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

Time-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 significant impacts on crops and studies conducted revealed that surface ozone is responsible for most of the crop-yield losses from air pollutants. Hence, this study aims to fit 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.