EXTREME VALUE ANALYSIS OF CARBON MONOXIDE (CO) CONCENTRATIONS IN AKURE CITY CENTRE

Abstract

This study uses extreme value theory (EVT) to assess the use of extreme value distributions of the Gumbel and Generalized Extreme value (GEV) models on the maximum quarter-hour, half-hour, one-hour and eight-hour average of concentrations of carbon monoxide (CO) data, measured between February 2009 and February 2010 in Akure, Ondo State, Nigeria. CO was measuredusing Lascar EL-USB-CO portable data logger with a sampling frequency of 30 seconds, installed above head height on a lamp post in the middle of the road at Oja-Oba on Oba Adesida road. Data analysis was achieved using the Extreme Package in the R statistical software. Parameters for all the distributions are estimated using the Maximum Likelihood Estimator (MLE). Performance indicators namely: the coefficient of variation and Root Mean Square Error (RMSE), are used to find thegoodness-of-fit of the distributions. The best distribution is selected based on the coefficient of variation and the smallest error measures. The results showed that the GEV is the best fit for quarter-hour, half-hour, one-hour maximum concentrations, while Gumbel was best for eight-hour maximum concentration. The result of this study suggests that extreme value theory is a useful tool for urban air quality management decision making.