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https://hdl.handle.net/2440/103182
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Type: | Journal article |
Title: | PM₁₀ dispersion in Adelaide and Its relationship with rainfall |
Other Titles: | PM(10) dispersion in Adelaide and Its relationship with rainfall |
Author: | Kamruzzaman, M. Aryal, R. Beecham, S. Mulcahy, D. Metcalfe, A. Slattery, S. Lee, S. |
Citation: | Water, Air and Soil Pollution: an international journal of environmental pollution, 2015; 226(12):400-1-400-10 |
Publisher: | Springer |
Issue Date: | 2015 |
ISSN: | 0049-6979 1573-2932 |
Statement of Responsibility: | 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 |
DOI: | 10.1007/s11270-015-2662-5 |
Published version: | http://dx.doi.org/10.1007/s11270-015-2662-5 |
Appears in Collections: | Aurora harvest 7 Mathematical Sciences publications |
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