Improving Fluorescence and Raman Techniques for Environmental Microplastic Analysis

A recent study conducted at the LaserLaB Amsterdam and Vrije Universiteit Amsterdam (the Netherlands) explored spectroscopic imaging techniques, including Raman and fluorescence microscopy, for characterizing microplastics (MPs), focusing on optimizing sample preparation, particularly density separation, and Nile Red staining. The improved density separation method, using a zinc chloride solution (1.4 g/cm³), achieved a 95% recovery rate. The new system, named Merel’s Environmental Separation System (and given the acronym MESSY) effectively separates MPs from sediment for filtration. The optimized Nile Red staining protocol enables broad categorization of MPs but can be influenced by fluorescent additives. Raman microspectroscopy is recommended for precise polymer identification, with a deep-UV Raman microscope proving effective for discriminating plastics, including carbon black-containing ones. Stimulated Raman scattering (SRS) offers a faster alternative compared to conventional Raman and is most accurate when multiple scans at different sample heights are performed. These advancements will aid future MP detection and quantification in environmental samples. Spectroscopy spoke to Merel Konings, corresponding author of the paper resulting from the study (and the “Merel” mentioned in the name of the system) about her work developing the method.

The primary focus of your paper (1) is on the optimization of the sample preparation methods for microspectroscopic imaging (MSI) techniques based on spontaneous Raman scattering, stimulated Raman scattering (SRS), or fluorescence, including a new design for a density separation apparatus (DSA) and optimization of the Nile Red (NR) staining procedure. What were the weaknesses in previously existing methods that inspired your team to optimize the process?

Fluorescence-based methods for microplastics (MPs) detection had been described by some research groups and Raman-based methods by others, but a direct comparison of their advantages and disadvantages for the same sample had not yet been reported. This gap in the literature underscored the need for a systematic evaluation of these techniques, with the first step being the optimization of methods for analyzing the same sample.

One major challenge in microplastic analysis is the extraction process. MPs are typically extracted via a density separation. However, many existing systems rely on switching valves or require manually transferring the microplastic fraction to a separate system, which increases the risks of sample losses. Additionally, low-density matrix particles often remained in the sample, and while digestion steps could remove them, there is also the risk of degrading certain microplastics.

Another issue was the way microplastics were selected for spectroscopic analysis. At the time of our research, MPs were commonly selected for spectroscopic analysis based on visual inspection under a stereomicroscope—an approach that is both time-consuming and prone to human error. Nile Red (NR) staining, as introduced by Maes et al. (2), offered a promising alternative for more sensitive and selective MP detection and categorization into polar and nonpolar plastics based on solvatochromic properties. However, additional experiments were needed to optimize the staining protocol for environmental samples.

What advantages does your method offer that are superior to other existing methods?

To make the extraction process more reliable and efficient, we developed MESSY- Merel’s Environmental Separation System, which has an integrated density separation and filtration step in a single unit. We were inspired by the JAMSTEC microplastic-sediment separator (JAMSS) (3), a simple two-part glass system. By minimizing transfers and sample handling, MESSY maintains recovery rates comparable to existing systems while uniquely consolidating the entire sample preparation procedure within a single unit—an approach not previously described.

To optimize the NR staining protocol, we systematically tested and optimized solvent composition, staining time, and dye concentration, leading to a more reliable protocol for environmental samples. Additionally, we provided insights into NR’s behavior, helping researchers refine their own protocols for more accurate and efficient MP analysis.

Briefly summarize your findings that resulted from these efforts. Was there anything surprising or interesting?

Our results confirmed that MESSY is highly effective for MPs extraction and recovery, as it integrates density separation, filtration, and optional extraction in a single unit. This design minimizes handling time and contamination risks, achieving an average recovery efficiency of 95 ± 5.5% across different polymer types. MPs are collected on a filter of choice, which allows for further microscopic and spectroscopic analysis.

When it came to optimizing Nile Red (NR) staining, we found that the best contrast between microplastics and the surrounding matrix was achieved when NR was fully dissolved in water–though this required fresh preparation to avoid crystal formation.Interestingly, nonpolar plastics, such as polystyrene, polyethylene, and polypropylene (PS, PE, PP) showed the most distinct fluorescence contrast when the dye concentration was low enough to form not more than a monolayer on the particles. This enabled polymer identification based on fluorescence emission alone, a result not previously reported. However, achieving this optimal contrast requires careful adjustment of dye concentration relative to MP concentration.

Your writing about optimizing the process was followed by an assessment of methods based on fluorescence microscopy, spontaneous Raman scattering microscopy at 532, 785, and 248.6 nm excitation, and SRS microscopy for detection or identification of microplastics. Would you please summarize what this assessment revealed?

