Next Article in Journal
The Exposure to Polypropylene Micro- and Nanoplastics Impairs Wound Healing and Tissue Regeneration in the Leech Hirudo verbana
Previous Article in Journal / Special Issue
Removal of Co-Occurring Microplastics and Metals in an Aqueous System by Pristine and Magnetised Larch Biochar
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Microplastics
Volume 4
Issue 3
10.3390/microplastics4030055
microplastics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Microplastic Distribution in a Small-Scale Aquatic System with Limited Anthropogenic Influence: A Case Study in Sasebo City, Japan

by
Huiho Jeong
1,
Daigo Fukuda
1,
Ahmed Elwaleed
1,
Quynh Thi Nguyen
1,
Pyae Sone Soe
1,
Byeong Kyu Min
2,
Hyeon Seo Cho
3,
Tetsuro Agusa
1 and
Yasuhiro Ishibashi
1,*
1
Faculty of Environmental & Symbiotic Sciences, Prefectural University of Kumamoto, Tsukide 3-1-100, Higashi-Ku, Kumamoto 862-8502, Japan
2
Wando Regional Office, National Fishery Products Quality Management Service, Wando 59116, Republic of Korea
3
Department of Ocean Integrated Science, College of Fisheries & Ocean Science, Chonnam National University, 50 Daehak-Ro, Yeosu 59626, Jeonnam, Republic of Korea
*
Author to whom correspondence should be addressed.
Microplastics 2025, 4(3), 55; https://doi.org/10.3390/microplastics4030055
Submission received: 21 March 2025 / Revised: 5 August 2025 / Accepted: 24 August 2025 / Published: 26 August 2025
(This article belongs to the Collection Feature Papers in Microplastics)
Browse Figures
Versions Notes

Abstract

This study presents the first investigation into the distribution of microplastics (MPs) in Sasebo City, Japan, using principal component analysis (PCA) in conjunction with water flow velocity and salinity variables. The mean MP abundance was 82.4 ± 47.7 items/m3 (SSB1–SSB4), showing no significant difference among sampling points. The fragment-to-fiber ratio was 76:24, and polypropylene and polyethylene (each 41%) were the main polymers. Fragment abundance increased with decreasing particle size, while fibers were rare below 700 μm. PCA indicated distinct MP polymer and shape distributions corresponding to stagnant water (SSB1), high-flow conditions (SSB2 and SSB3), and seawater (SSB4). Based on the literature, the study area represents a case of a small-scale aquatic system with limited anthropogenic influence due to moderate population, short river length, efficient effluent discharge, minimal industry, good water quality, and the absence of significant spatial variation in MP abundance. The infrequent precipitation during the sampling event supports the findings of the present study as a reliable baseline for objectively assessing MP contamination. Compared to aquatic systems of varying scales and anthropogenic influence, this baseline is applicable to both small-scale and large-scale aquatic systems with significant influences. This will serve as a valuable reference for future MP studies across diverse freshwater environments.

