Abstract：
Microplastics (MPs), recognized as emerging pollutants, pose significant potential impacts on the environment and human health. The investigation into atmospheric MPs is nascent due to the absence of effective characterization methods, leaving their concentration, distribution, sources, and impacts on human health largely undefined with evidence still emerging. This review compiles the latest literature on the sources, distribution, environmental behaviors, and toxicological effects of atmospheric MPs. It delves into the methodologies for source identification, distribution patterns, and the contemporary approaches to assess the toxicological effects of atmospheric MPs. Significantly, this review emphasizes the role of Machine Learning (ML) and Artificial Intelligence (AI) technologies as novel and promising tools in enhancing the precision and depth of research into atmospheric MPs, including but not limited to the spatiotemporal dynamics, source apportionment, and potential health impacts of atmospheric MPs. The integration of these advanced technologies facilitates a more nuanced understanding of MPs\' behavior and effects, marking a pivotal advancement in the field. This review aims to deliver an in-depth view of atmospheric MPs, enhancing knowledge and awareness of their environmental and human health impacts. It calls upon scholars to focus on the research of atmospheric MPs based on new technologies of ML and AI, improving the database as well as offering fresh perspectives on this critical issue.
摘要：
微塑料（MPs），被认为是新兴污染物，对环境和人类健康造成重大潜在影响。由于缺乏有效的表征方法，对大气议员的调查还处于起步阶段，离开他们的浓度，分布，来源,对人类健康的影响在很大程度上不确定，证据仍在出现。这篇评论汇编了有关来源的最新文献，分布，环境行为,大气MPs的毒理学影响。它深入研究了源识别的方法，分布模式，以及评估大气MPs毒理学影响的当代方法。重要的是,这篇综述强调了机器学习（ML）和人工智能（AI）技术作为新颖且有前途的工具在提高大气MPs研究的精度和深度方面的作用，包括但不限于时空动力学，来源分配，以及大气议员对健康的潜在影响。这些先进技术的整合有助于对国会议员的行为和影响有更细致的理解，标志着该领域的关键进步。这篇评论旨在深入了解大气议员，提高对环境和人类健康影响的认识和认识。它呼吁学者们专注于基于ML和AI新技术的大气MP的研究，改进数据库，并就这一关键问题提供新的观点。
