Quality assessment of recycled wood with and without non-wooden materials from selected recycling companies in Europe

Supporting Circular Economy Principles by Recycling Window Frames into Particleboard

The aim of the study was to identify limiting factors for reusing wood through the recycling of window frames by conducting research under fully controlled conditions. The research involved manufacturing new window frames, seasoning them, and then shredding them into wood particles to prepare a three-layer particleboard. The proportion of wood particles in recycling was 0, 5, 10, 25, 50, and 100 parts by weight of the manufactured particleboard. Mechanical property tests were conducted: modulus of elasticity (MOE) and modulus of rupture (MOR), internal bond (IB), screw withdrawal resistance (SWR), and physical properties: density profile (DP), thickness swelling (TS) after water immersion, water absorption (WA), as well as formaldehyde emission and total volatile organic compound (TVOCs) tests. The research indicates a significant potential for utilizing wood from this sector of the wood industry, particularly considering variants with a higher proportion of recycled wood. MOR and MOE results are most promising for variants above 50 parts by weight of recycled wood. Based on the results obtained, it is clear that the production process should be improved or the raw material modified to enhance the internal bonding of particleboard, as these results were the weakest. Thus, recycled wood from window joinery has the potential to be reincarnated as particleboard, which continues to be widely used in their production.

Comparison of classification methods performance for defining the best reuse of waste wood material using NIR spectroscopy

Recycling of post-consumer waste wood material is becoming an increasingly appealing alternative to disposal. However, its huge heterogeneity is calling for an assessment of the material characteristics in order to define the best recycling option and intended reuse. In fact, waste wood comes into a variety of uses/types of wood, along with several levels of contamination, and it can be divided into different categories based on its composition and quality grade. This study provides the measurement of more than a hundred waste wood samples and their characterisation using a hand-held NIR spectrophotometer. Three classification methods, i.e. K-nearest Neighbours (KNN), Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA) and PCA-KNN, have been compared to develop models for the sorting of waste wood in quality categories according to the best-suited reuse. In addition, the classification performance has been investigated as a function of the number of the spectral measurements of the sample and as the average of the spectral measurements. The results showed that PCA-KNN performs better than the other classification methods, especially when the material is ground to 5 cm of particle size and the spectral measurements are averaged across replicates (classification accuracy: 90.9 %). NIR spectroscopy, coupled with chemometrics, turned out to be a promising tool for the real-time sorting of waste wood material, ensuring a more accurate and sustainable waste wood management. Obtaining real-time information about the quality and characteristics of waste wood material translates into a decision of the best recycling option, increasing its recycling potential.

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

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.

Availability and Applicability of Wood and Crop Residues for the Production of Wood Composites

Due to high levels of volatility in both the agricultural and the forestry commodity markets, specifically, of timber and agricultural crops, it is important to identify the risks associated with the stability of supplies necessary for the production of composite materials in the Czech Republic. This study aims to accurately estimate the availability of selected raw materials that contain lignocellulose over the next 20 years. In addition, their suitability for the production of composite materials is assessed based on their physical properties. Furthermore, in the event of scarcity involving timber in the European Union, recycled wood and post-harvest residues could replace conventional raw materials in wood-based composites such as particleboards and chipboards. The viable potential of Czech forests is predicted to be between 740 and 750 million cubic meters of timber. For agricultural crops, it is estimated at 0.9 million hectares of wheat and 0.5 million hectares of canola under the current EU biofuel policy and at 0.4 million hectares if this policy is removed. According to moisture and fibre analyses carried out in our study, the most suitable candidate for wood-based composites production is soft wood.