Application of confocal laser Raman spectroscopy on marine sediment microplastics*

LIU Jing , , ZHANG Xin , , , DU Zengfeng , LUAN Zhendong , LI Lianfu , , XI Shichuan , , WANG Bing , CAO Lei , YAN Jun

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 simplifi ed 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 eff ects 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 simplifi ed 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 identifi ed in marine sediment. This work demonstrates that Raman spectroscopy is not only an eff ective tool for detecting environmental particles but also highly applicable for identifying particles extracted from marine sediment.

Keyword: 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 fi rst 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), identifi cation 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 identifi cation steps (Hanvey et al., 2017). Since the microplastics in the marine sediment are dispersed, particles should be concentrated by density fl otation (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 identifi cation 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 infl uence, the accuracy of sample identifi cations is not guaranteed (Lenz et al., 2015; Löder et al., 2015). Scanning electron microscopy (SEM) could be used to generate suffi ciently highresolution images (Fischer et al., 2012), but the chemical structure of microplastics could not be identifi ed.

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 effi ciency (Tagg et al., 2015). Raman spectroscopy reveals vibrational information specifi c 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 clarifi ed 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 ineff ective identifi cation 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 simplifi ed the identifi cation protocol used to detect microplastics in marine sediment by using confocal micro-Raman spectroscopy. Due to the eff ects 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 diffi cult 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 Ramanspectral 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-m2box corer and were used for the simulation recovery experiment to verify the eff ectiveness of the method proposed in this study. Besides, many small sized microplastics would remain in beaches after cleaning (Zhao et al., 2015). Therefore, to specifi cally identify small plastic waste in tourism beaches, marine sediment samples were collected by a stainless steel shovel from fi ve 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 fi lter funnel, a sand core fi lter, 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 fi lter funnel was custom designed for microparticle enrichment. In addition, 5-μm cellulose acetate fi lter paper was used for microplastic collection. A magnetic stirrer (Danrui Experimental Equipment Co. Ltd., Jiangsu, China) was fi tted 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

Fig.1 Comparison of the conventional process and simplifi ed process of microplastics pretreatment and identifi cation based on micro-Raman spectroscopy

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-1and 1 800-g/mm grating (spectral resolution: 1 cm-1) with a spectral center of 1 200 cm-1were applied. After wavenumber calibration with silicon, a 10×/0.25 magnifi cation 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× magnifi cation 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 Scientifi c, 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 fi ltration 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 Simplifi ed pretreatment process used for Raman detection

To build a rapid detection process, several procedures used in previous studies were simplifi ed. Conventional pretreatment methods require the acidbase digestion of organic matter, counting plastic particles, and, fi nally, identifi cation 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 simplifi ed procedure is detailed in Fig.1. By using a confocal Raman spectrometer for detection, the particles could be observed and identifi ed through a software window. Density fl otation is required to separate microplastic samples via static sedimentation. Saturated NaCl and NaI solutions were used to collect microplastics with diff erent densities (Thompson et al., 2004; Hidalgo-Ruz et al., 2012). However, the acid-base digestion step was omitted. After completing the vacuum fi ltration process, a confocal micro-Raman spectrometer was utilized to observe, count, and qualitatively identify the sample by comparing with the established microplastic reference library.

3.2 Newly designed fi ltration approach for Raman detection

After extracting the particles and marine sediment, the particles were fi ltered by a vacuum suction device and collected on a fi lter (Hanvey et al., 2017). Particle dispersion on a 5-cm diameter fi lter during suction fi ltration could lead to time-consuming inspection and ineffi cient detection, because analyzing the whole fi lter is labor intensive and is not time eff ective (Xu et al., 2019). Therefore, a custom-made variable-area fi lter cup was implemented in a vacuum suction process adapted to collect microparticles from sediment. A bottom view of the fi lter 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 fi ltration effi ciency. The samples were more concentrated within the square frame (Fig.2c) than on the conventional fi lter (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 fi lter cup applied for vacuum fi ltration (a); sample distribution on a fi lter with a conventional fi lter cup (b); and sample distribution on a fi lter with a variable-area fi lter cup (c)

3.3 Microplastic extraction recovery experiment

To demonstrate the practicability of the simplifi ed 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 fl otation 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°C is 1.20 g/mL (Hidalgo-Ruz et al., 2012), this solution was used to carry out density fl otation 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 fl otation (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 identifi es particle smaller than 20 μm while retaining their original morphology without organic matter digestion, simultaneously allowing the polymer type to be identifi ed.

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 Eff ect of the non-digestion process on Raman detection

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)

This study aimed to identify small microplastics from marine sediment according to a simplifi ed process. Therefore, to validate the eff ects 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 fl otation, 10 mL of 30% H2O2, which is a frequently used and eff ective 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 fi lter the microplastics for Raman detection. Microscopic observation of the samples digested by H2O2demonstrated 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 diffi cult; therefore, H2O2digestion could complicate analysis rather than facilitate it (Nuelle et al., 2014). For the samples without H2O2treatment, 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.

