Journal of Oceanology and Limnology   2020, Vol. 38 issue(5): 1502-1516     PDF       
http://dx.doi.org/10.1007/s00343-020-0129-z
Institute of Oceanology, Chinese Academy of Sciences
0

Article Information

LIU Jing, ZHANG Xin, DU Zengfeng, LUAN Zhendong, LI Lianfu, XI Shichuan, WANG Bing, CAO Lei, YAN Jun
Application of confocal laser Raman spectroscopy on marine sediment microplastics
Journal of Oceanology and Limnology, 38(5): 1502-1516
http://dx.doi.org/10.1007/s00343-020-0129-z

Article History

Received Mar. 17, 2020
accepted in principle May. 7, 2020
accepted for publication Jul. 7, 2020
Application of confocal laser Raman spectroscopy on marine sediment microplastics
LIU Jing1,3,4, ZHANG Xin1,2,3,4, DU Zengfeng1,4, LUAN Zhendong1,4, LI Lianfu1,3,4, XI Shichuan1,3,4, WANG Bing1,4, CAO Lei1,4, YAN Jun1,4     
1 Key Laboratory of Marine Geology and Environment & Center of Deep Sea Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;
2 Laboratory for Marine Geology, Pilot National Laboratory for Marine Science and Technology(Qingdao), Qingdao 266237, China;
3 University of Chinese Academy of Sciences, Beijing 100049, China;
4 Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China
Abstract: Marine sediment is the primary sink of microplastics and is an indicator of pollution levels. However, although there are well-developed detection methods, detection is rarely focused on lowmicrometer-sized particles, mainly due to technique limitations. In this study, a simplified process omitting digestion procedures was developed to pretreat microplastics obtained from marine sediment and was coupled with micro-Raman spectroscopy to identify microplastics. Based on the overall analysis of the characteristic peak assignments, a Raman spectral reference library was constructed for 18 types of plastic. In addition, the effects of the measurement parameters were systematically described. Field research was then conducted to validate the developed process and investigate microplastic contamination in Huiquan Bay, Qingdao, China. This simplified process could retain the original appearance of microparticles and accomplish the detection of < 500 μm-sized microplastics in environmental samples. Microplastics in the size range of 10-150 μm accounted for 76% of all microplastics, and 56% of the total particles was particles smaller than 50 μm. Polypropylene (42%) and polyethylene (20%) were predominant components of the particles. In particular, polypropylene particles smaller than 10 μm were identified in marine sediment. This work demonstrates that Raman spectroscopy is not only an effective tool for detecting environmental particles but also highly applicable for identifying particles extracted from marine sediment.
Keywords: microplastics    confocal    Raman spectroscopy    marine sediment    
1 INTRODUCTION

Microplastics have aroused global attention in recent years due to their wide distribution within the ecosystem (Browne et al., 2007; Andrady, 2011; Cole et al., 2011; Sun et al., 2016). Since the first report of microplastics in the western Sargasso Sea, microplastics have been found in multiple coastal areas and the deep sea ocean (Carpenter and Smith, 1972; Thompson et al., 2004; Cózar et al., 2014), in the Antarctic (Waller et al., 2017), in the Mariana Trench (Chiba et al., 2018), within marine organisms (Sun et al., 2018), and even in human bodies (Carbery et al., 2018). Marine sediment is regarded as a sink for microplastics (Kanhai et al., 2019). Although numerous experiments have been established for marine sediment (Van Cauwenberghe et al., 2015), identification protocols have varied across the various research areas (Qiu et al., 2016), and there is, as of yet, no optimized method for sediment detection (Hanvey et al., 2017).

The sample detection process consists of separation pretreatment and identification steps (Hanvey et al., 2017). Since the microplastics in the marine sediment are dispersed, particles should be concentrated by density flotation (Van Cauwenberghe et al., 2015). However, organic debris and colored pigments could interfere with the characteristic spectral peaks (Lenz et al., 2015). Therefore, complex digestion methods, such as those using acids (Claessens et al., 2013), bases (Claessens et al., 2013; Foekema et al., 2013), oxidation (Nuelle et al., 2014), and enzymes (Cole et al., 2014) are needed before detection.

Appropriate identification tools must be selected to evaluate microplastics (Song et al., 2015). Visual inspection could be an immediate and convenient method (Hidalgo-Ruz et al., 2012), but due to the strong subjective influence, the accuracy of sample identifications is not guaranteed (Lenz et al., 2015; Löder et al., 2015). Scanning electron microscopy (SEM) could be used to generate sufficiently highresolution images (Fischer et al., 2012), but the chemical structure of microplastics could not be identified.

Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy are considered the two dominant non-destructive spectroscopic techniques capable of identifying the physical properties and chemical compositions of microplastics in the environment (Hanvey et al., 2017). FTIR is an infrared absorption spectroscopy method that changes the molecular dipole moment to produce strong absorption vibrations (Frias et al., 2014) and has been widely developed to study sediment environments by exploiting its cost efficiency (Tagg et al., 2015). Raman spectroscopy reveals vibrational information specific to the molecular structure of microparticles (Araujo et al., 2018). The theoretical size detection limit can be less than 1 μm (Elert et al., 2017), and Raman imaging can reach a detection limit as low as 100 nm (Sobhani et al., 2020), while FTIR could hardly detect particles with sizes less than 20 μm (Lenz et al., 2015; Käppler et al., 2016; Schymanski et al., 2018). However, a limit has not yet been reached in environmental samples (Anger et al., 2018), since small microplastics may generate weak signals, providing results that are inconsistent with the actual situation (Song et al., 2015); additionally, the detection ability may mainly depend on the measurement parameters (Xu et al., 2019).

Microplastics with small particle sizes can easily disperse in the marine environment under the action of wind and waves and become accessible to living organisms (Kach and Ward, 2008; Wright et al., 2013; Vandermeersch et al., 2015). The smaller the microplastics, the greater the harm to the biota and ecosystem is (Tata et al., 2020). Although detecting microplastics with small particle sizes is very important, a few studies have provided information on particles smaller than 500 μm but have not clarified the size distribution (Sui et al., 2020; Wang et al., 2020), and only a few studies could identify particles smaller than 50 μm due to limitations in sample processing and the ineffective identification methods (Van Cauwenberghe et al., 2015; Imhof et al., 2016; Andrady, 2017; Jahan et al., 2019). Moreover, small microplastics account for a relatively large amount of microplastic pollution. In a transitional environment along the Italian coasts, 93% of the microplastics observed from sediment of the Lagoon of Venice was in the size range 30–500 μm (Vianello et al., 2013). Analyzing 20 coastal beaches along the coast of South Korea showed that 81% of the microplastics are smaller than 300 μm (Eo et al., 2018). For marine sediment samples collected from 13 representative stations in the eastern coastal areas of China, microplastic particles smaller than 500 μm accounted for the highest proportion among the whole size range from 32 μm to 4 964 μm (Wang et al., 2020).

