Abstract: Air quality in developed areas is being increasingly compromised by the effect of urbanization, which is favouring the presence of atmospheric pollutants derived from human-induced activities. Land cover change is one of the consequences most closely associated with urbanization, leading to a growing presence of dark built-up surfaces. The target of this investigation was to model the Catalonian Air Quality Index (CAQI) from the combined effect of the surface reflectance capacity of urban surfaces with solar radiation and elevation. Geoprocessing tools were used to produce the information required to characterise these variables in the buffer areas surrounding 75 different air quality monitoring stations located across the region. Cluster analysis and Multiple Linear Regression (MLR) were applied to group these stations according to their similarity and replicate the annual mean values of CAQI recorded in Catalonia in 2011, respectively. Finally, discriminant analysis enabled assigning ungauged areas to the cluster and MLR model that best fitted their solar radiation, surface reflectance and elevation features. The implementation of this approach resulted in highly accurate predictions of CAQI, providing a mechanism of identification of areas having a number of days with poor air quality during the year. Since these areas were related to the presence of land cover types with high sunlight absorption, the proposed methodology was suggested to support the adoption of measures aimed at controlling urban air pollution based on replacing built-up surfaces by green infrastructure.

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