Evaluation of Vertical Distribution Characteristics of Microplastics under 20 μm in River and Lake Waters in South Korea

Evaluation of Vertical Distribution Characteristics of Microplastics under 20 μm in River and Lake Waters in South Korea | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of Vertical Distribution Characteristics of Microplastics under 20 μm in River and Lake Waters in South Korea Junho Lee, Seonghyeon Ju, Chaehwi Lim, Kyung Tae Kim, Homin Kye, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2310693/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Following the alarming reports of microplastic pollution in the marine environment, increased attention has been given to microplastics in other environmental media. Despite the attention, there is limited information on the effects of microplastic distribution in freshwater systems. Further, because the size of microplastics varies widely in the environment, the commonly used sampling devices are not suitable for selectively extracting microplastics without causing cross-contamination. Thus, we developed a suitable device for microplastics of size 5–20 µm and studied microplastic distribution in freshwater at various depths by considering various types of microplastics and aqueous systems. Two large water systems, a lake and a river, were chosen to study microplastic distribution. The microplastic distribution characteristics in both water systems showed that polypropylene and polyethylene were the most abundant across all depths because of their production volume. Plastic types with higher density were found only at the lower layers, and polystyrene was found in the upper layers because of the environmental effects on its pore diameter and surface area. The Lake and River had higher microplasticdistribution in the lower layer and upper layer, respectively. This was because the flow rate in River was higher than that of Lake. The higher flow rate reduced the settling velocity in River. Thus, hydrodynamic stability influences the vertical distribution and concentrations of microplastics in the water systems. These results contribute to the understanding and control of microplastics. flow rate hydrodynamics microplastic sampling Raman spectroscopy vertical distribution water supply Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Since the study highlighting increasing microplastics in the oceans was published in 2004, various studies have been conducted on microplastics in the ocean (Thompson et al. 2004 ). Consequently, the interest in the fate of microplastics has been extended to various environmental media, such as soil, sediment, air, and freshwater (Alimi et al. 2018 ; Andrady 2011 ; Fu et al. 2021 ; Imhof et al. 2012 ; Nizzetto et al. 2016 ; Panko et al, 2013 ). Particularly, increasing attention is being given to microplastic research in aquatic systems such as freshwater, treated water, and drinking water, which can directly affect the ecosystems and human consumption (Horton et al. 2017 ). Further, these interests have led to the international acceptance of the definition of microplastics, which states that microplastics are small plastic pieces or fibers that are smaller than 5 mm in size. However, there is limited knowledge on the effects of microplastics on freshwater environments when compared to that of other environmental media, although freshwater is a well-known source of drinking water (Li et al. 2020 ). Based on the production method, microplastics are classified into primary and secondary microplastics. Primary microplastics, which are less than 5 mm, are synthesized for commercial purposes and found in personal care products and textiles. Secondary microplastics are fragments of larger plastics that breakdown upon exposure to natural factors such as ultraviolet radiation, wind, and water (E. Hernandez et al. 2017 ; L. Hernandez et al. 2017 ; McDevitt et al. 2017 ). Primary microplastics are regulated by laws; however, the regulation of secondary microplastics is difficult (Rochman et al. 2015). The surface of the exposed plastic may become more active, and the behavior of oxygen-containing functional groups could be altered (Hüffer et al. 2018 ; Liu et al. 2019 ; Müller et al. 2018 ). Accordingly, microplastics adsorbed with harmful heavy metals—such as Cr 6+ , Ni 2+ , and Cu 2+ —or organic substances present in the aquatic environment can be transported (Holmes et al. 2014 ). Further, microplastics of size 3 µm produced by natural surface aging were shown to be more significantly ingested and internalized into cells compared with that of pristine microplastics (Ramsperger et al. 2020 ). This possibility of microplastic internalization could reveal the potential of direct or indirect cell toxicity. However, widely-used sampling devices such as manta trawl and plankton net are designed for collecting 100–1000 µm-sized microplastics on water surface, and because parts of the sampling devices are plastic, there is a possibility of cross-contamination during sampling process (Prata et al. 2019 ). Furthermore, because the microplastic sizes vary in the environment, a size-suitable device is necessary to evaluate their distribution. Thus, in this study, microplastics of size 5–20 µm were targeted, and a sampling device capable of separating microplastics of sizes 1–5 µm and 20–50 µm was developed and used. In addition to various sizes, the intrinsic density of each microplastic is different; thus, the investigation of the distribution according to the water depth in the aquatic bodies is necessary. Based on aqueous system types, hydrodynamic differences can affect the distribution characteristics of microplastics. Generally, lakes are more stable than rivers in terms of flow rate, and interlayer convection because of temperature is much more frequent in lakes than rivers. In this study investigated small-sized microplastics under 20 µm from the most representative water sources, such as rivers and lakes, in Republic of Korea. Particularly, vertical distribution characteristics of plastics having a wide density distribution in fresh water were identified. Two representative freshwater sampling sites were chosen for comparing microplastic distribution characteristics by depth and hydrodynamics. Moreover, a sampling device to collect microplastics under 20 µm and minimize cross-contamination was developed. The water depth was measured at the sampling sites, and the samples were collected at each depth by dividing them into three layers. Organic matter pre-treatment and density separation of samples were performed for µ-Raman spectroscopy analysis. Materials And Methods Sample Site and Collection of each layer The microplastic samples were collected from Paldang lake (P-Lake) and Nakdong river (N-River) in South Korea during November 2021 (Fig. 1 ). P-Lake is a large water body and major water supply source. N-River is a large water body, and the national industrial park is located near the sampling point. A boat was used to reach the sampling point, which was adequately representative of the sampling site. After the boat engine stopped, we waited until the water layer stabilized to minimize the possibility of external influx during sampling. The depth of sampling points was measured. The upper layer water was collected at the depth of 2 m below the water surface to avoid contamination from materials floating on the water surface. A point 2 m above the bottom of water was selected as the lower layer to avoid contamination from substances that may rise from the bottom. For the middle layer, a point at half of the total depth was selected. Samples at that layer were collected using a silicon tube with pump. The collected samples were transferred to stainless steel (STS) containers. Samples collected from each layer were screened through 50 µm pore size sieve for isolate target sized samples (Fig. 2 a). Moreover, through screening process, soil particles, plant matter, and debris were separated. Sampling Device The sampling device was manufactured using STS without plastic components. The sampling device composed of a housing and cassette made from STS and silicon. The housing holds the cassette, which in turn holds the STS filter (Fig. 2 a). The filtration was performed using an aspirator bottle and vacuum pump. The collected aqueous sample was filtered through STS filter of pore size 1 µm. The device recovery was analyzed using synthetic polymers such as