Modeling of Brazilian Carbon Dioxide Emissions: a Review

• Autor(a) principal: Pedreira,Vitor Neves
• Data de Publicação: 2022
• Outros Autores: Brito,Marcos Lapa, Santos,Luiz Carlos Lobato dos, Simonelli,George
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Archives of Biology and Technology
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132022000100801
• topic: Brazil; Paris Agreement; Greenhouse gases; Emissions modeling

Abstract: Brazil is a signatory to the Paris Agreement and aims to reduce 43% of CO2 emissions by 2030, compared to 2005. However, changes in energy policies are needed to achieve this goal, evaluating the produced effects on emissions. One way to predict these effects is through mathematical modeling. In this paper, we carried out a literature review to identify the most used model types and independent variables to forecasting Brazilian CO2 emissions. The review showed that gray models and artificial neural networks are the most used ones. Furthermore, we also identified that economic growth and energy consumption are the main independent variables.