A GIS approach to modelling traffic related air pollution
There is increased concern regarding the effect of traffic related pollution on public heath. As the number of vehicles on the roads continues to rise, it is becoming increasingly more important to identify areas where the population may be at a greater risk to raised levels of pollution and areas where the implementation of policy to control and monitor levels of pollution would be beneficial. Traditionally, levels of air pollution have been established through dispersion modelling or monitoring. However, for modelling traffic related pollution for large populations, these methods have proved inappropriate. Three new approaches have been developed to model traffic related air pollution and are reported in this thesis. The approaches have been developed in a Geographical Information System (GIS) and involve generating detailed maps of the pollution surface from monitored data and information about the pollution sources. The new methods are compared against the geostatistical technique kriging. The first approach combines spatial interpolation from monitoring sites and dispersion modelling, linking the dispersion model to the GIS, the second combines GIS techniques for filtering data and spatial interpolation, and the third uses a combination of GIS techniques for filtering and statistical techniques. The three approaches are tested and validated by predicting levels of pollution at monitoring sites not used to develop the models. It was found that the new approaches provided more reliable estimates of pollution at unsampled locations than kriging, with the last of these proving to be the most effective. The adjusted r2 values for kriging, interpolation and dispersion, interpolation and filtering, and filtering and statistics were found to be 0.44, 0.63, 0.67 and 0.82 respectively. The approaches therefore have clear potential in the areas of air pollution management and epidemiology, where the maps can be used to help identify locations where levels of pollution exceed air quality standards, assess the relationship between air pollution and health outcome and examine the risk of exposure to raised levels of pollution.