Hidden costs of a typical embodied energy analysis: Brazilian sugarcane ethanol as a case study

Worldwide human production systems are tightly coupled to fossil-based energy, the source of which will not be available at low cost in the foreseeable future. Alternative energy sources are being sought for, among which those derived from biomass are considered to have great potential. Brazilian ethanol sugarcane produced at a large scale is being classified in scientific papers and politics as a renewable energy source. However, only the energy return on investment (EROI) and/or the amount of CO₂ released to atmosphere have been considered as indicators of renewability. This work aims to discuss some theoretical points, within an embodied energy analysis, that make its use inappropriate for answering all issues related to the concept of renewability. Emergy accounting (with an “m”) is used as a comparative tool and the Brazilian sugarcane ethanol is evaluated as case study. An EROI of 6.7 for ethanol was obtained, showing that for each unit of “commercial energy” invested within the process, 6.7 units of another kind of energy is obtained – this index shows an excellent value for energy efficiency, but it does not reflect the renewability of ethanol. On the other hand, emergy accounting shows a renewability index of 19%, indicating a low rating for sugarcane ethanol. All scientific methodologies available to assess potential energy sources have their pros and cons, but the analyst must be aware that each methodology supplies different indicators with different meanings. Energy analysts should use methodologies appropriately, avoiding wider conclusions not actually represented by indices calculated. - Highlights: • The renewability discourse of biofuels is discussed focusing on the Brazilian sugarcane ethanol. • Both energy efficiency and CO₂ emitted hardly indicate the renewability of biofuels. • Emergy evaluation is introduced as a potential tool when assessing renewability. • Analysts must use methodologies accordingly and avoid general conclusions not shown by indicators