Publication:
Development of models for forecasting of seasonal ground level ozone (O3)

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dc.citedby1
dc.contributor.authorNapi N.N.L.M.en_US
dc.contributor.authorAbdullah S.en_US
dc.contributor.authorMansor A.A.en_US
dc.contributor.authorAhmed A.N.en_US
dc.contributor.authorIsmail M.en_US
dc.contributor.authorid57224902975en_US
dc.contributor.authorid56509029800en_US
dc.contributor.authorid57211858557en_US
dc.contributor.authorid57214837520en_US
dc.contributor.authorid57210403363en_US
dc.date.accessioned2023-05-29T09:06:30Z
dc.date.available2023-05-29T09:06:30Z
dc.date.issued2021
dc.description.abstractOzone (O3) is a secondary pollutant that releases to the atmosphere through industrial and motor vehicles emission which give an adverse impact, especially on human health. The meteorological factor especially weather condition has influenced the production of O3 concentration in the atmosphere. This study aims to develop O3 forecasting model during different monsoon seasons. The data from the year 2012 until 2014 were acquired including O3, nitrogen oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), sulphur dioxide (SO2), wind speed (WS), ambient temperature (T) and relative humidity (RH) on an hourly basis. The Multiple Linear Regression (MLR) models were developed for the prediction of up to 3 hours in advance. Southwest Monsoon (SWM) was having a higher O3 concentration with a mean value of 0.024 ppm while Inter Monsoon 2 (IM2) was having the lowest concentration of O3, 0.019 ppm. The best fits MLR models for each monsoon were O3,t+1 as compared to O3,t+2 and O3,t+3. The better interpretation and prediction of O3 behaviour during monsoon conditions can help the responsible parties to plan early mitigation measures to address the air pollution problem. � School of Engineering, Taylor�s University.en_US
dc.description.natureFinalen_US
dc.identifier.epage3154
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85111739194
dc.identifier.spage3136
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85111739194&partnerID=40&md5=efdc3d753d423570bdb09f0a4c15d786
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26066
dc.identifier.volume16
dc.publisherTaylor's Universityen_US
dc.sourceScopus
dc.sourcetitleJournal of Engineering Science and Technology
dc.titleDevelopment of models for forecasting of seasonal ground level ozone (O3)en_US
dc.typeArticleen_US
dspace.entity.typePublication
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