Development of a Biomass Component Prediction Model Based on Elemental and Proximate Analyses

Emerging global environmental pollution issues have caused a reduction in coal utilization, leading to an increased research focus on biomass use as alternative. However, due the low heat values of biomass, studies this field are still progress. Biomass primarily comprises cellulose, hemicellulose, and lignin. To determine composition these three components, measurement methods recommended by TAPPI (Technical Association Pulp Paper Industry) NREL (National Renewable Energy Laboratory) typically employed involving equipment such HPLC. time consuming. In study, we proposed model for predicting lignin contents based elemental industrial analyses. A dataset comprising 174 samples was used develop model. This validated using 25 additional samples. The R2P were 0.6104–0.6362, 0.4803–0.5112, 0.7247–0.7914, respectively; however, R2CV obtained from validation results 0.7387–0.7837, 0.3280–0.4004, 0.7427–0.7757, respectively. optimal models selected lignin, hemicellulose C1, L2, 100-(C1-L2) or H2, Our predictions woody herbaceous including torrefied samples, should be applied with caution other types potential accuracy limitations. enhance prediction accuracy, future broaden range considered gather more data specifically related biomass.