Waste wood is becoming an appealing alternative material to virgin wood, and the main drivers are the increased demand for waste wood by the panel industry, the introduction of renewable energy policies, and the waste framework directive. In fact, the use of waste wood as a secondary resource is favored over both landfills and combustion. The best reuse and cascading use of the material are linked to its characteristics. That is why it is important to know the chemical composition and the variation in the properties of such a heterogeneous material. In this article, a sampling study was carried out in a panel board company located in the northern part of Italy. In order to investigate the heterogeneity of waste wood, all samples have been analyzed by near-infrared spectroscopy. Nested analysis of variance and principal component analysis have been used to evaluate the heterogeneity and the variation in sample properties. The approach gives information about how to ensure representative measurements and efficiently describe the variability of the material. The results suggest that it is important to have replicates or at least two subsamples for each lot and then measure each of these with at least 100 scans, in order to get representative measurements and describe the variability of the material. The determination of waste wood composition and variability is the focal point for improving the sorting process and increasing the reuse of waste wood, avoiding expensive landfills and risks for human health and the environment.
Keywords: NIR spectroscopy; PCA; heterogeneity; nested analysis of variance; sampling; variability.
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