Spatio-temporal modelling of ultrafine particle number concentration
Data(s) |
2013
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Resumo |
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. |
Formato |
application/pdf |
Identificador | |
Publicador |
Queensland University of Technology |
Relação |
http://eprints.qut.edu.au/63528/4/Samuel_Clifford_Thesis.pdf Clifford, Sam (2013) Spatio-temporal modelling of ultrafine particle number concentration. PhD by Publication, Queensland University of Technology. |
Direitos |
Copyright 2013 Samuel J. Clifford |
Fonte |
School of Chemistry, Physics & Mechanical Engineering; Institute of Health and Biomedical Innovation; Science & Engineering Faculty |
Palavras-Chave | #aerosols #bayesian statistics #statistics #spatial statistics #semi-parametric regression #air quality #ultrafine particles #time series #spatio-temporal statistics |
Tipo |
Thesis |