Multi-parametric optimization of the catalytic pyrolysis of pig hair into bio-oil

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Abstract

The low yield and poor fuel properties of bio-oil have made the pyrolysis production process uneconomic and also limited bio-oil usage. Proper manipulation of key pyrolysis variables is paramount in order to produce high-quality bio-oil that requires less upgrading. In this research, the pyrolysis of pig hair was carried out in a fixed-bed reactor using a calcium oxide catalyst derived from calcination of turtle shells. In the pyrolysis process, the influence of three variables-temperature, heating rate and catalyst weight-on two responses-bio-oil yield and its higher heating value (HHV)-were investigated using Response Surface Methodology. A second-order regression-model equation was obtained for each response. The optimum yield of the bio-oil and its HHV were obtained as 51.03% and 21.87 mJ/kg, respectively, at 545oC, 45.17oC/min and 2.504 g of pyrolysis temperature, heating rate and catalyst weight, respectively. The high R2 values of 0.9859 and 0.9527, respectively, obtained for the bio-oil yield and its HHV models using analysis of variance revealed that the models can adequately predict the bio-oil yield and its HHV from the pyrolysis process.

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Orugba, H. O., Chukwuneke, J. L., Olisakwe, H. C., & Digitemie, I. E. (2021). Multi-parametric optimization of the catalytic pyrolysis of pig hair into bio-oil. Clean Energy, 5(3), 527–535. https://doi.org/10.1093/ce/zkab038

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