Satellite Measurements to Enhance PM2.5 Air Quality Measurements

Particulate air quality monitoring is traditionally done by point surface measurements. Satellite measurements of aerosol properties have the potential to augment surface measurements. They can provide better spatial coverage to see pollutant levels in remote and non-monitored areas, track pollution transport, validate and guide models prediction, suggest the placement of future surface sensors, and provide another metric in epidemiological studies. The problem in implementation is that correlations between surface PM2.5 measurements and satellite aerosol optical depth measurements show a great deal of variation, between 0.2 and 0.98 depending on the season and location or region of comparison. In some cases, notably in the western US, there is little or no correlation (1, 2) using simple linear regression to match AOD to PM. Our group at NASA Ames has developed methods to improve these correlations by employing generalized additive models (GAMs). Our methodology is also unique because it uses only remote observations from several satellites to improve the correlation. The method has resulted in improvements in correlation coefficients between surface PM2.5 and satellite-derived PM2.5 in the Fresno area from 0.4 for a linear model to 0.73. Results for the Bakersfield site were even more dramatic, with correlation coefficients increasing from 0.1 with the linear model to 0.8 with the GAM. This presentation will discuss the methodology, results, limitations and potential future applications. References 1. J. Al-Saadi et al., Bull. Amer, Met. Soc., 1249 (2005). 2. J. A. Engle-Cox, C. H. Holloman, B. W. Coutant, R. M. Hoff, Atmos. En. 38, 2495 (2004).