Probability distributions assessment for modeling gas concentration in Campo Grande, MS, Brazil

Amaury de Souza, Zaccheus Olaofe Olaofe, Shiva Prashanth Kumar Kodicherla, Priscilla Ikefuti, Luciana Nobrega, Ismail Sabbah

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.


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DOI: http://dx.doi.org/10.17628/ecb.2017.6.569-578

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