Thermochemical Properties for Valorization of Amazonian Biomass as Fuel

João Moreira, Alan Carneiro, Diego Oliveira, Fernando Santos, Danielle Guerra (), Manoel Nogueira, Hendrick Rocha, Félix Charvet and Luís Tarelho
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João Moreira: Mechanical Engineering Graduated School, Federal University of Pará, Campus Universitário do Guamá, Belem 66075-110, Brazil
Alan Carneiro: Mechanical Engineering Graduated School, Federal University of Pará, Campus Universitário do Guamá, Belem 66075-110, Brazil
Diego Oliveira: Mechanical Engineering Graduated School, Federal University of Pará, Campus Universitário do Guamá, Belem 66075-110, Brazil
Fernando Santos: Mechanical Engineering Graduated School, Federal University of Pará, Campus Universitário do Guamá, Belem 66075-110, Brazil
Danielle Guerra: Mechanical Engineering Graduated School, Federal University of Pará, Campus Universitário do Guamá, Belem 66075-110, Brazil
Manoel Nogueira: Mechanical Engineering Graduated School, Federal University of Pará, Campus Universitário do Guamá, Belem 66075-110, Brazil
Hendrick Rocha: Mechanical Engineering Graduated School, Federal University of Pará, Campus Universitário do Guamá, Belem 66075-110, Brazil
Félix Charvet: Centre for Environmental and Marine Studies (CESAM), Department of Environment and Planning, University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal
Luís Tarelho: Centre for Environmental and Marine Studies (CESAM), Department of Environment and Planning, University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal

Energies, 2022, vol. 15, issue 19, 1-25

Abstract: 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.

Keywords: Amazonian biomass; proximate analysis; ultimate analysis; HHV equations; linear regression (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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