To better explore the pollution of microplastics with small particle sizes (< 500 μm), in this study, we simplified the identification protocol used to detect microplastics in marine sediment by using confocal micro-Raman spectroscopy. Due to the effects of photodegradation and hydrodynamics, the microplastics existing in the beach environment degrade very quickly and could be broken and decomposed into small particles (Andrady, 2011). Besides, although tourism beaches are routinely cleaned, the small sized microplastics could be difficult to remove and would be retained in beach sediment (Zhao et al., 2015). Consequently, to validate this process, we analyzed actual marine sediment samples from Huiquan Bay and expected to approach the theoretical detection limit in environmental samples.

2 MATERIAL AND METHOD 2.1 Material

In this work, raw particles of 18 microplastic types (Yousuo Chemical Technology Co. Ltd., Shandong, China), including those designated for domestic and industrial use, were purchased to build a Raman spectral database (Table 1). Additionally, the most common plastic types, including polyethylene (PE), polypropylene (PP), polystyrene (PS), polyethylene terephthalate (PET) and polyvinyl chloride (PVC) (Ivar do Sul and Costa, 2014; Andrady, 2017), were commercially obtained in ~10 μm (PP only), ~150 μm, and ~500 μm (including polyamide) sizes for the simulation recovery experiment. Ten-centimeter surface sediment samples were taken from Bohai Bay during the "Transparent Ocean" open cruise of R/V Kexue-3 in 2018 by using a 0.05-m2 box corer and were used for the simulation recovery experiment to verify the effectiveness of the method proposed in this study. Besides, many small sized microplastics would remain in beaches after cleaning (Zhao et al., 2015). Therefore, to specifically identify small plastic waste in tourism beaches, marine sediment samples were collected by a stainless steel shovel from five 25-cm× 25-cm squares at Huiquan Bay beach, Qingdao. The top 1-cm layer of sediment was carefully preserved in aluminum foil bags.

Table 1 Type, abbreviation, chemical formula, and density of the referenced plastic polymers
2.2 Experimental instrument

A vacuum suction device (Enbang Glass Technology Co. Ltd., Jiangsu, China) consisting of a filter funnel, a sand core filter, an aluminum alloy clamp, a rubber tube and a GM-0.33A vacuum pump (Jinteng Experimental Equipment Co. Ltd., Tianjin, China) was used. Among the components, the filter funnel was custom designed for microparticle enrichment. In addition, 5-μm cellulose acetate filter paper was used for microplastic collection. A magnetic stirrer (Danrui Experimental Equipment Co. Ltd., Jiangsu, China) was fitted to agitate the sediment samples. A confocal micro-Raman spectrometer (Alpha 300R system, WITec Company, Germany) was used for microplastic detection.

2.3 Raman analysis

All the microplastic samples were measured by confocal micro-Raman spectroscopy (Alpha 300R system, WITec Company) with laser wavelengths of 532 nm and 785 nm (Xi et al., 2019). A 600-g/mm grating (spectral resolution: 3 cm-1) with a spectral center of 2 100 cm-1 and 1 800-g/mm grating (spectral resolution: 1 cm-1) with a spectral center of 1 200 cm-1 were applied. After wavenumber calibration with silicon, a 10×/0.25 magnification lens was implemented to search for target particles, after which 20×/0.4, 50×/0.55, and 100×/0.9 lenses were used (Zeiss, EC, Epiplan) for observation and detection according to practical needs. The short working distance of approximately 300 μm achieved when using a 100×/0.9 lens (Anger et al., 2018) may lead to a high risk of sample and objective lens destruction. Therefore, an objective lens with a 50× magnification and an numerical aperture (NA) of 0.55 was mainly used. Project Five 5.0 software (WITec Company, Germany) was used for image processing and spectroscopic data export. GRAMS/AI (Thermo Fisher Scientific, Inc., Waltham, USA) was applied for baseline correction. Origin 8.1 (OriginLab, MA, USA) was used for spectral smoothing and image rendering.

2.4 Contamination prevention

The glassware used in the experiment, such as Petri dishes, beakers, and conical bottles, was washed three times with Milli-Q water before use and dried at 60℃. After adding the marine sediment sample to be tested, the top of the experimental glassware was wrapped with aluminum foil. During vacuum filtration and magnetic stirring, aluminum foil was also used to wrap the funnels in the vacuum suction device and the beakers used for mixing. In addition, latex gloves and cotton laboratory garments were worn during all operations throughout the experimental process to prevent contamination by plastic products.

3 SAMPLE TREATMENT FOR RAMAN DETECTION 3.1 Simplified pretreatment process used for Raman detection

To build a rapid detection process, several procedures used in previous studies were simplified. Conventional pretreatment methods require the acidbase digestion of organic matter, counting plastic particles, and, finally, identification of the plastic types (Liebezeit and Dubaish, 2012; Nuelle et al., 2014; Käppler et al., 2016). A technological schematic comparing the conventional method and the simplified procedure is detailed in Fig. 1. By using a confocal Raman spectrometer for detection, the particles could be observed and identified through a software window. Density flotation is required to separate microplastic samples via static sedimentation. Saturated NaCl and NaI solutions were used to collect microplastics with different densities (Thompson et al., 2004; HidalgoRuz et al., 2012). However, the acid-base digestion step was omitted. After completing the vacuum filtration process, a confocal micro-Raman spectrometer was utilized to observe, count, and qualitatively identify the sample by comparing with the established microplastic reference library.

