Abstract
Biomass is a carbon-neutral renewable energy resource. Biochar produced from biomass pyrolysis exhibits preferable characteristics and potential for fossil fuel substitution. For time- and cost-saving, it is vital to establish predictive models to predict biochar properties. However, limited studies focused on the accurate prediction of HHV of biochar by using proximate and ultimate analysis results of various biochar. Therefore, the multi-linear regression (MLR) and the machine learning (ML) models were developed to predict the measured HHV of biochar from the experiment data of this study. In detail, 52 types of biochars were produced by pyrolysis from rice straw, pig manure, soybean straw, wood sawdust, sewage sludge, Chlorella Vulgaris, and their mixtures at the temperature ranging from 300 to 800°C. The results showed that the co-pyrolysis of the mixed biomass provided an alternative method to increase the yield of biochar production. The contents of ash, fixed carbon (FC), and C increased as the incremental pyrolysis temperature for most biochars. The Pearson correlation (r) and relative importance analysis between HHV values and the indicators derived from the proximate and ultimate analysis were carried out, and the measured HHV was used to train and test the MLR and the ML models. Besides, ML algorithms, including gradient boosted regression, random forest, and support vector machine, were also employed to develop more widely applicable models for predicting HHV of biochar from an expanded dataset (total 149 data points, including 97 data collected from the published literature). Results showed HHV had strong correlations (|r| > 0.9, p 0.90. The ML models showed better performance with test R2 around 0.95 (random forest) and 0.97–0.98 before and after adding extra data for model construction, respectively. Feature importance analysis of the ML models showed that ash and C were the most important inputs to predict biochar HHV.
Highlights
Thermochemical conversion of biomass is one of the optional pathways to overcome the energy crisis, environmental pollution, and sustainable development issues of the world
The co-pyrolysis of the biomass mixture could improve the yield of most biochar, it would provide a feasible scheme for enhancing the yield of biochar
In the data composed of ultimate analysis (Tables 1 and S1 in supporting information), biochars derived from pig manure (PM) at the 400°C∼ had lower C content than that of feedstocks, and the similar results could be found in the study of Gascó et al
Summary
Thermochemical conversion of biomass is one of the optional pathways to overcome the energy crisis, environmental pollution, and sustainable development issues of the world. Significant momentum has been attained in the use of renewable biomass as an alternative to traditional fossil fuels in the energy application fields [2]. The characteristics of raw biomass, such as high moisture content, large volume, low energy density, and low combustion calorific value, are several significant problems upon its use as fuel. It is necessary to grasp the fuel properties (i.e., higher heating value (HHV)) of biochar for its application in the energy field. The use of instruments to determine the properties of biochar has some disadvantages, such as high cost and time-consuming. It is necessary and economical to develop the HHV prediction model based on some common characteristic indexes
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