Nile Red staining for the detection of microplastics: a comprehensive study on the emission spectra

doi:10.21203/rs.3.rs-2579237/v1

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Nile Red staining for the detection of microplastics: a comprehensive study on the emission spectra

https://doi.org/10.21203/rs.3.rs-2579237/v1

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Several research groups have explored Nile Red staining of artificial and natural environmental samples to provide an inexpensive and relatively fast analysis tool for identifying microplastics. Yet, most of these studies were based on a limited set of polymer samples, and primarily base polymers were investigated, i.e., uncolored and non-weathered polymers. Hence, the influence of pigments, weathering or erosion on the luminescence of stained microplastics is not yet well understood. To fill this gap, we performed photoluminescence (PL) spectroscopy and photoluminescence excitation spectroscopy on a variety of Nile Red-stained plastics and non-plastic samples. The investigated sample set includes commercially available plastic samples to investigate how additives and pigments in the polymer material impact the PL spectra via their auto-fluorescence. Besides, we study the influence of surface roughness on the emitted PL. Finally, we examined 20 microparticles collected from the Lahn River using PL spectroscopy to cross-validate our observations.

Nile Red

Photoluminescence spectroscopy

microplastic identification

In the field of microplastics, chemical identification and imaging methods are extensively explored to study the abundance [1, 2], breakdown [3, 4], sources [5], transport [6], and impacts of microplastics [7–9]. Furthermore, extensive studies are performed to quantify the microplastic contamination in sediment, water, or food samples. In most of these studies, state-of-the-art methods such as Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopy are utilised. However, these methods are laborious and expensive [10]. Besides, FTIR is limited to particle sizes larger than 10 µm due to the diffraction limit of the excitation beam [11]. The other technique, Raman spectroscopy, is relatively time-consuming [10] and requires extensive data processing to subtract the fluorescence originating from additives and pigments [12, 13].

Recently, other spectroscopic approaches have been explored, including laser-induced breakdown spectroscopy[14] and time-integrated [15, 16], as well as time-resolved PL spectroscopy [17]. Time-integrated PL is inexpensive yet less precise than the other mentioned methods when identifying the polymer class. Besides, the external quantum yields of plastics are low, leading to long integration times, particularly for base polymers, i.e., plastics to which no pigments have been added. Polymers containing additives and especially pigments could show much stronger photoluminescence. Yet, in general, particular pigments will alter the emission spectra of the base polymers, making it challenging to identify the polymer class.

Fortunately, another technique has been demonstrated: staining microplastics with different solvatochromic dyes. Several researchers investigated different solvatochromic dyes to stain microplastics: Maes et al. 2017 tested oil red EGN, Eosin B, Rose Bengal, Hostasol Yellow 3G, and Nile Red [18], Prata et al. 2019 tested Acridine Orange, Basic Blue 24, Crystal Violet, Lactophenol Blue, Neutral Red, Safranin-T, Tryphan Blue, and Nile Red [19], Sturm et al. 2021 tested Nile Red and its derivates [20] and Aoki 2022 tested fluorescein, Rhodamine 6G and Nile Red [21]. All the four studies declared Nile Red as the most efficient dye in staining plastics. Furthermore, Sancataldo et al. 2021 tested the dye 4-dimethylamino-40-nitrostilbene (DANS) on five different virgin microplastics. [22]. High fluorescence affinity to plastics and their corresponding spectral shifts, make DANS and NR a promising choice for microplastic staining. We chose to further exploit the utility of the most researched dye-Nile Red [21] in our study. NR allows for distinguishing microplastic particles from most of the non-plastic particles. The dye preferentially connects to polymer materials but adheres much less to natural particles. This approach requires an additional preparation step but produces a very strong photoluminescence from the stained plastics.

The cited previous studies proposed detection methods to separate plastics from non-plastics by testing them on a limited set of plastics. The detection conditions were arbitrarily chosen covering the UV, blue, green, and red regions for both the excitation and emission. Several of these studies have suggested an additional step of digestion with hydrogen peroxide to avoid false positives generated from fluorescent chitin-based non-plastics [23]. Furthermore, these studies have not addressed the changes in NR-based fluorescence of plastics in the presence of additives and pigments. For a further elaborate review on different studies on analysis of Nile Red stained microplastics refer to Shruti et al. 2021 [24].