Fig.1 Comparison of the conventional process and simplified process of microplastics pretreatment and identification based on micro-Raman spectroscopy
3.2 Newly designed filtration approach for Raman detection

After extracting the particles and marine sediment, the particles were filtered by a vacuum suction device and collected on a filter (Hanvey et al., 2017). Particle dispersion on a 5-cm diameter filter during suction filtration could lead to time-consuming inspection and inefficient detection, because analyzing the whole filter is labor intensive and is not time effective (Xu et al., 2019). Therefore, a custom-made variable-area filter cup was implemented in a vacuum suction process adapted to collect microparticles from sediment. A bottom view of the filter cup is shown in Fig. 2a. The original circular cup opening was reduced to a 2.5-cm×2.5-cm square outlet to enrich the microparticles by applying a stainless steel frame. Additionally, the surrounding area was sealed with rubber, which guaranteed air tightness and the vacuum filtration efficiency. The samples were more concentrated within the square frame (Fig. 2c) than on the conventional filter (Fig. 2b). By changing the internal dimensions of the stainless steel frame, the area of the outlet could be altered according to the sample content. In this way, distinct outlet sizes could be made depending on the sample needs.

Fig.2 Bottom view of a variable-area filter cup applied for vacuum filtration (a); sample distribution on a filter with a conventional filter cup (b); and sample distribution on a filter with a variable-area filter cup (c)
3.3 Microplastic extraction recovery experiment

To demonstrate the practicability of the simplified detection process, a simulation experiment was implemented in the laboratory. Commercial synthetic particles were separately added to marine sediments, homogenized, and stored for 7 days, because microorganism colonies of microplastics could form in the marine sediments within 7 days (Harrison et al., 2014). Marine sediments were collected from Bohai Bay to simulate a real marine environment.

We chose ~150-μm sizes of PE, PP, PS, polyamide (PA), PET, and PVC as the representative size used for the recovery experiment, since the survey of the total microplastic abundance from 20 sites along the coast of South Korea showed that the maximum value is in the size range of 100–150 μm (Eo et al., 2018). In addition, the solution chosen for density flotation depended on the microplastic density. For PP, PE, and PS, the maximum density is 1.1 g/cm3. Since the density of a saturated NaCl solution at 25℃ is 1.20 g/mL (Hidalgo-Ruz et al., 2012), this solution was used to carry out density flotation for 24 h. For PET (1.37–1.45 g/cm3) and PVC (1.16–1.58 g/cm3) particles, a NaI solution was selected for density flotation (Van Cauwenberghe et al., 2013). By comparing the obtained spectrum with the Raman microplastic library, the particle type could be determined instantly. All particles could be correlated with certain plastic types without organic digestion (Supplementary Fig.S1).

To verify the detection ability of Raman detection in our proposed method, we applied ~10-μm PP for the laboratory experiment, because FTIR is limited to particles larger than 20 μm (Schymanski et al., 2018). The PP particles appear clearly under a confocal microscope and result in distinct Raman spectra after the recovery experiment (Supplementary Fig.S2). Therefore, the method proposed in this study identifies particle smaller than 20 μm while retaining their original morphology without organic matter digestion, simultaneously allowing the polymer type to be identified.

To obtain the recovery rate for particles that could be counted with the naked eye, we purchased 500-μm sized PE, PP, PS, PET, and PVC in various densities to determine the recovery rate statistics in the next step. Fifty particles of each plastic kind were prepared to acquire a relatively accurate recovery rate percentage. Three replicated experiments were performed, and the average recovery rates are presented in Supplementary Table S1.

3.4 Effect of the non-digestion process on Raman detection

This study aimed to identify small microplastics from marine sediment according to a simplified process. Therefore, to validate the effects of the nondigestion process on the Raman detection of small particles from sediment, a controlled experiment was carried out. A marine sediment sample was divided into two 100-g portions. After density flotation, 10 mL of 30% H2O2, which is a frequently used and effective reagent (Nuelle et al., 2014), was added to one sample to digest organic matter for 24 h. The other sample was not processed with H2O2. Then, a vacuum suction device was used to filter the microplastics for Raman detection. Microscopic observation of the samples digested by H2O2 demonstrated that the samples had been bleached (Fig. 3a). Since microplastics from marine sediments are often whitish or transparent (Hidalgo-Ruz et al., 2012), distinguishing between natural particulates and transparent plastics is difficult; therefore, H2O2 digestion could complicate analysis rather than facilitate it (Nuelle et al., 2014). For the samples without H2O2 treatment, the original physical and chemical properties were preserved. Additionally, green organic substances (Fig. 3b) could be visually distinguished from the target microparticles in the microscopic images. The spectra could consequently provide more representative target information as a result of avoiding areas contaminated with pollutants or biological impurities.

Fig.3 Optical microscopic images of microparticles extracted from marine sediment after the digestion process (a) and after the non-digestion process (b); Raman spectrum of the digested microparticles from marine sediment (in red) compared with a reference spectrum (in blue) (c), and Raman spectrum of undigested microparticles from marine sediment (in red) compared with a reference spectrum of PP (in blue) (d)

Since environmental microplastics have varying characteristics (Koelmans et al., 2019), the Raman spectra obtained from particles after digestion may present a strong background level (Fig. 3c). In contrast, undigested microparticles with a size of approximately 100 μm still achieved an optimized signal quality (Fig. 3d). Moreover, in comparison with the reference Raman spectra, the particles could be identified as PP (Fig. 3c & d). However, biological residue could lead to inaccurate spectra and fluorescence in some instances (Hidalgo-Ruz et al., 2012; Araujo et al., 2018). Therefore, we could reduce fluorescence by changing the laser excitation wavelengths. With the progress of the experiment, to reduce false positive and false negative results, accumulating experience in interpreting spectra is necessary. In addition, the organic digestion protocol is considered to be helpful, especially in organic matter-rich sediment such as soil and sewage sludge (Li et al., 2019). Consequently, we suggest that the simplified process presented in this study be used in organic-poor sediment. As stated above, the small particles could be original appearance and qualitatively identified by using Raman technology after a non-digestion process. Furthermore, the Raman detection parameters should be implemented according to the characteristics of the samples treated with or without digestion steps.

