In Japan, the majority of waste plastics are classified into three categories: approximately 22% are used for material recycling, 3% are used for chemical recycling, and 62% are used for thermal recycling. Thermal recycling is not considered true recycling in the EU, however. To achieve a decarbonized society, Japan must increase the share of material recycling. The accurate identification of plastic materials is essential in this regard, and while near-infrared (NIR) spectroscopy is commonly employed in analyses, it cannot be used to assess degradation levels. Plastics characterized by different degrees of degradation can reduce the quality of recycled products and require additional treatment. In this study, we irradiated artificially degraded polyethylene and polypropylene samples using Fourier transform infrared (FTIR) spectroscopy and terahertz (THz) waves and subsequently compared them with undegraded samples. Our results provide experimental confirmation that THz waves can be used to determine the degree of plastic degradation. When combined with NIR-based material identification, this method could enhance the precision and efficiency of plastic recycling, contributing to a more sustainable recycling system.

Past studies have reported that carbon dioxide emissions during combustion vary depending on the tree species used as fuel. It has also been reported that the moisture content of wood affects combustion efficiency. From this perspective, identifying the tree species and moisture content is crucial for utilizing waste wood as a resource. Therefore, this study verified the effectiveness of non-destructive diagnosis using terahertz waves. Samples with adjusted moisture content were prepared for eight types of wood. Each wood sample was irradiated with multiple broadband terahertz electromagnetic waves, and their transmission characteristics were compared. Experimental results revealed a strong negative correlation (Pearson Correlation coefficient: −0.98~−0.71 square meter/gram) between the sample’s specific gravity and transmittance when irradiated with 65 GHz and 90 GHz sub-terahertz waves. This trend was particularly pronounced during 90 GHz sub-terahertz irradiation. Furthermore, it was found that the trend in transmittance variation differed depending on the wood’s moisture content. These results indicate that terahertz waves are effective as a wood identification method capable of distinguishing between coniferous and broadleaf trees. Furthermore, they are considered effective for predicting wood moisture content. This research is expected to contribute to promoting wood recycling and the sustainable use of wood resources.