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Title: Using a dynamic exposure model to improve understanding of exposure to urban air pollution
Author: Smith, James David
ISNI:       0000 0004 8505 3098
Awarding Body: King's College London
Current Institution: King's College London (University of London)
Date of Award: 2019
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Epidemiological studies of the negative effects on health of poor air quality are typically based on subjects' residential address. These 'static' methods may be assigning exposure to subjects/populations incorrectly. Possible sources of error include the coarse spatial and temporal scale of the pollutant data, failing to account for lack of movement of the subjects, and not adequately modelling the effects of microenvironments. This PhD takes a large Transport for London (TfL) survey (the 'LTDS') of Londoners daily activities and uses geographical information science techniques to create a detailed model (the 'LTDS-X') of Londoners typical movements including time of day, location and microenvironment. This model is then combined with the Kings version of the Community Multiscale Air Quality model (CMAQ-Urban), which is a multi-pollutant and multi-source high resolution spatial and temporal model of UK air quality. By combining the LTDS-X with CMAQ-Urban and then undertaking further micro-environmental modelling on top of this (in-car, in-train, indoors, the London Underground) detailed exposure estimates to PM2:5 and NO2 for the population of London are calculated and then compared to the 'static' exposure method. Results show that exposure indoors, and whether or not subjects use the London Underground (for PM2:5 exposure), were important determinants of Londoners daily exposure. The PM2:5 exposure modelling for when subjects were on the London Underground was therefore investigated further with a measurement campaign across the network, resulting in a spatial routing model of the network ('TubeAir'). As a stand-alone model this will be useful for future exposure studies in London, and its use was demonstrated on a sample journey. This research concludes by exploring the diffculty of evaluating hybrid exposure models in terms of the representativeness of any exposure calculated, by comparing measured concentrations on a repeated number of cycling journeys with modelled exposures on the same journey.
Supervisor: Barratt, Benjamin Malyon ; Walton, Heather Anne Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available