In 2020, we published a preliminary study exploring the potential of PL spectroscopy for the first time on a limited set of NR-stained plastics and non-plastics [25]. We demonstrated that acquiring full PL spectra provides useful additional information, enabling the differentiation of four investigated virgin plastic pieces into polar and non-polar categories.

Certainly, it is desirable to identify the individual polymer materials, just as can be done with FTIR spectroscopy and Raman spectroscopy. However, the shape of a photoluminescence spectrum results from the superposition of the weak intrinsic photoluminescence of the base polymer, the photoluminescence of a possibly added pigment or additive, and the photoluminescence of the NR dye. Hence, an identification of the base polymer can be difficult with the NR method if real colored plastic particles are investigated.

Yet, it is entirely sufficient for some applications to distinguish between synthetic polymers and natural materials. For example, it may be a question of how heavily a certain section of a river is polluted with microplastics. Once the areas of high contamination are identified, some cleaning processes can be carried out at these spots. In this case, it is not essential to distinguish different polymer materials. Besides, for scientific studies which aim for a detailed analysis of microplastic samples, NR staining and photoluminescence spectroscopy or imaging could be an essential first step to separate microplastic particles from non-plastic particles. The investigation with an FTIR spectrometer can be carried out in a second step, as staining with NR does not significantly change the FTIR spectrum [18, 26]. Such a protocol was already shown by Maes et al. in 2019 [18].

In this paper, we present a spectroscopic study on a much larger data set of NR-stained materials than in our previous publication [25]. In particular, we include colored plastics with pigments and additives and validate our observations on real microplastics collected from a river. Furthermore, we examine how the surface roughness of plastic particles affects the PL spectra. In addition, we perform photoluminescence excitation (PLE) spectroscopy to determine the optimum excitation wavelength for NR-stained materials.

Investigated samples

To analyse a wider variety of plastics, thirteen different plastic types (Table 1) were obtained from five different sources. The raw material in the form of pre-production pellets were obtained from Reinhard Bretthauer GmbH (PE-LD, PE-HD, PP, PS, PET, PA, PC, PMMA, ABS, SAN, POM, TPU) and Plastic World Solutions GmbH (PVC). Commercially available foils with different colors (PP, PVC) were obtained from Modulor GmbH. Post-consumer plastics were collected based on the RIC labels from different supermarkets. Two recycled plastic types (PA, PC) were collected from General Industries Deutschland GmbH. The non-plastics shown in this paper, such as wood, sediment, chitin-based organics, leaves, roots, and stems, were collected from the natural environment.

Table 1

List of plastic samples investigated.
Provider	Polymer type	Form
Reinhard Bretthauer GmbH	LDPE, HDPE, PS, PET, PP, PA, PC, PMMA, ABS, SAN, POM, TPU	Pre-production pellets
Plastic World Solutions GmbH	PVC	Pre-production pellets
Modulor GmbH	PP, PVC	Colored foils
General Industries Deutschland GmbH	PA, PC	Recycled pellets
Post-consumer waste	PE-LD, PE-HD, PS, PET, PP	RIC labeled plastic

To validate our observations, 20 microparticles (> 1 mm) were obtained from Lahn River sediment samples. The sediment samples underwent MPSS-based density separation with sodium chloride after Weber et al. [27]. The size fractionation of this sample was performed following the protocol of Prume et al. [28]. After density separation and size fractionation, potential microplastic particles were identified with stereo microscopy, and the chemical identification was performed with µATR-FTIR spectroscopy.

Methods

Staining protocol

The staining protocol for all the experiments in this paper was performed after Konde et al.. The samples were stained for 10 min at 50°C with 50 µg/ml of NR dissolved in equal volumes of ethanol and acetone [25].

Experimental setups

PLE spectroscopy is an optical method in which the PL emitted from a sample is measured as a function of the excitation wavelength. The PL is monitored at a wavelength close to the maximum of the emission spectrum. Here, the PLE spectra were obtained using an FL-2500 spectrofluorometer (HITACHI). A 300 nm/min scan speed with no cycle time and without additional filters was used. Three replicates each from a different spot on single sample were acquired. Since many NR-stained plastics show the most intense luminescence in the range between 600 and 620 nm [25] the detection window was set to 620 nm. The detection window had a spectral width of 2.5 nm, and the excitation window had a spectral width of 5 nm.