1. Introduction

The use of plastic has become an indispensable part of modern human life. Plastics released into aquatic environments are primarily degraded through photolysis [1]. Microplastics (MPs), defined as particles smaller than 5 mm in diameter, have emerged as a concern due to their small size, which facilitates bioaccumulation [2]. Humans can ingest MPs from aquatic food sources [3,4], including riverine, estuarine, and oceanic fishes [5,6,7,8], as well as bivalves, gastropods, crustaceans [9,10], and even aquatic insects [11]. Recent scientific studies have shown that MPs can be detected in various parts of the human body [12], including the heart [13], lungs [14,15], placenta [16], and digestive system [17,18], posing potential health risks. From this perspective, determining the MP distribution characteristics in aquatic environments has enormous significance. MPs have been widely reported in various aquatic systems, such as catchments [19,20], freshwater [21,22], and seawater [23,24,25,26].
The abundance of MPs in aquatic environments has been primarily attributed to the presence and intensity of local MP sources [22,27,28,29,30]. Kataoka et al. [21] previously demonstrated that population density and the degree of urbanization are significant factors affecting both the numerical and mass abundances of MPs in Japanese riverine systems. However, recent studies have further highlighted hydrological conditions as critical variables affecting MP distribution, particularly influencing their dilution or accumulation [31,32,33,34]. Such accumulation patterns have been distinctly observed in small-scale rivers in Japan with limited wastewater treatment infrastructure [30,35].
For instance, numerical abundances of MPs were reported as 82,300 items/m3 in the Koya River (river length: 44 km) and 87,800 items/m3 in the Fushino River (30 km) [30]. Between 86,000 and 1,061,000 items/m3 were found in the Awano, Ayaragi, Asa, and Majime Rivers, whose river lengths range from 8.3 to 44 km [35]. Such high levels of MPs have been assessed using the pollution load index (PLI), which involves comparison with a baseline level [30,35]. However, due to the lack of an established baseline level for small-scale rivers, the lowest MP abundance observed within the corresponding study area was used as the baseline level for calculating the PLI [30,35]. While this approach provides a simple estimation concept, it introduces uncertainty in selecting the baseline level, which may lead to underestimation or overestimation. Therefore, identifying baseline MP abundances in small-scale aquatic environments with limited anthropogenic influences is essential for providing objective references in comparative MP studies. However, MP distribution under these conditions has been relatively neglected compared to larger and more heavily polluted aquatic environments [27,29,30,34,35,36,37,38,39].
The Sasebo River system in Nagasaki Prefecture, Japan, offers an appropriate context for investigating MP distribution under such conditions due to its short river length of 5.22 km and small basin area of 14.69 km2 [40]. One sewage treatment plant (STP) discharges its effluent directly into Sasebo Bay rather than into the river, thereby minimizing sewage input into the freshwater system [41]. Unlike previous studies that have primarily focused on larger or heavily polluted water bodies, the present study provides a distinctive perspective by suggesting a baseline in a small-scale aquatic environment with limited anthropogenic influence.
Accordingly, this study presents the first investigation of MP distribution characteristics in the aquatic environment of Sasebo City, Nagasaki Prefecture, Japan, using principal component analysis (PCA). Furthermore, the study explores the potential of the Sasebo River as a representative case of a small-scale aquatic system with limited anthropogenic influence. The validity of the present findings as a baseline is discussed through comparison with other studies. Therefore, the results will provide a foundation for future comparisons and an objective evaluation of MP contamination.

2. Materials and Methods

2.1. Microplastic (MP) Sample Collection

MP samples were collected from four sampling points—SSB1 (33°11′53.1″ N, 129°43′40.1″ E), SSB2 (33°11′24.8″ N, 129°43′04.2″ E), SSB3 (33°10′41.9″ N, 129°42′52.3″ E), and SSB4 (33°10′7.8″ N, 129°43′7.5″ E)—in Sasebo City, Nagasaki Prefecture, Japan, on 22 May 2022 (Figure 1). The sampling points were spaced approximately 1 km apart to characterize spatial variation in MP distribution along the river continuum from upstream to downstream. Boulders and gravel were present in the riverbed, and sediment samples were not collected.
At each sampling point, surface water (0–30 cm) was collected in triplicate to ensure reproducibility in estimating MP abundance. Each replicate consisted of 300 L of bulk water obtained using a 25 L basket (i.e., 12 scoops). The collected water was filtered through a 100 μm mesh plankton net (Rigo Co. Ltd., Tokyo, Japan) to retain suspended materials. The filtered water was discarded, and the materials retained on the plankton net were collected by rinsing the net with ultrapure water. The rinsate was then transferred into a glass jar pre-rinsed three times with 70% ethanol and ultrapure water.

2.2. Surface Water Flow Velocity and Salinity

A mechanical propeller-type flowmeter equipped with a low-speed impeller (2030 Series Mechanical Flowmeter, General Oceanics, Inc., Miami, FL, USA) was moored for 30 s to measure the surface water flow velocity. The velocity was calculated using Equations (1) and (2) as instructed in the user manual provided by the manufacturer [42]:
D (m) = (Cf − Ci) × R
S (cm/s) = D/T × c,
where D is the measured distance (m), Ci and Cf are the initial and final rotor counts (count), R is the adjusted low-speed rotor constant (0.057560 m/count) [42], S is the water flow velocity (cm/s), T is the measurement time (s), and c is the unit conversion constant (100 cm/m). The measurement process was repeated three times, and the mean velocity was calculated. The manufacturer specifies that the flowmeter measurement range for the low-speed impeller is 6–100 cm/s.
Salinity was measured using a seawater refractometer (Master-S/Mill Alpha, ATAGO Co., Ltd., Tokyo, Japan). The measurement was repeated three times, and the mean salinity was calculated. The measurement range is 0–100‰, and the accuracy is ±2‰.

