Abstract
Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R 2 > 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material.
Highlights
Lignocellulosic biomass is the only renewable resource that can be used in the production of biofuels and platform chemicals in addition to bioenergy
The objective of this study was to employ Fourier transform infrared reflectance (FTIR) spectroscopy coupled with partial least squares (PLS) regression to rapidly predict the chemical composition, thermal reactivity, and energy content of logging residue of loblolly pine, the most economically important tree species in the USA
For chemical composition, developed models generally did a better job of predicting the extractives and lignin content than the carbohydrates; for the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R2 > 0.80, ratio of performance to deviation (RPD) > 2.0)
Summary
Lignocellulosic biomass is the only renewable resource that can be used in the production of biofuels and platform chemicals in addition to bioenergy. As the most abundant carbon neutral resource, using biomass instead of fossil fuels can help mitigate environmental pollution. Many physical, chemical, and structural factors can hinder the conversion of biomass into fuels and chemicals. A better understanding of the properties of biomass will be important in the allocation of feedstock to the appropriate end use. An ability to determine these properties in a timely manner is necessary in the optimization of conversion technologies for the successful commercialization of biomass-based products. There is a need for high throughput methods and equipment in the monitoring and characterization of the raw feedstock as conventional methods have been laborious and destructive
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