Análise do comportamento estatístico das emissões de CO2 no Brasil

Abstract

The Earth's global warming is a global concern. It’s consequences of profound climate changes could lead to unsustainable living conditions on Earth. There are many factors pointed out by the pertinent literature, international bodies, and agreements between countries about the consequences of global warming and that it is necessary to act. The necessary measures to create strategies and solutions for climate change and global warming will be environmentally, socially, and economically more effective and relevant if based on scientific and technical studies. This work is based on data from the Brazilian System of Estimates of Greenhouse Gas Emissions and Removals and aims to apply multivariate data analysis tools to describe the behavior of CO2 emissions in Brazil, considering the main economic activities and the Brazilian states; and use geostatistics tools for analysis and modeling of semivariograms and interpolation by kriging, to describe the spatial variability and make maps of CO2 emission in the state of Minas Gerais. In the multivariate analysis, the hierarchical cluster analysis technique was used with the Euclidean distance and Ward's criterion, considering the federative units as the cluster objects and CO2 emissions from different economic activities as the cluster variables. The cluster analysis identified four groups of states related to the quantity of CO2 emissions in the country, the group comprising the states of Pará and Mato Grosso having the highest volume of emissions in the period analyzed, from 1990 to 2019. In the geostatistical analysis, semivariograms were used to describe the behavior of the spatial variability of CO2 emission in the cities of Minas Gerais and kriging was the interpolation method from which the emission map in the state was generated, resulting in the spatial dependence of emissions with a practical range of 1.86 and 3.00 degrees, and allowing to graphically identify the regions of the state with the highest CO2e emissions. It is expected that the study can contribute to the scientific community and society by jointly promoting programs and solutions to reduce greenhouse gas emissions and, consequently, promote the sustainability and ecological transformation of economic activities, ensuring the reduction of harmful human interference in the environment.