Biochar yield prediction using response surface methodology: effect of fixed carbon and pyrolysis operating conditions

Generating value from wastes via pyrolysis has been increasingly researched in recent times. Biochar is a versatile pyrolysis product with yields based on many process parameters, including feedstock type and particle size, and operating conditions such as pyrolysis reactor, heating rate, residence time, and reaction temperature. The heterogeneous nature of waste biomass creates challenges in controlling the pyrolysis' product selectivity. Intensive and time-consuming experimental studies are often required to determine product distribution for the pyrolysis of each unique feedstock. Alternatively, prediction models that learn from a wide range of existing experimental data may provide insight into potential yields for different biomass sources. Several advanced models exist in the literature which can predict the yield of biochar and subsequent products based on operating temperature. However, these models do not consider the combined effect of biomass characteristics and operating conditions on biochar yield, which is considered a decisive factor for biochar formation. As such, the objective of this study is to develop a prediction model based on the biomass' fixed carbon content (14-22%), reaction temperature (350-750 degrees C), and heating rate (5-10 degrees C/min) using the response surface methodology. Biomasses, date stones, spent coffee grounds, and cow manure have been used to design a Box-Behnken experiment based on the three factors for the biochar yield response. An empirical equation is developed based on a statistically significant quadratic model to produce optimized biochar yield with high prediction accuracy. The study discussed the 3D response and diagnostic plots and conducted validation experiments to confirm the applicability of the developed model. The biochar yields are significantly affected by the fixed carbon content of the feedstock and the reaction temperature, and the experimental validation confirms the accuracy of biochar yield quantification. The model can be easily applied for further process flow modeling of biomass pyrolysis, only relying on proximate feed analysis, operating temperature, and heating rate.

Automated summary

Research on generating value from wastes through pyrolysis has been growing. Biochar, a versatile pyrolysis product, is influenced by various process parameters. Predicting biochar yield based on these parameters is crucial. Existing models consider operating temperature but neglect the combined effect of biomass characteristics and conditions. This study aims to develop a prediction model based on fixed carbon content, reaction temperature, and heating rate, using response surface methodology. Experiments confirm the model's accuracy and it can be easily applied in biomass pyrolysis process modeling.