Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia

Ground-level ozone (O3) is a secondary pollutant and has an adverse effect on human health, agriculture and ecosystems. The aim of this study is to develop model and to predict future O3concentrations level in Shah Alam for next day (D+1), next two days (D+2) and next three days (D+3) using traditio...

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Published in:Journal of Environmental Science and Technology
Main Author: Muhamad M.; Ul-Saufie A.Z.; Deni S.M.
Format: Article
Language:English
Published: Asian Network for Scientific Information 2015
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930690434&doi=10.3923%2fjest.2015.102.112&partnerID=40&md5=0c5c02ca79d069ac897b79844f3b2873
id 2-s2.0-84930690434
spelling 2-s2.0-84930690434
Muhamad M.; Ul-Saufie A.Z.; Deni S.M.
Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
2015
Journal of Environmental Science and Technology
8
3
10.3923/jest.2015.102.112
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930690434&doi=10.3923%2fjest.2015.102.112&partnerID=40&md5=0c5c02ca79d069ac897b79844f3b2873
Ground-level ozone (O3) is a secondary pollutant and has an adverse effect on human health, agriculture and ecosystems. The aim of this study is to develop model and to predict future O3concentrations level in Shah Alam for next day (D+1), next two days (D+2) and next three days (D+3) using traditional method of Multiple Linear Regression (MLR) based on the concept of Ordinary Least Square estimate (OLS). This study uses daily average data of air pollutants (O3, NOx, NO, SO2, NO2, CO) and meteorological variables (WS, T, RH) that was selected from 2002 until 2013 as independent variables. The performance indicator of the models are measured by accuracy measures (Prediction accuracy, Index agreement and Coefficient of determination) and error measures (Root mean square error, Normalized absolute value). The average accuracy measures (AI, PA and R2) show that the prediction for D+1, D+2 and D+3 is 0.4492, 0.3797 and 0.304 respectively. Meanwhile, the average error measures (RMSE, NAE) show that the prediction for D+1, D+2 and D+3 is 0.1453, 0.1374 and 0.1302, respectively. © 2015 Asian Network for Scientific Information.
Asian Network for Scientific Information
19947887
English
Article

author Muhamad M.; Ul-Saufie A.Z.; Deni S.M.
spellingShingle Muhamad M.; Ul-Saufie A.Z.; Deni S.M.
Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
author_facet Muhamad M.; Ul-Saufie A.Z.; Deni S.M.
author_sort Muhamad M.; Ul-Saufie A.Z.; Deni S.M.
title Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
title_short Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
title_full Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
title_fullStr Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
title_full_unstemmed Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
title_sort Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in malaysia
publishDate 2015
container_title Journal of Environmental Science and Technology
container_volume 8
container_issue 3
doi_str_mv 10.3923/jest.2015.102.112
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930690434&doi=10.3923%2fjest.2015.102.112&partnerID=40&md5=0c5c02ca79d069ac897b79844f3b2873
description Ground-level ozone (O3) is a secondary pollutant and has an adverse effect on human health, agriculture and ecosystems. The aim of this study is to develop model and to predict future O3concentrations level in Shah Alam for next day (D+1), next two days (D+2) and next three days (D+3) using traditional method of Multiple Linear Regression (MLR) based on the concept of Ordinary Least Square estimate (OLS). This study uses daily average data of air pollutants (O3, NOx, NO, SO2, NO2, CO) and meteorological variables (WS, T, RH) that was selected from 2002 until 2013 as independent variables. The performance indicator of the models are measured by accuracy measures (Prediction accuracy, Index agreement and Coefficient of determination) and error measures (Root mean square error, Normalized absolute value). The average accuracy measures (AI, PA and R2) show that the prediction for D+1, D+2 and D+3 is 0.4492, 0.3797 and 0.304 respectively. Meanwhile, the average error measures (RMSE, NAE) show that the prediction for D+1, D+2 and D+3 is 0.1453, 0.1374 and 0.1302, respectively. © 2015 Asian Network for Scientific Information.
publisher Asian Network for Scientific Information
issn 19947887
language English
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