Thermochemical Properties for Valorization of Amazonian Biomass as Fuel

The use of agroforestry residues for energy purposes has long been a reality in Brazil. About 84.8% of the produced electricity comes from renewable resources; vegetable biomass contributes 9.1% to this total. This percentage has the potential to increase if Amazon biomass residues are processed to be used as fuel. The major difficulty for this scenario is the lack of available information on energy properties, mainly the HHVs for Amazon agroforestry biomass types. Considering that there are important deviations in the equations for predicting the HHVs of Amazon biomass types in the literature, the main objective of this work was to propose equations to determine the HHVs of these biomass types using the proximate or ultimate analysis results as input. The methodology adopted to develop such equations was simple and multiple linear regression methods, using experimental results for HHVs and proximate and ultimate analyses for biomass types from the north region of Brazil. Four distinct equations were considered based on ranges from the proximate and ultimate analyses of the biomass types to deliver better results. The obtained equations were validated by application to 28 other biomass types from the same region. The proposed HHV equations presented good agreement between predicted and experimental values, with errors below 5% for equations based on proximate analysis and below 3% for equations based on ultimate analysis.

Automated summary

The use of agroforestry residues for energy purposes in Brazil has been a long-standing reality. However, the lack of available information on energy properties of Amazon biomass types has hindered the potential increase in renewable energy contribution. This study aimed to propose equations to determine the higher heating values (HHVs) of these biomass types using experimental results and analyses. The validation of the proposed equations showed good agreement with experimental values, providing a reliable method for predicting HHVs of Amazon biomass types.