In Europe, the volume of waste wood is increasing. Waste wood can be reused, promoting circular economy and avoiding landfills. It can be used as a bioenergy feedstock reducing the use of fossil fuels, or be reused for producing new composite wood material. Only wood with hazardous substances needs to be disposed. To this aim waste wood samples were collected from a panel board company and several recycling centres in Italy and Denmark. The samples were assigned to waste wood categories and analysed by Near Infrared Spectroscopy. Principal Component Analysis was used to investigate sample variability and Soft Independent Modelling of Class Analogies (SIMCA) for classifying the samples according to the appropriate reuse: energy production, panel board production or landfill. The results are good, with a classification rate of 90% for virgin wood material and 86.7% for treated wood material. The classification of waste wood is key for turning it into a secondary resource.

Classification of waste wood categories according to the best reuse using FT-NIR spectroscopy and chemometrics / Mancini, Manuela; Rinnan, Åsmund. - In: ANALYTICA CHIMICA ACTA. - ISSN 0003-2670. - 1275:(2023). [10.1016/j.aca.2023.341564]

Classification of waste wood categories according to the best reuse using FT-NIR spectroscopy and chemometrics

Mancini, Manuela
Primo
;
2023-01-01

Abstract

In Europe, the volume of waste wood is increasing. Waste wood can be reused, promoting circular economy and avoiding landfills. It can be used as a bioenergy feedstock reducing the use of fossil fuels, or be reused for producing new composite wood material. Only wood with hazardous substances needs to be disposed. To this aim waste wood samples were collected from a panel board company and several recycling centres in Italy and Denmark. The samples were assigned to waste wood categories and analysed by Near Infrared Spectroscopy. Principal Component Analysis was used to investigate sample variability and Soft Independent Modelling of Class Analogies (SIMCA) for classifying the samples according to the appropriate reuse: energy production, panel board production or landfill. The results are good, with a classification rate of 90% for virgin wood material and 86.7% for treated wood material. The classification of waste wood is key for turning it into a secondary resource.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/324534
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