Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/34088
Title: Space-time modelling of exposure to air pollution using GIS.
Authors: Gulliver, John.
First Published: 2002
Award date: 2002
Abstract: This thesis develops, tests and applies methods for space-time modelling of exposure to air pollution using GIS. This involves linkage of five main sub-models; a traffic model, a model of urban air pollution --- combining local and 'background' pollution models --- a network analysis tool for modelling exposure during journeys, and a time-activity model. The model can provide exposure estimates for individuals or population groups. The study took place entirely within Northampton, UK. The model used to estimate hourly PM10 concentrations at outdoor locations gave a moderate fit to monitored data. Results were shown to be comparable with the best results from other studies. This research also found a strong, linear relationship between concentrations of PM10 during simultaneous monitoring of walking and in-car concentrations. This relationship was used to calibrate modelled outdoor pollution levels to give in-car concentrations. Modelled journey-time exposures for walking performed equally with predictions made using a fixed-site monitor located close to journey routes. The model did not perform as well as the fixed-site monitor in predicting in-car exposures. The application of the model to a walk-to-school policy, in which modelled local traffic levels were reduced by 20%, demonstrated that the benefits of the reduction were not spread evenly across a sample of schoolchildren, but varied depending on the route used to school and the location of homes and schools. For those switching between car and walk there may be positive or negative effects of the policy in terms of savings in average hourly exposures, depending on their specific journey and time activity patterns. The results from this research showed that, although the model worked reasonably well in estimating exposures, a number of improvements are needed. These include better models of background concentrations, more detailed models of in-car conditions, and extending exposure modelling to include dose-response estimates.
Links: http://hdl.handle.net/2381/34088
Type: Thesis
Rights: Copyright © the author. All rights reserved.
Appears in Collections:Theses, College of Arts, Humanities & Law
Leicester Theses

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