MULTIVARIATE TECHNIQUES APPLIED TO EVALUATION OF LIGNOCELLULOSIC RESIDUES FOR BIOENERGY PRODUCTION
DOI:
https://doi.org/10.5902/1980509812361Keywords:
multivariate analysis, biomass, energy.Abstract
http://dx.doi.org/10.5902/1980509812361
The evaluation of lignocellulosic wastes for bioenergy production demands to consider several characteristicsand properties that may be correlated. This fact demands the use of various multivariate analysis techniquesthat allow the evaluation of relevant energetic factors. This work aimed to apply cluster analysis and principalcomponents analyses for the selection and evaluation of lignocellulosic wastes for bioenergy production.8 types of residual biomass were used, whose the elemental components (C, H, O, N, S) content, lignin, totalextractives and ashes contents, basic density and higher and lower heating values were determined. Bothmultivariate techniques applied for evaluation and selection of lignocellulosic wastes were efficient andsimilarities were observed between the biomass groups formed by them. Through the interpretation of thefirst principal component obtained, it was possible to create a global development index for the evaluationof the viability of energetic uses of biomass. The interpretation of the second principal component alloweda contrast between nitrogen and sulfur contents with oxygen content.
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References
AKKAYA, A. V. Proximate analysis based multiple regression models for higher heating value estimation of low rank coals. Fuel Processing Technology, v. 90, n. 2, p. 165–170, 2009.
ALVARENGA, M. I. N.; DAVIDE, A. C. Características físicas e químicas de um Latossolo Vermelho-Escuro e a sustentabilidade de agroecossistemas. Revista Brasileira de Ciência do Solo, v. 23, p. 933-942, 1999.
ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 8633: Carvão Vegetal – determinação do poder calorífico. Rio de Janeiro, Brasil, 1984.
ASSOCIAÇÃO BRASILEIRA TÉCNICA DE CELULOSE E PAPEL. M11/77: teor de cinzas. São Paulo, 1974a. 8 p.
ASSOCIAÇÃO BRASILEIRA TÉCNICA DE CELULOSE E PAPEL. M3/69: Métodos de ensaio. São Paulo, Brasil, 1974b. 8p.
ASSOCIAÇÃO BRASILEIRA TÉCNICA DE CELULOSE E PAPEL. M70/71: Métodos de ensaio. São Paulo, Brasil, 1974c. 8p.
AZZINI, A.; SALGADO, A. L. B.; TEIXEIRA, J. P. F. Curva de maturação da Crotalarea juncea L. em função da densidade do caule. Bragantia, v. 40, n. 1, p. 1-10, 1981.
BECH, N.; JENSEN, P. A.; DAM-JOHANSEN, K. Determining the elemental composition of fuels by bomb calorimetry and the inverse correlation of HHV with elemental composition. Biomass and Bioenergy, v. 33, n. 3, p. 534 – 537, 2009.
BILGEN, S.; KAYGUSUZ, K. The calculation of the chemical exergies of coal-based fuels by using the higher heating values. Applied Energy, v. 85, n. 8, p. 776 –785, 2008.
BRAND, M. A. Energia de biomassa florestal. Rio de Janeiro: Interciência, 2010. 131 p.
CAIXETA, R. P. et al. Propriedades e classificação da madeira aplicadas à seleção de genótipos de Eucalyptus. Revista Árvore, v. 27, n. 1, p. 43-51, 2003.
CORDERO, T. et al. Predicting heating values of lignocellulosics and carbonaceous materials from proximate analysis. Fuel, v. 80, n. 1, p. 1567-157, 2001.
DEMIRBAS, A. Relationships between lignin contents and heating values of biomass. Energy Conversion and Management, v. 42, n. 2, p. 183-188, 2001.
DEMIRBAS, A; DEMIRBAS, H. A. Estimating the calorific values of lignocellulosic fuels. Journal Energy, Exploration & Exploitation, v. 20, n. 1, p. 105-111, 2004.
EROL, M.; HAYKIRI-ACMA H.; KUÇUKBAYRAK, S. Calorific value estimation of biomass from their proximate analyses data. Renewable Energy, Oxford, v. 35, n. 1, p. 170–173, 2010.
