Abstract

The predominant air pollutants in urban cities are (NOx = (NO + NO2), O3 and (OX = (O3 + NO2). This research focused on pollutant variables that cause damage to human health as well as to the environment. Thus, seven statistical models {Weibull (W), Gamma (G), Log-normal (L), Frechet (Fr), Burr(Bur), Rayleigh (R) and Rician (Ri)} were chosen to fit the observations of the air pollutants. An average hourly data from one year to 2015 were considered. In addition, performance indicators {Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE)} were applied, to determine the quality criteria for adjustment of the frequency distributions. The best distribution that adapts to the observations of the variables was the RICIAN distribution, the log-normal distribution for COD. The probabilities of the concentration of exceedances were calculated,(predicted) from the cumulative density function (cdf) obtained from the best fit distributions.

Key words: Statistical analysis; distribution of probability; performance indicators; air pollutants.