Performance of a portable NIR spectrometer for the determination of moisture content of industrial wood chips fuel

•A portable NIR spectroscope was used to estimate moisture content of biomass fuels.•Validity, accuracy and precision of 3 prediction models were compared.•Moisture estimate with portable NIR is reliable, fast and non-destructive.•Results of the prediction models differed mostly on the extreme moist...

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Bibliographic Details
Published in:Fuel (Guildford) 2022-07, Vol.320, p.123948, Article 123948
Main Authors: Toscano, Giuseppe, Leoni, Elena, Gasperini, Thomas, Picchi, Gianni
Format: Article
Language:English
Subjects:
Bioenergy
Biofuels
Biomass
Drying ovens
Energy conversion
Energy policy
Environmental policy
Fuel quality
Fuel storage
Infrared spectrometers
Mathematical models
Moisture content
Moisture effects
Near infrared radiation
NIR
Nondestructive testing
Parameters
Portability
Prediction models
Quality control
Renewable energy
Supply chains
Sustainability
Water content
Wood
Wood chips
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Summary:•A portable NIR spectroscope was used to estimate moisture content of biomass fuels.•Validity, accuracy and precision of 3 prediction models were compared.•Moisture estimate with portable NIR is reliable, fast and non-destructive.•Results of the prediction models differed mostly on the extreme moisture content values.•NIR spectroscopy is highly suitable to analyze fuel quality along the supply chain. The environmental policy of the European Union is boosting the development of renewable energies. Among these, bioenergy holds the main share and is expected to further increase. Such development requires a higher degree of efficiency in the whole supply chain. This is achieved also with an enhanced fuel quality control and a better matching with the energy conversion systems. For solid biofuels, moisture content is the main quality parameters, influencing the sustainability of the whole energy system. With the aim to provide a real-time and portable tool for moisture measurement, a hand-held near infrared spectrometer was tested on a dataset of 817 wood chip samples provided by an industrial facility. A set of key performance parameters were used to compare the estimation of three alternative prediction models and the standard oven dry method. Results show a satisfactory reliability with R2 ranging from 0.86 to 0.89 depending on the model. A single measure can be acquired in few seconds, and the potential to deploy the non-destructive analysis directly at the fuel storage (yard) and at different steps of the supply chain discloses a wide range of options to efficiently control fuel quality.
ISSN:0016-2361
1873-7153
DOI:10.1016/j.fuel.2022.123948