Classification of waste wood categories according to the best reuse using FT-NIR spectroscopy and chemometrics
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Classification of waste wood categories according to the best reuse using FT-NIR spectroscopy and chemometrics. / Mancini, Manuela; Rinnan, Åsmund.
I: Analytica Chimica Acta, Bind 1275, 341564, 2023.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Classification of waste wood categories according to the best reuse using FT-NIR spectroscopy and chemometrics
AU - Mancini, Manuela
AU - Rinnan, Åsmund
N1 - Publisher Copyright: © 2023 The Authors
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Circular economy
KW - Classification
KW - Material reuse
KW - Sorting
KW - Spectroscopy
U2 - 10.1016/j.aca.2023.341564
DO - 10.1016/j.aca.2023.341564
M3 - Journal article
C2 - 37524459
AN - SCOPUS:85165377062
VL - 1275
JO - Analytica Chimica Acta
JF - Analytica Chimica Acta
SN - 0003-2670
M1 - 341564
ER -
ID: 361591107