Abstract
The aim of this study is to use a range of statistical tools to assess particulate matter less than 10 μm (PM10) in the atmosphere that has been measured daily at five locations in South Australia over a 7-year period. We consider a wind rose model to provide a graphical display of the frequency distribution of wind speed to explore the role of PM10 accumulation over time. A generalised least squares technique with a first-order autoregressive model was applied to the realisation of average changes in PM10, and these were assessed at the 5 % significance level. This study found the change in variability of PM10 concentration over time. The pre-whitened PM10 series were considered as realisations of white noise using correlogram plots. Furthermore, a robust regression technique involving wet (>0.5-mm rainfall) and dry properties (<0.5-mm rainfall) was used to assess the influence of rainfall on PM10 distributions for the city of Adelaide.
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