Plastic product consumption and disposal are widespread. Given that these products are derived from crude oil, it is critical to reduce their consumption and effectively recycle plastic waste as recycled resources to achieve a low-carbon society. Japan enacted the “Containers and Packaging Recycling Law” in 2000, encouraging the recycling of plastic packaging and containers. However, material recycling of plastic waste has stalled due to recycling costs and technical challenges. This paper examines and evaluates the transition process and operational status of Japan’s recycling policy for plastic containers and packaging, as well as clarifies the limits of resources recycling. The limits and issues of current identification technology are discussed by analyzing the characteristics of plastic marks and detecting the material compositions of waste samples. The paper also discusses a new sorting technology that uses terahertz waves to improve plastic recycling. This analysis revealed that plastic containers are typically made of two or more plastic materials, which makes resources recycling more difficult. Terahertz waves are safer than other high-accuracy sorting technologies currently in use. Thus, material recycling can be expanded by accurately analyzing the composition of plastic waste and introducing sorting devices appropriate for achieving the circular economy with sustainable resource recycling.

Accurate identification of plastic materials from post-consumer food container and packaging waste is crucial for enhancing the purity and added value of recycled materials, thereby promoting recycling and addressing the issue of plastic pollution. However, the diverse characteristics of post-consumer plastics-such as variations in shape and additives-cause variations in spectral features like transmittance, even within the same material type. In this study, we combined near-infrared (NIR) and terahertz (THz) spectroscopies with machine learning (ML) techniques, specifically XGBoost and Bayesian optimization, to accurately identify transparent polyethylene terephthalate (PET), transparent polystyrene (PS), and black PS. We achieved a precision score exceeding 90%. Furthermore, using explainable AI (XAI) techniques, we evaluated the roles of NIR and THz waves in distinguishing between these plastics. We found that transmittance measured at a frequency of 0.140 THz was effective for identifying transparent PS, while the transmittance at 0.075 THz was crucial for identifying transparent PET. Additionally, NIR spectroscopy proved to be highly effective in distinguishing black PS from transparent plastics. Our findings indicate that the significance of THz frequencies varies depending on the material, highlighting that the identification technology developed in this study not only complements widely used NIR spectroscopy but also offers valuable insights into selecting effective frequencies for high-precision identification systems. Additionally, we discuss potential directions for further research to advance identification systems utilizing THz spectroscopy and ML techniques based on these findings.

Waste recycling is critical for the development of smart cities. Local authorities are responsible for the disposal of waste plastics, but the extent of material recycling is insufficient, and much of the waste generated is incinerated. This conflicts with the trend of decarbonisation. Of particular note are the effects of the COVID-19 pandemic, during and after which large quantities of waste plastics, such as plastic containers and packaging, were generated. In order to develop a sustainable smart city, we need an effective scheme where we can separate materials before they are taken to the local authorities and recyclers. In other words, if material identification can be performed at the place of disposal, the burden on recyclers can be reduced, and a smart city can be created. In this study, we developed and demonstrated smart material identification equipment for waste plastic materials made of PET, PS, PP, and PE using GaP THz and sub-THz wavelengths. As basic information, we used a GaP terahertz spectrometer to sweep frequencies from 0.5 THz to 7 THz and measure the spectrum, and the transmittance rate was measured using the sub-THz device. The sub-THz device used a specific frequency below 0.14 THz. This is a smaller, more carriable, and less expensive semiconductor electronic device than the GaP. Moreover, the sub-terahertz device used in the development of this equipment is compact, harmless to the human body, and can be used in public environments. As a result, smart equipment was developed and tested in places such as supermarkets, office entrances, and canteens. The identification of materials can facilitate material recycling. In this study, we found that measuring devices designed to identify the PET and PS components of transparent containers and packaging plastics, and the PP and PE components of PET bottle caps, could effectively identify molecular weights, demonstrating new possibilities for waste management and recycling systems in smart cities. With the ability to collect and analyse data, these devices can be powerful tools for pre-sorting.

In Japan, when people take their waste bottle caps to designated recycling companies, JPY 5/kg is donated to developing countries for polio vaccine dissemination activities. The waste volume of plastic bottles and caps is increasing every year, and there is not a day that goes by that we do not see more bottles and caps. PET bottles are more easily recycled, as the bottle body is made of a single material. However, bottle caps are made of two different materials (PP and PE), which are difficult to identify perfectly when utilising the existing NIR technology in the recycling field. This is because the designs and colours of PP and PE bottle caps are becoming more diverse, with black and dark-coloured caps being difficult to sort using NIR technology. In addition, their specific gravity is almost the same; therefore, it is difficult to separate them by their water-based specific gravity, which is an approach commonly used by recyclers. Unidentified caps are sent for thermal recycling, which runs counter to the need for decarbonisation. They may also be mixed with identified caps and sold as recycled raw material, resulting in a reduction in the purity of the recycled plastic. If PP and PE caps can be identified using simple technology, it is expected to promote high resource recycling. Therefore, in order to develop such a sorting process, this study proposes a new method for the material identification of waste caps using terahertz waves. Therefore, this research aims to identify a new identification method for waste plastic caps, which has been a challenge both domestically and internationally. Specifically, we describe the limitations of the conventional methods for identifying PP and PE bottle caps according to their weight, specific gravity, and melting point and propose an identification method using terahertz waves, demonstrating its measurement-related merits and high identification accuracy.

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.

Post-consumer plastic waste poses increasing challenges in urban areas, where recycling heavily relies on consumer cooperation. In Japan, two recycling routes for post-consumer plastic waste from households exist, the municipal recycling route and the retailer recycling route, with the latter requiring more voluntary effort. This study aims to explore the diversity of consumers’ cooperative behaviors in Japan’s post-consumer plastic waste recycling system, with a focus on the retailer route. We conducted an online survey with 758 respondents from Sendai, Kawasaki, and Kyoto in urban Japan, using a structured questionnaire based on the knowledge–attitude–practice (KAP) framework. K-means clustering was conducted to identify behaviorally distinct consumer groups. Three clusters were revealed: Fully Engaged Consumers, Knowledge-Driven Consumers, and Passively Engaged Consumers. These groups exhibited distinct differences in cooperative recycling behaviors and socio-demographic characteristics. Our findings demonstrate the heterogeneity of consumer cooperation and underscore the importance of targeted strategies. By focusing on the retailer recycling route and consumer segmentation, this study addresses key gaps in Japan’s research on urban plastic waste. The results provide a theoretical and empirical foundation for differentiated policy-making, ultimately supporting the transition to a more sustainable and circular economy in post-consumer plastic waste recycling in urban Japan.