Recent studies worldwide have revealed the relation between urban air pollution, particularly fine aerosols, and human health. The current state of the art in air quality assessment, monitoring and management comprises analytical measurements and atmospheric transport modeling. Earth observation from satellites provides an additional information layer through the calculation of synoptic air pollution indicators, such as atmospheric turbidity. Fusion of these data sources with ancillary data, including classification of population vulnerability to the adverse health effects of fine particulate and, especially, PM10 pollution, in the ambient air, integrates them into an optimally managed environmental information processing tool. Several algorithms pertaining to urban air pollution assessment using HSR satellite imagery have been developed and applied to urban sites in Europe such as Athens, Greece, the Po valley in Northern Italy, and Munich, Germany. Implementing these computational procedures on moderate spatial resolution (MSR) satellite data and coupling the result with the output of HSR data processing provides comprehensive and dynamic information on the spatial distribution of PM10 concentration. The result of EO data processing is corrected to account for the relative importance of the signal due to anthropogenic fine particles, concentrated in the lower troposphere. Fusing the corrected maps of PM10 concentration with data on vulnerable population distribution and implementation of epidemiology-derived exposure-response relationships results in the calculation of indices of the public health risk from PM10 concentration in the ambient air. Results from the pilot application of this technique for integrated environmental and health assessment in the urban environment are given.