Use of satellite-based aerosol optical depth and spatial clustering to predict ambient PM2.5 concentrations.

ABSTRACT: Satellite-based PM(2.5) monitoring has the potential to complement ground PM(2.5) monitoring networks, especially for regions with sparsely distributed monitors. Satellite remote sensing provides data on aerosol optical depth (AOD), which reflects particle abundance in the atmospheric column. Thus AOD has been used in statistical models to predict ground-level PM(2.5) concentrations. However, previous studies have shown that AOD may not be a strong predictor of PM(2.5) ground levels. Another shortcoming of remote sensing is the large number of non-retrieval days (i.e., days without satellite data available) due to clouds and snow- and ice-cover. In this paper we propose statistical approaches to overcome these two shortcomings, thereby making satellite imagery a viable method to estimate P

SUBMITTER: Lee HJ 

PROVIDER: S-EPMC3454441 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature