Drivers and barriers for the carbon market in the context of agribusiness

• Grant number: 23/18128-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2024
• End date: June 30, 2025
• Field of knowledge: Engineering - Production Engineering
• Principal Investigator: Marcelo Seido Nagano
• Grantee: Victor Henrique D'Avila
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Global warming, caused mainly by the emission of Greenhouse Gases (GHG), is one of humanity's main concerns due to its negative environmental, economic, and social consequences. Policies aimed at reducing GHG emissions have been developed, such as the Kyoto Protocol and the Paris Agreement, and many other actions are being developed. In this context, the carbon market has gained increasing prominence, and the agribusiness sector plays a fundamental role, as agribusiness activities are responsible for more than a quarter of global GHG emissions. However, no studies were found that provide an overview of the main drivers and barriers of the carbon market for the agribusiness sector, as most studies address the topic in isolation, thus not providing a general overview of the topic. Therefore, this project aims to identify the drivers and barriers to implementing a carbon market in agribusiness. To this end, a Systematic Literature Review (SLR) will be carried out to survey the state of the art on the topic and the variables that impact this context. After this, a case study will be carried out in agribusiness companies that operate in the carbon market to validate the variables identified in the RSL. It is expected that the results of the project will generate a big picture of the drivers and barriers of the carbon market for the agribusiness sector, facilitating understanding and providing a generalist and reflective view on the topic, contributing to the academic community with articles and for the business community providing a global vision to assist in decision making through the variables involved.