ABSTRACT
The current decision support tools must assist in a timely manner the local authorities to adapt proper plans that minimize the resulting ecological and epidemiological impacts in a smart city. The chapter presents an Environmental Decision Support System (EDSS) with web-based GIS capabilities that was developed for the assessment of fine particulate matter (PM2.5) impact in urban areas. It describes the EDSS components including the spatiotemporal analysis tools that present air quality synthetic indicators according to the corresponding geographic location and spatial topologies of the analysed area. A waveletfeed-forward neural network provides the forecasted results. The EDSS integrates an enhancing interpolation mechanism that improves the covering of the city with modeled PM2.5 concentrations. EDSS is able to draw isolines resulted from the interpolation of PM measurements at spatial scale. The cluster analysis for PM distribution allows the classification of the urban areas into six categories of pollution levels based on 2012 US EPA revised breakpoints. Potential exposure to PM is calculated based on the critical hours that are extracted using statistical analysis and filtering techniques. The EDSS estimates the route distance, time spent on the route, exposure levels, and potential inhaled doses for various age categories.