Fluorescence microscopy of NR-stained MPs allows detection based on fluorescence intensity and course categorization into polar polyethylene terephthalate, polyamide, and poly(methyl methacrylate) (PET, PA, PMMA) and nonpolar (PS, PE, PP) plastics. The staining also improved detection of black plastics (often containing carbon black), though their fluorescence remained weaker compared to plastics of other colorant composition. However, fluorescent additives in certain plastics strongly influenced the emission color, and organic nonpolar residues such as lipids, might cause false positives. We found the fluorescence microscopy technique a useful asset for rapid detection of MPs, but it cannot provide unambiguous identification of the polymer type. We therefore think the combination of fluorescence microscopy and Raman spectroscopy is very feasible for accurately detecting and identifying microplastics in an environmental sample. Notably, NR does not interfere with Raman spectra when used at reasonable concentrations.

We also evaluated spontaneous Raman spectroscopy for identifying MPs, especially those with different colorants. Our results showed that the choice of laser wavelength significantly impacts its performance: the 532 nm (green) laser is highly efficient but affected by fluorescence and resonance enhancement from colorants. The 785 nm (red) laser provides strong chemical specificity for all polymers but still struggles with polymers containing a high concentration of carbon black. However, the 248.6 nm (deep-UV) laser successfully identified all polymer types, including carbon-black-containing MPs, a previously unreported finding. This makes deep-UV Raman a valuable tool for MP composition analysis. One downside of Raman spectroscopy is that it’s relatively slow (each spectrum takes ~1 second), and mapping a large area of interest is therefore prohibitively time-consuming. Detecting MPs based on NR fluorescence, followed by Raman spectroscopy at target locations for confirmation and identification of the polymer type, would be a much more feasible approach.

Finally, we looked atstimulated Raman scattering (SRS) microscopy, which offers a faster alternative for scanning a large area of interest: the system is 2–3 orders of magnitude faster than conventional Raman mapping when performed at different heights with multiplexing capabilities and provides targeted MP identification (4). This makes SRS a highly promising technique for microplastic analysis in environmental samples.

What difficulties did you encounter in this work, and how did you overcome them?

One of the main challenges with the discussed techniques was the inability to perform multiple analyses on the same sample simultaneously, such as fluorescence microscopy and Raman spectroscopy. To overcome this, we installed a blue laser, guided by a multimode fiber, as an excitation source and put a separate orange filter in front of the oculars for the analyst to look through. This setup enabled precise selection of fluorescent particles for Raman analysis, a combination we found to be very suitable for accurate MPs detection and identification of the base polymer.

How did you process the data to obtain the results you were looking for?

All spectra were processed using MATLAB. Each spectrum was background corrected (5) and then normalized. Since the deep-UV spectra had a lower laser power compared to traditional Raman systems, they were slightly smoothened.

Were there any limitations to this research that are important to note?

This research primarily focuses on the optimization and evaluation of fluorescence and Raman techniques for microplastic analysis. However, quantifying MP concentrations while simultaneously determining their physical properties—the ultimate objective of these techniques—is still a work in progress and has not yet been thoroughly validated. This would require further investigation into the method’s accuracy for environmental samples with reference materials (which are very scarce), control of MP contamination in the lab, and a comprehensive assessment of the extraction procedure. While this is not a direct limitation of the study itself, it is a crucial step toward fully realizing the potential of these analytical techniques.

How could the findings of this method be applied practically in analytical laboratories?

The findings of this study have direct applications in analytical laboratories focused on environmental monitoring and microplastic research. The MESSY system is intended for processing dry samples, such as sediments or suspended matter, as its dimensions are too small to allow density separation of particles dispersed in large volumes of water. Additionally, our insights into Nile Red staining behavior provide researchers with a more reliable approach to refining their protocols, ultimately improving the accuracy and efficiency of microplastic analysis.

The evaluation of excitation wavelengths for Raman spectroscopy offers valuable guidance to researchers working with this technique, helping them optimize their experimental setup based on sample composition and fluorescence interference. Interestingly, while the benefits of deep-UV Raman were first described by Johnson and Asher in 1984 (6), our department has since conducted tests with this technique in various contexts, including plastic recycling and forensic analysis of party drugs. In all cases, regardless of the presence of fluorescent compounds in the samples or carbon black, the main ingredients of the samples could be successfully identified—highlighting the broad potential of this method beyond microplastic research.

Moving forward, are you considering and implementing any improvements to the method?

Yes, we are actively working on further improvements to enhance the method. The effectiveness of fluorescence and Raman-based microplastic analysis heavily depends on the digestion protocol. Without proper digestion, environmental samples can contain large amounts of organic matter, increasing the number of particles on the filter and complicating fluorescence-based detection due to a higher occurrence of false positives. This also makes particle selection for Raman analysis more challenging. While existing literature does provide digestion protocols, they often lack detailed assessments of their impact on the physical integrity of microplastics. Therefore, a key focus of our work now is developing a digestion protocol specifically optimized for microspectroscopic analysis. This will not only reduce false positives in fluorescence microscopy and improve the efficiency of Raman-based identification but also ensure that the physical properties of microplastics are preserved for further analysis.

Are there any next steps in this research?

Absolutely! Microplastic research has been a prominent topic for some time, and rightfully so, given the growing body of evidence on their presence and potential toxicity, as demonstrated by research groups worldwide. However, available information is scattered and difficult to compare. For environmental monitoring, reliable methods are required that allow the analysis of a statistically meaningful number of samples. Our goal is to advance current methodologies by addressing practical challenges associated with fluorescence and microspectroscopic techniques, enabling faster and more accurate microplastic analysis.

