Microplastics (MPs), defined as plastic particles smaller than 5 mm, are increasingly recognized as widespread environmental contaminants occurring in aquatic, terrestrial, and atmospheric ecosystems. Their small size, diverse morphology, and complex polymer composition make accurate detection, identification, and quantification analytically challenging. This review summarizes recent advances in analytical techniques for detecting MPs in environmental samples, including microscopic, spectroscopic, mass spectrometric, thermal analytical, hyperspectral imaging, and artificial intelligence (AI)-assisted approaches. The fundamental principles, strengths, and limitations of each technique are critically evaluated in the context of environmental monitoring and analytical performance. Despite considerable progress, significant challenges remain, particularly in the reliable detection of nanoplastics (NPs), real-time in situ monitoring, and the establishment of standardized analytical protocols. Emerging strategies that integrate AI-driven spectral analysis, hyperspectral imaging, and thermogravimetric analysis show promise for improving the accuracy and throughput of MP detection. Overall, this review highlights the importance of integrating conventional analytical methods with advanced computational tools and developing high-throughput, environmentally sustainable detection strategies to improve our understanding of the environmental fate of MPs and NPs as well as support future risk assessment and policy development.
Rehman et al. (2026) studied this question.