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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578675
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dc.contributor.authorShaadan N (UITM)
dc.contributor.authorDeni S. M (UITM)
dc.contributor.authorJemain A. A (UKM)
dc.date.accessioned2023-11-06T03:05:36Z-
dc.date.available2023-11-06T03:05:36Z-
dc.date.issued2018-01
dc.identifier.issn0128-7680
dc.identifier.otherukmvital:116119
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578675-
dc.descriptionInformation on situation of air pollution is critically needed as input in four disciplines of research including risk management, risk evaluation, environmental epidemiology, as well as for status and trend analysis. Two normal practices were identified to evaluate daily air pollution situation; first, pollution magnitude has been treated as the common indicator, and second, the analysis was often conducted based on hourly average data. However, the information on the magnitude level alone to represent the pollution condition based on a rigid point data such as the average was seen as insufficient. Thus, to fill the gap, this study was conducted based on continuously measured data in the form of curves, which is also known as functional data, whereby pollution duration is emphasised. A statistical method based on curve ranking was used in the investigation. The application of the method at Klang, Petaling Jaya and Shah Alam air quality monitoring stations located in the Klang Valley, Malaysia, has shown that pollution duration decreases as the magnitude increases. Shah Alam has the longest pollution duration at low and medium magnitude levels. Meanwhile, all the three stations experienced quite a similar length of average pollution duration for the high magnitude level, that is, about 2.5 days. It was also shown that the occurrence of PM10 pollution at the area is significantly not random.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journals
dc.relation.urihttp://www.pertanika.upm.edu.my/regular_issues.php?jtype=2&journal=JST-26-1-1
dc.rightsUKM
dc.subjectAir pollution
dc.subjectFunctional data analysis
dc.subjectPM10
dc.subjectCurve ranking
dc.subjectMalaysia
dc.titleInvestigating the randomness and duration of pm10 pollution using functional data analysis
dc.typeJournal Article
dc.format.volume26
dc.format.pages299-308
dc.format.issue1
Appears in Collections:Journal Content Pages/ Kandungan Halaman Jurnal

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