4 RAMAN SPECTRAL CHARACTERISTICS OF MICROPLASTICS 4.1 Spectral characteristics of reference microplastics

As Raman is a fingerprint identification technology, the Raman spectra of each microplastic type have representative peak positions (Koenig, 1971; Gerrard and Maddam, 1986; Araujo et al., 2018). Therefore, the characteristic peaks of each microplastic are unique due to the vibrations of different bonds. To identify a variety of microplastics, the spectrum of 18 types of raw industrial plastic materials is discussed separately to assign the peak positions (Supplementary Tables S2–S19). This library contributes to identifying various microplastics with the same bond vibration modes and provides an index for further research. For example, the peak at 1 001 cm-1 is attributed to a mono meta substituted benzene ring and could be used to classify polymers with benzene rings (Colthup et al., 1990), such as PS, acrylonitrile-butadiene-styrene (ABS) and polyphenylene oxide (PPO). This similarity indicates that the plastic type cannot be determined by only considering a single benzene ring vibrational peak. The plastic type can be comprehensively determined only after assigning all the characteristic peaks of each microplastic to reduce potential errors. The unknown particles could therefore be identified by comparing the obtained Raman spectra with the complete Raman spectrum library (Choy et al., 2019). The identification of vibrational modes varies in the literature. We used the specific citations for vibrational mode identification, but acknowledge the range of terms used from one table to another.

4.2 Effect of pigment on Raman spectra of microplastics

Distinctly colored particles extracted from deep sea sediment from the Southern Ocean (2 749 m) were identified as possible microplastics by comparing their Raman spectra with those of pigments (Van Cauwenberghe et al., 2013) instead of the reference spectra of plastics. Therefore, a representative pigment used in the plastic dyeing industry, phthalocyanine blue (Lewis, 2003), and commercial PE colored polymers were selected to comprehensively investigate the effect of pigments on microparticles (Fig. 4). The green spectrum represents a standard PE spectrum. The phthalocyanine blue spectrum is presented in the middle, and the phthalocyanine blue PE spectrum is shown at the bottom. The characteristic bands of phthalocyanine blue, obtained with a 785 nm laser Raman spectrometer, are located at 598, 681, 748, 952, 1 109, 1 144, 1 338, 1 450, and 1 524 cm-1. Similarly, the phthalocyanine blue PE spectrum shows highly consistent bands at 595, 682, 749, 954, 1 089, 1 144, 1 343, 1 453, and 1 529 cm-1 (Fig. 4).

Fig.4 Comparison of the Raman spectra of PE (in green), phthalocyanine blue pigment (in blue) and phthalocyanine blue PE (in red)

These results suggest that the original characteristic bands of the colored PE were masked by those of the phthalocyanine blue pigment, which resembles the findings described byVan Cauwenberghe et al. (2013). This conclusion indicates that coloring agents could interfere with microplastics measurements (Van Cauwenberghe et al., 2013; Lenz et al., 2015; Araujo et al., 2018). Additionally, organic pigments often have a non-natural origin and are most commonly used in the plastic industry (Lewis, 2003), which could indicate the anthropogenic source of colored particles (Van Cauwenberghe et al., 2013). Therefore, matching colored particles to plastics may be impossible, since the reference spectra were merely collected for standard colorless polymers. Additionally, these characteristics could contribute to underestimating colored microplastics. Because of this drawback, spectra of colored polymers must be included in the reference database. Therefore, the spectra for 9 kinds of commercial colored polymers, polyethylene with a light yellow color, medium chrome yellow, permanent orange, pink, oil red, phthalocyanine green, phthalocyanine blue, light gray, and carbon black coating, were implemented in the reference Raman library (Fig. 5).

Fig.5 Raman reference library of colored microplastics
5 VERIFICATION IN REAL CASE 5.1 Occurrence of microplastics

The simplified process described above could effectively detect microplastics in laboratory simulations. In addition, a microplastic reference Raman library including colored polymers was implemented. To validate this process in real samples, marine sediment from Huiquan Bay was investigated. After extraction and detection of ~200 particles, the identification process resulted in a total of 41 particles in the 5–500 μm range. Moreover, 7 types of microplastics were identified, including PP, PE, polytetrafluoroethylene (PTFE), PA, PS, PET, and ABS.

The morphology of representative microparticles is shown in Fig. 6ai, which corresponds to particles A–I, respectively. By referring to the established reference library, 7 types of microplastics were identified (Fig. 7). The chemical composition of the particles was determined by referring to the established microplastic Raman spectral library (Supplementary Tables S2–S19). Additionally, peaks with positions deviating by ~5 cm-1 could be assigned to be the same vibration type, due to errors in marine particles experiments and in the establishment of reference library. Particles A, B and C, with different shapes, were classified as PP by spectral comparison. The characteristic vibration bands of particles A, B, and C at 809 cm-1, 975 cm-1, 1 156 cm-1, and 1 220 cm-1 were assigned to C-C stretching, and the bands at 1 361 cm-1 and 1 458 cm-1 were assigned to the CH2 bending and CH3 bending (Supplementary Table S3). The bands from 2 800 cm-1 to 3 000 cm-1 correspond to C-H (-CH3) stretching modes (Fig. 7a) (Supplementary Table S3). Particle D was identified as PE. The Raman spectrum of particle D has characteristic bands at 1 061 cm-1, a band at 1 128 cm-1 corresponding to C-C stretching, a band at 1 295 cm-1 corresponding to CH2 twisting, a band at 1 440 cm-1 corresponding to CH2 bending and bands from 2 800 cm-1 to 3 000 cm-1 corresponding to C-H (-CH2) stretching (Fig. 7b) (Supplementary Table S2). Particle E was tentatively identified as PA by comparing the characteristic vibrations. The band at 1 446 cm-1 was assigned to CH2 bending, and that at 1 648 cm-1 was assigned to amide I C=O stretching (Supplementary Table S5). The characteristic band at 3 295 cm-1 was assigned to N-H stretching (Fig. 7c) (Supplementary Table S5). Particle F was identified as PS due to the characteristic vibration of the benzene ring attributed to the peak at 1 002 cm-1 and benzene ring C-C symmetric stretching attributed to the peak at 1 602 cm-1 (Fig. 7d) (Supplementary Table S4). In addition, because particle G also has a band at 2 239 cm-1 for C≡N stretching, it was identified as ABS (Fig. 7e) (Supplementary Table S9). Particle H was characterized as PET due to the unique band at 857 cm-1 attributed to C-C breathing stretching and the band at 1 727 cm-1 attributed to C=O stretching. The region from 2 800 cm-1 to 3 000 cm-1 is associated with aliphatic C-H stretching modes, while that from 3 000 cm-1 to 3 100 cm-1 is associated with aromatic C-H stretching (Fig. 7f) (Supplementary Table S6). Particle I was clearly identified as PTFE. The typical PTFE bands are located at 729 cm-1 for CF2 stretching, 1 215 cm-1 for C-C stretching, 1 296 cm-1 for CF2 stretching and 1 379 cm-1 for CF stretching (Supplementary Table S8). Particle I indeed is very consistent with the PTFE spectrum (Fig. 7g).