polypropylene (PP), polystyrene (PS), polyethylene (PE), polyvinyl chloride (PVC), and polyethylene terephthalate (PET). The average diameter of polymers was 13–18 µm. These polymers were made by Korea Testing & Research Institute (KTR) using multi-sieve shaking after ultra-fine particle grind. The device recovery was analyzed by comparing the weight of STS filter of pore size 1 µm by micro-balance. Sample Filtration And Pre-treatment The collected samples were screened and filtered near sampling sites. The screened samples were filtered through an STS filter with pore size 1 µm using the manufactured sampling device. After transferring the residue to the laboratory without opening the housing to minimize contamination, the organic matter that could interfere with spectroscopic analysis was removed by wet peroxide oxidation (WPO) using H 2 O 2 solution, which is the most widely used method in many studies (Hidalgo-Ruz et al. 2012 ; Nuelle et al. 2014 ; Quinn et al. 2017 ; Shim et al. 2016 ; Wu et al. 2020 ; Zhao et al. 2017 ). During the WPO, the residue along with 35% H 2 O 2 solution was subjected to ultrasonic extraction. After extraction, it was heated in the oven at 90°C for 3 h to oxidize organic matter from the microplastic surface. After WPO, the solution was filtered through STS filter with 1 µm pore size to isolate microplastics, and the filter was backwashed into ZnCl 2 solution by ultrasonic filtration (Fig. 2 b). ZnCl 2 is widely used for density separation in microplastics pre-treatments (Coppock et al. 2017 ). After ultrasonic treatment, the solution was rested for 1 h and the beaker was covered to allow floating of microplastics. After the supernatant was collected, screening process was performed to selectively extract samples of targeted size using 20 µm STS filter. The screened sample was filtered with an Si-filter and washed three to five times using ethanol to collect maximum remaining microplastics. The Si-filter pore size is 5 µm. Salts were removed using a chelating agent such as EDTA. Finally, the microplastics were subjected to µ-Raman spectroscopy. Reagents Hydrogen peroxide (35%) solution was purchased from Daejung Chemical & Metals Co. LTD in Republic of Korea. Ethanol (99%), Zinc chloride (98%) powder, and ethylenediaminetetraacetic acid disodium salt solution (EDTA-2Na, 0.1 M) were obtained from DUKSAN pure chemicals Inc in Republic of Korea. High-performance liquid chromatography (HPLC) grade water for field blank samples was purchased from J. T. Baker. Distilled–deionized (DI) water was used in all experiments. Analysis The STS filter surface of the sampling device was analyzed by scanning electron microscopy (JSM-6701F; JEOL Ltd.). Micro-Raman spectroscopy (XploRA™ Plus; HORIBA, Japan) was performed to analyze the collected particles through silicon filter (Si-filter). The pre-treated sample was filtered through Si-filter with 5 µm pore size and analyzed. A micro-balance (BM-20; A&D Company, Ltd., Japan) was used to weigh the STS filter for assessing the recovery of the sampling device and pretreatment process. Control Of Cross-contamination The solutions used in all processes were filtered using glass fiber filters paper (GF/F, Whatman) of pore size 0.7 µm. Further, glass and STS equipment were used in the process instead of plastic materials. To minimize cross-contamination, the air flow inside the laboratory was controlled by removing or turning off the air-conditioner and fan, and cotton clothes were worn during sampling and pretreatment process. Blank To confirm that microplastics were introduced during field sampling, blank samples were prepared by filtering HPLC-grade water through STS filter in the field. During pre-treatment, the DI water was purified using glass-fiber filter and filtered through STS filter. The blank samples were analyzed by µ-Raman spectroscopy. Results And Discussion Evaluation of Sampling Device To evaluate the device recovery, polymers under size 20 µm were used. The synthetic polymer species used were PP, PS, PET, PVC, and HDPE. Recovery was measured by the difference in weight of the STS filter in the device before and after filtration. The recovery rates of synthetic polymers used in the study are presented in Table 1 . The average recovery rate was 94.083%. The recovery rate based on the weight difference may not be accurate because of factors such as moisture, temperature, and vibration. Therefore, thermal extraction desorption-gas chromatography–mass spectrometry (TED-GC–MS) was conducted for accurate weight measurement. Thermal analysis showed a recovery rate of 87.015% (Table 1 ). This result has an error range of around 10% compared to the weight analysis method, and it could be confirmed that the device used in this study showed a relatively high recovery rate. Table 1 Recovery efficiency of sampling device using manufactured polymers of size < 20 µm assessed by weighing the filter and by thermal extraction desorption-gas chromatography-mass spectrometry (TED-GC-MS) Species of microplastics (a) Recovery (%) PP 97.287 PS 94.190 PET 97.341 PVC 86.539 HDPE 95.060 Average recovery of sampling device 94.083 Recovery using TED-GC–MS (PS) 84.269 (a) PP, polypropylene; PS, polystyrene; PET, polyethylene terephthalate; PVC, polyvinyl chloride; HDPE, high-density polyethylene Table 2 shows the results of blank sample analysis by µ-Raman spectroscopy. The blank samples were prepared before filtering the environmental samples using 4 L HPLC-grade water. The results of blank samples showed the presence of 0.25–4.25 particles/L. This result indicates concentration of microplastics which caused device and cross-contamination in filtration process. Through blank sample analysis, it is possible to minimize the error of analysis results. Manta trawl and plankton net have been used for research on microplastics in aqueous systems. Although these devices are useful for separating particles of a specific size range, they have components made of plastics. Plastic fragments generated from these devices during sampling can cause cross-contamination, which affects the results of microplastic analysis. The blank sample analysis manta trawl and plankton net showed 1.85–31 microplastic particles (Bikker et al., 2020 ; Mu et al., 2019a ; Mu et al., 2019b ). Through comparing blank sample results, it was confirmed that the device manufactured in this study had relatively little cross-contamination than other devices. Further, these net-based sampling devices are suitable for studying microplastics of sizes over 100 µm in aqueous media surfaces but are not suitable for those under 20 µm, which are targeted in this study. Therefore, manufacturing a new sampling device with minimal cross-contamination while selectively separating 20 µm plastic was necessary. The results of recovery rate and the blank analysis showed that the manufactured device was highly efficient and had low cross-contamination. Table 2 Microplastic concentrations in blank samples (HPLC-grade water) after filtering through manufactured sampling device Species of microplastics Concentration (particles/L) P-Lake N-River PP 0.25 4.25 PS 0.00 0.50 PET 0.50 0.00 PVC 0.25 0.00 PE 1.00 3.00 Size Of The Microplastics The microplastics were divided by their sizes as follows: 50 µm. The concentrations of microplastics over 50 µm size was 7.70 particles/L and 8.37 particles/L in P-Lake and N-River, respectively (Fig. 3 ). The proportion of over 50 µm size to total results was 3.53% and 2.62%, respectively, in P-Lake and N-River. The ratio is the smallest, and it can be seen as the effect of screening using 50 µm pore size sieves in the sample collection process. The concentrations of microplastics of size 20–50 µm were 43.14 particles/L and 73.81 particles/L in P-Lake and N-River, respectively. The concentrations of microplastics of size 5–20 µm, which were targeted in this study, were 133.61 particles/L and 202.07 particles/L in P-Lake and N-River, respectively. The concentrations of microplastics of size < 5 µm were 33.33 particles/L and 33.24 particles/L in P-Lake and N-River, respectively. The proportion of microplastics of size 5–20 µm was 61.3% and 63.3% of the total microplastics particles in P-Lake and N-River, respectively. The proportion of 5–20 µm size microplastics was highest among the total microplastics. The efficiency of multiple stage size classification of the manufactured device was high for sampling in aqueous media, particularly