环境微纳塑料的分析方法进展

Microplastics, an emerging pollutant, have been a topic of increasing concern in recent years. Establishing reliable detection methods is a key goal for studying the concentration, fate, and ecological risks of microplastics and nanoplastics in the environment. At present, many review papers have outlined various methods of sampling, separation/enrichment, qualitative and quantitative analysis of plastics in different environments, and even proposed 'unified' or 'standardized' methods. However, due to the different research objectives and the maturity of the detection techniques, it is difficult to generalize a set of methods applicable to all monitoring or research. Because of the particle shape and size effects of microplastics and nanoplastics, we define three size categories of microplastics and nanoplastics, namely large microplastics (0.02-5 mm), small microplastics (1-20 μm), and nanoplastics (1-1000 nm) in this review. This article summarizes the research progress of detection techniques and specifies the development goals for the three categories of microplastics and nanoplastics. For large microplastics above 20 μm, there are variouse detection protocols for particle analysis, resulting in inconsistent quality of data and therefore less comparability among reports. Choosing a unified sampling and analysis method is the paramount goal of environmental monitoring. For small microplastics below 20 μm, the determination of concentration is not accurate. Therefore, it is important to develop more reliable, qualitative, and quantitative methods. For particles and water-soluble polymers below 1000 nm, the development of detection methodology is lagging, and efforts should be put on proposing more pretreatment and analysis methods, which will be potential alternative for future environmental monitoring protocol. In future research, we should vigorously develop reliable qualitative and quantitative methods, research on detection of water-soluble polymer and environmental behavior of micro- and nano- plastics, and their predictive models to conduct a comprehensive ecological risk assessment on the basis of more reliable data.