Abstract
Socioeconomic-driven processes such as deforestation, forest degradation, forest fires, overgrazing, overharvesting of fuelwood and slash-and-burn practices constitute the primary sources of Greenhouse Gases (GHG) emissions in developing countries. Climate policies can induce the development of clean technology and offer incentives to accelerate reforestation. The Brazilian government has already acknowledged the urgency to invest in policies to reduce anthropogenic CO2 emissions in the Legal Brazilian Amazon (BA). In this work, we propose a scheme to estimate the required investments in clean technology and reforestation to achieve a prescribed short term target value for the atmospheric CO2 emission. Initially, a mathematical model is fitted to the available data to allow forecasting the values of the short term emissions of CO2 under a combination of investments in clean technology and reforestation. The investments to reduce the emissions of CO2 below a target value (400 million tons/year, starting at the initial value of 450) in 3 years’ time are proportional to the regional GDP. Using computer simulation it is possible to generate a range of possible investment values in clean technology and reforestation, so that the prescribed emission reduction is achieved without hindering economic growth. This strategy provides the necessary investment flexibility for the implementation of realistic climate policies.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Physica A: Statistical Mechanics and its Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.