The PL spectra were obtained using a self-built PL setup (Fig. 1). A 495 nm longpass (LP) filter was placed in front of the fiber to block the entering of excitation light into the spectrometer from Lasertack GmbH (model LR2, in the 300–1000 nm configuration). Based on the obtained PLE spectra, we chose an excitation wavelength of 450 nm (700mW blue Laser module from Insaneware.de). All the PL spectra were recorded under the same excitation and acquisition conditions. The same accounts for the set of PLE spectra. Moreover, for better comparison, all intensities were normalized to values between 0 and 1. To account for surface inhomogeneities, the samples were measured multiple times at different spots. The measured curves were averaged so that the mean is shown as a solid line in the appropriate color, and the error bars are shown as slightly paler bands around the curves.

The samples taken from the field were investigated with a different procedure. After staining these particles with Nile Red, they were first examined using a fluorescence imaging system. The basic concept of this setup is similar to that of the setup shown in Fig. 1. However, instead of a laser, here we used for optical excitation an LED in combination with a band-pass filter. The resulting spectrum used for the excitation of the sample is centred around 440 nm and has a spectral width of 25 nm. It is shown in the SI in Figure S4. The LED emission was unfocused to excite an extended sample area. This means that the excitation density in these experiments was much lower than in the measurements in which the luminescence spectrum of the materials was determined. Furthermore, no spectrometer was used, but the emission of the two-dimensional sample was imaged onto a CCD chip. A 495 nm longpass filter was placed in front of this chip to block the excitation light.

For the ATR-FTIR measurements, which we carried out to classify the microparticles obtained from the Lahn River, we used a Lumos II microscope (Bruker Optics GmbH, Ettlingen). Samples were measured with 50 scans, open aperture, and low crystal (germanium) pressure. After the measurement, the resulting spectra were subjected to an atmospheric compensation (CO₂, H₂O) using the operating software OPUS (version 8.5.29).

PL and PLE spectra of Nile Red solution and stained plastics

Spectra of base polymers

The PLE and PL spectra of the NR solution are shown in Fig. 2 in the top left panel of the figure. It can be seen that the NR solution can be excited particularly well in the regions around 450 and 470 nm as at both wavelengths PLE maxima are observed. The emission of the NR solution is strongly red-shifted and shows its maximum around 630 nm. The emission spectrum is otherwise structureless and slightly asymmetric, with a longer tail towards the longer wavelengths.

The other panels in Fig. 2 show the spectra of base polymers stained with NR solution. For all spectra shown, the solvent has evaporated, and the NR molecules cover the surface of the plastics.

The interaction of the dye molecules with the polymers changes both the PLE and PL spectra. The Stokes shift between the spectra is much smaller than that observed in the case of the NR solution. The excitation maximum at 470 nm is still observed. The optimal excitation window shifts towards longer wavelengths. The maximum absorption for all polymers stained with NR is around 520 nm. These data show that excitation at 405 nm, as proposed in our previous publication [25] seems to be suboptimal for the excitation of NR-stained plastics.

The emission spectra of a few NR-stained plastics (PP, PE-LD, and PE-HD) show peaks positioned around 530 nm, i.e., at the same wavelength at which the excitation wavelength is optimal, based on the PLE spectrum. For this reason, we suggest an excitation wavelength between 450 and 480 nm. This avoids that the filter, which must be used to suppress the excitation laser, cuts the spectral window for the detection of PL too much. In addition, the spectral tails of the excitation laser will not protrude into the PL detection window. Within this range there are several laser/ LED light sources. We, however, used a 450 nm laser for the excitation for the superior spectral characteristics and general commercial availability.

It is known that the emission spectra of Nile Red shifts with the polarity of the solvent (solvatochromic behaviour) [29]. Since different plastics have different surface polarities, it is not surprising that the emission of Nile Red molecules on the sample surface also shows different emission maxima for different plastics. This can be observed in Fig. 2; the spectra are sorted by their emission maximum. PP has the emission maximum at the shortest wavelength, and the emission of TPU peaks at the longest wavelength.