2.3. Laboratory Pretreatment of MP Samples

This study modified the method proposed by Sugiura et al. [29], who reported acceptable recovery rates. Briefly, the collected MP sample in the glass jar was filtered onto a cellulose nitrate filter (47 mm diameter, 8 μm pore size; Whatman PLC., Maidstone, UK), and the filter was dissolved at 40 °C using 10 mL of 1 M NaOH solution (CAS#1310-73-2, FUJIFILM Wako Pure Chemical Corp., Osaka, Japan). The solution was neutralized with 10 mL of 1 M HCl solution (7782-63-0, FUJIFILM Wako Pure Chemical Corp., Osaka, Japan).
After neutralization, 50 mL of 30% H2O2 (7722-84-1, FUJIFILM Wako Pure Chemical Corp., Osaka, Japan) and 5 mL of 50 mM FeSO4·7H2O solution (7782-63-0, FUJIFILM Wako Pure Chemical Corp., Osaka, Japan) were sequentially added for the digestion of organic matter [43,44,45,46]. This solution was covered with aluminum foil and placed under a fume hood with fluorescent light for five days.
The resulting solution was poured into a glass separatory funnel containing 250 mL of 6.7 M NaI (7681-82-5, FUJIFILM Wako Pure Chemical Corp., Osaka, Japan) with a density of 1.6 g/cm3. The funnel was manually shaken for one minute and allowed to settle overnight in the fume hood. The supernatant was filtered onto a stainless-steel filter (47 mm diameter, 100 μm pore size), and the density separation process was repeated twice using the settled portion at the bottom of the funnel. This resulted in a total of three stainless-steel filters, each containing retained suspended materials from one round of separation.
After the final density separation process, each stainless-steel filter was individually sonicated with approximately 50 mL of ultrapure water for 15 min to detach the retained suspended materials into the liquid phase. The liquid phases from the three stainless-steel filters were then sequentially filtered onto a single polytetrafluoroethylene (PTFE) membrane filter (47 mm diameter, 5 μm pore size; Merck Millipore Ltd., Tullagreen, Ireland). To improve the efficiency of subsequent array analysis using an FTIR (Fourier-transform infrared spectroscopy) microscope, the filtration area was deliberately restricted to a 17 mm diameter circle (227 mm2) using a filtration set (Sibata Scientific Technology Ltd., Saitama, Japan), thereby increasing the particle concentration within the filtered area of the membrane. For complete removal of any remaining materials, each filter and each beaker was rinsed with ultrapure water more than six times during the final filtration step.

2.4. MP Polymer Identification

An FTIR microscope equipped with a high-speed imaging array detector was used in this study (Nicolet iN10MX, Thermo Fisher Scientific Inc., Waltham, MA, USA). Three arbitrarily selected square areas (5 mm × 5 mm each; total area = 75 mm2) on the PTFE filter of each sample were inspected. The analysis was conducted in transmission mode, with an infrared spectral range of 4000–715 cm−1, a resolution of 16 cm−1, and a spatial step size of 25 μm × 25 μm. Plastic polymer types were identified through analysis of approximately 40,000 spectra per inspected area using OMNIC software version 9.8.286 (Thermo Fisher Scientific Inc., Waltham, MA, USA). This method offers advantages over FTIR-ATR (attenuated total reflectance), including the ability to scan entire particles within the designated filter area, rapid spectral acquisition, elimination of manual particle selection, and detection of MPs as small as 20 μm [23,24,25,27,37,47].
Only spectra with a matching accuracy greater than 70% were identified as polymers based on comparison with reference polymer spectra, such as those of alkyd resin, epoxy resin, isoprene, polyacrylate styrene (PAS), polyethylene (PE), polyethylene terephthalate (PET), polymethyl methacrylate (PMMA), polypropylene (PP), polyvinyl acetate (PVA), polyvinyl alcohol, polyvinyl chloride (PVC), polyamide 6 (PA), polystyrene (PS), and polyurethane (PU). In addition, nine polymer spectra obtained from commercial products, namely PE, PET, PMMA, PP, PVA, PVC, PA, PS, and PU, were compared simultaneously [37,47]. The representative reference polymer spectra are shown in Figure S1.
The total number of detected MP particles (N items) was counted in three arbitrarily selected areas of the PTFE membrane. The numerical abundance of MPs was calculated using Equation (3) [47,48]:
Numerical abundance of MPs (items/m3) = (N × At/Ai) × (1/V),
where At and Ai are the total filtered area (227 mm2) and the inspected area (75 mm2), on the PTFE membrane filter, respectively, and V is the volume of filtered water (0.3 m3).

