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

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

Ecological Modelling, 2011, vol. 222, issue 15, 2835-2840

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.

Keywords: Carbon emission; Optimal control; Multi-objective control; Optimization; Amazon forest (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380011002614
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:222:y:2011:i:15:p:2835-2840

DOI: 10.1016/j.ecolmodel.2011.05.003

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().