Based on Fig. 2, one may be tempted to identify the base polymer on the basis of the spectral PL maximum or at least to establish categories that correspond to the polarity of the polymer. Unfortunately, this is not possible for real-world samples. As we show in the following, the emission spectra can change considerably due to pigments in the polymer. Furthermore, surface roughness, which will occur as a consequence of aging, can lead to small additional shifts of the PL maxima. One should also be aware that the PL emission maxima depend on the staining protocol. This aspect is discussed in the SI (Figure S1).

Influence of pigments

Most of the microplastics found in the environment are not base polymers but originate from consumer products. In these plastic pieces, typically additives have been added to the base polymers to change the polymer properties. In particular, in most cases, pigments have been added to give the polymers a color.

On some spectroscopy techniques the presence of pigments will have little effect. The influence on FTIR spectra, for example, is very small since the polymer matrix around the pigments is still present and causes signals that are practically unchanged. The situation is different for autofluorescence. In this case, the pigments lead to additional photoluminescence signals that can superimpose the luminescence of the base polymers. Hence, the question arises of how the presence of pigments affects the spectra of NR-colored polymers.

To answer this question, we have stained a large number of consumer products using the NR staining protocol described in the methods section. The polymer type was identified by the RIC label. Figure 3 shows exemplary spectra obtained for PP and PET-based polymers. The spectra were normalized and offset for clarity. The colors of the individual curves correspond to the colors of the plastic pieces.

The lower two curves shown in grey in both parts of the figure were obtained from base polymers, i.e. polymers that were transparent (grey dashed lines in Fig. 3) or contained white (grey solid lines in Fig. 3) pigments but no colored pigments. They correspond to the curves we already know from Fig. 2. In the case of PP, for example, there are green or blue curves that show an almost identical course. These were obtained on green or blue PP-based consumer products. However, there are also red curves or black curves that show a clearly different progression. For PET, too, it can be seen that the pigments significantly change the spectra of NR-stained polymers.

These observations, that green or blue pigments do not significantly change the spectra of PP, or that red or black pigments necessarily change the spectra of PET, can certainly not be generalized because there are many different pigments for each color. For this reason, one should draw the conclusion that it will not be possible to infer the composition of an NR-stained polymer on the basis of a photoluminescence spectrum. Further spectra for PE, PS, and PVC are shown in the SI (Figure S2) to support this conclusion.

Figure 3. Photoluminescence spectra of several NR-stained PP and PET based consumer plastics. The colours of the spectra indicate the color of the plastic pieces. The grey solid lines indicate spectra obtained on white samples, and the grey dashed lines represent spectra obtained on transparent samples. The shaded region indicates the deviations in spectra due to sample non-homogeneity.

Influence of physical degradation of plastics

As most microplastic particles from the environment underwent physical degradation and, hence, are likely to have rough surfaces, we investigate in the following how changes in surface roughness affect the spectra of attached NR molecules. We investigate this for PS as an example. Before staining, a flat PS plate was roughened using five different emery papers with different grits: 60, 150, 320, and 600 (i.e., the lower the number, the higher the surface roughness). The PL spectra are shown in Fig. 4.

As can be seen, the fluorescence intensity increases with increasing surface roughness. Besides, one can notice a slight spectral red shift with increasing surface roughness. The surface roughness of microplastics is generally high due to physical degradation. Thus, microplastic particles found in the environment can be expected to be more luminous than a smooth industrial sheet of virgin plastic. Generally, this is, of course, advantageous for a good detection rate.

Figure 4. Photoluminescence spectra that were obtained on an NR-stained roughened PS sample plate. The variations in fluorescence intensity are shown on the left, while the variation in spectral shape is shown with normalised spectra on the right. The sample plate was sectioned and roughened with emery paper of different grits, as mentioned in the legend.

Field samples

Finally, we discuss the spectra of real NR-stained microplastic particles and non-plastic particles that were found in a river sediment sample. Twenty microparticles obtained from sediment samples from the Lahn River were examined. Based on the µATR-FTIR measurement, within the 20 microparticles, nine were identified as plastics and eleven as non-plastic materials. In addition, the plastic type of all nine plastic microparticles could be determined.