Right now, we’re focused on improving fluorescence and microspectroscopic techniques to make microplastic analysis faster and more accurate. For fluorescence microscopy, we’re developing an automated method using an in-house MATLAB algorithm to detect, categorize, and semi-quantify microplastics on filters. Instead of manually inspecting each sample, the algorithm analyzes fluorescence intensity, emission color, and particle shape, which could make screening much quicker and more cost-effective. When higher accuracy is required, this method could also act as a pre-selection step for Raman spectroscopy, helping to target specific particles for further analysis.

Looking ahead, we aim to integrate fluorescence microscopy and Raman spectroscopy into a single system, allowing the algorithm to pinpoint coordinates for automated Raman analysis, thereby streamlining the workflow to allow a faster and more accurate analysis of MPs in an environmental sample. Ultimately, our objective is to refine these techniques for simultaneous quantification of microplastic concentrations and characterization of their physical properties, contributing to a more comprehensive assessment of MP exposure and potential environmental hazards. Another future goal is the detection of nanoplastics (7) that currently remain undetected with most techniques but could potentially be more harmful than microplastics. That’s definitely a challenge we’re excited to take on!

This is the first of what I am sure will be many published papers that you will be a part of as your career progresses. What are your feelings regarding this achievement?

I'm incredibly grateful to my supervisor, Dr. Freek Ariese, for giving me the opportunity to publish my bachelor's research and present it at both national and international conferences. It’s been an amazing journey—I've learned so much, from developing research skills to figuring out how to communicate my findings effectively. Seeing people engage with our work has been really rewarding, and it’s made me even more excited about academia. Publishing this paper taught me to be critical of my own work and to share it in a way that’s clear and impactful. More than anything, this experience has strengthened my passion for research and inspired me to pursue a PhD. I want to keep contributing to meaningful research that, hopefully, makes a difference in the world.

References

1. Konings, M. C.; Zada, L.; Schmidt, R. W.; Ariese F. Optimization of Sample Preparation, Fluorescence- and Raman Techniques for Environmental Microplastics. Spectrochim. Acta A Mol. Biomol. Spectrosc. 2024, 319, 124537. DOI: 10.1016/j.saa.2024.124537

2. Maes T.; Jessop, R.; Wellner, N.; Haupt, K.; Mayes, A. G. A Rapid-Screening Approach to Detect and Quantify Microplastics Based on Fluorescent Tagging with Nile Red. Sci. Rep. 2017, 7, 44501. DOI: 10.1038/srep44501

3. Coppock, R. L.; Cole, M.; Lindeque, P. K.; Queirós, A M.; Galloway, T. S. A Small-Scale, Portable Method for Extracting Microplastics from Marine Sediments. Environ. Pollut. 2017,230, 829-837. DOI: 10.1016/j.envpol.2017.07.017

4. Zada, L.; Leslie, H.A.; Vethaak, A.D.; Tinnevelt, G. H.; Jansen, J. J.; de Boer, J.F.; Ariese F. Fast Microplastics Identification with Stimulated Raman Scattering Microscopy. J.Raman Spectrosc. 2018, 49, 1136-1144. DOI: 10.1002/jrs.5367

5. Background correction. MATLAB Help Center website.https://www.mathworks.com/matlabcentral/fileexchange/27429-background-correction (accessed 2025-03-12)

6. Johnson, C. R.; Asher, S. A. A New Selective Technique for Characterization of Polycyclic Aromatic Hydrocarbons in Complex Samples: UV Resonance Raman Spectrometry of Coal Liquids. Anal. Chem. 1984, 56, 2258-2261. DOI: 10.1021/ac00276a065

7. Huber, M.J.; Zada, L.; Ivleva, N.P.; Ariese F. Multi-Parameter Analysis of Nanoplastics in Flow: Taking Advantage of High Sensitivity and Time Resolution Enabled by Stimulated Raman Scattering. Anal. Chem. 2024, 96, 8949–8955.DOI: 10.1021/acs.analchem.3c05881

Merel Konings is a master's student in chemistry (analytical sciences) at the University of Amsterdam and Vrije Universiteit Amsterdam. She earned a bachelor’s degree in (analytical) chemistry with honors from Leiden University of Applied Sciences and is close to graduating from the MSc-program. She is currently completing her graduation internship at the Analytical Chemistry Group, Van 't Hoff Institute for Molecular Sciences at the University of Amsterdam. Under the supervision of Prof. Maarten van Bommel and Dr. Bob Pirok, Merel focusses on optimizing active modulation techniques in liquid chromatography to study light-induced degradation of dyes used in art objects. She also works part-time as a student assistant at LaserLaB Amsterdam/Vrije Universiteit Amsterdam in the Department of Biophotonics and Medical Imaging, where, under the guidance of Dr. Freek Ariese, she optimizes fluorescence and Raman techniques for microplastic analysis. Photo courtesy of Konings.