A.M. RAZALI and Ari Pani Desvina, - and M.S. SAPUAN and A. ZAHARIM (2012) Distributional Fit of Carbon Monoxide Data. Advances in Environment, Computational Chemistry and Bioscience . Wseas LLC. ISBN 978-1-61804-147-0

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Abstract

Air pollution is a problem that concerns many of us all over the world and it is a negative side effect of industrial development. Air pollution from cars and factories, in conjunction with a very humid climate, produce a highly corrosive environment. Land transportation provide a significant contribution to half of the total emission of PM 2.5, CO, HC and NOx, where air pollution levels have been exceeded or almost exceeded the ambient air quality standard. This study determine the distributional fit of carbon monoxide (CO) data obtained from Solar Energy Research Institute (SERI), Universiti Kebangsaan Malaysia, Bangi from 16 September 2008 to 16 January 2009. The distribution models used in this study were exponential, gamma, generalized extreme value, lognormal and Weibull distributions. Parameters for all distribution models were estimated by using maximum likelihood method. The goodness of fit of the models were determined by using Kolmogorov-Smirnov and Anderson Darling statistics. The lognormal distribution model was found to fit better than other distribution models. Key-Words: - Statistical distribution models, air pollution, maximum likelihood method, goodness of fit tests.

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