Carbon-relative molar mass is a new parameter for experimentation with different biomasses. Prediction of higher heating value case study

Abstract The higher heating value (HHV) prediction is an important aspect of biomass management. Numerous empirical models based on the elemental composition of biomass have been proposed; however, their predictive accuracy often remains limited, with coefficients of determination typically around 80%. This paper presents a new parameter, the carbon-relative molar mass (CRMM) of biomass, for predicting HHV. Randomly generated data on the elemental composition and ash content of biomass were used for model parameters determination. Experimental data of lignocellulosic biomass components and biochar samples were used for model validation. The CRMM predominantly depends on the carbon and oxygen content when randomly chosen data are used. However, for real biomass and biochar samples, the influence of hydrogen and sulfur increases. A polynomial model for determining CRMM with an R (Awasthi et al. Fuel 342:127790, 2023) value of 0.9886 is proposed. Mathematical models describing the influence of CRMM on HHVdaf were developed. A very strong dependence of the analytically determined HHVdaf on CRMM was found, with an explanation rate close to 86%. This value is higher than those of typical empirical models based on the elemental composition of biomass. This promising discovery warrants further study with a wider range of biomass types and other solid fuels.