China has become the largest electric vehicle (EV) market in the world since 2015. Consequently, the lithium-ion battery (LiB) market in China is also expanding fast. LiB makers are continually introducing new types of LiBs into the market to improve LiBs’ performance. However, there will be a considerable amount of waste LiBs generated in China. These waste LiBs should be appropriately recycled to avoid resources’ waste or environmental pollution problems. Yet, because LiBs’ type keeps changing, the environmental impact and profitability of the waste LiB recycling industry in China become uncertain. In this research, we reveal the detailed life cycle process of EVs’ LiBs in China first. Then, the environmental impact of each type of LiB is speculated using the life cycle assessment (LCA) method. Moreover, we clarify how LiBs’ evolution will affect the economic effect of the waste battery recycling industry in China. We perform a sensitivity analysis focusing on waste LiBs’ collection rate. We found that along with LiBs’ evolution, their environmental impact is decreasing. Furthermore, if waste LiBs could be appropriately recycled, their life cycle environmental impact would be further dramatically decreased. On the other hand, the profitability of the waste battery recycling industry in China would decrease in the future. Moreover, it is essential to improve waste LiBs’ collection rate to establish an efficient waste LiB industry. Such a trend should be noticed by the Chinese government and waste LiB recycling operators to establish a sustainable waste LiB recycling industry in the future.

In Indonesia, plastic constitutes the second largest component of municipal solid waste; however, 58% remains uncollected. Most plastic recycling depends on informal sectors, accounting for only 10% of the total, leaving the remainder to potentially harm the environment. This paper analyzes how cities in Indonesia have tackled their plastic waste problems from the perspective of the integrated sustainable waste management framework. This study focuses on plastic waste management (PWM) in three cities: Bandung, Yogyakarta, and Magelang. Data were collected from 41 semi-structured interviews, a plastic waste composition data analysis, and site visits. The research outcomes include a comprehensive analysis of stakeholder roles, plastic waste flow, plastic waste composition data, and various challenges in PWM. This study identifies three main stakeholders in collecting plastic wastes: the Department of Environment as the main local government body, community-based waste banks, and private waste management companies. Most recyclable plastic waste is recovered through waste banks and private collection services. In 2022, the predominant types of plastic waste in Bandung, Yogyakarta, and Magelang City were soft plastics, thick plastics, and hard plastics, respectively. The challenges for the PWM stem from various aspects in political, legal, and institutional; environmental; financial and technical; and socio-cultural spheres. Positive trends towards an integrated system are observed, although full integration has not yet been achieved. The research recommends a multi-stakeholder cooperative approach involving municipal authorities, waste banks, and private collectors, responsive to local conditions and emphasizing sustainability aspects throughout waste management stages for a sustainable resource recycling in developing countries.

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.