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Jasper Lewis, Russell De Young, and D. Allen Chu

Abstract

A study of air quality was performed using a compact, aircraft aerosol lidar designed in the Science Directorate at NASA Langley Research Center and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals. Five flights of lidar measurements conducted in the Hampton–Norfolk–Virginia Beach, Virginia, region showed complex regional aerosol distributions. Comparisons with MODIS AOD at 10 km × 10 km and 5 km × 5 km resolutions show good agreement, with correlation R 2 values of 0.82 and 0.88, respectively. Linear regressions of particulate matter with a diameter of less than 2.5 μm (PM2.5) and AOD within the ranges of 5–40 μg m−3 and 0.05–0.7, respectively, result in R 2 values of ∼0.64 and ∼0.82 for MODIS and the Compact Aerosol Lidar, respectively. The linear regressions reflect approximately 51 μg m−3 to 1 AOD. These relationships are in agreement with previous findings for air pollution aerosols in the eastern United States and in northern Italy. However, large vertical variation is seen case by case, with planetary boundary layer heights ranging between 0.7 and 2 km and uncertainties ranging between 0.1 and 0.4 km. The results of the case studies suggest that AOD can be used as an indicator of surface measurements of PM2.5 but with larger uncertainties associated with small aerosol loading (AOD < 0.3).

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Jassim Al-Saadi, James Szykman, R. Bradley Pierce, Chieko Kittaka, Doreen Neil, D. Allen Chu, Lorraine Remer, Liam Gumley, Elaine Prins, Lewis Weinstock, Clinton MacDonald, Richard Wayland, Fred Dimmick, and Jack Fishman

Accurate air quality forecasts can allow for mitigation of the health risks associated with high levels of air pollution. During September 2003, a team of NASA, NOAA, and EPA researchers demonstrated a prototype tool for improving fine particulate matter (PM2.5) air quality forecasts using satellite aerosol observations. Daily forecast products were generated from a near-real-time fusion of multiple input data products, including aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS)/Earth Observing System (EOS) instrument on the NASA Terra satellite, PM2.5 concentration from over 300 state/local/national surface monitoring stations, meteorological fields from the NOAA/NCEP Eta Model, and fire locations from the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) product. The products were disseminated via a Web interface to a small group of forecasters representing state and local air management agencies and the EPA. The MODIS data improved forecaster knowledge of synoptic-scale air pollution events, particularly over oceans and in regions devoid of surface monitors. Forecast trajectories initialized in regions of high AOD offered guidance for identifying potential episodes of poor air quality. The capability of this approach was illustrated with a case study showing that aerosol resulting from wildfires in the northwestern United States and southwestern Canada is transported across the continent to influence air quality in the Great Lakes region a few days later. The timing of this demonstration was selected to help improve the accuracy of the EPA's AIRNow (www.epa.gov/airnow/) next-day PM2.5 air quality index forecast, which began on 1 October 2003. Based on the positive response from air quality managers and forecasters, this prototype was expanded and transitioned to an operational provider during the summer of 2004.

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