fresh water, for isolation of microplastics. However, the proportion other than the target size accounts for more than 30%. Microplastics have various shapes such as circular, fiber, and fragments. In particular, in the case of the fiber shape, the size of the cross-sectional area and the overall size may be different. As a result, some losses may occur in the filtration process. Therefore, it is assumed that some fiber-type microplastics not be screened or size-classified. Concentration Of Total Microplastics Figure 4 shows the concentration of total particles and microplastics. The concentrations of both total particles and microplastics were higher in N-River than those in P-Lake. There may be a correlation between the total particle concentration and the total microplastics concentration. Therefore, in this study, a factor R mp was used to indicate the proportion of microplastic particles among total particles. $${R}_{mp} = \frac{particles of microplastics}{Total particles}$$ The R mp in P-Lake and N-River are 1.6×10 − 2 and 1.1×10 − 2 , respectively. In other words, P-Lake has a relatively higher microplastic concentration compared to the total particle than N-River. Several studies have shown that hydrological characteristics such as river type, flow rate, water depth, algae, and discharge amount affect microplastics (Mani et al. 2020; Yan et al.2021; Zhang et al. 2020 ). In addition, morphological characteristics such as dams and dam reservoirs are also considered to have an effect (Wu et al. 2020 ; Corcoran et al. 2019 ). As shown in Table 3 , the flow rate of the N-River was 62.945 m 3 /s, which was higher than that of the P-Lake (0.102 m 3 /s). In addition, the precipitation from November 1 to the sampling date was slightly larger in N-River. As a result, the flow rate and precipitation of the N-River were relatively greater than that of the P-Lake, which affected the concentration of particulate substances, that is, the SS concentration (Table 3 ). Furthermore, it can be seen that it affects the concentration of microplastics. However, the total depth of P-Lake is 21 m, which is deeper than the N-River (8 m). In addition, the P-Lake area is a dam which artificially build for water supply. Construction structures such as dams and reservoirs affect the behavior and movement of microplastics (Sarkar et al. 2021 ; Liro et al. 2020 ). In addition, artificial structures act as a factor that improves the sedimentation condition of microplastics (Di et al. 2018; Kumar et al. 2021 ; Watkins et al. 2019 ). The P-Lake area which is artificially constructed and has deeper water depth has higher microplastic sedimentation conditions than the N-River area. As a result, the R mp value of the P-Lake having a higher precipitation condition might be high. Therefore, the shape, structure, flow rate, precipitation, and depth of the river could affect not only the precipitation state of microplastics but also the concentration. In particular, through the R mp factor presented in this study, it might be a factor that can indirectly indicate the microplastic precipitation state, flow rate, and the structure at the sampling point. Table 3 Temperature, suspended solid (SS), flow rate, and precipitation recorded in sampling site Site Total depth (m) Temperature of water (°C) SS (a) (mg/L) Flow rate (a) (m 3 /s) Precipitation Duration (b) (days) Amount (mm) P-Lake 21.0 12.2 3.2 0.102 23 28.7 N-River 9.8 13.46 6.56 62.945 25 39.7 (a) The result of SS concentration and flow rate was obtained from the Water Environment Information System of the Ministry of Environment of South Korea. (b) The precipitation measurement duration for sampling sites is from November 1 to the sampling date (P-Lake = November 23, N-River = November 25). Concentration Of Microplastics By Layer And Species Figure 5 shows the concentration of microplastics at three layers of depth at the sampling points. The concentrations in the upper layers of P-Lake and N-River were 23.95 particles/L and 182.07 particles/L, respectively. The concentration in the upper layer of N-River was higher than that of P-Lake. In the case of the middle layer, the proportion was similar, with P-Lake at 25% and N-River at 22%. However, the microplastic concentration in the lower layer was 138.38 particles/L at P-Lake, which was higher than that in the N-Lake (65.27 particles/L). In P-Lake, the microplastic concentration in upper layer was lower than that in the lower layer. In N-River, the microplastic concentration in upper layer was higher than that in the lower layer. Similar to the relation between the total particles and SS concentration, the environmental factors could possibly affect the distribution of microplastics by layers. The flow rate in the two sampling sites was the biggest difference (Table 3 ). The cross-sectional distance of the sampling point is 567 m for P-Lake and 207 m for N-River. The cross-sectional area according to the depth is 11,907 m 2 for P-Lake and 2,028 m 2 for N-River. Therefore, the velocity is 8.57 × 10 − 6 m/s for P-Lake and 31.03 m/s for N-River. It means that the velocity of the P-Lake is very small compared to the N-River, and the number of Reynolds is small. Reynolds number is also a factor that distinguishes laminar flow and turbulence of fluids. In relatively small P-Lakes, laminar flow can be governed, and in N-River, turbulence can be dominated (Kumar et al. 2021 ; Waldschläger et al. 2019). But the concentration of microplastics will not be affected by only the Reynolds number. This is because very complex factors such as microplastic density, shape, hydrological properties, aggregation, aging, and biological system (Jódar-Reyes et al. 2006 ; Liu et al. 2020 ; Miao et al. 2021 ; Song et al. 2019 ). However, in the case of P-Lake, where laminar flow prevails, the concentration of lower layer may be relatively high due to the sedimentation of microplastics. Conversely, in the case of N-River, where turbulence is dominant, the concentration of upper layer may be higher than that of lower layer due to inter-layer mixing or convection during the process of microplastics settling. Concentration Of Microplastics By Species The distribution of microplastics based on their type and depending on the depths is shown in Fig. 6 . Grey color indicates PE, green color is PP, blue is PS, and red is PET. PE and PP were found in the highest proportions in all the layers and sites. The composition of PE was 6–72% and PP was 18–75%. The abundant concentrations of these two plastic species could be because of the quantity of their production. The highest produced plastic groups are PE (36%), PP (21%), and PVC (12%), which are followed by PET, polyurethane, and PS (< 10% each) (Geyer et al. 2017 ). PE and PP with the highest production ratio are mainly used as materials for packaging. PET was found only in the lower layers. The concentration of PET in the lake and river was 9.7 particles/L (7%) and 3.0 particles/L (5%), respectively. The density of PE, PP, and PS is approximately 0.90–1.10 g/cm 3 , while that of PET is about 1.38–1.41 g/cm 3 . Because the density of PET is relatively higher than that of other plastics, it can be assumed to sink lower and was measured only in the lower layer. Similarly, High-density PE (HDPE) sinking in deeper seawaters has been reported (Dai et al. 2018 ). The proportion of PS decreased, from 35–4% in the lake and 19–5% in the river, as the depth increased. Aged PS had increased surface roughness and decreased average pore diameter (5.1 ± 0.2 nm) than pristine PS (39.3 ± 0.5 nm). Further, the specific surface area increased from 2.0 ± 0.1 m 2 /g to 7.9 ± 0.2 m 2 /g (Fu et al. 2021 ; Sun et al. 2020 ). The porosity could influence the buoyancy of PS. Because PS gains buoyancy with aging, its proportion can be assumed to decrease with increase in the depth. PS is mainly used as thermal packaging material by foaming and buoyancy material in fishing. Therefore, because of the buoyancy characteristics of PS, the distribution of PS decreased with increasing depth. Conclusions A device suitable for sampling microplastics < 20 µm size in fresh water was manufactured. The microplastics were collected according to depth, and their distribution characteristics were identified. PE and PP had the highest proportion in all layers, because of their abundant production. The proportion of PS decreased with increasing depth because of the changes in buoyancy caused by