The regression analysis of fast pyrolysis product yields and determination of product quality

Abstract

The main objective of this study was to investigate the influence of pyrolysis parameters on product yields with experimental and to evaluate of results with the regression models. For this purpose; hornbeam sawdust was used as a biomass sample in the experiments. Variables investigated were pyrolysis temperature between 300 and 800°C and heating rates between 50 and 700°C/min. The experimental results indicated that a maximum bio-oil yield of 40.4% was obtained at a heating rate of 500°C/min and pyrolysis temperature of 600°C. The experimental results have been analyzed with several linear and nonlinear regression models. As a results; logarithmic+quadratic models with R2(adj.)=80.8 and 91 are the best fit regression models to the bio-char and bio-oil yield as a function of heating rate, respectively. Also, regression models were investigated with bio-oil yield and bio-char yield as a dependent variables and temperature as independent variable. The best fit regression model for the relationship between bio-oil yield and temperature has been identified as quadratic model with R2(adj.)=92.7; while for the relationship between bio-char yield and temperature with the R2(adj.)=92.9 is logarithmic model. The chemical characteristics of the bio-oil and bio-char product were identified by elemental and calorific analyses. The bio-oils were then analyzed using GC/MS technique.