Kamruzzaman, M.Aryal, R.Beecham, S.Mulcahy, D.Metcalfe, A.Slattery, S.Lee, S.2016-12-182016-12-182015Water, Air and Soil Pollution: an international journal of environmental pollution, 2015; 226(12):400-1-400-100049-69791573-2932http://hdl.handle.net/2440/103182The 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 firstorder 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.en© Springer International Publishing Switzerland 2015Correlogram; generalised least squares; pre-whitened PM10; rainfall; wind rose modelJournal article003004210910.1007/s11270-015-2662-50003654926000122-s2.0-84946601412221348Metcalfe, A. [0000-0002-7680-3577]