aging-related physicochemical changes in pore diameter and surface area. Further, many PS products are manufactured by foaming, which may also contribute to buoyancy. PET and HDPE were found only in lower layers although the size was < 20 µm, which could be attributed to its density. Finally, the microplastic concentration might be affected by the types of the water system. The hydrodynamic stability varies with the types of water system, which can affect the concentration of layers. Declarations Funding This research was supported by Korea Environment Industry & Technology Institute (KEITI) through Measurement and Risk assessment Program for Management of Microplastics Project, funded by Korea Ministry of Environment (MOE) (Grant numbers 2020003110005). Author contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [Junho Lee], [Seonghyun Ju], [Chaehwi Lim], [Kyung Tae Kim], [Homin Kye], [Jiyoon Kim], [Jihoon Lee], [Seonbaek Kim], [Hye-Won Yu], [Ingyu Lee], [Hyunook Kim]and [Yeojoon Yoon]. The first draft of the manuscript was written by [Junho Lee] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Declarations The authors have no relevant financial or non-financial interests to disclose References Alimi, O. S., Budarz, J. F., Hernandez, L. M., & Tufenkji, N. (2018). Microplastics and Nanoplastics in Aquatic Environments: Aggregation, Deposition, and Enhanced Contaminant Transport. Environmental Science & Technology, 52 (4), 1704–1724. https://doi.org/10.1021/acs.est.7b05559 Andrady, A. L. (2011). Microplastics in the marine environment. 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Laboratory simulation of microplastics weathering and its adsorption behaviors in an aqueous environment: A systematic review. Environmental Pollution, 265, 114864. https://doi.org/10.1016/j.envpol.2020.114864 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, 838–838. https://doi.org/10.1126/science.1094559 Waldschläger, K., & Schüttrumpf, H. (2019). Effects of particle properties on the settling and rise velocities of microplastics in freshwater under laboratory conditions. Environmental science & technology , 53(4), 1958-1966. https://doi.org/10.1021/acs.est.8b06794 Watkins, L., McGrattan, S., Sullivan, P. J., & Walter, M. T. (2019). The effect of dams on river transport of microplastic pollution. Science of the Total Environment , 664, 834-840.https://doi.org/10.1016/j.scitotenv.2019.02.028 Wu, F., Pennings, S. C., Tong, C., & Xu, Y. (2020). Variation in microplastics composition at small spatial and temporal scales in a tidal flat of the Yangtze Estuary, China. Science of The Total Environment , 699, 134252. https://doi.org/10.1016/j.scitotenv.2019.134252 Wu, M., Yang, C., Du, C., & Liu, H. (2020). Microplastics in waters and soils: Occurrence, analytical methods and ecotoxicological effects. Ecotoxicology and Environmental Safety, 202, 110910. https://doi.org/10.1016/j.ecoenv.2020.110910 Yan, M., Wang, L., Dai, Y., Sun, H., & Liu, C. (2021). Behavior of microplastics in inland waters: aggregation, settlement, and transport. Bulletin of Environmental Contamination and Toxicology , 107(4), 700-709. https://doi.org/10.1007/s00128-020-03087-2 Zhang, L., Liu, J., Xie, Y., Zhong, S., Yang, B., Lu, D., & Zhong, Q. (2020). Distribution of microplastics in surface water and sediments of Qin river in Beibu Gulf, China. Science of the Total Environment , 708, 135176. https://doi.org/10.1016/j.scitotenv.2019.135176 Zhao, S., Danley, M., Ward, J. E., Li, D., & Mincer, T. J. (2017). An approach for extraction, characterization and quantitation of microplastic in natural marine snow using Raman microscopy. Analytical Methods, 9 (9), 1470–1478. https://doi.org/10.1039/c6ay02302a Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2310693","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":154934815,"identity":"fe52ab51-dd41-4b15-9e18-48eec308d1a7","order_by":0,"name":"Junho Lee","email":"","orcid":"","institution":"Yonsei University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junho","middleName":"","lastName":"Lee","suffix":""},{"id":154934816,"identity":"9f6fc133-624d-48b8-bb14-baf9ea8dc18b","order_by":1,"name":"Seonghyeon Ju","email":"","orcid":"","institution":"Yonsei University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Seonghyeon","middleName":"","lastName":"Ju","suffix":""},{"id":154934817,"identity":"9c7aad1c-5bd3-4218-800e-3394c5aebe25","order_by":2,"name":"Chaehwi Lim","email":"","orcid":"","institution":"Yonsei University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chaehwi","middleName":"","lastName":"Lim","suffix":""},{"id":154934818,"identity":"7350e5cf-e751-4f16-8146-50140bb17885","order_by":3,"name":"Kyung Tae Kim","email":"","orcid":"","institution":"Yonsei University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kyung","middleName":"Tae","lastName":"Kim","suffix":""},{"id":154934819,"identity":"98e19766-0101-407e-a1ea-d9a0fb4720ea","order_by":4,"name":"Homin Kye","email":"","orcid":"","institution":"Yonsei 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01:59:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2310693/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2310693/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":29677806,"identity":"cc6d0279-7f36-4b09-a302-7878587d2d3b","added_by":"auto","created_at":"2022-11-29 18:27:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":767700,"visible":true,"origin":"","legend":"\u003cp\u003eMap of P Lake (a) and N River (b) in South Korea and sampling sites were indicated with red dots\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2310693/v1/99425db1254664ee47d718c7.png"},{"id":29677223,"identity":"d89a921b-c6db-4fc9-aed0-3ca9d8a0a6fb","added_by":"auto","created_at":"2022-11-29 18:19:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":95755,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the manufactured sampling device (a) and its filtration process and pre-treatment process of the sampling before analysis (b)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2310693/v1/02b33438d23e3e0484b8bb2f.png"},{"id":29677226,"identity":"312a62b9-934e-4d11-b8c1-2ef7924f7684","added_by":"auto","created_at":"2022-11-29 18:19:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":93738,"visible":true,"origin":"","legend":"\u003cp\u003eConcentration of microplastics (particles/L) of sampling sites. The blue color indicates under 5 μm size microplastics, orange color is 5-20 μm size, grey color is 20-50 μm, and yellow means over 50 μm size.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2310693/v1/b62979b4bcbd2d1a1ec1a633.png"},{"id":29677224,"identity":"cb2b5290-fa1f-4150-b709-50b993a75738","added_by":"auto","created_at":"2022-11-29 18:19:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":75346,"visible":true,"origin":"","legend":"\u003cp\u003eConcentration of total particles (particles/L) including microplastics and concentration of microplastics (particles/L) alone in P-Lake and N-River\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2310693/v1/2ba25034ece79feb8844e722.png"},{"id":29677225,"identity":"eb0e6fca-6592-4d93-8257-57b267435810","added_by":"auto","created_at":"2022-11-29 18:19:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":102821,"visible":true,"origin":"","legend":"\u003cp\u003eConcentration of microplastics (particles/L) by water depth. Blue indicate concentration of microplastics of lower layers, green is middle layer, and yellow is upper layers.