Sustainable production of bio-oil from doum shell waste: effect of temperature, catalyst, and co-pyrolysis
摘要
The current study presents an innovative approach to biofuel production by investigating the pyrolysis of doum (Hyphaene thebaica) shell, an underutilized biomass waste, under thermal, catalyst, and co-pyrolysis conditions. Unlike previous studies that primarily focus on conventional biomass sources or plastic waste co-pyrolysis, this research explores the unique co-pyrolysis of doum shell with liquid reed black liquor, an industrial lignin-rich by-product, presenting a novel pathway for improving the quality and yield of bio-oil. Pyrolysis was conducted using a fixed-bed reactor at temperatures of 400, 450, and 550°C. Catalytic pyrolysis used bentonite clay, as a natural catalyst, at loadings of 10, 20, and 30%. Co-pyrolysis of doum shell with black liquor was investigated at blending ratios of 10, 30, and 50%. The obtained results indicated that increasing temperature increased bio-oil yield from 16 to 20% with an enhancement of 25%. The catalyst pyrolysis increased bio-oil yield from 20 to 26% with an increase of 30% at a mass ratio of 20%. The co-pyrolysis of doum shell increased bio-oil yield by 38, 48, and 44% for mass ratios of 10, 30, and 50%, respectively, with a maximum increase of 140% compared to thermal pyrolysis. The catalyst and co-pyrolysis increased the heating value of bio-oil by 15.34% and 25% and decreased oxygen content by 59.8 and 89.6%, respectively, markedly enhancing the quality of bio-oil. A machine learning optimization study using random forest regression predicted the maximum bio-oil yield of 49.72%, which can be achieved under optimal conditions of 450 °C, 15% catalyst, and 25% black liquor, with high model accuracy (R2 = 99%). This study contributes to the sustainable valorization of doum shell waste in combination with natural catalysts and industrial waste, offering an energy-efficient and scalable pathway for renewable biofuel production. It also provides crucial insights into waste management and data-driven optimization for the next-generation of biomass pyrolysis systems.