# Analysis of the Sugarane Biomass Use to Produce Green Hydrogen: Brazilian Case Study
## 1 Introduction
The CO\({}_{2}\) emitted still contributes to atmospheric concentrations, even if it is part of a short-term carbon cycle rather than releasing long-stored fossil carbon. This underscores the need to convert ethanol (C\({}_{2}\)H\({}_{6}\)O) into a fuel whose complete combustion is truly green, meaning it results in no pollutant emissions. In this study, data were collected through a comprehensive analysis and synthesis of technical-scientific articles and reports from relevant funding agencies to ensure a thorough understanding of the challenges and opportunities in green hydrogen production. The data used in this analysis were obtained from the Scopus and Clarivate Analytics Web of Science, focusing on publications from 2019 to 2023 written in English. The choice of this time frame was based on the significant growth in research and development related to green hydrogen during this period, driven by increasing global interest in sustainable energy solutions and advancements in hydrogen production technologies. The search included articles related to the following keywords: green hydrogen, biohydrogen, renewable hydrogen, sustainable hydrogen, sugarcane biomass, and lignocellulosic biomass. A total of 131 articles were retrieved from Scopus and 307 from Clarivate Analytics WoS. After removing duplicates, 335 unique articles remained for analysis. The exclusion criteria included articles published outside the 2019-2023 period, documents not written in English, publications not directly related to the specified keywords, and non-peer-reviewed articles or non-scientific documents such as conference abstracts and book chapters. The R programming language was used to analyze and integrate data from both databases, facilitating the bibliometric analysis of relevant articles  
To ground the research in a practical context, sugarcane production was chosen as a case study, focusing specifically on Brazil's 2023/2024 harvest, with data sourced from the 4 th survey by the National Supply Company (Conab) conducted in April 2024. Additionally, projections for ethanol production were assessed through the national agricultural sector's statistical database, managed jointly by the Organization for Economic Cooperation and Development (OECD) and the United Nations Food and Agriculture Organization (FAO). This methodological approach provides a foundation for exploring the potential of sugarcane biomass within a sustainable framework and identifies viable pathways for reducing carbon emissions associated with hydrogen production. Figure 1 illustrates a comparison of total and per capita sugarcane biomass production among the world's leading producers in 2023, using data from the World Bank and FAO. This visual comparison highlights Brazil's dominance in the field, supporting the selection of the country as the focal point of this study. Figure 1: Comparison of total and per capita sugarcane biomass production among leading producers (2023). Data were sourced from the World Bank and FAO. Brazil was selected as the case study due to its unparalleled leadership in sugarcane production and ethanol output, as well as its significant role in the global renewable energy landscape. With its extensive sugarcane industry and advanced bioenergy infrastructure, Brazil provides an ideal context for exploring the potential of sugarcane biomass in green hydrogen production. Recent studies explored various innovative strategies to enhance the flexibility of green hydrogen production. One proposal involves the development of electrolysis ships capable of traveling to regions with the lowest renewable energy costs worldwide. This mobility would enable the use of affordable electricity for on-site green hydrogen production [14]. Another concept, known as the Hydrogen Deep Ocean Link, was proposed to address challenges such as hydrogen compression, long-term storage, intercontinental transportation, and transit between islands, aiming to reduce associated costs [15].