Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add filters








Language
Year range
1.
Braz. arch. biol. technol ; 65: e22210594, 2022. tab, graf
Article in English | LILACS-Express | LILACS | ID: biblio-1364464

ABSTRACT

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.

SELECTION OF CITATIONS
SEARCH DETAIL