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|Title:||PM₁₀ dispersion in Adelaide and Its relationship with rainfall|
|Other Titles:||PM(10) dispersion in Adelaide and Its relationship with rainfall|
|Citation:||Water, Air, and Soil Pollution, 2015; 226(12):400-1-400-10|
|Mohammad Kamruzzaman, Rupak Aryal, Simon Beecham, Dennis Mulcahy, Andrew. V. Metcalfe, Samantha Slattery, Seoung Soo Lee|
|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 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.|
|Keywords:||Correlogram; generalised least squares; pre-whitened PM10; rainfall; wind rose model|
|Rights:||© Springer International Publishing Switzerland 2015|
|Appears in Collections:||Mathematical Sciences publications|
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