Fig.6 Optical microscopic images of marine sediment microparticles with various types, shapes and sizes (a – i)
Fig.7 Raman spectra of microparticles from marine sediment (in red) and their Raman reference library matches (in blue) (a–g)

In addition to the spectra demonstrated above, one of the evaluated particles presented bands at 1 655 cm-1 and 3 010 cm-1 in addition to the characteristic bands of PE; these additional bands were assigned to vibrations of lipids (You et al., 2016). Due to the various conformation (Andreassen, 1999) and compound additives in polymers (Erni-Cassola et al., 2017) and the mixture of biological and inorganic materials, the spectra of microplastics from marine environments will not always conform completely with the standard spectra (Lenz et al., 2015). Consequently, spectra of polymers exposed to environmental stressors should be included in the reference library to increase the discovery rate (Lenz et al., 2015; Araujo et al., 2018). Weathered plastic materials and non-plastic substances are regarded as references in several studies (Lenz et al., 2015; Choy et al., 2019). Therefore, to maintain a complete database, we would update the reference library with representative spectra consistent with research progress in future work.

Not only did the spectra of undigested particles have a high signal-to-noise ratio, but the undigested samples also retained their original morphology, according to the optical microscopy images (Fig. 6). These results indicate the good detection performance of Raman spectroscopy for detecting marine samples. Since microparticles can be simultaneously observed and identified with a Raman microscope, this spectroscopic method can be used to not only obtain chemical information but also study morphological features (Lenz et al., 2015). Microplastics obtained from this site with sizes smaller than 10 micrometers were also found in their original state by Raman spectroscopy (Fig. 6b). This result suggests that researchers could better trace the source and potential fate of microplastics with Raman detection than with existing methods and, moreover, understand the feasibility of organism ingestion (Fortin et al., 2019).

5.2 Size and abundance of microplastics

Various types of environmental samples with small sizes were analyzed through the established simplified process. The findings indicate that over half of the particles (< 500 μm) at this site had sizes smaller than 50 μm (Fig. 8a). Among the particles, nearly one-fifth comprised microplastics smaller than 10 μm (Fig. 8a). Among the 41 particles that accurately correlated with certain plastic types, PP particles were the most abundant (42%) (Fig. 8b), which agrees with research performed at Bigbury Beach (UK) (Erni-Cassola et al., 2017) and resembles results (Tang et al., 2018) from coastal areas in Xiamen (China). PP polymers were present in all the size ranges and accounted for all the particles that were smaller than 10 μm and 50% of the particles with sizes ranging from 10–50 μm (Fig. 8c).

Fig.8 Proportional composition of microplastic sizes (a) and types (b) and the percentage distribution of microplastic types (c) from marine sediment samples

In addition, PE polymers were found to be the second most common type and accounted for 18.8% of the particles in the 10–50 μm size range. In general, PP and PE are considered to be the most frequently used plastics and are found in materials such as commercial packaging (Andrady, 2011). Additionally, as a result of being less dense than water, PP and PE particles could be transported with currents and deposited in sediment (Zhang et al., 2016). PTFE was also found in large quantities (Fig. 8b). As a result of its excellent performance, high intensity and substantial toughness, PTFE has wide applications in marine operations. PS particles accounted for 2% of the particles in the 50– 150 μm size range (Fig. 8b). After breaking down due to human activity and waves, PS particles may drift with wind and water (Van Cauwenberghe et al., 2015; Wang et al., 2016). PET and PA were mainly found in fibers owing to their use in synthetic textile fibers. Because of their high density, PET and PA are much more easily retained in marine sediments (Engler, 2012).

A previous study investigated particle sizes from 50 μm to 5 000 μm in Huiquan Bay by FTIR spectroscopy (Luo et al., 2019). This study considered small microplastics with sizes smaller than 50 μm. The findings clearly indicate that small sized microplastics occupy a large proportion of marine sediments. Small microplastics posed a high risk to marine organisms (Yao et al., 2019). Therefore, with the Raman spectroscopic method, smaller microplastics could be included in the analytical statistics, because the detection limit of this method is lower than that of FTIR, which could decrease the possibility of underestimating the quantity of small microplastics. Accordingly, the Raman spectroscopic method could be used to comprehensively study the microparticle behavior and ultimate fate of small microplastics in marine environments.

The pore size of the filter could also result in inconsistent findings among studies (Hanvey et al., 2017). A trawl of 333 μm is widely applied in water sampling which may result in less abundance of microplastics smaller than the mesh (Qiu et al., 2016; Eo et al., 2018). This study used a filter with a 5-μm pore size, which indicates that microparticles smaller than 5 μm could not be captured. However, particles less than 5 μm may originate from woven fabric; such a size could impede optical detection (Anger et al., 2018). Moreover, when identifying particles with 1-μm sizes, interference from contaminants in the air and other sources is likely (Fortin et al., 2019). Therefore, a 5-μm filter could be a rational choice when considering the measurement time and efficiency.

As illustrated above, microplastics extracted from marine sediment and smaller than 10 μm could be detected with a simplified process by using confocal micro-Raman spectroscopy. Even though Raman spectroscopy could theoretically identify 1-μm particles, the detection ability for environmental samples may depend on the sample complexity, treatment method and measurement parameters (Anger et al., 2018). Future work should therefore continue to explore appropriate detection processes for applications in diverse environments and investigate the size limitations of detection.

6 CONCLUSION

Microplastic detection in marine sediment is a multiple-step process that lacks optimized procedures for the pretreatment steps and identification protocols. In addition, a lower size limit has not been reached in environmental samples. This study provides an efficient process for detecting and characterizing small microplastics by using Raman spectroscopy. High-quality Raman signals of microplastics were obtained despite omitting the organic matter digestion process. We validated this simplified process in marine sediment samples with microplastics smaller than 500 μm in Huiquan Bay and identified PP microparticles smaller than 10 μm from marine sediment. We expect Raman technology to enable a more complete and standardized process for microplastic detection and anticipate wider applications of Raman analysis in future research works.

