Trends in the occurrence and accumulation of microplastics in urban soil of Nanjing and their policy implications

Using artificial intelligence to rapidly identify microplastics pollution and predict microplastics environmental behaviors

With the massive release of microplastics (MPs) into the environment, research related to MPs is advancing rapidly. Effective research methods are necessary to identify the chemical composition, shape, distribution, and environmental impacts of MPs. In recent years, artificial intelligence (AI)-driven machine learning methods have demonstrated excellent performance in analyzing MPs in soil and water. This review provides a comprehensive overview of machine learning methods for the prediction of MPs for various tasks, and discusses in detail the data source, data preprocessing, algorithm principle, and algorithm limitation of applied machine learning. In addition, this review discusses the limitation of current machine learning methods for various task analysis in MPs along with future prospect. Finally, this review finds research potential in future work in building large generalized MPs datasets, designing high-performance but low-computational-complexity algorithms, and evaluating model interpretability.

Sedimentary record of microplastics in coastal wetland, eastern China

Microplastic (MP) dynamics can reflect history of plastic production and waste management in nearby areas. However, the stratigraphy of MPs in coastal wetlands and their link to policy and economic pattern changes are currently unclear. Here, MP stratigraphic records in sediment core from coastal wetlands in Yancheng, China, were used to reconstruct plastic pollution history. Neural network models simulated how policy intervention and economic development affected MP accumulation over time. We showed that MP abundance curves with boundaries from 1920 to 2019 had four stages. MP growth slowed or even decreased in the mid-to-late 1980s due to improved waste management and wastewater treatment since the late 1980s. Human activities were the primary factor affecting MP abundance and shape, followed by sediment properties. We predict that the environmental impact of MPs will continue to increase in the next decade. Current plastic policy measures focus on predictable waste emissions, but hidden sources like clothing fibers and tire wear that significantly contribute to MP pollution require further attention.

Prevalence of Plastic Usage and the Factors Associated With It Among Adults in Perambalur District of South India: A Cross-Sectional Study

Background People extensively use and dispose of plastic products because of their durability, affordability, and lightweight. The excessive production and consumption of plastics has led to pollution that has negative effects on both society and the environment. Nearly all Indian states and union territories have prohibited the usage of plastic bags, with Tamil Nadu being the fourth state in the country to implement such a prohibition. The study aims to determine the prevalence of plastic usage, its associated factors, and awareness regarding the laws related to the plastic ban. Methodology We conducted a cross-sectional study on 1200 adults above 18 years of age using multistage sampling. We undertook the study for three months in the district of Perambalur, in South India. The semi-structured questionnaire was used as a research tool, which contained information on socio-demographics, plastic utilization, understanding of plastic prohibition, its need, and views on bisphenol A (BPA). We entered the gathered data in Microsoft Excel (Microsoft Corporation, Redmond, WA) and analyzed using SPSS version 26 (IBM Corp., Armonk, NY). If the P-value was less than 0.05, we deemed it statistically significant. Results The mean age of the study participants was 44.47 ± 15.09 years. Plastic is being used by most of the study participants because of its wide availability and convenience of usage. Approximately 42.43% (n=471) of the participants adhere to non-segregation waste disposal practices in public bins. Approximately 1100 (92.5%) of the participants incorporate plastic into their daily routine. Among the participants, approximately 15.7% (188) were knowledgeable about bisphenol A (BPA), while about 92.6% (1111) of them were knowledgeable about plastic substitutes. Individuals belonging to the younger age group, male gender, higher education background, living in urban areas, living in joint families, and not engaged in agriculture were the primary users of plastic, and this trend was statistically significant (p <0.001). Conclusion In the study, the prevalence of plastic usage was higher among the participants who followed unsanitary methods of disposal. Despite the awareness of the hazards of plastic and the regulations against its use, its consumption remains high. Plastic consumption is higher in the urbanized area across residential, educational, occupational, and young age demographics. The mere act of raising awareness is insufficient; it is necessary to convert awareness into action to protect both the environment and humanity.