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2310693/v1/e1cadb96ba15dec828c27144.png"},{"id":29677228,"identity":"3b4400ba-e0d5-4025-8d53-fac233512872","added_by":"auto","created_at":"2022-11-29 18:19:07","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":263927,"visible":true,"origin":"","legend":"\u003cp\u003eConcentration of microplastics (particles/L) and their distribution proportion by water depth and plastic types\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-2310693/v1/e01665a3a4adb39408f3acb9.png"},{"id":30791913,"identity":"c4988bcc-b500-4100-93a6-486d38bfbcba","added_by":"auto","created_at":"2022-12-27 08:29:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1619711,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2310693/v1/c132b831-0d17-4495-9205-c9551126d37f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of Vertical Distribution Characteristics of Microplastics under 20 μm in River and Lake Waters in South Korea","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince the study highlighting increasing microplastics in the oceans was published in 2004, various studies have been conducted on microplastics in the ocean (Thompson et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Consequently, the interest in the fate of microplastics has been extended to various environmental media, such as soil, sediment, air, and freshwater (Alimi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Andrady \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Fu et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Imhof et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Nizzetto et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Panko et al, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Particularly, increasing attention is being given to microplastic research in aquatic systems such as freshwater, treated water, and drinking water, which can directly affect the ecosystems and human consumption (Horton et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Further, these interests have led to the international acceptance of the definition of microplastics, which states that microplastics are small plastic pieces or fibers that are smaller than 5 mm in size. However, there is limited knowledge on the effects of microplastics on freshwater environments when compared to that of other environmental media, although freshwater is a well-known source of drinking water (Li et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Based on the production method, microplastics are classified into primary and secondary microplastics. Primary microplastics, which are less than 5 mm, are synthesized for commercial purposes and found in personal care products and textiles. Secondary microplastics are fragments of larger plastics that breakdown upon exposure to natural factors such as ultraviolet radiation, wind, and water (E. Hernandez et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; L. Hernandez et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; McDevitt et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Primary microplastics are regulated by laws; however, the regulation of secondary microplastics is difficult (Rochman et al. 2015). The surface of the exposed plastic may become more active, and the behavior of oxygen-containing functional groups could be altered (H\u0026uuml;ffer et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; M\u0026uuml;ller et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Accordingly, microplastics adsorbed with harmful heavy metals\u0026mdash;such as Cr\u003csup\u003e6+\u003c/sup\u003e, Ni\u003csup\u003e2+\u003c/sup\u003e, and Cu\u003csup\u003e2+\u003c/sup\u003e\u0026mdash;or organic substances present in the aquatic environment can be transported (Holmes et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Further, microplastics of size 3 \u0026micro;m produced by natural surface aging were shown to be more significantly ingested and internalized into cells compared with that of pristine microplastics (Ramsperger et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This possibility of microplastic internalization could reveal the potential of direct or indirect cell toxicity. However, widely-used sampling devices such as manta trawl and plankton net are designed for collecting 100\u0026ndash;1000 \u0026micro;m-sized microplastics on water surface, and because parts of the sampling devices are plastic, there is a possibility of cross-contamination during sampling process (Prata et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, because the microplastic sizes vary in the environment, a size-suitable device is necessary to evaluate their distribution. Thus, in this study, microplastics of size 5\u0026ndash;20 \u0026micro;m were targeted, and a sampling device capable of separating microplastics of sizes 1\u0026ndash;5 \u0026micro;m and 20\u0026ndash;50 \u0026micro;m was developed and used. In addition to various sizes, the intrinsic density of each microplastic is different; thus, the investigation of the distribution according to the water depth in the aquatic bodies is necessary. Based on aqueous system types, hydrodynamic differences can affect the distribution characteristics of microplastics. Generally, lakes are more stable than rivers in terms of flow rate, and interlayer convection because of temperature is much more frequent in lakes than rivers.\u003c/p\u003e \u003cp\u003eIn this study investigated small-sized microplastics under 20 \u0026micro;m from the most representative water sources, such as rivers and lakes, in Republic of Korea. Particularly, vertical distribution characteristics of plastics having a wide density distribution in fresh water were identified. Two representative freshwater sampling sites were chosen for comparing microplastic distribution characteristics by depth and hydrodynamics. Moreover, a sampling device to collect microplastics under 20 \u0026micro;m and minimize cross-contamination was developed. The water depth was measured at the sampling sites, and the samples were collected at each depth by dividing them into three layers. Organic matter pre-treatment and density separation of samples were performed for \u0026micro;-Raman spectroscopy analysis.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample Site and Collection of each layer\u003c/h2\u003e \u003cp\u003eThe microplastic samples were collected from Paldang lake (P-Lake) and Nakdong river (N-River) in South Korea during November 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). P-Lake is a large water body and major water supply source. N-River is a large water body, and the national industrial park is located near the sampling point. A boat was used to reach the sampling point, which was adequately representative of the sampling site. After the boat engine stopped, we waited until the water layer stabilized to minimize the possibility of external influx during sampling. The depth of sampling points was measured. The upper layer water was collected at the depth of 2 m below the water surface to avoid contamination from materials floating on the water surface. A point 2 m above the bottom of water was selected as the lower layer to avoid contamination from substances that may rise from the bottom. For the middle layer, a point at half of the total depth was selected. Samples at that layer were collected using a silicon tube with pump. The collected samples were transferred to stainless steel (STS) containers. Samples collected from each layer were screened through 50 \u0026micro;m pore size sieve for isolate target sized samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Moreover, through screening process, soil particles, plant matter, and debris were separated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSampling Device\u003c/h3\u003e\n\u003cp\u003eThe sampling device was manufactured using STS without plastic components. The sampling device composed of a housing and cassette made from STS and silicon. The housing holds the cassette, which in turn holds the STS filter (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The filtration was performed using an aspirator bottle and vacuum pump. The collected aqueous sample was filtered through STS filter of pore size 1 \u0026micro;m. The device recovery was analyzed using synthetic polymers such as polypropylene (PP), polystyrene (PS), polyethylene (PE), polyvinyl chloride (PVC), and polyethylene terephthalate (PET). The average diameter of polymers was 13\u0026ndash;18 \u0026micro;m. These polymers were made by Korea Testing \u0026amp; Research Institute (KTR) using multi-sieve shaking after ultra-fine particle grind. The device recovery was analyzed by comparing the weight of STS filter of pore size 1 \u0026micro;m by micro-balance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eSample Filtration And Pre-treatment\u003c/h3\u003e\n\u003cp\u003eThe collected samples were screened and filtered near sampling sites. The screened samples were filtered through an STS filter with pore size 1 \u0026micro;m using the manufactured sampling device. After transferring the residue to the laboratory without opening the housing to minimize contamination, the organic matter that could interfere with spectroscopic analysis was removed by wet peroxide oxidation (WPO) using H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e solution, which is the most widely