Modelagem do setor agropecuário dentro de modelo de análise integrada brasileiro

• Ano de defesa: 2019
• Autor(a) principal: Angelkorte, Gerd Brantes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio de Janeiro; Brasil; Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia; Programa de Pós-Graduação em Planejamento Energético; UFRJ
• Palavras-chave em Português: Modelagem integrada; Uso do solo; Mudanças climáticas; CNPQ::ENGENHARIAS
• Link de acesso: http://hdl.handle.net/11422/13767

The brazilian agricultural sector is one of the largest in the world and presents a great potential for production of low carbon bioenergetics supplies. However, there are concerns with productive means, fertilizers quantities, chemical defensives, water for irrigation and animal use, besides the GHG emissions. The purpose of this study was to improve the current brazilian agricultural modelling inside BLUES, establishing a high level of detail through the creation of new agricultural technologies capable of representing the current state of the sector, enabling the analysis of potential trade-offs between agricultural productivity and energy, hydro and chemical inputs intensities. Three new agricultural technologies were developed (Historic Pattern, High Productivity and Green+), the livestock technologies were updated by integrating data from water for animal use and agriculture food consumption, it was developed new hydro restraints, area for agriculture expansion and organic inputs production. The models were also compared before and after the implementation of the new agricultural module in different scenarios of global warming. It was perceived that the high level of detail was essential for reducing GHG emissions and the use of BECCS, also with the implementation of high productivity technologies, the model identified as advantageous this kind of technology, instead of opening new agriculture frontiers in native forest areas. Moreover, there were significant improvements on SDGS concerning poverty (1), hunger (2), water (6), GHG emissions (13) and land degradation and biodiversity (15).