Publications by authors named "Givanildo de Gois"

Daily violations of air quality have an impact on urban populations and cause damage to the environment. Thus, the study evaluated the violations of the daily concentrations of SO, NO, and PM, in regions of the State of São Paulo (SSP), based on the National Environment Council (CONAMA) resolution no 491/2018 and the World Health Organization (WHO - World Health Organization. (2016).

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Article Synopsis
  • The study investigates the rainfall dynamics in Northeastern Brazil, focusing on the Metropolitan Region of Maceió, to understand its implications on the urban environment.
  • The research validates the CHELSA rainfall data with local measurements and analyzes trends from 1960 to 2016, finding significant variability and trends influenced by climate patterns like El Niño and La Niña.
  • Results indicate that rainfall changes depend on various factors, and these insights can inform conservation plans in vulnerable socio-environmental areas.
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The objectives of this study are: (i) to evaluate the space-temporal variability of fire foci by environmental satellites, CHIRPS and remote sensing products based on applied statistics, and (ii) to identify the relational pattern between the distribution of fire foci and the environmental, meteorological, and socioeconomic variables in the mesoregions of Minas Gerais (MG) - Brazil. This study used a time series of fire foci from 1998 to 2015 via BDQueimadas. The temporal record of fire foci was evaluated by Mann-Kendall (MK), Pettitt (P), Shapiro-Wilk (SW), and Bartlett (B) tests.

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The objective is to evaluate the fire foci dynamics via environmental satellites and their relationship with socioenvironmental factors and meteorological systems in the state of Alagoas, Brazil. Data considered the period between 2000 and 2017 and was obtained from CPTEC/INPE. Annual and monthly analyzes were performed based on descriptive, exploratory (boxplot) and multivariate statistics analyzes (cluster analysis (CA), principal component analysis (PCA)) and Poisson regression models (based on 2000 and 2010 census data).

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