7 DATA AVAILABILITY STATEMENT

All data generated and/or analyzed during this study are available from the corresponding author upon reasonable request.

8 ACKNOWLEDGMENT

We thank ZHANG Jieyang and Dr. YANG Lijian for their help collecting the marine sediment sample from Shandong Peninsula. We appreciate the “Transparent Ocean” open cruise organized by the Pilot National Laboratory for Marine Science and Technology (Qingdao) and Center for Ocean MegaScience, CAS.

References
Andrady A L. 2011. Microplastics in the marine environment. Marine Pollution Bulletin, 62(8): 1 596-1 605. DOI:10.1016/j.marpolbul.2011.05.030
Andrady A L. 2017. The plastic in microplastics:a review. Marine Pollution Bulletin, 119(1): 12-22. DOI:10.1016/j.marpolbul.2017.01.082
Andreassen E. 1999. Infrared and Raman spectroscopy of polypropylene. Polypropylene.Springer, Dordrecht. DOI:10.1007/978-94-011-4421-6_46
Anger P M, von der Esch E, Baumann T, Elsner M, Niessner R, Ivleva N P. 2018. Raman microspectroscopy as a tool for microplastic particle analysis. TrAC Trends in Analytical Chemistry, 109: 214-226. DOI:10.1016/j.trac.2018.10.010
Araujo C F, Nolasco M M, Ribeiro A M P, Ribeiro-Claro P J A. 2018. Identification of microplastics using Raman spectroscopy:latest developments and future prospects. Water Research, 142: 426-440. DOI:10.1016/j.watres.2018.05.060
Browne M A, Galloway T, Thompson R. 2007. Microplastican emerging contaminant of potential concern?. Integrated Environmental Assessment and Management, 3(4): 559-561. DOI:10.1002/ieam.5630030412
Carbery M, O'Connor W, Palanisami T. 2018. Trophic transfer of microplastics and mixed contaminants in the marine food web and implications for human health. Environment International, 115: 400-409. DOI:10.1016/j.envint.2018.03.007
Carpenter E J, Smith Jr K L. 1972. Plastics on the Sargasso Sea surface. Science, 175(4027): 1 240-1 241. DOI:10.1126/science.175.4027.1240
Chiba S, Saito H, Fletcher R, Yogi T, Kayo M, Miyagi S, Ogido M, Fujikura K. 2018. Human footprint in the abyss:30 year records of deep-sea plastic debris. Marine Policy, 96: 204-212. DOI:10.1016/j.marpol.2018.03.022
Choy C A, Robison B H, Gagne T O, Erwin B, Firl E, Halden R U, Hamilton J A, Katija K, Lisin S E, Rolsky C, Van Houtan K S. 2019. The vertical distribution and biological transport of marine microplastics across the epipelagic and mesopelagic water column. Scientific Reports, 9(1): 7843. DOI:10.1038/s41598-019-44117-2
Claessens M, Van Cauwenberghe L, Vandegehuchte M B, Janssen C R. 2013. New techniques for the detection of microplastics in sediments and field collected organisms. Marine Pollution Bulletin, 70(1-2): 227-233. DOI:10.1016/j.marpolbul.2013.03.009
Cole M, Lindeque P, Halsband C, Galloway T S. 2011. Microplastics as contaminants in the marine environment:a review. Marine Pollution Bulletin, 62(12): 2 588-2 597. DOI:10.1016/j.marpolbul.2011.09.025
Cole M, Webb H, Lindeque P K, Fileman E S, Halsband C, Galloway T S. 2014. Isolation of microplastics in biotarich seawater samples and marine organisms. Scientific Reports, 4: 4 528. DOI:10.1038/srep04528
Colthup N B, Daly L H, Wiberley S E. 1990. Aromatic and heteroaromatic rings. In: Colthup N B, Daly L H, Wiberley S E eds. Introduction to Infrared and Raman Spectroscopy. 3rd edn. Academic Press, London.
Cózar A, Echevarría F, González-Gordillo J I, Irigoien X, Úbeda B, Hernández-León S, Palma A T, Navarro S, García-de-Lomas J, Ruiz A, Fernández-de-Puelles M L, Duarte C M. 2014. Plastic debris in the open ocean.
Proceedings of the National Academy of Sciences of the United States of America, 111(28): 10 239-10 244, https: //doi.org/10.1073/pnas.1314705111.
Elert A M, Becker R, Duemichen E, Eisentraut P, Falkenhagen J, Sturm H, Braun U. 2017. Comparison of different methods for MP detection:what can we learn from them, and why asking the right question before measurements matters?. Environmental Pollution. DOI:10.1016/j.envpol.2017.08.074
Engler R E. 2012. The complex interaction between marine debris and toxic chemicals in the ocean. Environmental Science & Technology, 46(22): 12 302-12 315. DOI:10.1021/es3027105
Eo S, Hong S H, Song Y K, Lee J, Lee J, Shim W J. 2018. Abundance, composition, and distribution of microplastics larger than 20 μm in sand beaches of South Korea. Environmental Pollution, 238: 894-902. DOI:10.1016/j.envpol.2018.03.096
Erni-Cassola G, Gibson M I, Thompson R C, Christie-Oleza J A. 2017. Lost, but found with Nile red:a novel method for detecting and quantifying small microplastics (1 mm to 20 μm) in environmental samples. Environmental Science & Technology, 51(23): 13 641-13 648. DOI:10.1021/acs.est.7b04512
Fischer E R, Hansen B T, Nair V, Hoyt F H, Dorward D W. 2012. Scanning electron microscopy. Current Protocols in Microbiology, 25(1): 2B.2.1-2B.2.47. DOI:10.1002/9780471729259.mc02b02s25
Foekema E M, De Gruijter C, Mergia M T, van Franeker J A, Murk A J, Koelmans A A. 2013. Plastic in North Sea fish. Environmental Science & Technology, 47(15): 8 818-8 824. DOI:10.1021/es400931b
Fortin S, Song B, Burbage C. 2019. Quantifying and identifying microplastics in the effluent of advanced wastewater treatment systems using Raman microspectroscopy. Marine Pollution Bulletin, 149: 110579. DOI:10.1016/j.marpolbul.2019.110579
