Spatial Prediction of Transport Related Urban Air Quality

The aim of this study is to explore the relationship between, transport, land-use and air quality and mapping of air pollutants by means of spatial information sciences, which would provide useful information for decision-makers. Integrated transport, land-use and air quality monitoring are prioritized especially in metropolitan areas. The complexity is straight forward, since data, indicators, variables, methods and approaches vary and isolated. Within the environmental studies, due to reasons of cost and measurement techniques, there exists limited number of sample points. Air quality studies are not exceptions, where sample points are sparse observations. This greatly reduces the availability of appropriate interpolation methods for estimating the total air quality. Geostatistics and multi-variate techniques provide the framework and the tools to build a consistent model for “integrating” information from various sources. Geostatistics introduce useful for up-scaling from the data that have been collected at limited points to provide complete areal coverage where the accuracy of the prediction is known. Air quality measurements namely SO2 and PM obtained at the Istanbul Metropolitan Area between 1994 and 2007 were evaluated via spatial information sciences and results were discussed.