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Decadal Time Series Analysis of Satellite-Derived PM2.5

This study explores the health impacts of ambient fine particulate matter (PM2.5) exposure using satellite-derived data. It presents spatially coherent regional trends in PM2.5 concentrations and evaluates surface to column relationships. The research utilizes satellite data from MISR and SeaWiFS, along with the GEOS-Chem model, to assess long-term trends and regional components influencing PM2.5 levels.

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Decadal Time Series Analysis of Satellite-Derived PM2.5

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  1. Time Series Analysis of Satellite-Derived PM2.5 Brian Boys, Randall V. Martin, Aaron van Donkelaar, Ryan MacDonell, Nai-Yung C. Hsu* NASA/Goddard Space Flight Ctr*

  2. Negative health outcomes from fine particulate (PM2.5) exposure Increased morbidity and mortality from both acute and chronic exposure to ambient fine particulate matter (PM2.5) ~ 1 year increase of life expectancy for decreasing long-term exposure of PM2.5 by 10 ug/m3

  3. Satellite-derived surface PM2.5: from satellite retrieved column AOD and modeled ‘surface PM2.5/column AOD’ • Satellites used: • MISR on TERRA, Dec 1999 - ? • Designed for multianlge viewing of • aerosols • ~400 km swath width, ~7 day coverage • Model used: • GEOS-Chem (GC) chemical transport model* • Model version 9.01.03 @ 2x2.5 deg horizontal • resolution with MERRA meteorological fields • SeaWiFS on SeaStar, Aug 1997 – Dec 2010 • Designed to measure ocean colour • ~1500 km swath width, ~2 day coverage ‘η’ X www.geos.chem.org*

  4. Spatially coherent regional trends in satellite-derived PM2.5 MISR 2000 - 2011 SeaWiFS 1998 - 2010 2 1 1.5 -2 -1.5 -1 -0.5 0.5 0 Trend [µg m-3 yr-1]

  5. Evaluation of modeled ‘PM2.5 /column AOD’ [η] E. US Chicago PM2.5 [µg m-3] / AOD ηmodel ηinsitu Improving modeled η with region specific Calipso correction factor* JJA DJF Calipso obs. Corr. Fac. van Donkelaar et al, in prep*

  6. Significant trends in satellite-derived PM2.5: MISR MISR 2000-2011 0.1 0.05 MISR P- value 0.01 -1 1 2 -2 1.5 -0.25 -1.5 0.25 0 Trend [µg m-3 yr-1] GEOS-Chem, coinciently sampled with MISR

  7. Significant trends in satellite-derived PM2.5: SeaWiFS SeaWiFS 1998 -2010 0.1 0.05 SeaWiFS P- value 0.01 -1 1 2 -2 1.5 -0.25 -1.5 0.25 0 Trend [µg m-3 yr-1] GEOS-Chem, coincidently sampled with SeaWiFS

  8. Regional average of satellite-derived PM2.5: E. US trend represented by GEOS-Chem secondary inorganics (SI) fraction MISR SeaWiFS PM 2.5 [µg m-3] GEOS- Chem GEOS- Chem GEOS-Chem secondary inorganics GEOS-Chem secondary inorganics

  9. Regional average of satellite-derived PM2.5: P. Gulf trend represented by GEOS-Chem fine dust fraction MISR SeaWiFS PM 2.5 [µg m-3] GEOS- Chem GEOS- Chem GEOS-Chem fine dust GEOS-Chem fine dust

  10. Regional average of satellite-derived PM2.5: India trend represented by GEOS-Chem SI, OC, and BC MISR SeaWiFS GEOS- Chem PM 2.5 [µg m-3] GEOS- Chem GEOS-Chem secondary inorganics GEOS-Chem secondary inorganics GEOS-Chem BC & OC GEOS-Chem BC & OC

  11. Regional average of satellite-derived PM2.5: E. Asia trend represented by GEOS-Chem SI, OC, and BC MISR SeaWiFS GEOS- Chem PM 2.5 [µg m-3] GEOS- Chem GEOS-Chem secondary inorganics GEOS- Chem GEOS-Chem secondary inorganics GEOS-Chem BC & OC GEOS-Chem BC & OC

  12. Comparison of MISR and SeaWiFS: sampling effects E. US P. Gulf MISR MISR SeaWiFS PM2.5 [µg m-3] SeaWiFS GCMISR GCMISR GCSeaWiFS GCSeaWiFS E. Asia India MISR GCMISR MISR SeaWiFS PM2.5 [µg m-3] SeaWiFS GCMISR GCSeaWiFS GCSeaWiFS

  13. Conclusions • Decadal(+) time series of AOD retrieving satellites • Satellite-derived surface PM2.5 concentrations show spatially coherent regional change • Evolution of surface to column relationship important for satellite-derived surface PM estimates • Representation of regional trend components through GEOS-Chem Acknowledgments

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