The measurement of microplastics (MPs) in drinking water is moving beyond its traditional role as a research application and becoming part of routine laboratory testing. As regulatory requirements develop, standardized monitoring programs are likely to increase the number of drinking-water samples that laboratories must process.
This creates a need for methods that combine dependable polymer identification with the speed and throughput required for large-scale analysis.
The LUMOS II ILIM, together with the ParticlePlus™ workflow, is designed to meet these requirements. Complete 25 mm filters can be analyzed with a total turnaround time of less than 30 minutes per sample. Automated measurement and AI-based polymer classification provide reproducible, operator-independent microplastic results suitable for routine laboratory use.
This article presents the method used to analyze a drinking-water sample collected in Hungary.
Experimental
ParticlePlus™ is a workflow developed for IR laser imaging (ILIM) microscopes. The study used the following configuration:
- Sample details: A 20 L sample of raw drinking water was collected in Hungary and filtered through a 25 mm Whatman® aluminum oxide filter with a 0.2 μm pore size. The filter was supplied by Eurofins Analytical Services Hungary Kft.
- Measurement setup: Automated whole-filter imaging was performed with the LUMOS II ILIM in transmission mode using the ParticlePlus™ software workflow. The laser wavenumber was stepped at intervals of 4 cm-1 across the MIR fingerprint range from 1800–1250 cm-1.
- Data analysis: After acquisition, the hyperspectral dataset was automatically processed with Bruker’s Microplastic Identifier (MPID), without requiring operator input. The identification threshold was set at 750.
Results
The complete 25 mm filter required 17 minutes from the end of filtration to the final result. Full-filter acquisition of 22.5 million IR spectra took 12 minutes, while automated data processing required a further five minutes.
MPID carried out the microplastic analysis automatically using machine-learning (ML) models for unsupervised particle detection and classification. The software also determined particle-specific characteristics, including size, morphology, and spatial distribution. Further information about MPID is provided in Product Note M210.
In total, 71 particles were detected and identified. These included 59 polymer particles and 12 calcium carbonate (CaCO3) particles, demonstrating that the method can differentiate polymeric material from inorganic particles. Polyethylene (PE) was the most frequently detected polymer, with 21 particles, corresponding to 36% of all identified polymers.
The remaining polymer particles included polypropylene (PP, 11), polyethylene terephthalate (PET, 9), polyamide (PA, 7), and polymethyl methacrylate (PMMA, 1). Based on the volume of water analyzed, the measured concentration was 2.9 MPs per liter.
Detected particle sizes extended from 8 μm to 83 μm. The largest proportion, 43%, was within the 20–50 μm range. This result shows agreement with the particle-size range commonly reported for environmental microplastics in drinking water.
Figure 1. Comprehensive results summary for the drinking water sample. Image Credit: Bruker Optics
The performance of unsupervised polymer classification was demonstrated by comparing the mean spectra of the detected PE and PP particles, the two most abundant polymer groups, with their respective library reference spectra.
The strong agreement between the measured and reference spectra confirms the reliability of the AI-based identification and shows that accurate polymer classification can be achieved within a short analysis time.
Conclusion
- A total analysis time of less than 30 minutes per 25 mm filter supports high-throughput routine testing.
- MPID provides dependable particle detection and classification using unsupervised, AI-based analysis, eliminating the need for manual spectral review.
- Polymer identity, particle size, morphology, and spatial distribution are determined simultaneously, providing detailed characterization of each particle.
- The LUMOS II ILIM combined with ParticlePlu™ provides a suitable solution for large-scale drinking-water monitoring.
The Fastest IR Microscope Ever Built: LUMOS II ILIM
Image Credit: Bruker Optics
Acknowledgments
Produced using materials originally authored by Domenic Dreisbach (PhD), Product Manager, Bruker Optics GmbH & Co. KG.
This information has been sourced, reviewed, and adapted from materials provided by Bruker Optics.
For more information on this source, please visit Bruker Optics.