PM10 analysis for three industrialized areas using extreme value

One of the concerns of the air pollution studies is to compute the concentrations of one or more pollutants' species in space and time in relation to the independent variables, for instance emissions into the atmosphere, meteorological factors and parameters. One of the most significant statist...

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Published in:Sains Malaysiana
Main Author: Ahmat H.; Yahaya A.S.; Ramli N.A.
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2015
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923863247&doi=10.17576%2fjsm-2015-4402-03&partnerID=40&md5=cd7c8809741f482b6dfaf867c7ac0701
id 2-s2.0-84923863247
spelling 2-s2.0-84923863247
Ahmat H.; Yahaya A.S.; Ramli N.A.
PM10 analysis for three industrialized areas using extreme value
2015
Sains Malaysiana
44
2
10.17576/jsm-2015-4402-03
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923863247&doi=10.17576%2fjsm-2015-4402-03&partnerID=40&md5=cd7c8809741f482b6dfaf867c7ac0701
One of the concerns of the air pollution studies is to compute the concentrations of one or more pollutants' species in space and time in relation to the independent variables, for instance emissions into the atmosphere, meteorological factors and parameters. One of the most significant statistical disciplines developed for the applied sciences and many other disciplines for the last few decades is the extreme value theory (EVT). This study assesses the use of extreme value distributions of the two-parameter Gumbel, two and three-parameter Weibull, Generalized Extreme Value (GEV) and two and three-parameter Generalized Pareto Distribution (GPD) on the maximum concentration of daily PM10 data recorded in the year 2010 - 2012 in Pasir Gudang, Johor; Bukit Rambai, Melaka; and Nilai, Negeri Sembilan. Parameters for all distributions are estimated using the Method of Moments (MOM) and Maximum Likelihood Estimator (MLE). Six performance indicators namely; the accuracy measures which include predictive accuracy (PA), coefficient of determination (R2), Index of Agreement (IA) and error measures that consist of Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Normalized Absolute Error (NAE) are used to find the goodness-of-fit of the distribution. The best distribution is selected based on the highest accuracy measures and the smallest error measures. The results showed that the GEV is the best fit for daily maximum concentration for PM10 for all monitoring stations. The analysis also demonstrates that the estimated numbers of days in which the concentration of PM10 exceeded the Malaysian Ambient Air Quality Guidelines (MAAQG) of 150 mg/m3 are between 1/2 and 1 1/2 days.
Penerbit Universiti Kebangsaan Malaysia
1266039
English
Article
All Open Access; Gold Open Access
author Ahmat H.; Yahaya A.S.; Ramli N.A.
spellingShingle Ahmat H.; Yahaya A.S.; Ramli N.A.
PM10 analysis for three industrialized areas using extreme value
author_facet Ahmat H.; Yahaya A.S.; Ramli N.A.
author_sort Ahmat H.; Yahaya A.S.; Ramli N.A.
title PM10 analysis for three industrialized areas using extreme value
title_short PM10 analysis for three industrialized areas using extreme value
title_full PM10 analysis for three industrialized areas using extreme value
title_fullStr PM10 analysis for three industrialized areas using extreme value
title_full_unstemmed PM10 analysis for three industrialized areas using extreme value
title_sort PM10 analysis for three industrialized areas using extreme value
publishDate 2015
container_title Sains Malaysiana
container_volume 44
container_issue 2
doi_str_mv 10.17576/jsm-2015-4402-03
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923863247&doi=10.17576%2fjsm-2015-4402-03&partnerID=40&md5=cd7c8809741f482b6dfaf867c7ac0701
description One of the concerns of the air pollution studies is to compute the concentrations of one or more pollutants' species in space and time in relation to the independent variables, for instance emissions into the atmosphere, meteorological factors and parameters. One of the most significant statistical disciplines developed for the applied sciences and many other disciplines for the last few decades is the extreme value theory (EVT). This study assesses the use of extreme value distributions of the two-parameter Gumbel, two and three-parameter Weibull, Generalized Extreme Value (GEV) and two and three-parameter Generalized Pareto Distribution (GPD) on the maximum concentration of daily PM10 data recorded in the year 2010 - 2012 in Pasir Gudang, Johor; Bukit Rambai, Melaka; and Nilai, Negeri Sembilan. Parameters for all distributions are estimated using the Method of Moments (MOM) and Maximum Likelihood Estimator (MLE). Six performance indicators namely; the accuracy measures which include predictive accuracy (PA), coefficient of determination (R2), Index of Agreement (IA) and error measures that consist of Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Normalized Absolute Error (NAE) are used to find the goodness-of-fit of the distribution. The best distribution is selected based on the highest accuracy measures and the smallest error measures. The results showed that the GEV is the best fit for daily maximum concentration for PM10 for all monitoring stations. The analysis also demonstrates that the estimated numbers of days in which the concentration of PM10 exceeded the Malaysian Ambient Air Quality Guidelines (MAAQG) of 150 mg/m3 are between 1/2 and 1 1/2 days.
publisher Penerbit Universiti Kebangsaan Malaysia
issn 1266039
language English
format Article
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
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