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 identifi ed as PP (Fig.3c & d). However, biological residue could lead to inaccurate spectra and fl uorescence in some instances (Hidalgo-Ruz et al., 2012; Araujo et al., 2018). Therefore, we could reduce fl uorescence 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 simplifi ed process presented in this study be used in organic-poor sediment. As stated above, the small particles could be original appearance and qualitatively identifi ed 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 fi ngerprint identifi cation 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 diff erent 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-1is 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 identifi ed by comparing the obtained Raman spectra with the complete Raman spectrum library (Choy et al., 2019). The identifi cation of vibrational modes varies in the literature. We used the specifi c citations for vibrational mode identifi cation, but acknowledge the range of terms used from one table to another.

4.2 Eff ect of pigment on Raman spectra of microplastics

Distinctly colored particles extracted from deep sea sediment from the Southern Ocean (2 749 m) were identifi ed 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 eff ect 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).

These results suggest that the original characteristic bands of the colored PE were masked by those of the phthalocyanine blue pigment, which resembles the fi ndings described by Van 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 simplifi ed process described above could eff ectively 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 identifi cation process resulted in a total of 41 particles in the 5-500 μm range. Moreover, 7 types of microplastics were identifi ed, including PP, PE, polytetrafl uoroethylene (PTFE), PA, PS, PET, and ABS.

Fig.6 Optical microscopic images of marine sediment microparticles with various types, shapes and sizes (a- i)

The morphology of representative microparticles is shown in Fig.6a-i, which corresponds to particles A-I, respectively. By referring to the established reference library, 7 types of microplastics were identifi ed (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-1could 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 diff erent shapes, were classifi ed 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-1were assigned to C-C stretching, and the bands at 1 361 cm-1and 1 458 cm-1were assigned to the CH2bending and CH3bending (Supplementary Table S3). The bands from 2 800 cm-1to 3 000 cm-1correspond to C-H (-CH3) stretching modes (Fig.7a) (Supplementary Table S3). Particle D was identifi ed as PE. The Raman spectrum of particle D has characteristic bands at 1 061 cm-1, a band at 1 128 cm-1corresponding to C-C stretching, a band at 1 295 cm-1corresponding to CH2twisting, a band at 1 440 cm-1corresponding to CH2bending and bands from 2 800 cm-1to 3 000 cm-1corresponding to C-H (-CH2) stretching (Fig.7b) (Supplementary Table S2). Particle E was tentatively identifi ed as PA by comparing the characteristic vibrations. The band at 1 446 cm-1was assigned to CH2bending, and that at 1 648 cm-1was assigned to amide I C=O stretching (Supplementary Table S5). The characteristic band at 3 295 cm-1was assigned to N-H stretching (Fig.7c) (Supplementary Table S5). Particle F was identifi ed as PS due to the characteristic vibration of the benzene ring attributed to the peak at 1 002 cm-1and 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-1for C≡N stretching, it was identifi ed as ABS (Fig.7e) (Supplementary Table S9). Particle H was characterized as PET due to the unique band at 857 cm-1attributed to C-C breathing stretching and the band at 1 727 cm-1attributed to C=O stretching. The region from 2 800 cm-1to 3 000 cm-1is associated with aliphatic C-H stretching modes, while that from 3 000 cm-1to 3 100 cm-1is associated with aromatic C-H stretching (Fig.7f) (Supplementary Table S6). Particle I was clearly identifi ed as PTFE. The typical PTFE bands are located at 729 cm-1for CF2stretching, 1 215 cm-1for C-C stretching, 1 296 cm-1for CF2stretching and 1 379 cm-1for CF stretching (Supplementary Table S8). Particle I indeed is very consistent with the PTFE spectrum (Fig.7g).

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-1and 3 010 cm-1in 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 identifi ed 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).

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

5.2 Size and abundance of microplastics

Various types of environmental samples with small sizes were analyzed through the established simplifi ed process. The fi ndings 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-fi fth 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).

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 fi bers owing to their use in synthetic textile fi bers. 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 fi ndings 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 fi lter could also result in inconsistent fi ndings 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 fi lter 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 fi lter could be a rational choice when considering the measurement time and effi ciency.

As illustrated above, microplastics extracted from marine sediment and smaller than 10 μm could be detected with a simplifi ed 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 identifi cation protocols. In addition, a lower size limit has not been reached in environmental samples. This study provides an effi cient 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 simplifi ed process in marine sediment samples with microplastics smaller than 500 μm in Huiquan Bay and identifi ed 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 Mega-Science, CAS.

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