Monte Carlo parametric modeling for predicting biomass calorific value

• Published in: Journal of thermal analysis and calorimetry Vol. 118; no. 3; pp. 1789 - 1796
• Main Authors: Christoforou, Elias A., Fokaides, Paris A., Kyriakides, Ioannis
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.12.2014; Springer
• Subjects: Analysis; Analytical Chemistry; Biomass; Calorific value; Calorimetry; Chemistry; Chemistry and Materials Science; Computer simulation; Inorganic Chemistry; Mathematical models; Measurement Science and Instrumentation; Monte Carlo method; Monte Carlo methods; Olives; Physical Chemistry; Polymer Sciences; Thermal properties; Monte Carlo methods; Olive husk; Calorific value; Biomass; Elemental analysis
• ISSN: 1388-6150; 1588-2926; 1572-8943
• DOI: 10.1007/s10973-014-4027-5

Due to the nonlinear relationship between the calorific value and the elemental concentration of biomass, methods such as linear regression, widely used in the literature to model this relationship, produce models that fail to provide well-grounded results. In this study, a novel approach, based on Monte Carlo parametric modeling, for calculating the calorific value of biomass from measurements provided by elemental analysis, is presented. Olive husk, a biomass source widely used in the Mediterranean basin, was the subject under investigation. A comprehensive analysis of the thermal properties of olive husk was conducted. The elemental analysis, as well as the calorific value, the moisture content the sampling and the preparation of the examined biomass were performed using the appropriate CEN standards and procedures. Based on the Monte Carlo parametric modeling, the parameters of an exponential model linking the elemental analysis and the calorific value of olive husk were estimated. This study is anticipated to provide further insight to the discussion on models for predicting the calorific value of biomass, by introducing a novel mathematical approach.