The Prediction of Gross Calorific Value Using Infrared (IR) Spectroscopy and Multivariate Analysis

The gross calorific value (GCV) of a fuel, also known as the higher heating value (HHV) or gross heat of combustion, is the amount of heat released by a specified quantity (initially at 25°C) once it is combusted and the products returned to that temperature. Fuwape (1989) noted that extractive-free wood from Gmelina arborea (Roxb), a hardwood, had a lower gross heat of combustion than the unextracted wood. In a later study, finding that extractive-free plant parts resulted in lower HHVs than the unextracted parts, Demirbas (2003) produced an equation relating the differential HHV to extractives content. The application of near-infrared (NIR) spectroscopy, coupled with multivariate analysis, has been used as a rapid means to determine a range of woody biomass properties. Recently, it has been applied to biofuel properties. For example, Lestander and Rhen (2005) used this technique to determine the calorific content in Norway spruce, and suggested its applicability to process monitoring in biofuel plants. Maranan and Laborie (2007) applied this technique to the determination of calorific value of Populus spp. Calibration models proved useful for the rapid determination of calorific value, however, it was less accurate than the standard method. This is not surprising given that Gillon et al. (1997) had previously determined this technique to be considerably less accurate than results obtained directly by calorimetry, based on various fuel samples (e.g., wood, leaves, and bark). Nevertheless, it was stated that this method could be a useful tool when a large number of measurements are required. The first objective of the current study is to determine if there is a significant (i.e., measurable) impact of extractives content on GCV when using a single softwood species. The other objective being the rapid determination of the GCV of milled samples of longleaf pine (Pinus palustris) using infrared (IR) spectroscopy coupled with multivariate analysis. The application of IR spectroscopy (as opposed to NIR spectroscopy) also allows the spectral investigation of the samples to determine the chemical features that are important in the GCV and extractive predictions.