Use of neural network and multivariate statistics in the assessment of pellets produced from the exploitation of agro-industrial residues

• Published in: Environmental science and pollution research international Vol. 29; no. 47; pp. 71882 - 71893
• Main Authors: Resende, Dieimes Ribeiro, da Silva Araujo, Elesandra, Lorenço, Mário Sérgio, Lira Zidanes, Uasmim, Akira Mori, Fábio, Fernando Trugilho, Paulo, Lúcia Bianchi, Maria
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2022; Springer Nature B.V
• Subjects: Agribusiness; Agricultural wastes; Aquatic Pollution; Artificial neural networks; Atmospheric Protection/Air Quality Control/Air Pollution; Bagasse; Biofuels; Biomass; Calorific value; Charcoal; Clean energy; Coffee; Continuous cropping; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental science; Mathematical models; Multivariate analysis; Multivariate statistical analysis; Neural networks; Pellets; Quality standards; Research Article; Residues; Statistical analysis; Statistical models; Sugarcane; Waste Water Technology; Water Management; Water Pollution Control; Coffee husk; Sustainable pellets; Residual biomass; Charcoal fines; Sugarcane bagasse
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-022-20883-x

The production of pellets from residual biomass generated monocropping by Brazilian agribusiness is an environmentally and economically interesting alternative in view of the growing demand for clean, low-cost, and efficient energy. In this way, pellets were produced with sugarcane bagasse and coffee processing residues, in different proportions with charcoal fines, aiming to improve the energy properties and add value to the residual biomass. The pellets had their properties compared to the commercial quality standard. Artificial neural networks and multivariate statistical models were used to validate the best treatments for biofuel production. The obtained pellets presented the minimum characteristics required by DIN EN 14961–6. However, the sugarcane bagasse biomass distinguished itself for use in energy pellets, more specifically, the treatment with 20% of fine charcoal because of its higher net calorific value (17.85 MJ·kg −1 ) and energy density (13.30 GJ·m −3 ), achieving the characteristics required for type A pellets in commercial standards. The statistical techniques were efficient and grouped the treatments with similar properties, as well as validated the sugarcane biomass mixed with charcoal fines for pellet production. Thus, these results demonstrate that waste charcoal fines mixed with agro-industrial biomass have great potential to integrate the production chain for energy generation. Graphical abstract