Stowell et. al: Estimating PM2.5 in Southern California using satellite data: factors that affect model performance.

In the article, the authors focus on a region where traditional satellite AOD models have not performed as well compared to other areas of the US, in order to determine which region-specific parameters have the highest impact on model accuracy. Using a two-stage linear approach, the authors identified important meteorological and land use parameters including temperature, relative humidity, wind, road distance, distance to coast and other local factors. Of note, a variable representing the ratio of PM2.5 to PM10 particles was included to account for airborne dust. This parameter is not generally used in other regional analyses and was an important addition to the Southern California model, improving accuracy from R2 of 0.70 to 0.80. This study adds significantly to the current body of research in the region of the Southwestern US, suggesting that the influence of PM10 to AOD should be considered in areas with high concentrations of airborne dust.

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