Abstract

Net CO 2 emissions due to land-use change (LUC) resulting from the conversion of natural forest vegetation in Brazil were analyzed over 25 years (1990-2015). Recognized data sources were studied and emission values were compared. Our analysis included LUC emissions over time, which were stratified by biome. In addition, implications for the fulfillment of commitments assumed by Brazil in the Paris Agreement were discussed. Net LUC greenhouse gas (GHG) emissions from 1990 to 2015 totaled 26GtCO 2 eq. These values were published and updated officially on the National Emissions Registration System. Another renowned source of information regarding Brazil’s GHG emissions is the System for Greenhouse Gas Emissions and Removals Estimates, which is managed by the Climate Observatory. Although this platform uses a different methodology, it displayed total values that were very similar to the official estimates, except for some differences between individual biome emissions. The Food and Agriculture Organization Corporate Statistical Database, which is based on reports of forest resources, reported lower values of about 21GtCO 2 eq, thereby showing significant differences among biomes when compared to the two aforementioned sources. Amazonia was responsible for 65% to 80% of all emissions domestic during the studied period. Considering these reductions and the commitments assumed by Brazil (43% reduction in emissions by 2030), the country is expected to reach its goal and contribute to the Paris Agreement. All three analyzed data sources reported estimates for CO 2 emissions with differences of up to 18%. The Amazon biome contributed the most to emissions over the studied period, regardless of the source. All analyzed reports displayed reductions in LUC CO 2 emissions in Brazil for the last few years of analysis. These results indicate the possibility of Brazil fulfilling the commitments established by the Paris Agreement. The main differences among the methodologies analyzed are due to the vegetation cover mapping approaches.

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