Tracking Metal Contamination on Microplastics

Microplastics, which are small fragments of plastic no more than 5 mm in length, remain an ongoing environmental problem.^1,2 Because these tiny fragments of plastic are easy to miss, they are pervasive in the environment, whether in water or on land. As a result, researchers have been exploring new methods to detect and quantify microplastics.¹

In a recent study, a team of researchers at the Gwangju Institute of Science and Technology in South Korea have developed a single optical platform that can identify plastic particle type and quantify adsorbed heavy metals from the same measurement spot, which addresses a longstanding gap in microplastic contamination monitoring.³ The findings from this study were published in the journal Analytical Methods.³

What is the platform the researchers developed?

The system the researchers built integrates laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy along a shared optical path. This design allows both molecular and elemental data to be collected consecutively from the identical location on a microplastic particle, which is a capability the authors say conventional workflows cannot offer without separate instruments and sample preparation steps.³

What problem were the researchers trying to solve in their study?

Microplastics are increasingly recognized as vectors for toxic metals and organic pollutants, which can adsorb onto particle surfaces in contaminated water and soil.³ Understanding which metals bind to which polymer types is central to assessing environmental risk and potential toxicity pathways.³ The problem is that standard approaches have key limitations. These limitations include measuring bulk samples and an inability to correlate a specific contaminant with a specific particle.³ The new platform targets that limitation directly, enabling single-particle-level correlation between polymer identity and metal burden.³

How did the researchers test their system in their study?

Three certified plastic bead types (in this case, polystyrene (PS), polyethylene (PE), and polypropylene (PP)) were used in the study. The researchers used Raman spectroscopy to distinguish the three polymers using their characteristic vibrational bands.³

Simulating environmental contamination required the researchers to immerse PS beads for five days in lead and copper solutions at concentrations ranging from 1 to 1,000 ppm.³ LIBS analysis of the exposed beads detected distinct emission lines for lead (405.8 nm) and copper (324.8 nm), with signal intensity scaling to concentration within a linear range below 100 ppm, where self-absorption effects remained minimal.³

What were the results of the study?

The researchers found that quantitative calibration produced limits of detection of 2.29 ppm for lead and 1.61 ppm for copper.³ These thresholds align with metal concentrations reported for microplastic surfaces in contaminated aquatic environments, suggesting the instrument's sensitivity is appropriate for real-world screening rather than laboratory demonstration alone.³

On the molecular side, machine learning (ML)-based clustering of the Raman spectra achieved unsupervised classification accuracy of up to 99.3% in sorting the polymer types without prior labeling.³

What was the trade-off the researchers made in this study?

One aspect to this system that the researchers noted was that they had to sacrifice maximum achievable sensitivity for practicality. By using nanosecond-pulse LIBS instead of calibration-free variants, the researchers achieved robust low-ppm quantification combined with compatibility for semi-portable instrumentation.³

What is next in this research area?

Current laboratory-scale LIBS instruments perform similarly well when compared with the research team’s combined platform. To build on this study, the researchers point to mid-level data fusion as a logical next step, seeing as it would allow for automated classification of particles by both polymer type and contamination level in a single pass.³

Such a capability, the researchers say, would support higher-throughput, in situ environmental monitoring and risk assessment for microplastic pollution, moving the technology from proof-of-concept toward field deployment.³

References

1. Workman, Jr., J. A Review of Spectroscopic Techniques used for the Quantification and Classification of Microplastics and Nanoplastics in the Environment. Spectrosc. Suppl. 2024, 39 (wp11). DOI: 10.56530/spectroscopy.ac7567r4
2. Wetzel, W. Detecting Environmental Microplastics and Nanoplastics With Spectroscopy. Spectroscopy Online, 2026. https://www.spectroscopyonline.com/view/detecting-environmental-microplastics-and-nanoplastics-with-spectroscopy (accessed August 25, 2026).
3. Shin, S.; Park, J.; Kong, D.-J. Integrated LIBS-Raman Spectroscopic Platform for Concurrent Elemental and Molecular Analysis. Anal. Methods 2026, 18 (6), 1270–1278. DOI: 10.1039/d5ay01789k