; Castanho et al., 2007)

8 Accounting for Urban Bias Here, we use MODIS Land surface product (MOD09, Vermote et al.) to derive a new VIS/SWIR surface relationship for urban areas where urban % > 20%. VIS/SWIR ratio versus Urban% R VIS = f (R SWIR, Angles, NDVI SWIR, Urban%)

9 Inter- Comparison with AERONET

10 DISCOVER-AQ, Houston 10 km 2 3 km 2

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13 Chicago (0.41±0.14, 0.26±0.09) Washington DC (0.21±0.02, 0.17±0.01) Atlanta (0.18±0.04, 0.15±0.03) C6 vs C6_Urban – Aqua, April 18, 2010 C6, C6_Urban

14 Spring Time Reduction in AOD over Urban Regions

15 Aerosol Retrieval Improvements over Large Urban Corridors of Eastern USA Spring 2010 Philadelphia / New York

16 Washington DC / Baltimore Aerosol Retrieval Improvements over Large Urban Corridors of Eastern USA Spring 2010

17 Atlanta Aerosol Retrieval Improvements over Large Urban Corridors of Eastern USA Spring 2010

18 Implication to Surface PM Air Quality Driving surface PM from column AOD measurements is challenging problem, having more reliable AOD over urban areas will improve PM estimation skills of statistical/physical models MODEL Surface PM Satellite AOD Ancillary Data

19 MODIS land surface reflectance and land cover classification data sets have been used to define a VIS/SWIR surface reflectance relationship to be used over urban surfaces (urban percentage > 20%). The standard C6 MODIS Dark-Target surface reflectance relationship was replaced. Reduced AOD is seen over urban areas. Compared to AERONET observations, these new retrievals remove some of the high bias normally seen over large urban areas. Ongoing/Future Work Evaluating the urban surface relationship over global cities, testing over longer time series. Evaluating Aerosol Models used over Urban Areas in the DTA. Implementing into the MODIS Dark Target Land algorithm? Exploring impacts of new AOD retrieval on regional and global studies of air quality, PM2.5 and health Summary


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