TIME-SERIES ANALYSIS OF GROUND-LEVEL OZONE IN MUDA IRRIGATION SCHEME AREA (MADA), KEDAH.

dc.contributor.authorMARZUKI ISMAIL
dc.date.accessioned2017-10-04T03:20:38Z
dc.date.available2017-10-04T03:20:38Z
dc.date.issued2011
dc.description.abstractTime-series analysis and forecasting has become a major tool in many applications in air pollution and environmental management fields. The forecast of air pollution can be used as warning to the public and for decision makers to establish strategies and measures in cases of high air-pollution levels. It has long been recognised that pollutant gases cause signifcant impacts on crops and studies conducted revealed that surface ozone is responsible for most of the cropyield losses from air pollutants. Hence, this study aims to ft and exemplify time-series analysis in forecasting ozone concentrations in Sungai Petani, a town situated in the Muda Irrigation Scheme Area (MADA), Kedah. In this study, Box-Jenkins methodology was used to build an Autoregressive Integrated Moving Average (ARIMA) model for monthly ozone data from 1999-2007 with a total of 108 readings. Parametric seasonally-adjusted ARIMA (1,0,1)x(2,1,2)12 with constant model was successfully applied to predict the long-term trend of ozone concentration. The detection of a steady statistically-significant upward trend for ozone concentration in Sungai Petani is quite alarming because MADA produces 40% of the total rice production in Malaysia. This is likely due to sources of ozone precursors related to industrial activities from nearby areas and the increase in road-traffic volume.en_US
dc.identifier.issn18238556
dc.identifier.urihttp://hdl.handle.net/123456789/6939
dc.language.isoenen_US
dc.publisherJournal of Sustainability Science and Managementen_US
dc.subjectSurface ozoneen_US
dc.subjecttime-series analysisen_US
dc.subjectARIMAen_US
dc.subjectseasonal variationen_US
dc.subjectMADA areaen_US
dc.titleTIME-SERIES ANALYSIS OF GROUND-LEVEL OZONE IN MUDA IRRIGATION SCHEME AREA (MADA), KEDAH.en_US
dc.typeArticleen_US
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