Abstract
Daily monitoring of unhealthy particles suspended in the low troposphere is of major concern around the world, and ground-based measuring stations represent a reliable but still inadequate means for a full spatial coverage assessment. Advances in satellite sensors have provided new datasets and though less precise than insitu observations, they can be combined altogether to enhance the prediction of particulate matter. In this article we evaluate a methodology for automatic multi-variate estimation of PM