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Recent progress and technological advancements for detection of micro/nano-plastics in the environment
Summary
This review surveys the latest analytical tools for detecting micro- and nanoplastics across environmental samples, covering imaging, spectroscopy, electrochemical sensors, and artificial intelligence. It highlights how the very small size and chemical complexity of nanoplastics makes detection especially challenging, and discusses how AI integration is improving accuracy and throughput. Advancing detection methods is foundational to understanding the true scale of microplastic contamination and its risks to ecosystems and human health.
Micro and nanoplastics (MNPs) are an omnipresent and analytically challenging contaminant class that has been emerged in aquatic, terrestrial, atmospheric, and alimentary matrices. The diminutive dimensions and wide prevalence of MNPs in complex mixtures render their detection especially challenging. This review evaluates the state-of-the-art analytical strategies for detection of MNPs, classified as per imaging-based approaches, spectroscopy techniques, and other emerging practices such as electrochemical sensing platforms and artificial intelligence (AI) integration. The analysis critically deliberates the impact of the colloidal properties of MNPs on the performance of sensors. The colloid and interface science can help to decode the physicochemical behavior of MNPs, which may aid in sensor design. The integration of AI approaches with different detection modalities possess the capability to extract latent features from noisy spectral and imaging data, enhancing efficiency and scalability of the existing detection techniques. This review also evaluates the capabilities of remote monitoring platforms, including hyperspectral imaging. The performance of these conventional and advanced approaches is critically evaluated for MNP analysis in real-field. The choice of a particular approach is dependent on the type of information required from the sample. The integration of different sensing modalities can help in realization of scalable and real-time monitoring of MNPs in several environmental metrics. Finally, future perspectives are discussed to advance the analytical sensitivity of MNPs detection approaches, along with their harmonization to address the global issue of MNP pollution.
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