A Comprehensive Analysis of the Risks Associated with the Determination of Biofuels’ Calorific Value by Bomb Calorimetry

• Published in: Energies (Basel) 2022-04, Vol.15 (8), p.2771
• Main Authors: Shehab, Moaaz, Stratulat, Camelia, Ozcan, Kemal, Boztepe, Aylin, Isleyen, Alper, Zondervan, Edwin, Moshammer, Kai
• Format: Article
• Language: English
• Subjects: Biodiesel fuels; Biofuels; Biomass; Bomb calorimetry; Calorific value; Calorimetry; Confidence intervals; Coverage; Energy; Heat measurement; Heterogeneity; Industrial plant emissions; Laboratories; Moisture content; Pellets; Physical properties; repeatability; Reproducibility; Uncertainty; Water content; Wood; wood biomass; Wood chips
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en15082771

Two of the most commonly used solid biomass sources for fuel are wood chips and wood pellets. The calorific value and the moisture content of those biofuels determine the efficiency of the CHP and the biorefinery plants. Therefore, with the increased shift towards a biobased economy, the biomass cost and its physical properties must be precisely determined. Most of the current standards are lacking and provide neither enough details about the issues caused by the biomass heterogeneity nor with the variation in experimental practice. Phenomena such as data scattering, poor repeatability and wide uncertainty, are mostly observed during the measurements of the calorific value and the moisture content. To overcome such issues, an interlaboratory comparison between three national metrology institutes using bomb calorimetry has taken place. The comparison helped to identify the root causes behind the poor reproducibility of the wood samples. Factors such as the equilibrium moisture content of the biomass, the pellet mass, the applied pressure to form the pellet, the handling techniques and the determination errors are highlighted and analyzed. The final results paved the way to provide an enhanced detailed experimental practice where the repeatability and reproducibility have been strongly improved. Moreover, the detailed uncertainty sources and calculations are presented. It has been found that by fulfilling the recommended approach the measurement repeatability improved by up to 50–80%, while the final uncertainty improved by 10–30%. This enhancement leads to a maximum relative expanded uncertainty of around ±1% (coverage factor of k = 2 and a confidence level of 95%).