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An optimized policy for the reduction of CO2 emission in the Brazilian Legal Amazon

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  • Caetano, Marco Antonio Leonel
  • Gherardi, Douglas Francisco Marcolino
  • Yoneyama, Takashi

Abstract

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 5×106km2 from which 4×106km2 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 3,708,000km2, demanding a reforestation of 454,037km2. 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.

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  • Caetano, Marco Antonio Leonel & Gherardi, Douglas Francisco Marcolino & Yoneyama, Takashi, 2011. "An optimized policy for the reduction of CO2 emission in the Brazilian Legal Amazon," Ecological Modelling, Elsevier, vol. 222(15), pages 2835-2840.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:15:p:2835-2840
    DOI: 10.1016/j.ecolmodel.2011.05.003
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    4. Caetano, Marco Antonio Leonel & Gherardi, Douglas Francisco Marcolino & Yoneyama, Takashi, 2013. "A constraint satisfaction method applied to the problem of controlling the CO2 emission in the Legal Brazilian Amazon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5322-5329.

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