%0 Journal Article
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@nexthigherunit 8JMKD3MGPCW/3ER446E
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%@resumeid 8JMKD3MGP5W/3C9JGU3
%X The Brazilian government has already acknowledged the importance of investing in the development and application of technologies to reduce or prevent CO2 emissions resulting from human activities in the Legal Brazilian Amazon (BA). The BA corresponds to a total area of 5 × 106 km2 from which 4 × 106 km2 was originally covered by the rain forest. One way to interfere with the net balance of greenhouse gases (GHG) emissions is to increase the forest area to sequester CO2 from the atmosphere. The single most important cause of depletion of the rain forest is cattle ranching. In this work, we present an effective policy to reduce the net balance of CO2 emissions using optimal control theory to obtain a compromising partition of investments in reforestation and promotion of clear technology to achieve a CO2 emission target for 2020. The simulation indicates that a CO2 emission target for 2020 of 376 million tonnes requires an estimated forest area by 2020 of 3,708,000 km2, demanding a reforestation of 454,037 km2. Even though the regional economic growth can foster the necessary political environment for the commitment with optimal emission targets, the reduction of 38.9% of carbon emissions until 2020 proposed by Brazilian government seems too ambitious.
%@mirrorrepository sid.inpe.br/mtc-m19@80/2009/08.21.17.02.53
%8 Aug.
%N 15
%T An Opitimized policy for the reduction of CO2 emission in the Brazilian legal Amazon
%@secondarytype PRE PI
%K Amazon forest, Carbon emission, Multi-objective control, Optimal control, Optimization, Amazon forests, Brazilian Amazon, Carbon emission, Carbon emissions, Cattle ranching, Economic growths, Emission targets, Forest area, Human activities, Multi-objective control, Optimal control theory, Optimal controls, Rain forests.
%@usergroup administrator
%@usergroup banon
%@usergroup secretaria.cpa@dir.inpe.br
%@group DSR-OBT-INPE-MCT-BR
%@group DSR-OBT-INPE-MCT-BR
%@e-mailaddress secretaria.cpa@dir.inpe.br
%3 sdarticle-3.pdf
%@secondarykey INPE--PRE/
%@secondarymark B2_CIÊNCIA_DA_COMPUTAÇÃO A2_CIÊNCIA_DE_ALIMENTOS A1_CIÊNCIAS_AGRÁRIAS_I A1_CIÊNCIAS_BIOLÓGICAS_I B2_CIÊNCIAS_BIOLÓGICAS_II A2_ECOLOGIA_E_MEIO_AMBIENTE B2_ECONOMIA A1_ENGENHARIAS_I A2_ENGENHARIAS_II A2_ENGENHARIAS_III B1_ENGENHARIAS_IV A2_GEOCIÊNCIAS A1_INTERDISCIPLINAR A2_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA
%@issn 0304-3800
%2 sid.inpe.br/mtc-m19/2011/07.13.14.23.26
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation TA, Instituto Tecnológico de Aeronáutica, São José dos Campos, Brazil
%B Ecological Modelling
%@versiontype publisher
%P 2835-2840
%4 sid.inpe.br/mtc-m19/2011/07.13.14.23
%@documentstage not transferred
%D 2011
%V 222
%@doi 10.1016/j.ecolmodel.2011.05.003
%A Caetano, Marco Antonio Leonel,
%A Gherardi, Douglas Francisco Marcolino,
%A Yoneyama, Takashi,
%@dissemination WEBSCI; PORTALCAPES; COMPENDEX.
%@area SRE