Characteristic and Prediction of Carbon Monoxide Concentration using Time Series Analysis in Selected Urban Area in Malaysia

• Published in: MATEC Web of Conferences
• Main Author: Abdul Hamid H.; Mohd Japeri A.Z.U.-S.; Ahmat H.
• Format: Conference paper
• Language: English
• Published: EDP Sciences 2017
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018548881&doi=10.1051%2fmatecconf%2f201710305001&partnerID=40&md5=6d61061a940d3a21e8c8ca7e7d5abf0e

Carbon monoxide (CO) is a poisonous, colorless, odourless and tasteless gas. The main source of carbon monoxide is from motor vehicles and carbon monoxide levels in residential areas closely reflect the traffic density. Prediction of carbon monoxide is important to give an early warning to sufferer of respiratory problems and also can help the related authorities to be more prepared to prevent and take suitable action to overcome the problem. This research was carried out using secondary data from Department of Environment Malaysia from 2013 to 2014. The main objectives of this research is to understand the characteristic of CO concentration and also to find the most suitable time series model to predict the CO concentration in Bachang, Melaka and Kuala Terengganu. Based on the lowest AIC value and several error measure, the results show that ARMA (1,1) is the most appropriate model to predict CO concentration level in Bachang, Melaka while ARMA (1,2) is the most suitable model with smallest error to predict the CO concentration level for residential area in Kuala Terengganu. © The Authors, published by EDP Sciences, 2017.