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Microplastic pollution is a growing environmental and health concern, posing serious risks to aquatic ecosystems and human well-being. This review explores recent advancements in optical methods for Microplastic (MP) detection, focusing on Spectroscopic techniques, Imaging techniques, optical sensor technologies, and speckle pattern analysis for their speed, sensitivity, and non-destructive analysis. Emerging techniques such as SERS and FLIM, along with AI-driven computational models, are enhancing automation and accuracy. However, challenges remain, including organic matter interference, diverse particle properties, and the lack of standardised protocols. Ongoing efforts in standardisation and ML integrations are improving detection in complex samples. The review highlights the need for portable, cost-effective technologies and interdisciplinary collaboration to refine detection sensitivity and enable real-time environmental monitoring. Recent innovations, including handheld Raman devices, smartphone-based spectrometers, and deep-learning-enhanced HSI, are paving the way for more accurate MP detection, ultimately supporting pollution mitigation and ecosystem protection.
K. et al. (Mon,) studied this question.