Summary
Plastics have become ubiquitous in modern life, and concerns are rising about the presence of microplastics and especially nanoplastics, which—with sizes under 1 μm—are small enough to more readily enter the human body. However, nanoplastics are extremely difficult to detect and characterize due to the need for both nanoscale sensitivity and precise chemical identification. This study addresses that challenge by developing a hyperspectral stimulated Raman scattering (SRS) imaging platform combined with an automated, data-driven plastic identification algorithm capable of analyzing individual micro- and nanoplastic particles with high speed and chemical specificity. After validating that narrow-band SRS enables rapid detection of nanoplastics below 100 nm, the researchers created a robust spectral-matching algorithm to accurately identify common plastic polymers despite the complexities of narrow-band hyperspectral signals. Using bottled water as a real-world test system, the platform detected and identified vast numbers of micro- and nanoplastics, revealing concentrations around 2.4 ± 1.3 × 10⁵ particles per liter, with approximately 90% being nanoplastics—a level orders of magnitude higher than previously reported using less sensitive methods. High-throughput single-particle analysis uncovered remarkable heterogeneity in particle composition and morphology, demonstrating that plastic type and shape are not straightforwardly linked. This multidimensional profiling provides new insights into the largely unexplored world of nanoplastics and establishes powerful analytical tools for future environmental and health research.
PMID: 38190543
PMCID: PMC10801917
DOI: 10.1073/pnas.2300582121
Abstract
Plastics are now omnipresent in our daily lives. The existence of microplastics (1 µm to 5 mm in length) and possibly even nanoplastics (<1 μm) has recently raised health concerns. In particular, nanoplastics are believed to be more toxic since their smaller size renders them much more amenable, compared to microplastics, to enter the human body. However, detecting nanoplastics imposes tremendous analytical challenges on both the nano-level sensitivity and the plastic-identifying specificity, leading to a knowledge gap in this mysterious nanoworld surrounding us. To address these challenges, we developed a hyperspectral stimulated Raman scattering (SRS) imaging platform with an automated plastic identification algorithm that allows micro-nano plastic analysis at the single-particle level with high chemical specificity and throughput. We first validated the sensitivity enhancement of the narrow band of SRS to enable high-speed single nanoplastic detection below 100 nm. We then devised a data-driven spectral matching algorithm to address spectral identification challenges imposed by sensitive narrow-band hyperspectral imaging and achieve robust determination of common plastic polymers. With the established technique, we studied the micro-nano plastics from bottled water as a model system. We successfully detected and identified nanoplastics from major plastic types. Micro-nano plastics concentrations were estimated to be about 2.4 ± 1.3 × 105 particles per liter of bottled water, about 90% of which are nanoplastics. This is orders of magnitude more than the microplastic abundance reported previously in bottled water. High-throughput single-particle counting revealed extraordinary particle heterogeneity and nonorthogonality between plastic composition and morphologies; the resulting multidimensional profiling sheds light on the science of nanoplastics.
Qian N, Gao X, Lang X, Deng H, Bratu TM, Chen Q, Stapleton P, Yan B, Min W. Rapid single-particle chemical imaging of nanoplastics by SRS microscopy. Proc Natl Acad Sci U S A. 2024 Jan 16;121(3):e2300582121. doi: 10.1073/pnas.2300582121. Epub 2024 Jan 8. PMID: 38190543; PMCID: PMC10801917.