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Analysis of Ozone Concentrations Using Probability Distributions.

Authors :
de Souza, Amaury
Aristone, Flavio
Fernandes, Widinei A.
Oliveira, Ana Paula Garcia
Olaofe, Zaccheus
Abreu, Marcel Carvalho
Junior, José Francisco de Oliveira
Cavazzana, Guilherme
dos Santos, Cicero Manoel
Pobocikova, Ivana
Source :
Ozone: Science & Engineering. Nov-Dec2020, Vol. 42 Issue 6, p539-550. 12p.
Publication Year :
2020

Abstract

This present study aims to evaluate the stratospheric ozone that was continuously measured during 2016 over Campo Grande, the capital of South Mato Grosso state, Brazil. To determine the best-adjusted distribution describing the ozone (O3) co-generation data in Campo Grande, 15 functions were used while modeling the numerical results. Five sets of data were used: the entire year, spring (September to December), summer (December to March, high solar radiation data), autumn (March to June), and winter (June to September, low solar radiation data) to study the seasonal variation in the statistical behavior of the probability distribution functions. The distribution performances are evaluated using three tests of quality, namely Kolmogorov–Smirnov (K-S), Anderson–Darling (A-D), and Chi-square tests. Finally, all the results of the fitted quality tests have been compared. It has been observed that the generalized extreme value distribution provides a good fit all along the year, while for specific seasons the best distributions vary. The best distributions, according to the seasons, are Gamma 3P for the winter, lognormal 3P for spring, Weibull for summer and Gamma 3P for autumn, respectively. There was a coincidence in the probability distribution function adjustment in winter and autumn, period with lower O3 concentrations, kurtosis, and skewness. In the summer and spring, it was observed higher concentrations of O3, kurtosis, and asymmetry and different probability distribution functions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01919512
Volume :
42
Issue :
6
Database :
Academic Search Index
Journal :
Ozone: Science & Engineering
Publication Type :
Academic Journal
Accession number :
147248159
Full Text :
https://doi.org/10.1080/01919512.2020.1736987