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Abstract
The increased use of wood as a sustainable building material offers significant potential for reducing CO₂ emissions in the construction sector. At the same time, the natural variability of wood products, particularly their volatile organic compounds (VOCs), poses challenges for indoor air quality. Monoterpenes such as α-pinene and 3-carene dominate the emissions of pine wood and are the focus of current research aimed at assessing and reducing VOC emissions and exposure. The standardized approach to emission analysis, based on the chamber method according to DIN EN 16516:2017, is time-consuming. This project report demonstrates that near-infrared spectroscopy (NIR), combined with multivariate analytical methods, can provide an efficient and precise alternative. The results show that reliable predictive models for terpene emissions from pine wood could be developed using NIR technology. For α-pinene and 3-carene, cross-validated correlation coefficients of R²CV = 0.77 were achieved, indicating good model quality. The mean deviation in cross-validation (RMSECV) was 1,257 μg/m³ for α-pinene and 1,232 μg/m³ for 3-carene. These models enable a rapid evaluation of product emissions, with model accuracy performing particularly well at medium and higher concentrations. However, limitations exist in the lower concentration range, which restricts the applicability of the method in such cases. The applicability to wood materials such as strands (long, thin chips) used for the production of OSB, proved problematic due to transmission effects and high spectral variability. To make the technology usable for woodbased materials, advanced calibration approaches are required. Overall, NIR technology represents a promising complement to existing analytical methods and opens up new perspectives for the sustainable processing of wood products.