Crédito de Carbono com Prova de Reserva a Partir de Propriedades Rurais como Mecanismo de Mitigação de Emissões Globais em Conformidade com a Regulamentação de Desmatamento-EUDR e Mercados Regulados de Crédito de Carbono

Abstract

The growing urgency of the climate crisis poses significant challenges to the agricultural sector, demanding innovative solutions that reconcile productivity and sustainability. In this context, this thesis aimed to develop and validate an integrated and technologically advanced model for generating carbon credits on Brazilian rural properties, combining cutting-edge technologies with sustainable and regenerative management practices in accordance with regulated market standards, to promote the decarbonization of the economy, the valuation of ecosystem services, and climate justice in the agricultural sector. This thesis was structured in the form of articles. The first article investigated the feasibility of using sensors, artificial intelligence, and blockchain to transform rural properties into positive climate assets, generating traceable and secure carbon credits. The methodology involved analyzing data from four rural properties, focusing on quantifying carbon retention in the soil and biomass. The results demonstrated the accuracy of the technologies employed and the potential of forest and agricultural areas as legitimate sources of carbon credit. The second article aimed to demonstrate the technical and legal feasibility of generating carbon credits on Brazilian rural properties, emphasizing traceability, security, and tokenization of credits. The methodology involved analyzing geospatial data, remote sensing, and applying convolutional neural networks. The results indicated that, with the proper use of emerging technologies and in compliance with legal frameworks, rural properties of different sizes can consolidate themselves as safe and economically viable environmental assets. The third article proposed an integrated model to quantify net negative emissions on rural properties with native forests, aiming to generate carbon credits and promote climate justice. The methodology combined artificial intelligence, georeferenced data, and environmental auditing principles. The results demonstrated that the proposed model can generate carbon credits and promote climate justice, adequately remunerating countries with positive climate performance. In conclusion, this thesis demonstrates the feasibility of an innovative and integrated model for generating carbon credits on Brazilian rural properties, which aligns with regulated market standards. The combination of advanced technologies, sustainable management practices, and the valuation of ecosystem services presents a promising path to promote the decarbonization of the economy, the valorization of the agricultural sector, and climate justice, contributing to a more sustainable and resilient future.