Frias J P G L, Otero V, Sobral P. 2014. Evidence of microplastics in samples of zooplankton from Portuguese coastal waters. Marine Environmental Research, 95: 89-95. DOI:10.1016/j.marenvres.2014.01.001
Gerrard D L, Maddam W F. 1986. Polymer characterization by Raman spectroscopy. Applied Spectroscopy Reviews, 22(2-3): 251-334. DOI:10.1080/05704928608070179
Hanvey J S, Lewis P J, Lavers J L, Crosbie N D, Pozo K, Clarke B O. 2017. A review of analytical techniques for quantifying microplastics in sediments. Analytical Methods, 9(9): 1 369-1 383. DOI:10.1039/c6ay02707e
Harrison J P, Schratzberger M, Sapp M, Osborn A M. 2014. Rapid bacterial colonization of low-density polyethylene microplastics in coastal sediment microcosms. BMC Microbiology, 14: 232. DOI:10.1186/s12866-014-0232-4
Hidalgo-Ruz V, Gutow L, Thompson R C, Thiel M. 2012. Microplastics in the marine environment:a review of the methods used for identification and quantification. Environmental Science & Technology, 46(6): 3 060-3 075. DOI:10.1021/es2031505
Imhof H K, Laforsch C, Wiesheu A C, Schmid J, Anger P M, Niessner R, Ivleva N P. 2016. Pigments and plastic in limnetic ecosystems:a qualitative and quantitative study on microparticles of different size classes. Water Research, 98: 64-74. DOI:10.1016/j.watres.2016.03.015
Ivar do Sul J A, Costa M F. 2014. The present and future of microplastic pollution in the marine environment. Environmental Pollution, 185: 352-364. DOI:10.1016/j.envpol.2013.10.036
Jahan S, Strezov V, Weldekidan H, Kumar R, Kan T, Sarkodie S A, He J, Dastjerdi B, Wilson S P. 2019. Interrelationship of microplastic pollution in sediments and oysters in a seaport environment of the eastern coast of Australia. Science of the Total Environment, 695: 133924. DOI:10.1016/j.scitotenv.2019.133924
Kach D J, Ward J E. 2008. The role of marine aggregates in the ingestion of picoplankton-size particles by suspensionfeeding molluscs. Marine Biology, 153(5): 797-805. DOI:10.1007/s00227-007-0852-4
Kanhai L D K, Johansson C, Frias J P G L, Gardfeldt K, Thompson R C, O'Connor I. 2019. Deep sea sediments of the Arctic Central Basin:a potential sink for microplastics. Deep Sea Research Part I:Oceanographic Research Papers, 145: 137-142. DOI:10.1016/j.dsr.2019.03.003
Käppler A, Fischer D, Oberbeckmann S, Schernewski G, Labrenz M, Eichhorn K J, Voit B. 2016. Analysis of environmental microplastics by vibrational microspectroscopy:FTIR, Raman or both?. Analytical and Bioanalytical Chemistry, 408(29): 8 377-8 391. DOI:10.1007/s00216-016-9956-3
Koelmans A A, Mohamed Nor N H, Hermsen E, Kooi M, Mintenig S M, De France J. 2019. Microplastics in freshwaters and drinking water:critical review and assessment of data quality. Water Research, 155: 410-422. DOI:10.1016/j.watres.2019.02.054
Koenig J L. 1971. Raman scattering of synthetic polymers-a review. Applied Spectroscopy Reviews, 4(2): 233-305. DOI:10.1080/05704927108082605
Lenz R, Enders K, Stedmon C A, Mackenzie D M A, Nielsen T G. 2015. A critical assessment of visual identification of marine microplastic using Raman spectroscopy for analysis improvement. Marine Pollution Bulletin, 100(1): 82-91. DOI:10.1016/j.marpolbul.2015.09.026
Lewis P A. 2003. Organic colorants. In: Charvat R A ed.Coloring of Plastics: Fundamentals. John Wiley & Sons, Hoboken.
Li Q L, Wu J T, Zhao X P, Gu X Y, Ji R. 2019. Separation and identification of microplastics from soil and sewage sludge. Environmental Pollution, 254: 113076. DOI:10.1016/j.envpol.2019.113076
Liebezeit G, Dubaish F. 2012. Microplastics in beaches of the East Frisian Islands Spiekeroog and Kachelotplate. Bulletin of Environmental Contamination and Toxicology, 89(1): 213-217. DOI:10.1007/s00128-012-0642-7
Löder M G J, Kuczera M, Mintenig S, Lorenz C, Gerdts G. 2015. Focal plane array detector-based micro-Fouriertransform infrared imaging for the analysis of microplastics in environmental samples. Environmental Chemistry, 12(5): 563-581. DOI:10.1071/en14205
Luo Y D, Lin Q H, Jia F L, Xu G D, Li F M. 2019. Distribution characteristics of microplastics in Qingdao coastal beaches. Environmental Science, 40(6): 2 631-2 638. (in Chinese with English abstract) DOI:10.13227/j.hjkx.201810074.(inChinesewithEnglishabstract)
Nuelle M T, Dekiff J H, Remy D, Fries E. 2014. A new analytical approach for monitoring microplastics in marine sediments. Environmental Pollution, 184: 161-169. DOI:10.1016/j.envpol.2013.07.027
Qiu Q X, Tan Z, Wang J D, Peng J P, Li M M, Zhan Z W. 2016. Extraction, enumeration and identification methods for monitoring microplastics in the environment. Estuarine, Coastal and Shelf Science, 176: 102-109. DOI:10.1016/j.ecss.2016.04.012
Schymanski D, Goldbeck C, Humpf H U, Fürst P. 2018. Analysis of microplastics in water by micro-Raman spectroscopy:release of plastic particles from different packaging into mineral water. Water Research, 129: 154-162. DOI:10.1016/j.watres.2017.11.011
Sobhani Z, Zhang X, Gibson C, Naidu R, Mallavarapu M, Fang C. 2020. Identification and visualisation of microplastics/nanoplastics by Raman imaging (i):down to 100 nm. Water Research, 174: 115658. DOI:10.1016/j.watres.2020.115658
Song Y K, Hong S H, Jang M, Han G M, Rani M, Lee J, Shim W J. 2015. A comparison of microscopic and spectroscopic identification methods for analysis of microplastics in environmental samples. Marine Pollution Bulletin, 93(1-2): 202-209. DOI:10.1016/j.marpolbul.2015.01.015
