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Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai

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Main Authors: Norazian, Mohamed Noor, Tan, Cheng Yau, Nor Azam, Ramli, Ahmad Shukri, Yahaya, Noor Faizah Fitri, Md Yusof
Other Authors: norazian@unimap.edu.my
Format: Article
Language:English
Published: AENSI Publications 2016
Subjects:
Exceedences
Particulate matter
Performance indicators
Probability distributions
Return period
Statistical analysis
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41153
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spelling my.unimap-411532016-03-19T04:45:29Z Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai Norazian, Mohamed Noor Tan, Cheng Yau Nor Azam, Ramli Ahmad Shukri, Yahaya Noor Faizah Fitri, Md Yusof norazian@unimap.edu.my Exceedences Particulate matter Performance indicators Probability distributions Return period Statistical analysis Link to publisher's homepage at http://ajbasweb.com In Malaysia, the predominant air pollutants are suspended particulate matter (SPM) and nitrogen dioxide (NO 2). This research focused on PM10 as they may trigger harm to human health as well as environment. Six distributions, namely Weibull, log-normal, gamma, Rayleigh, Gumbel and Frechet were chosen to model the PM10 observations at two industrial areas: Nilai and Shah Alam. One-year period hourly average data for 2006 and 2007 were used in this research. For parameters estimation, method of maximum likelihood estimation (MLE) was selected. Four performance indicators that are mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R 2) and prediction accuracy (PA), were applied to determine the goodness-of-fit criteria of the distributions. The best distribution that fits the PM10 observations was found to be gamma distribution for Nilai whereas for Shah Alam, log-normal distribution is more appropriate. The probabilities of the exceedences concentration were calculated and the return period for the coming year was predicted from the cumulative density function (cdf) obtained from the best-fit distributions. For the 2006 data, Nilai was predicted to exceed 150 μg/m 3 for 2.7 days in 2007 with a return period of one occurrence per 137 days. Shah Alam was predicted to exceed 150 μg/m3 for 5.9 days in 2007 with a return period of one occurrence per 62 days. Both areas do not exceed the MAAQG of 150 μg/m3 based on 2007 data. 2016-03-19T04:42:58Z 2016-03-19T04:42:58Z 2011-12 Article Australian Journal of Basic and Applied Sciences, vol.5 (12), 2011, pages 2796-2811 1991-8178 http://ajbasweb.com http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41153 en AENSI Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Exceedences
Particulate matter
Performance indicators
Probability distributions
Return period
Statistical analysis
spellingShingle Exceedences
Particulate matter
Performance indicators
Probability distributions
Return period
Statistical analysis
Norazian, Mohamed Noor
Tan, Cheng Yau
Nor Azam, Ramli
Ahmad Shukri, Yahaya
Noor Faizah Fitri, Md Yusof
Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai
description Link to publisher's homepage at http://ajbasweb.com
author2 norazian@unimap.edu.my
author_facet norazian@unimap.edu.my
Norazian, Mohamed Noor
Tan, Cheng Yau
Nor Azam, Ramli
Ahmad Shukri, Yahaya
Noor Faizah Fitri, Md Yusof
format Article
author Norazian, Mohamed Noor
Tan, Cheng Yau
Nor Azam, Ramli
Ahmad Shukri, Yahaya
Noor Faizah Fitri, Md Yusof
author_sort Norazian, Mohamed Noor
title Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai
title_short Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai
title_full Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai
title_fullStr Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai
title_full_unstemmed Assessment of various probability distributions to model Pm 10 concentration for industrialized area in peninsula Malaysia: a case study in Shah Alam and Nilai
title_sort assessment of various probability distributions to model pm 10 concentration for industrialized area in peninsula malaysia: a case study in shah alam and nilai
publisher AENSI Publications
publishDate 2016
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41153
_version_ 1643799595656937472
score 13.211869

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