Advancements and challenges in microplastic detection and risk assessment: Integrating AI and standardized methods

Abstract

Microplastics (MPs) pose significant threats to ecosystems and human health due to their persistence and widespread distribution. This paper provides a comprehensive review of sampling methods for MPs in aquatic environments, soils, and biological samples, assessing pre-treatment procedures like digestion and separation. It examines the application and limitations of identification techniques, including microscopic observation, spectroscopic analysis, and thermal analysis. The review highlights the potential of AI technology to enhance detection efficiency and precision. It underscores the necessity of standardized protocols for consistent sampling and detection, and the importance of systematic risk assessment methodologies for managing environmental and health risks associated with MPs. The paper concludes with recommendations for future research, emphasizing the standardization of methods, advancement of detection technologies, integration of AI, and comprehensive health risk assessments. This review will be helpful for researchers to comprehensively understand the current main detection technologies and risk assessment methods of the MP, and to accelerate the establishment of an artificial intelligence regulatory framework for MPs.