Synergy of Hydrothermal and Organic Acid Washing Treatments in Chinese Fir Wood Vinegar Preparation

Machine learning prediction of contents of oxygenated components in bio-oil using extreme gradient boosting method under different pyrolysis conditions

This work aims to develop a prediction model for the contents of oxygenated components in bio-oil based on machine learning according to different pyrolysis conditions and biomass characteristics. The prediction model was constructed using the extreme gradient boosting (XGB) method, and the prediction accuracy was evaluated using the test dataset. The partial dependence analysis (PDA) method was used to derive the pattern of influence of each input feature individually or in combination on the output variable. The results show that the prediction models constructed from biomass ultimate analysis and pyrolysis conditions can predict the contents of oxygenated components in bio-oil more accurately than the models constructed from biomass proximate analysis. Moderate C and O contents, higher H content of biomass, lower flow rate, and higher pyrolysis temperature can improve bio-oil quality.

Hydrothermal Carbonization of Searsia lancea Trees Grown on Mine Drainage: Processing Variables and Product Composition

A 12-year-old planted woodlands Searsia lancea tree, grown on acid mine drainage for phytoremediation of polluted groundwater on gold and uranium mines in South Africa, was used in this research. The research describes the fuel-related characteristics and the influence of different operating conditions on the hydrothermal carbonization of the biomass and the combustion profiles of discard coal/biomass hydrochar pellets. The raw biomass was treated at temperatures ranging from 200-280 °C and residence time of 30-90 min. The hydrochar produced at 280 °C and residence time of 90 min had the highest calorific value of 29.71 MJ/kg compared to 17.23 and 16.73 MJ/kg obtained from the raw biomass and discard coal, respectively. Regression equations developed using the central composite design (CCD) indicated that the values obtained experimentally agree with the predicted values from the models for mass yield, calorific value, and ash content. The reactivity tests showed that the 100% hydrochar pellet had the highest reactivity and lowest ignition and burnout temperature compared to biocoal pellets and discard coal. The process water contained relatively low concentrations of major elements, and the study had shown that different high-grade biocoal pellets can be produced from the S. lancea tree.