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Monitoring and Modelling of PM 2.5

Monitoring and Modelling of PM 2.5. Aaron van Donkelaar and Randall Martin October 4, 2012. Introduction. Three important questions: How accurate is it? How spatially representative is it? How temporal representative is it?. Three sources of information: Measured

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Monitoring and Modelling of PM 2.5

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  1. Monitoring and Modelling of PM2.5 Aaron van Donkelaar and Randall Martin October 4, 2012

  2. Introduction Three important questions: • How accurate is it? • How spatially representative is it? • How temporal representative is it? Three sources of information: • Measured • Chemical Transport Models • Remote Sensing

  3. Measured observations are essential • Most direct and accurate data source • Essential for validation Network dependent • Data accessibility • Site density • Collection method/standard • Site selection criteria

  4. The SPARTAN network is developing to increase global in-situ coverage • Location Criteria • High population density • Proximity to AERONET (AOD) observations • Uncertainty in PM2.5 concentrations • Strong Potential • Publically available • Globally consistent • Highly relevant for satellite-derived PM2.5

  5. Chemical Transport Models (CTM) allow continuous, global coverage • Year-specific emissions • Dust, sea salt, sulfate-ammonium-nitrate system, organic carbon, black carbon, SOA • Detailed aerosol-oxidant chemistry • Resolution of 100’s x 100’s km • Numerous tracers, 100’s reactions • Assimilated meteorology

  6. CTM accuracy varies by region • Accuracy due to impact of: • Local emission inventories • Regionally relevant chemical reactions • Meteorology • Able to test impact of emissions using case studies Within NA: r =0.87 slope = 1.26 bias = -3.14 μg/m3 Outside NA: r = 0.63 (0.71) slope = 0.51 (0.56) bias = 8.51 (2.75) μg/m3 GEOS-Chem v8-01-04

  7. Satellite retrievals give total aerosol column …but look through the entire atmosphere down to the surface Satellite retrievals rely on the same principles as surface visibility… Beijing Aug 13, 2008PM10 = 12 μg m-3 Loss of contrast Increased reflectance Aug 18, 2008PM10= 278 μg m-3 BBC Gangetic River Valley, India

  8. The aerosol column is related to PM2.5 We relate satellite-basedretrievals of aerosol optical depth(τ) to PM2.5 using a global chemical transport model • MISR • Multi-angle • 4 bands • 6-9 day coverage Estimated PM2.5 = η· τ GEOS-Chem Chemical Transport Model vertical structure ▪ aerosol type ▪ meteorological effects ▪ • MODIS • Single viewpoint • 36 bands • daily coverage van Donkelaar et al. Environ. Health Perspect. 2010 Atmos Environ. 2011 8

  9. Significant agreement with coincident ground measurements over NA Annual Mean PM2.5 [μg/m3] (2001-2006) Satellite Derived Satellite-Derived [μg/m3] In-situ In-situ PM2.5 [μg/m3]

  10. Satellite-derived PM2.5 shows global agreement Outside Canada/US N = 244 (84 non-EU) r = 0.83 (0.83) Slope = 0.86 (0.91) Bias = 1.15 (-2.64) μg/m3 CTM Agreement: r = 0.63 (0.71) slope = 0.51 (0.56) bias = 8.51 (2.75) μg/m3 • Accuracy impacted by • Representation of surface brightness • Simulated aerosol vertical profile • Sampling affected by cloud cover and snow

  11. A Combined PM2.5/NO2 Indicator from Satellite 150 75 0 PM2.5 [μg/m3] PM2.5 Eastern China 15 7.5 0 Shanghai Beijing Delhi Karachi Seoul Cairo Lima Tehran Los Angeles Berlin Moscow Nairobi MPI [unitless] NO2 25 15 5 0 1 2 5 7 9 11 13 15 Satellite-Based Multipollutant Index (Unitless) 0 4 8 12 PM2.5 [μg/m3] MPI *Satellite-based surface NO2 concentrations can be estimated using a CTM to relate the column to surface quantities similar to satellite-derived PM2.5. Moscow 2.5 1.5 0.5 MPI [unitless] Cooper et al., EHP, 2012

  12. Remote sensed, modelled and measured PM2.5 each improve global monitoring Future Work Remote Sensing: Improved algorithms to increase accuracy and resolution Modelling: Develop representation of processes Develop assimilation capability to inform AOD/PM2.5 Measurements: More needed for evaluation throughout the world Acknowledgements Health Canada NSERC NASA

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