Analysis of Ozone Concentrations Using Probability Distributions

Rev Epidemiol Control Infect

Abreu

Júnior

et al. 2021

Self Cite

Justification and Objectives: Brazil lacks consistent epidemiological data on the respiratory morbidity of children and older adults, which makes it difficult to plan and execute effective preventive and health promotion actions. The objective of this study was to analyze the adjustments of distributions (Weibull, Normal, Gamma, Logistic) of historical series of hospitalizations for respiratory diseases (total hospitalizations), from 2011 to 2015, in Campo Grande, Mato Grosso do Sul. Methods: to determine the statistical models, four statistical indicators (coefficient of determination, mean root square error, mean absolute error and mean absolute percentage error) were performed from 2011 to 2015. Parameter estimates are obtained for the models adopted in the study, with and without a regression structure. Results: the results showed that Weibull, Gamma, Normal and Logistic distributions, applied to the series of hospitalizations for respiratory diseases in Campo Grande, were satisfactory in determining the shape and scale parameters, and the statistical indicators R2, MAE, RSME and MAPE confirmed the data goodness-of-fit, and the graphical analysis indicated a satisfactory distribution fit. Conclusion: the analysis of monthly values indicates that Gamma is the best of the four distributions based on those selected. The regression model can be adjusted to the data and used as an alternative distribution that describes the hospitalization data considered in Campo Grande, Brazil.

Section: Model Fitting With Parameter Estimationmentioning

confidence: 90%

Section: Model Fitting With Parameter Estimationmentioning

confidence: 99%

Section: Model Fitting With Parameter Estimationmentioning

confidence: 99%

Section: Model Fitting With Parameter Estimationmentioning

confidence: 99%

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Statistical modeling of hospital admissions for pneumonia in Campo Grande

Rev Epidemiol Control Infect

Abreu

Júnior

et al. 2021

Self Cite

“…By photolysis of molecular oxygen at shorter UV wavelengths, the stratospheric ozone is produced and destroyed by catalytic cycles involving nitrogen (N 2 ), hydrogen (H 2 ), and halogen radicals (Miles et al 2015;Souza et al 2020a). Furthermore, the O 3 has adverse effects on human health and ecosystem productivity (Wang et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Total column ozone (O 3 ) and nitrogen dioxide (NO 2 ) via satellite and their relationship with the burned area and climatic data in biomes of Central-West Brazil

Oliveira‐Júnior

Abreu

et al. 2022

Preprint

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The total column ozone (O3) and nitrogen dioxide (NO2) levels based on the satellite remote sensing for a period from 2005 to 2020 along with air temperature, rainfall and burned area in three biomes (Cerrado, Pantanal, and Atlantic Forest) from Mato Grosso do Sul - Brazil was evaluated. The annual variations of O3 ranged from 260 DU for the Pantanal to 347 DU for the Cerrado. Whereas the NO2 concentrations ranged from 2.95×1015 molecules for the Cerrado to 3.01×1015 molecules for the Atlantic Forest. The differences between NO2 and O3 concentrations on monthly and seasonal time scales, with higher values during the dry period (between July and October). The NO2 and O3 concentrations positively correlated with the burn areas in Pantanal and Cerrado, while the rainfall negatively correlated with these gases’ concentrations in these biomes The first principal component in all biomes is a comparison between rainfall and NO2, O3, a burned area, and air temperature with higher values of eigenvalues for the burned area in Pantanal, followed by Cerrado and Atlantic Forest, indicating more fires in Pantanal. Rainfall showed the highest value in the first principal components (PC). The second component in the Atlantic Forest was a balance between rainfall and air temperature with NO2, O3 and burned area. In the Cerrado and Pantanal, a comparison is made between burned area and NO2, with rainfall, air temperature and O3. There are differences in the behavior of NO2 and O3 concentrations in biomes, driven by different environmental and anthropic variables.

Modeling of the air temperature using the Extreme Value Theory for selected biomes in Mato Grosso do Sul (Brazil)

Reis

Stoch Environ Res Risk Assess

Graf

et al. 2022

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This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007–2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov–Smirnov test, the corrected Akaike criterion AIC c , the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R 2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28–32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes. Supplementary Information The online version contains supplementary material available at 10.1007/s00477-022-02206-1.