ANALYSIS OF CARBON DIOXIDE EMISSIONS AND REMOVALS IN BRAZILIAN BIOMES FROM 1990 TO 2023
DOI:
https://doi.org/10.66104/b9sdem73Keywords:
Biomes, Emissions, Removals, Carbon dioxide, Climate changeAbstract
Brazil is covered by six biomes with vast biodiversity, predominantly native vegetation and forest formations. These are: Amazon, Caatinga, Cerrado, Atlantic Forest, Pampa, and Pantanal. Different changes in land use and forests directly influence the increase or decrease of carbon dioxide (CO2). Using CO2 emissions and removals data from 1990 to 2023, available from the SEEG platform (System for Estimating Emissions and Removals of Greenhouse Gases), it was possible to evaluate patterns of behavior of these important measures during this period. For both emissions and removals, the biomes showed, according to the Mann-Kendall test, a significant decreasing trend, despite the fluctuations observed during the period. The Caatinga was the only biome that recorded negative net emissions in some years, implying that removals exceeded emissions. However, it is necessary to highlight the growth in emissions in the most recent years in this biome and the Pantanal. Clustering using the k-means method identified similarities between biomes, isolating the Amazon and grouping the others together. Cerrado and Atlantic Forest were grouped together in one category, and Caatinga, Pampa, and Pantanal together in another for emissions. In the case of removals, Caatinga, Cerrado, and Atlantic Forest formed one group, and Pampa and Pantanal formed a third group. The results offer important insights to guide conservation strategies and more effective public policies in addressing climate change.
Downloads
References
BRITO MORAIS, Ygor Cristiano et al. Análise do Sequestro de Carbono em áreas de Caatinga do Semiárido Pernambucano. Revista Brasileira de Meteorologia, v. 32, p. 585-599, 2017. DOI: https://doi.org/10.1590/0102-7786324007
BUSTAMANTE, M. M. C. et al. Engagement of scientific community and transparency in C accounting: the Brazilian case for anthropogenic greenhouse gas emissions from land use, land-use change and forestry. Environmental Research Letters, v. 13, n. 5, p. 055005, 2018. DOI: 10.1088/1748-9326/aabb37.
HYNDMAN, R. J.; ATHANASOPOULOS, G. Forecasting: Principles and Practice. 3. ed. [S. l.]: OTexts, 2021. Disponível em: https://otexts.com/fpp3/. Acesso em: 15 nov. 2025.
Instituto Brasileiro de Geografia e Estatística. Censo Agropecuário 2017: resultados definitivos. Rio de Janeiro: IBGE, 2019. Disponível em: https://biblioteca.ibge.gov.br. Acesso em: 12 out. 2025.
HAMED, K. H., and RAO, A. R., 1998: A modified Mann–Kendall trend test for autocorrelated data. Journal of Hydrology, Volume 204, Issues 1–4, 1998, Pages 182-196, ISSN 0022-1694, https://doi.org/10.1016/S0022-1694(97)00125-X
MANLY, B. F. J.; ALBERTO, J. A. N. Métodos Estatísticos Multivariados Uma Introdução. 4ª ed. Editora: Bookman. ISBN: 9788582604984, 2019.
MARTINI, A.; PANCIERI, S. D.; TORRES, F. T. P. Análise da fragmentação florestal por meio de métricas da paisagem na região de ecótono entre Cerrado e Mata Atlântica. Geografia UERJ, v. 47, p. 1–20, jan./jun. 2025. DOI: 10.12957/geouerj.2025.84818.
R CORE TEAM. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2025. <https://www.R-project.org/>
SEEG. Nota metodológica SEEG 11: Setor Mudanças de Uso da Terra e Florestas. Versão 2. Brasília: Instituto de Pesquisa Ambiental da Amazônia, 2024. 89 p. Sistema de Estimativas de Emissões e Remoções de Gases de Efeito Estufa (SEEG). Plataforma SEEG: sistema de estimativas de emissões e remoções de gases de efeito estufa. Base de dados online. Disponível em: https://plataforma.seeg.eco.br/. Acesso em: 20 out. 2025.
SILGE, J. widyr: Tidy Tools for Pairwise Distances in R. [S. l.]: widyr, 2023. Disponível em: https://juliasilge.github.io/widyr/. Acesso em: 12 jan. 2026.
Organização das Nações Unidas. Transformando nosso mundo: a Agenda 2030 para o desenvolvimento sustentável. Nova Iorque: ONU, 2015.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Bruna Naiure de Santana Souza, Mauricio Santana Lordêlo
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish in this journal agree to the following terms:
Authors retain copyright and grant the journal the right of first publication, with the work simultaneously licensed under the Creative Commons Attribution License, which permits the sharing of the work with proper acknowledgment of authorship and initial publication in this journal;
Authors are authorized to enter into separate, additional agreements for the non-exclusive distribution of the version of the work published in this journal (e.g., posting in an institutional repository or publishing it as a book chapter), provided that authorship and initial publication in this journal are properly acknowledged, and that the work is adapted to the template of the respective repository;
Authors are permitted and encouraged to post and distribute their work online (e.g., in institutional repositories or on their personal websites) at any point before or during the editorial process, as this may lead to productive exchanges and increase the impact and citation of the published work (see The Effect of Open Access);
Authors are responsible for correctly providing their personal information, including name, keywords, abstracts, and other relevant data, thereby defining how they wish to be cited. The journal’s editorial board is not responsible for any errors or inconsistencies in these records.
PRIVACY POLICY
The names and email addresses provided to this journal will be used exclusively for the purposes of this publication and will not be made available for any other purpose or to third parties.
Note: All content of the work is the sole responsibility of the author and the advisor.