used method in many studies (Hidalgo-Ruz et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Nuelle et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Quinn et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Shim et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wu et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). During the WPO, the residue along with 35% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e solution was subjected to ultrasonic extraction. After extraction, it was heated in the oven at 90\u0026deg;C for 3 h to oxidize organic matter from the microplastic surface. After WPO, the solution was filtered through STS filter with 1 \u0026micro;m pore size to isolate microplastics, and the filter was backwashed into ZnCl\u003csub\u003e2\u003c/sub\u003e solution by ultrasonic filtration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). ZnCl\u003csub\u003e2\u003c/sub\u003e is widely used for density separation in microplastics pre-treatments (Coppock et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). After ultrasonic treatment, the solution was rested for 1 h and the beaker was covered to allow floating of microplastics. After the supernatant was collected, screening process was performed to selectively extract samples of targeted size using 20 \u0026micro;m STS filter. The screened sample was filtered with an Si-filter and washed three to five times using ethanol to collect maximum remaining microplastics. The Si-filter pore size is 5 \u0026micro;m. Salts were removed using a chelating agent such as EDTA. Finally, the microplastics were subjected to \u0026micro;-Raman spectroscopy.\u003c/p\u003e\n\u003ch3\u003eReagents\u003c/h3\u003e\n\u003cp\u003eHydrogen peroxide (35%) solution was purchased from Daejung Chemical \u0026amp; Metals Co. LTD in Republic of Korea. Ethanol (99%), Zinc chloride (98%) powder, and ethylenediaminetetraacetic acid disodium salt solution (EDTA-2Na, 0.1 M) were obtained from DUKSAN pure chemicals Inc in Republic of Korea. High-performance liquid chromatography (HPLC) grade water for field blank samples was purchased from J. T. Baker. Distilled\u0026ndash;deionized (DI) water was used in all experiments.\u003c/p\u003e\n\u003ch3\u003eAnalysis\u003c/h3\u003e\n\u003cp\u003eThe STS filter surface of the sampling device was analyzed by scanning electron microscopy (JSM-6701F; JEOL Ltd.). Micro-Raman spectroscopy (XploRA\u0026trade; Plus; HORIBA, Japan) was performed to analyze the collected particles through silicon filter (Si-filter). The pre-treated sample was filtered through Si-filter with 5 \u0026micro;m pore size and analyzed. A micro-balance (BM-20; A\u0026amp;D Company, Ltd., Japan) was used to weigh the STS filter for assessing the recovery of the sampling device and pretreatment process.\u003c/p\u003e\n\u003ch3\u003eControl Of Cross-contamination\u003c/h3\u003e\n\u003cp\u003eThe solutions used in all processes were filtered using glass fiber filters paper (GF/F, Whatman) of pore size 0.7 \u0026micro;m. Further, glass and STS equipment were used in the process instead of plastic materials. To minimize cross-contamination, the air flow inside the laboratory was controlled by removing or turning off the air-conditioner and fan, and cotton clothes were worn during sampling and pretreatment process.\u003c/p\u003e\n\u003ch3\u003eBlank\u003c/h3\u003e\n\u003cp\u003eTo confirm that microplastics were introduced during field sampling, blank samples were prepared by filtering HPLC-grade water through STS filter in the field. During pre-treatment, the DI water was purified using glass-fiber filter and filtered through STS filter. The blank samples were analyzed by \u0026micro;-Raman spectroscopy.\u003c/p\u003e"},{"header":"Results And Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of Sampling Device\u003c/h2\u003e \u003cp\u003eTo evaluate the device recovery, polymers under size 20 \u0026micro;m were used. The synthetic polymer species used were PP, PS, PET, PVC, and HDPE. Recovery was measured by the difference in weight of the STS filter in the device before and after filtration. The recovery rates of synthetic polymers used in the study are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The average recovery rate was 94.083%. The recovery rate based on the weight difference may not be accurate because of factors such as moisture, temperature, and vibration. Therefore, thermal extraction desorption-gas chromatography\u0026ndash;mass spectrometry (TED-GC\u0026ndash;MS) was conducted for accurate weight measurement. Thermal analysis showed a recovery rate of 87.015% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This result has an error range of around 10% compared to the weight analysis method, and it could be confirmed that the device used in this study showed a relatively high recovery rate.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRecovery efficiency of sampling device using manufactured polymers of size\u0026thinsp;\u0026lt;\u0026thinsp;20 \u0026micro;m assessed by weighing the filter and by thermal extraction desorption-gas chromatography-mass spectrometry (TED-GC-MS)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies of microplastics \u003csup\u003e(a)\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRecovery (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97.287\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97.341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86.539\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDPE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage recovery of sampling device\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecovery using TED-GC\u0026ndash;MS (PS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84.269\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e(a) PP, polypropylene; PS, polystyrene; PET, polyethylene terephthalate; PVC, polyvinyl chloride; HDPE, high-density polyethylene\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the results of blank sample analysis by \u0026micro;-Raman spectroscopy. The blank samples were prepared before filtering the environmental samples using 4 L HPLC-grade water. The results of blank samples showed the presence of 0.25\u0026ndash;4.25 particles/L. This result indicates concentration of microplastics which caused device and cross-contamination in filtration process. Through blank sample analysis, it is possible to minimize the error of analysis results. Manta trawl and plankton net have been used for research on microplastics in aqueous systems. Although these devices are useful for separating particles of a specific size range, they have components made of plastics. Plastic fragments generated from these devices during sampling can cause cross-contamination, which affects the results of microplastic analysis. The blank sample analysis manta trawl and plankton net showed 1.85\u0026ndash;31 microplastic particles (Bikker et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mu et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e; Mu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). Through comparing blank sample results, it was confirmed that the device manufactured in this study had relatively little cross-contamination than other devices. Further, these net-based sampling devices are suitable for studying microplastics of sizes over 100 \u0026micro;m in aqueous media surfaces but are not suitable for those under 20 \u0026micro;m, which are targeted in this study. Therefore, manufacturing a new sampling device with minimal cross-contamination while selectively separating 20 \u0026micro;m plastic was necessary. The results of recovery rate and the blank analysis showed that the manufactured device was highly efficient and had low cross-contamination.