Higher heating values estimation of horticultural biomass from their proximate and ultimate analyses data

Higher heating value (HHV) and composition of biomass, coal and other solid fuels are important properties which define the energy content and determine the clean and efficient use of these fuels. Moreover, the HHV is one of the most important properties of biomass fuels when it comes to design calculations or numerical simulations of thermal conversion systems for biomass. There are a number of equations proposed in the literature for estimating the HHV of biomass fuels from the basic analysis data, i.e. proximate and ultimate analysis composition. However, the ultimate analysis requires very expensive equipment and highly trained analysts. The proximate analysis on the other hand only requires standard laboratory equipment and can be run by any competent scientist or engineer. The objective of this paper is to find useful correlations for calculating the HHV of biomass generated after pruning of major horticultural varieties, using the proximate and ultimate analyses data. In order to obtain these equations, biomass samples of major horticultural species taken after branch pruning were laboratory analyzed in order to determine calorific values and proximate analyses. The accuracy of these equations is statistically evaluated in order to provide quantitative evidence for the correlation selection in the engineering applications for utilization of horticultural biomass in thermal energy production. The measured HHV of the horticultural biomass samples varied between 17.95 and 20.01 MJ/kg. The statistic analyses of all proposed equations showed that their correlation coefficients range from 0.291 to 0.714. An average absolute error was determined at a range from 0.557 to 2.685 and average bias error was between -1.984 and 2.658. The equations based on the proximate data have a consistent and sound accuracy, within which the correlation coefficient was in a range from 0.448 to 0.664 whereas the proximate analysis provides only an empirical composition of the biomass. Contrary to this, the correlation resulting from the ultimate analysis varied in a much larger range, i.e. between 0.291 and 0.714.