Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia

The declining of air quality mostly affects the elderly, children, people with asthma, as well as a restriction on outdoor activities. Therefore, there is an importance to provide a statistical modelling to forecast the future values of surface layer ozone (O3) concentration. The objectives of...

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Main Author:	Raffee, Ahmad Fauzi
Format:	Thesis
Language:	English English English
Published:	2021
Subjects:	HD72-88 Economic growth development planning
Online Access:	http://eprints.uthm.edu.my/4002/1/24p%20AHMAD%20FAUZI%20RAFFEE.pdf http://eprints.uthm.edu.my/4002/2/AHMAD%20FAUZI%20RAFFEE%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/4002/3/AHMAD%20FAUZI%20RAFFEE%20WATERMARK.pdf
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id	my-uthm-ep.4002
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spelling	my-uthm-ep.40022022-02-03T02:15:19Z Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia 2021-08 Raffee, Ahmad Fauzi HD72-88 Economic growth, development, planning The declining of air quality mostly affects the elderly, children, people with asthma, as well as a restriction on outdoor activities. Therefore, there is an importance to provide a statistical modelling to forecast the future values of surface layer ozone (O3) concentration. The objectives of this study are to obtain the best multivariate time series (MTS) model and develop an online air quality forecasting system for O3 concentration in Malaysia. The implementations of MTS model improve the recent statistical model on air quality for short-term prediction. Ten air quality monitoring stations situated at four (4) different types of location were selected in this study. The first type is industrial represent by Pasir Gudang, Perai, and Nilai, second type is urban represent by Kuala Terengganu, Kota Bharu, and Alor Setar. The third is suburban located in Banting, Kangar, and Tanjung Malim, also the only background station at Jerantut. The hourly record data from 2010 to 2017 were used to assess the characteristics and behaviour of O3 concentration. Meanwhile, the monthly record data of O3, particulate matter (PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), temperature (T), wind speed (WS), and relative humidity (RH) were used to examine the best MTS models. Three methods of MTS namely vector autoregressive (VAR), vector moving average (VMA), and vector autoregressive moving average (VARMA), has been applied in this study. Based on the performance error, the most appropriate MTS model located in Pasir Gudang, Kota Bharu and Kangar is VAR(1), Kuala Terengganu and Alor Setar for VAR(2), Perai and Nilai for VAR(3), Tanjung Malim for VAR(4) and Banting for VAR(5). Only Jerantut obtained the VMA(2) as the best model. The lowest root mean square error (RMSE) and normalized absolute error is 0.0053 and <0.0001 which is for MTS model in Perai and Kuala Terengganu, respectively. Meanwhile, for mean absolute error (MAE), the lowest is in Banting and Jerantut at 0.0013. The online air quality forecasting system for O3 was successfully developed based on the best MTS models to represent each monitoring station. 2021-08 Thesis http://eprints.uthm.edu.my/4002/ http://eprints.uthm.edu.my/4002/1/24p%20AHMAD%20FAUZI%20RAFFEE.pdf text en public http://eprints.uthm.edu.my/4002/2/AHMAD%20FAUZI%20RAFFEE%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/4002/3/AHMAD%20FAUZI%20RAFFEE%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Awam dan Alam Bina
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	HD72-88 Economic growth development planning
spellingShingle	HD72-88 Economic growth development planning Raffee, Ahmad Fauzi Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia
description	The declining of air quality mostly affects the elderly, children, people with asthma, as well as a restriction on outdoor activities. Therefore, there is an importance to provide a statistical modelling to forecast the future values of surface layer ozone (O3) concentration. The objectives of this study are to obtain the best multivariate time series (MTS) model and develop an online air quality forecasting system for O3 concentration in Malaysia. The implementations of MTS model improve the recent statistical model on air quality for short-term prediction. Ten air quality monitoring stations situated at four (4) different types of location were selected in this study. The first type is industrial represent by Pasir Gudang, Perai, and Nilai, second type is urban represent by Kuala Terengganu, Kota Bharu, and Alor Setar. The third is suburban located in Banting, Kangar, and Tanjung Malim, also the only background station at Jerantut. The hourly record data from 2010 to 2017 were used to assess the characteristics and behaviour of O3 concentration. Meanwhile, the monthly record data of O3, particulate matter (PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), temperature (T), wind speed (WS), and relative humidity (RH) were used to examine the best MTS models. Three methods of MTS namely vector autoregressive (VAR), vector moving average (VMA), and vector autoregressive moving average (VARMA), has been applied in this study. Based on the performance error, the most appropriate MTS model located in Pasir Gudang, Kota Bharu and Kangar is VAR(1), Kuala Terengganu and Alor Setar for VAR(2), Perai and Nilai for VAR(3), Tanjung Malim for VAR(4) and Banting for VAR(5). Only Jerantut obtained the VMA(2) as the best model. The lowest root mean square error (RMSE) and normalized absolute error is 0.0053 and <0.0001 which is for MTS model in Perai and Kuala Terengganu, respectively. Meanwhile, for mean absolute error (MAE), the lowest is in Banting and Jerantut at 0.0013. The online air quality forecasting system for O3 was successfully developed based on the best MTS models to represent each monitoring station.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Raffee, Ahmad Fauzi
author_facet	Raffee, Ahmad Fauzi
author_sort	Raffee, Ahmad Fauzi
title	Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia
title_short	Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia
title_full	Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia
title_fullStr	Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia
title_full_unstemmed	Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia
title_sort	multivariate time series analysis for short-term forecasting of ground level ozone (o3) in malaysia
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Awam dan Alam Bina
publishDate	2021
url	http://eprints.uthm.edu.my/4002/1/24p%20AHMAD%20FAUZI%20RAFFEE.pdf http://eprints.uthm.edu.my/4002/2/AHMAD%20FAUZI%20RAFFEE%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/4002/3/AHMAD%20FAUZI%20RAFFEE%20WATERMARK.pdf
_version_	1747831047730495488

Multivariate time series analysis for short-term forecasting of ground level ozone (O3) in Malaysia

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