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMicroplastic concentrations in blank samples (HPLC-grade water) after filtering through manufactured sampling device\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies of microplastics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eConcentration (particles/L)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eP-Lake\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eN-River\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSize Of The Microplastics\u003c/h3\u003e\n\u003cp\u003eThe microplastics were divided by their sizes as follows: \u0026lt;5 \u0026micro;m, 5\u0026ndash;20 \u0026micro;m, 20\u0026ndash;50 \u0026micro;m, and \u0026gt;\u0026thinsp;50 \u0026micro;m. The concentrations of microplastics over 50 \u0026micro;m size was 7.70 particles/L and 8.37 particles/L in P-Lake and N-River, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The proportion of over 50 \u0026micro;m size to total results was 3.53% and 2.62%, respectively, in P-Lake and N-River. The ratio is the smallest, and it can be seen as the effect of screening using 50 \u0026micro;m pore size sieves in the sample collection process. The concentrations of microplastics of size 20\u0026ndash;50 \u0026micro;m were 43.14 particles/L and 73.81 particles/L in P-Lake and N-River, respectively. The concentrations of microplastics of size 5\u0026ndash;20 \u0026micro;m, which were targeted in this study, were 133.61 particles/L and 202.07 particles/L in P-Lake and N-River, respectively. The concentrations of microplastics of size\u0026thinsp;\u0026lt;\u0026thinsp;5 \u0026micro;m were 33.33 particles/L and 33.24 particles/L in P-Lake and N-River, respectively. The proportion of microplastics of size 5\u0026ndash;20 \u0026micro;m was 61.3% and 63.3% of the total microplastics particles in P-Lake and N-River, respectively. The proportion of 5\u0026ndash;20 \u0026micro;m size microplastics was highest among the total microplastics. The efficiency of multiple stage size classification of the manufactured device was high for sampling in aqueous media, particularly fresh water, for isolation of microplastics. However, the proportion other than the target size accounts for more than 30%. Microplastics have various shapes such as circular, fiber, and fragments. In particular, in the case of the fiber shape, the size of the cross-sectional area and the overall size may be different. As a result, some losses may occur in the filtration process. Therefore, it is assumed that some fiber-type microplastics not be screened or size-classified.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eConcentration Of Total Microplastics\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the concentration of total particles and microplastics. The concentrations of both total particles and microplastics were higher in N-River than those in P-Lake. There may be a correlation between the total particle concentration and the total microplastics concentration. Therefore, in this study, a factor \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003emp\u003c/em\u003e\u003c/sub\u003e was used to indicate the proportion of microplastic particles among total particles.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${R}_{mp} = \\frac{particles of microplastics}{Total particles}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003emp\u003c/em\u003e\u003c/sub\u003e in P-Lake and N-River are 1.6\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e and 1.1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, respectively. In other words, P-Lake has a relatively higher microplastic concentration compared to the total particle than N-River. Several studies have shown that hydrological characteristics such as river type, flow rate, water depth, algae, and discharge amount affect microplastics (Mani et al. 2020; Yan et al.2021; Zhang et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, morphological characteristics such as dams and dam reservoirs are also considered to have an effect (Wu et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Corcoran et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the flow rate of the N-River was 62.945 m\u003csup\u003e3\u003c/sup\u003e/s, which was higher than that of the P-Lake (0.102 m\u003csup\u003e3\u003c/sup\u003e/s). In addition, the precipitation from November 1 to the sampling date was slightly larger in N-River. As a result, the flow rate and precipitation of the N-River were relatively greater than that of the P-Lake, which affected the concentration of particulate substances, that is, the SS concentration (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Furthermore, it can be seen that it affects the concentration of microplastics. However, the total depth of P-Lake is 21 m, which is deeper than the N-River (8 m). In addition, the P-Lake area is a dam which artificially build for water supply. Construction structures such as dams and reservoirs affect the behavior and movement of microplastics (Sarkar et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liro et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition, artificial structures act as a factor that improves the sedimentation condition of microplastics (Di et al. 2018; Kumar et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Watkins et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The P-Lake area which is artificially constructed and has deeper water depth has higher microplastic sedimentation conditions than the N-River area. As a result, the \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003emp\u003c/em\u003e\u003c/sub\u003e value of the P-Lake having a higher precipitation condition might be high. Therefore, the shape, structure, flow rate, precipitation, and depth of the river could affect not only the precipitation state of microplastics but also the concentration. In particular, through the \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003emp\u003c/em\u003e\u003c/sub\u003e factor presented in this study, it might be a factor that can indirectly indicate the microplastic precipitation state, flow rate, and the structure at the sampling point.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTemperature, suspended solid (SS), flow rate, and precipitation recorded in sampling site\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal depth (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTemperature of water (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSS\u003csup\u003e(a)\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFlow rate \u003csup\u003e(a)\u003c/sup\u003e (m\u003csup\u003e3\u003c/sup\u003e/s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ePrecipitation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eDuration\u003c/b\u003e \u003csup\u003e\u003cb\u003e(b)\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(days)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eAmount\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(mm)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-Lake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN-River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e39.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e(a) The result of SS concentration and flow rate was obtained from the Water Environment Information System of the Ministry of Environment of South Korea. (b) The precipitation measurement duration for sampling sites is from November 1 to the sampling date (P-Lake\u0026thinsp;=\u0026thinsp;November 23, N-River\u0026thinsp;=\u0026thinsp;November 25).\u003c/p\u003e\n\u003ch3\u003eConcentration Of Microplastics By Layer And Species\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the concentration of microplastics at three layers of depth at the sampling points. The concentrations in the upper layers of P-Lake and N-River were 23.95 particles/L and 182.07 particles/L, respectively. The concentration in the upper layer of N-River was higher than that of P-Lake. In the case of the middle layer, the proportion was similar, with P-Lake at 25% and N-River at 22%. However, the microplastic concentration in the lower layer was 138.38 particles/L at P-Lake, which was higher than that in the N-Lake (65.27 particles/L). In P-Lake, the microplastic concentration in upper layer was lower than that in the lower layer. In N-River, the microplastic concentration in upper layer was higher than that in the lower layer. Similar to the relation between the total particles and SS concentration, the environmental factors could possibly affect the distribution of microplastics by layers. The flow rate in the two sampling sites was the biggest difference (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The cross-sectional distance of the sampling point is 567 m for P-Lake and 207 m for N-River. The cross-sectional area according to the depth is 11,907 m\u003csup\u003e2\u003c/sup\u003e for P-Lake and 2,028 m\u003csup\u003e2\u003c/sup\u003e for N-River. Therefore, the velocity is 8.57 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e m/s for P-Lake and 31.03 m/s for N-River. It means that the velocity of the P-Lake is very small compared to the N-River, and the number of Reynolds is small. Reynolds number is also a factor that distinguishes laminar flow and turbulence of fluids. In relatively small P-Lakes, laminar flow can be governed, and in N-River, turbulence can be dominated (Kumar et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Waldschl\u0026auml;ger et al. 2019). But the concentration of microplastics will not be affected by only the Reynolds number. This is because very complex factors such as microplastic density, shape, hydrological properties, aggregation, aging, and biological system (J\u0026oacute;dar-Reyes et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Miao et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Song et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, in the case of P-Lake, where laminar flow prevails, the concentration of lower layer may be relatively high due to the sedimentation of microplastics. Conversely, in the case of N-River, where turbulence is dominant, the concentration of upper layer may be higher than that of lower layer due to inter-layer mixing or convection during the process of microplastics settling.