FERREIRA, D. F. Estatística Multivariada. 1. ed. Lavras: UFLA, 2008. 662 p.
FRIEDL, A. et al. Prediction of heating values of biomass fuel from elemental composition. Analytica Chimica Acta, v. 544, n. 1-2, p. 191–198, 2005.
GANI, A.; NARUSE, I. Effect of cellulose and lignin content on pyrolysis and combustion characteristics for several types of biomass. Renewable Energy, Oxford, v. 32, n. 4, p. 649-661, 2007.
GÓMEZ, C. J. et al. Thermogravimetry/mass spectrometry study of woody residues and an herbaceous biomass crop using PCA techniques. Journal. Anaytical Applied Pyrolysis, v. 80, n. 2, p. 416–426, 2007.
HAIR JR., J. F. et al. Análise multivariada de dados. 6. ed. Porto Alegre: Bookman, 2009. 688 p.
HUANG, C. et al. Ultimate analysis and heating value prediction of straw by near infrared spectroscopy. Waste Management, v. 29, n. 6, p.1793–1797, 2009.
JOHNSON, R. A; WICHERN, D. W. Applied multivariate statistical analysis. New Jersey: Prentice-Hall, 1992. 607 p.
KENT, M.; COKER, P. Vegetation description and analysis. Baffins Lane, John Wiley & Sons, 1992. 363 p.
KUMAR, R. et al.. Effect of tree-age on calorific value and other fuel properties of Eucalyptus hybrid. Journal of Forestry Research, v. 21, n. 4, p.514 – 516, 2010.
KUMAR, M.; GUPTA, R. C.; SHARMA, T. Effect of carbonisation conditions on the yield and chemical composition of Acacia and Eucalyptus wood chars. Biomass and Bioenergy, v. 3, n. 3, p. 411– 417, 1992.
MAJUMDER, A. K. et al. Development of a new proximate analysis based correlation to predict calorific value of coal. Fuel, v. 87, n. 13-14, p. 3077-3081, 2008.
MARRIOTT, F. H. C. The interpretation of multiple observation. New York: Academic Press, 1974. 117 p.
MINGOTI, S. A. Análise de dados através de métodos de estatística multivariada: uma abordagem aplicada. Belo Horizonte: UFMG, 2005. 297 p.
MINISTÉRIO DE MINAS E ENERGIA. Disponível em: http://www.mme. gov.br/mme/menu/todas_publicacoes.html . Acesso em 15 de Setembro de 2010.
NORDIN, A. Chemical and elemental characteristics of biomass fuels. Biomass and Bioenergy, v. 6, n. 5, p. 339–347, 1994.
PARIKH, J.; CHANNIWALA, S. A.; GHOSAL, G. K. A correlation for calculating HHV from proximate analysis of solid fuels. Fuel, v. 84, n. 5, p. 487–494, 2005.
PAULA, L. E. R. et al. Characterization of residues from plant biomass for use in energy generation. Cerne, Lavras, v. 17, n. 2, p. 237-246, 2011.
PIMENTEL-GOMES, F. Curso de estatística experimental. 15. ed. Piracicaba: FEALQ, 2009. 451 p.
PROTÁSIO, T. P. et al. Relação entre o poder calorífico superior e os componentes elementares e minerais da biomassa vegetal. Pesquisa Florestal Brasileira, Colombo, v. 31, n. 66, p. 122 -133, 2011. DOI: 10.4336/2011.pfb.31.66.113
R DEVELOPMENT CORE TEAM. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Disponível em: <http://www.R-project.org>. Acesso em 10 de Dezembro de 2010.
SHAFIZADEH, F. Basic principles of direct combustion. In: Sofer SS, Zabrosky OR (ed.). Biomass conversion process for energy and fuels. New York: Plenum Press, 1981. p. 103–112.
SHENG, C.; AZEVEDO , J. L. T. Estimating the higher heating value of biomass fuels from basic analysis data. Biomass and Bioenergy, v. 28, n. 5, p. 499-507, 2005.
TELMO, C.; LOUSADA, J. Heating values of wood pellets from different species. Biomass and Bioenergy, v. 35, n. 7, p. 2634-2639, 2011.
