A new approach to environmental data fusion for integrated assessment of particulate matter loading and its effect on health in the urban environment

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 particulate pollution in the ambient air integrates them into an optimally managed environmental information processing tool. The computational assessment method described in this work permits a detailed spatial characterization of the domain of interest with a view to optimizing air quality management in order to reduce the corresponding adverse health impact. Results from the pilot application of this technique for integrated environmental and health assessment in the urban environment are given.