Sui Q, Zhang L J, Xia B, Chen B J, Sun X M, Zhu L, Wang R Y, Qu K M. 2020. Spatiotemporal distribution, source identification and inventory of microplastics in surface sediments from Sanggou Bay, China. Science of the Total Environment, 723: 138064. DOI:10.1016/j.scitotenv.2020.138064
Sun C J, Jiang F H, Li J X, Zheng L. 2016. The research progress in source, distribution, ecological and environmental effects of marine microplastics. Advances in Marine Science, 34(4): 449-461. (in Chinese with English abstract) DOI:10.3969/j.issn.1671-6647.2016.04.001.(inChinesewithEnglishabstract)
Sun X X, Liang J H, Zhu M L, Zhao Y F, Zhang B. 2018. Microplastics in seawater and zooplankton from the Yellow Sea. Environmental Pollution, 242: 585-595. DOI:10.1016/j.envpol.2018.07.014
Tagg A S, Sapp M, Harrison J P, Ojeda J J. 2015. Identification and quantification of microplastics in wastewater using focal plane array-based reflectance micro-FT-IR imaging. Analytical Chemistry, 87(12): 6 032-6 040. DOI:10.1021/acs.analchem.5b00495
Tang G W, Liu M Y, Zhou Q, He H X, Chen K, Zhang H B, Hu J H, Huang Q H, Luo Y M, Ke H W, Chen B, Xu X R, Cai M G. 2018. Microplastics and polycyclic aromatic hydrocarbons (PAHs) in Xiamen coastal areas:implications for anthropogenic impacts. Science of the Total Environment, 634: 811-820. DOI:10.1016/j.scitotenv.2018.03.336
Tata T, Belabed B E, Bououdina M, Bellucci S. 2020. Occurrence and characterization of surface sediment microplastics and litter from North African coasts of Mediterranean Sea:preliminary research and first evidence. Science of the Total Environment, 713: 136664. DOI:10.1016/j.scitotenv.2020.136664
Thompson R C, Olsen Y, Mitchell R P, Davis A, Rowland S J, John A W G, McGonigle D, Russell A E. 2004. Lost at sea:where is all the plastic?. Science, 304(5372): 838. DOI:10.1126/science.1094559
Uddin S, Fowler S W, Saeed T. 2020. Microplastic particles in the Persian/Arabian Gulf-a review on sampling and identification. Marine Pollution Bulletin, 154: 111100. DOI:10.1016/j.marpolbul.2020.111100
Van Cauwenberghe L, Devriese L, Galgani F, Robbens J, Janssen C R. 2015. Microplastics in sediments:a review of techniques, occurrence and effects. Marine Environmental Research, 111: 5-17. DOI:10.1016/j.marenvres.2015.06.007
Van Cauwenberghe L, Vanreusel A, Mees J, Janssen C R. 2013. Microplastic pollution in deep-sea sediments. Environmental Pollution, 182: 495-499. DOI:10.1016/j.envpol.2013.08.013
Vandermeersch G, Van Cauwenberghe L, Janssen C R, Marques A, Granby K, Fait G, Kotterman M J, Diogène J, Bekaert K, Robbens J, Devriese L. 2015. A critical view on microplastic quantification in aquatic organisms. Environmental Research, 143: 46-55. DOI:10.1016/j.envres.2015.07.016
Vianello A, Boldrin A, Guerriero P, Moschino V, Rella R, Sturaro A, Da Ros L. 2013. Microplastic particles in sediments of Lagoon of Venice, Italy:first observations on occurrence, spatial patterns and identification. Estuarine, Coastal and Shelf Science, 130: 54-61. DOI:10.1016/j.ecss.2013.03.022
Waller C L, Griffiths H J, Waluda C M, Thorpe S E, Loaiza I, Moreno B, Pacherres C O, Hughes K A. 2017. Microplastics in the Antarctic marine system:an emerging area of research. Science of the Total Environment, 598: 220-227. DOI:10.1016/j.scitotenv.2017.03.283
Wang J D, Tan Z, Peng J P, Qiu Q X, Li M M. 2016. The behaviors of microplastics in the marine environment. Marine Environmental Research, 113: 7-17. DOI:10.1016/j.marenvres.2015.10.014
Wang Q, Shan E C, Zhang B, Teng J, Wu D, Yang X, Zhang C, Zhang W J, Sun X Y, Zhao J M. 2020. Microplastic pollution in intertidal sediments along the coastline of China. Environmental Pollution, 263: 114428. DOI:10.1016/j.envpol.2020.114428
Wright S L, Thompson R C, Galloway T S. 2013. The physical impacts of microplastics on marine organisms:a review. Environmental Pollution, 178: 483-492. DOI:10.1016/j.envpol.2013.02.031
Xi S C, Zhang X, Luan Z D, Du Z F, Li L F, Liang Z W, Lian C, Yan J. 2019. Micro-Raman study of thermal transformations of sulfide and oxysalt minerals based on the heat induced by laser. Minerals, 9(12): 751. DOI:10.3390/min9120751
Xu J L, Thomas K V, Luo Z S, Gowen A A. 2019. FTIR and Raman imaging for microplastics analysis:state of the art, challenges and prospects. TrAC Trends in Analytical Chemistry, 119: 115629. DOI:10.1016/j.trac.2019.115629
Yao P, Zhou B, Lu Y H, Yin Y, Zong Y Q, Chen M T, O'Donnell Z. 2019. A review of microplastics in sediments:spatial and temporal occurrences, biological effects, and analytic methods. Quaternary International, 519: 274-281. DOI:10.1016/j.quaint.2019.03.028
You S X, Tu H H, Zhao Y B, Liu Y, Chaney E J, Marjanovic M, Boppart S A. 2016. Raman spectroscopic analysis reveals abnormal fatty acid composition in tumor micro-and macroenvironments in human breast and rat mammary cancer. Scientific Reports, 6: 32922. DOI:10.1038/srep32922
Zhang K, Su J, Xiong X, Wu X, Wu C X, Liu J T. 2016. Microplastic pollution of lakeshore sediments from remote lakes in Tibet plateau, China. Environmental Pollution, 219: 450-455. DOI:10.1016/j.envpol.2016.05.048
Zhao S Y, Zhu L X, Li D J. 2015. Characterization of small plastic debris on tourism beaches around the South China Sea. Regional Studies in Marine Science, 1: 55-62. DOI:10.1016/j.rsma.2015.04.001