Spatio-temporal modelling of ultrafine particle number concentration

Clifford, Sam (2013) Spatio-temporal modelling of ultrafine particle number concentration. PhD by Publication, Queensland University of Technology.

Abstract

This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates.

The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.

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142 since deposited on 22 Oct 2013
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ID Code: 63528
Item Type: QUT Thesis (PhD by Publication)
Supervisor: Morawska, Lidia, Mengersen, Kerrie, & Low Choy, Samantha
Keywords: aerosols, bayesian statistics, statistics, spatial statistics, semi-parametric regression, air quality, ultrafine particles, time series, spatio-temporal statistics
Divisions: Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > Institutes > Institute of Health and Biomedical Innovation
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Copyright Owner: Copyright 2013 Samuel J. Clifford
Deposited On: 22 Oct 2013 00:30
Last Modified: 09 Sep 2015 04:03

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