Biomass Identification from Proximate Analysis: Characterization of Residual Vegetable Materials in Andean Areas

Author:

Velázquez Martí Borja1ORCID,Gaibor-Chávez Juan2,Franco Rodríguez John Eloy3ORCID,López Cortés Isabel4ORCID

Affiliation:

1. Departamento de Ingeniería Rural y Agroalimentaria, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain

2. Departamento de Investigación, Centro de Investigación del Ambiente, Grupo de Investigación de la Biomasa, Universidad Estatal de Bolívar, Av. Ernesto Che Guevara, Sector Laguacoto II, Guaranda 020150, Ecuador

3. Facultad de Educación Técnica Para el Desarrollo, Universidad Católica de Santiago de Guayaquil, Av. Carlos Julio de Arosemena km 1.5, Guayaquil 090615, Ecuador

4. Departamento de Producción Vegetal, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain

Abstract

This work was aimed at the characterization of residual generated biomass from pruned tree species present in the Andean areas of Ecuador as a source of energy, both in plantations and in urban areas, as a response to the change in the energy matrix proposed by the Ecuadorian government. From the proximate analysis (volatiles, ashes, and fixed carbon content), elemental analysis (C, H, N, S, O, and Cl), structural analysis (cellulose, lignin, and hemicellulose content), and higher heating value, the studied species were pine (Pinus radiata), cypress (Cupressus macrocarpa), eucalyptus (Eucalyptus globulus), poplar (Populus sp.), arupo (Chionanthus pubescens), alder (Alnus Acuminata), caper spurge (Euphorbia laurifolia), and lime (Sambucus nigra L.) trees. We evaluated the influence of the presence of leaves in the biomass. From this characterization, we developed a method based on obtaining the main components for the identification of the biomass’s species. If the origin of the biomass was unknown, this method enabled us to identify the species, with all its characteristics. If the origin of the biomass was unknown, this innovative method enabled the identification of the species from the lignocellulosic biomass, with all of its characteristics. Finally, we developed regression models that relate the higher heating value to the elemental, proximate, and structural composition.

Publisher

MDPI AG

Subject

Agronomy and Crop Science

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