Some Applications of Satellite Remote Sensing for Air Quality: Implications for a Geostationary Constellation Randall Martin, Dalhousie and Harvard-Smithsonian.

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Presentation transcript:

Some Applications of Satellite Remote Sensing for Air Quality: Implications for a Geostationary Constellation Randall Martin, Dalhousie and Harvard-Smithsonian Chulkyu Lee, Aaron van Donkelaar, Lok Lamsal, Dalhousie University National Institute of Meteorological Research (Korea) Nick Krotkov, Ralph Kahn, Rob Levy, NASA Andreas Richter, University of Bremen

Some Air Quality Applications of Satellite Observations Key pollutants: PM 2.5, O 3, NO 2 (AQHI) Top-down Constraints on Emissions (to improve AQ and climate simulations) Smog Alert, Toronto Estimating Surface Concentrations (large regions w/o ground-based obs) Long-Range Transport of Pollution

Encouraging Consistency of Simulated and Measured Profiles Martin et al., JGR, 2004 Texas AQS In Situ GEOS-Chem Lee et al., JGR, 2009 SO 2 NO 2 Optical depth above altitude z Total column optical depth Model (GC) CALIPSO (CAL) Altitude [km] van Donkelaar et al., EHP, 2010 Aerosol Extinction

General Approach to Estimate Surface Concentration Daily Tropospheric Column S → Surface Concentration Ω → Tropospheric column In Situ GEOS-Chem Coincident Model Profile

Promising Ground-Level NO 2 Inferred From OMI for 2005: Need Higher Temporal and Spatial Resolution Temporal Correlation with In Situ Over 2005 Lamsal et al., JGR, 2008 Spatial Correlation of Annual Mean vs In Situ for North America = 0.78 ×  In situ —— OMI

Evaluation with measurements outside Canada/US Global Climatology ( ) of PM 2.5 from MODIS & MISR AOD: Need Higher Temporal and Spatial Resolution Number sitesCorrelationSlopeBias (ug/m 3 ) Including Europe Excluding Europe van Donkelaar et al., EHP, 2010 Evaluation for US/Canada r=0.77 slope=1.07 n=1057

80% of world population exceeds WHO guideline of 10 μg/m 3 30% of eastern Asia exposed to >50 μg/m 3 in annual mean 0.61±0.20 years life lost per 10 μg/m 3 [Pope et al., 2009] Estimate decreased life expectancy due to PM 2.5 exposure Data Valuable to Assess Global PM 2.5 Exposure: Constellation Required for Global High Resolution van Donkelaar et al., EHP, 2010 PM 2.5 Exposure [μg/m 3 ] WHO Guideline AQG IT-3 IT-2 IT Population [%]

Insight into Aerosol Source/Type with Precursor Observations Lee et al., JGR, 2009 Satellite SO 2 data corrected with local air mass factor improves agreement versus aircraft observations (INTEX-A and B) Orig: slope = 1.6, r=0.71 New: slope = 0.95, r=0.92 Improved SO 2 Vertical Columns for 2006 Orig: slope = 1.3, r=0.78 New: slope = 1.1, r=0.89 OMISCIAMACHY

Global Sulfur Emissions Over Land for 2006 Volcanic SO 2 Columns (>10 DU) Excluded From Inversion 47.0 Tg S/yr 54.6 Tg S/yr r = 0.77 vs bottom-up SO 2 Emissions (10 11 molecules cm -2 s -1 ) Chulkyu Lee Top-Down (OMI) Bottom-Up in GEOS-Chem (EDGAR2000, NEI99, EMEP2005, Streets2006) Scaled to Tg S/yr Top-Down (SCIAMACHY) r = 0.78 vs bottom-up

Geostationary Constellation Valuable to Connect Long-Range Transport Events Aaron van Donkelaar

Challenge: Large Inter-retrieval Differences Need for Inter-instrument Calibration and Common Retrievals Tropospheric NO 2 Column (10 15 molecules cm -2 ) SO 2 Slant Columns 2006OMI NO 2 DJF 2005 Lamsal et al., JGR, 2010 AOD τ [unitless ] SP DP MODIS MISR Lee et al., JGR, 2009van Donkelaar et al., EHP, 2010 SCIAMACHY OMI

Challenges Intercalibration of geostationary instruments & retrievals High spatial resolution obs (urban scales, cloud-free, validation) Resolve current inter-retrieval differences New algorithms (i.e. tropospheric residual for geostationary) Boundary-layer ozone (clever retrievals, precursor emissions, assimilation) Continue develop simulation of vertical profile Comprehensive assimilation capability Encouraging Prospects for Satellite Remote Sensing of Air Quality Attributes of Geostationary Constellation Resolves diurnal processes in global-scale analyses (emissions, long-range transport, air quality)