DefinePK

Abstract

Ozone (O3) is one of the strongest atmospheric oxidants and is designated as a criteria pollutant in the atmospheric surface layer. Surface O3 contributes to a number of environmental problem including adverse effects on health, vegetation and materials, as well as climate forcing. Thus it is necessary to gain a good understanding of the characteristics of O3 pollution. In this research, four theoretical distributions namely Weibull, Beta, Lognormal and Inverse Gaussian distribution were used to find the best distribution that can fit the O3 data at Cheras, Selangor. Statistical distribution models are based upon probability and capable of estimating the entire range of pollutant concentration. Probability density functions (pdf) and cumulative distribution functions (cdf) will be used to predict the time of the day with high ozone concentrations and hence can be used as a prediction tool. Parameter estimation for each type of distribution was estimated by using the method of maximum likelihood estimator (MLE). The best distribution was determined using the plots of cumulative distribution functions (cdf) and performance indicator including Root Mean Square Error (RMSE), Prediction Accuracy (PA) and Coefficient of Determination (R2). The results revealed that the best distribution to represent O3 concentration level in Cheras for 2010 is the Beta distribution. Based on the prediction using Beta distribution, it can be concluded that the O3 concentration level in Cheras exceed the Malaysian Ambient Air Quality Guidelines of 0.01 parts per million (ppm).