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Forensic Tracing Systems for Nanoplastics

2026
Yash Bhardwaj, Khushbu Katiyar, Kazi Mizaan, Baljeet Yadav, Anuj Kumar, Sameer Saharan, Mahipal Singh Sankhla

Summary

Nanoplastics—tiny plastic particles too small to see—are showing up everywhere in our environment, but figuring out where they came from and how much we're exposed to has been really hard to pin down. This paper reviews new tools that combine lab techniques (like chemical testing) with AI to better detect these particles and trace them back to their source. This matters because better tracking could eventually help scientists understand our real-world exposure to nanoplastics and assess the health risks they might pose, though this research focuses on building the detection tools rather than proving specific health harms yet.

Nanoplastics are increasingly recognized as a One Health concern because of their persistence, environmental mobility, and potential impacts across interconnected ecosystems, wildlife, and human populations. Their small size and heterogeneous composition make detection, source tracing, and exposure assessment challenging when conventional analytical approaches are used alone. This chapter per the authors discusses an integrated forensic framework combining biotechnological methods with artificial intelligence (AI)-based analytics to improve detection and characterization of nanoplastics across complex environmental matrices. Forensic tracing systems—including molecular assays, spectroscopic and imaging techniques, and bioassays—are examined as complementary approaches for material discrimination, while computational models integrate heterogeneous datasets and strengthen source attribution. Ultimately, this chapter connects automated detection, forensic tracing, and exposure modeling within a One Health framework to support environmental risk assessment and management.

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