合成塑料生产的升级和废物管理的不足导致水生生态系统中普遍存在的微塑料(MP)污染。议员们,通常定义为小于5毫米的颗粒,已经成为淡水环境中的新兴污染物。尽管自2014年以来,人们对国会议员的关注有所增加,但研究主要集中在海洋环境上,迫切需要进行更深入的批判性审查,以系统地总结当前的全球努力,知识差距,以及淡水系统中MP监测的研究重点。这篇综述通过检查分布来评估目前对淡水环境中MP监测的理解,特点,和议员的来源,伴随着具有定量证据的分析方法的进展。我们的研究结果表明,国会议员广泛分布在全球淡水系统中,在人类经济活动激烈的地区发现了更高的丰度,比如美国,欧洲,和中国。MP丰度分布在不同的水体中有所不同(例如,河流,湖泊,河口,和湿地),采样方法和大小范围选择显着影响报告的MP丰度。尽管全球做出了巨大努力,对特定地区和设施的MP污染仍缺乏统一的分析框架和理解。未来的研究应优先考虑标准化分析协议和开源MP数据集的开发,以促进数据比较。此外,探索最先进的人工智能的潜力,准确,MPs的大规模建模和表征对于为管理淡水生态系统中的MP污染提供有效策略至关重要。
The escalating production of synthetic plastics and inadequate waste management have led to pervasive microplastic (MP) contamination in aquatic ecosystems. MPs, typically defined as particles smaller than 5 mm, have become an emerging pollutant in freshwater environments. While significant concern about MPs has risen since 2014, research has predominantly concentrated on marine settings, there is an urgent need for a more in-depth critical review to systematically summarize the current global efforts, knowledge gaps, and research priorities for MP monitoring in freshwater systems. This review evaluates the current understanding of MP monitoring in freshwater environments by examining the distribution, characteristics, and sources of MPs, alongside the progression of analytical methods with quantitative evidence. Our findings suggest that MPs are widely distributed in global freshwater systems, with higher abundances found in areas with intense human economic activities, such as the United States, Europe, and China. MP abundance distributions vary across different water bodies (e.g., rivers, lakes, estuaries, and wetlands), with sampling methods and size range selections significantly influencing reported MP abundances. Despite great global efforts, there is still a lack of harmonized analyzing framework and understanding of MP pollution in specific regions and facilities. Future research should prioritize the development of standardized analysis protocols and open-source MP datasets to facilitate data comparison. Additionally, exploring the potential of state-of-the-art artificial intelligence for rapid, accurate, and large-scale modeling and characterization of MPs is crucial to inform effective strategies for managing MP pollution in freshwater ecosystems.