Zhang Hailong, Duan Qiannan, Yan Pengwei, Lee Jianchao, Wu Weidong, Zhou Chi, Zhai Baoxin, Yang Xiangyi
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, PR China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, PR China.
Mar Pollut Bull. 2025 Mar;212:117529. doi: 10.1016/j.marpolbul.2025.117529. Epub 2025 Jan 4.
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.
微塑料因其持久性和广泛分布,对生态系统和人类健康构成重大威胁。本文全面综述了在水生环境、土壤和生物样本中微塑料的采样方法,评估了诸如消解和分离等预处理程序。研究了识别技术的应用及局限性,包括显微镜观察、光谱分析和热分析。该综述强调了人工智能技术在提高检测效率和精度方面的潜力。强调了采用标准化方案以实现一致采样和检测的必要性,以及系统风险评估方法对于管理与微塑料相关的环境和健康风险的重要性。本文最后给出了未来研究的建议,强调方法的标准化、检测技术的进步、人工智能的整合以及全面的健康风险评估。这篇综述将有助于研究人员全面了解当前微塑料的主要检测技术和风险评估方法,并加速建立微塑料的人工智能监管框架。