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eConcentration Of Microplastics By Species\u003c/h3\u003e\n\u003cp\u003eThe distribution of microplastics based on their type and depending on the depths is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Grey color indicates PE, green color is PP, blue is PS, and red is PET. PE and PP were found in the highest proportions in all the layers and sites. The composition of PE was 6\u0026ndash;72% and PP was 18\u0026ndash;75%. The abundant concentrations of these two plastic species could be because of the quantity of their production. The highest produced plastic groups are PE (36%), PP (21%), and PVC (12%), which are followed by PET, polyurethane, and PS (\u0026lt;\u0026thinsp;10% each) (Geyer et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). PE and PP with the highest production ratio are mainly used as materials for packaging.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePET was found only in the lower layers. The concentration of PET in the lake and river was 9.7 particles/L (7%) and 3.0 particles/L (5%), respectively. The density of PE, PP, and PS is approximately 0.90\u0026ndash;1.10 g/cm\u003csup\u003e3\u003c/sup\u003e, while that of PET is about 1.38\u0026ndash;1.41 g/cm\u003csup\u003e3\u003c/sup\u003e. Because the density of PET is relatively higher than that of other plastics, it can be assumed to sink lower and was measured only in the lower layer. Similarly, High-density PE (HDPE) sinking in deeper seawaters has been reported (Dai et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The proportion of PS decreased, from 35\u0026ndash;4% in the lake and 19\u0026ndash;5% in the river, as the depth increased. Aged PS had increased surface roughness and decreased average pore diameter (5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 nm) than pristine PS (39.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 nm). Further, the specific surface area increased from 2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 m\u003csup\u003e2\u003c/sup\u003e/g to 7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 m\u003csup\u003e2\u003c/sup\u003e/g (Fu et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sun et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The porosity could influence the buoyancy of PS. Because PS gains buoyancy with aging, its proportion can be assumed to decrease with increase in the depth. PS is mainly used as thermal packaging material by foaming and buoyancy material in fishing. Therefore, because of the buoyancy characteristics of PS, the distribution of PS decreased with increasing depth.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA device suitable for sampling microplastics\u0026thinsp;\u0026lt;\u0026thinsp;20 \u0026micro;m size in fresh water was manufactured. The microplastics were collected according to depth, and their distribution characteristics were identified. PE and PP had the highest proportion in all layers, because of their abundant production. The proportion of PS decreased with increasing depth because of the changes in buoyancy caused by aging-related physicochemical changes in pore diameter and surface area. Further, many PS products are manufactured by foaming, which may also contribute to buoyancy. PET and HDPE were found only in lower layers although the size was \u0026lt;\u0026thinsp;20 \u0026micro;m, which could be attributed to its density. Finally, the microplastic concentration might be affected by the types of the water system. The hydrodynamic stability varies with the types of water system, which can affect the concentration of layers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Korea Environment Industry \u0026amp; Technology Institute (KEITI) through Measurement and Risk assessment Program for Management of Microplastics Project, funded by Korea Ministry of Environment (MOE) (Grant numbers 2020003110005).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [Junho Lee], [Seonghyun Ju], [Chaehwi Lim], [Kyung Tae Kim], [Homin Kye], [Jiyoon Kim], [Jihoon Lee], [Seonbaek Kim], [Hye-Won Yu], [Ingyu Lee], [Hyunook Kim]and [Yeojoon Yoon]. The first draft of the manuscript was written by [Junho Lee] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlimi, O. S., Budarz, J. F., Hernandez, L. M., \u0026amp; Tufenkji, N. (2018). 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An approach for extraction, characterization and quantitation of microplastic in natural marine snow using Raman microscopy. \u003cem\u003eAnalytical Methods, 9\u003c/em\u003e(9), 1470\u0026ndash;1478. https://doi.org/10.1039/c6ay02302a\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"flow rate, hydrodynamics, microplastic sampling, Raman spectroscopy, vertical distribution, water supply","lastPublishedDoi":"10.21203/rs.3.rs-2310693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2310693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFollowing the alarming reports of microplastic pollution in the marine environment, increased attention has been given to microplastics in other environmental media. Despite the attention, there is limited information on the effects of microplastic distribution in freshwater systems. Further, because the size of microplastics varies widely in the environment, the commonly used sampling devices are not suitable for selectively extracting microplastics without causing cross-contamination. Thus, we developed a suitable device for microplastics of size 5–20 µm and studied microplastic distribution in freshwater at various depths by considering various types of microplastics and aqueous systems. Two large water systems, a lake and a river, were chosen to study microplastic distribution. The microplastic distribution characteristics in both water systems showed that polypropylene and polyethylene were the most abundant across all depths because of their production volume. Plastic types with higher density were found only at the lower layers, and polystyrene was found in the upper layers because of the environmental effects on its pore diameter and surface area. The Lake and River had higher microplasticdistribution in the lower layer and upper layer, respectively. This was because the flow rate in River was higher than that of Lake. The higher flow rate reduced the settling velocity in River. Thus, hydrodynamic stability influences the vertical distribution and concentrations of microplastics in the water systems. These results contribute to the understanding and control of microplastics.\u003c/p\u003e","manuscriptTitle":"Evaluation of Vertical Distribution Characteristics of Microplastics under 20 μm in River and Lake Waters in South Korea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-29 18:19:02","doi":"10.21203/rs.3.rs-2310693/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"483ddeb0-b71b-4af8-9f42-e66f931aa88e","owner":[],"postedDate":"November 29th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-12-27T08:29:16+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-29 18:19:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2310693","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2310693","identity":"rs-2310693","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}