Of the 20 particles studied, only ten show pronounced luminescence when excited with the unfocused LED. The particles that do not show luminescence under these excitation conditions are all natural materials. For those, a luminescence spectrum can be obtained when the more intense and focused laser is used (compare Fig. 1). These spectra are shown in figure S3 of the SI. These spectra often differ significantly from those of NR-stained plastics (see also Fig. 8 in Konde et al. [25]).

A photo of the luminescent particles is shown in Fig. 5(A). As we will show below, these are the nine plastic particles and one non-plastic particle. This, of course, is exactly the desired result. Plastic particles show a more pronounced luminescence and can thus be differentiated from non-plastic particles.

In Fig. 5(A), the ten particles are numbered. The table in Fig. 5(B) shows which particles are involved. The luminescence spectra of these samples was determined using the setup shown in Fig. 1 The spectra are shown in the four sub images in Fig. 5(C); to have a direct comparison, spectra obtained on base polymers are inserted and are indicated with grey color curves.

The observation made here is consistent with the conclusions drawn earlier in the manuscript. Many of the real microplastic particles stained with NR show a spectrum which is clearly different from the spectrum obtained for the base polymer of which they are mostly composed. This is particularly clear in the case of PE. In the case of PP, the spectra are less different from those of the base polymer. However, this is probably a coincidence since only a few particles were examined here. In Fig. 3, there were also many spectra for PP-based plastic materials that deviated from those obtained for pure PP.

Of course, it is not completely excluded that there may be individual plastic particles that show only a weak luminescence, and which are, therefore, not spotted by this method.

All in all, this examination of real microplastic samples obtained from the field again shows that they can be detected rather reliably by their luminescence strength. Yet, individual non-plastic particles from the environmental matrix also show significant luminescence and could lead to some false positives. Yet, these will be discovered during a subsequent investigation, e.g., with FTIR spectroscopy. Besides, staining a sediment sample with NR can be very helpful in estimating the total microplastic load of the sample.

We have shown that NR staining works well to distinguish plastics from non-plastics based on their luminescence spectrum. This is in line with earlier work. Besides, we have shown that the ideal excitation wavelength to detect stained microplastics is lies the range between 450 and 480 nm.

The NR spectra depend on the polarity of the material and are thus, in principle sensitive to the plastics type. Thus, a classification of the polymer type might work for base polymers. But it does not work for real-world microplastics, as demonstrated in this paper. In real-world samples, pigments have in many cases a strong impact on the luminescence spectrum of NR-stained plastics. Furthermore, we have shown that surface roughness gives rise to small spectral shifts of the PL spectrum.

NR: Nile Red, PL: Photoluminescence, PLE: PL excitation, FTIR: Fourier-transform infrared spectroscopy, µATR-FTIR: micro-Attenuated total reflectance FTIR, LP: long pass, MPSS: MicroPlastic Sediment Separator MPSS, UV: ultraviolet, DANS: dye 4-dimethylamino-40-nitrostilbene, Polymer abbreviations (e.g., PE): Listed in Table S1, LED: light emitting diode, CCD: Charge-coupled device,

a. Ethics approval and consent to participate

Not applicable.

b. Consent for publication

Not applicable.

c. Availability of data and material

The datasets generated during and/or analyzed dur-ing the current study are available from the corresponding author on reasonable request.

d. Competing interests

The authors declare that they have no competing interests.

e. Funding and acknowledgements

This work was in part supported by the state of Hesse by the following two LOEWE-Exploration Grants (Grant No. III L5 - 519/06/000.002-(0005)) and (Grant No. Ill L 5- 519/06/00.002-(0009))

f. Authors' contributions

S.K. built, conducted, and evaluated the PL measurements, J.P. conducted and evaluated FTIR measurements, S.K. and M.K. analyzed the results, S.K and M.K. wrote the manuscript, S.B., M.G., and M.K. supervised the project. All authors reviewed the manuscript.

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No competing interests reported.

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Nile Red staining for the detection of microplastics: a comprehensive study on the emission spectra

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Abstract

Figures

Introduction

Materials And Methods

Investigated samples

Methods

Staining protocol

Experimental setups

Results & Discussions

PL and PLE spectra of Nile Red solution and stained plastics

Spectra of base polymers

Influence of pigments

Influence of physical degradation of plastics

Field samples

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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