2.5. MP Shape and Size Classification

All plastic particles identified through the FTIR microscope were subsequently examined individually using a stereoscopic zoom microscope (SMZ25, Nikon Corp., Tokyo, Japan; magnification range 3.0×–15.0×) with NIS-Elements BR software version 5.30.00 [Build 1531] (Nikon Corp., Tokyo, Japan), in order to classify particle shapes and measure particle sizes.
MP particles were visually classified into the following shape categories [2]: fragments (irregularly shaped hard solids), pellets (hard solids that are generally spherical or granular), fibers (elongated fibrous materials at least ten times longer than their width), foams (soft expanded polystyrene particles), and films (flat, flexible particles with either smooth or angular edges).
The maximum Feret diameter of all non-fiber MP shapes was measured as the longest straight-line distance between a pair of parallel lines aligned with opposing boundaries of the particle shape [47,49] (Figure 2a), using a size measurement tool in the software. For fibers, length was measured by tracing a continuous line from one end of the fiber to the other, and thickness was determined as the vertical distance between the upper and lower surfaces (Figure 2b).

2.6. Quality Control Procedures

All pretreatment procedures were conducted in a fume hood, and nitrile gloves, a 100% cotton laboratory coat, and a mask were worn during the experiments. Three blank tests were conducted for quality control using 500 mL of ultrapure water with a resistivity of 18.2 MΩ·cm (Direct-Q 3UV, Merck Millipore Ltd., Bedford, MA, USA). No MPs were detected in blank samples, indicating negligible contamination. Ultrapure water was also used to rinse the experimental apparatus before use. Stainless-steel filters were sonicated for 1 h and rinsed with 70% ethanol and ultrapure water, and all filter papers were also rinsed using ultrapure water to ensure cleanliness before use.

2.7. Literature Survey

A land use and river network map (Figure 1) was obtained from the National Land Numerical Information (NLNI) database of Japan (https://nlftp.mlit.go.jp/ksj/ (accessed on 1 March 2025) and visualized using QGIS software version 3.10.1-A Coruña (https://www.qgis.org/en/site/ (accessed on 1 March 2025)).

2.8. Statistical Analysis

The Shapiro–Wilk test, one-way ANOVA, Kruskal–Wallis test, and Pearson correlation test were employed to assess normality, compare the mean and median MP abundance values, and evaluate correlation, respectively. The selection of statistical analyses to compare means or medians depended on the results of the normality test.
The input variables for PCA consisted of water flow velocity, salinity, and MP abundances quantified separately for the following polymer and shape types: PP fragment, PE fragment, PS fragment, PA fragment, PVC fragment, alkyd resin fragment, PMMA fragment, PAS fragment, epoxy resin fragment, PP fiber, PE fiber, PA fiber, PVC fiber, PMMA fiber, and PVA fiber. All variables were standardized using Equation (4) prior to performing PCA [50,51]. The entire statistical analysis was executed using IBM SPSS Statistics version 20 (IBM Corp., Armonk, NY, USA):
Standardized score = (x − μ)/σ,
where x, μ, and σ represent the measured value, mean, and standard deviation of each variable, respectively.

3. Results

3.1. Water Flow Velocity and Salinity Profiles

Upstream SSB1 featured stationary water, creating an environment distinct from the other sampling points. In contrast, water flow velocities were 53.2 cm/s at SSB2 and 108.9 cm/s at SSB3. The flow velocity at SSB4 was extremely low, falling below the 6 cm/s measurement limit of the mechanical flow meter. SSB4 was influenced by the tidal effects of Sasebo Bay, exhibiting a salinity of 30‰. All sampling points except for SSB4 exhibited zero salinity, indicating freshwater conditions. Accordingly, water flow velocities of 0 cm/s, 53.2 cm/s, 108.9 cm/s, and 3.0 cm/s and salinities of 0‰, 0‰, 0‰, and 30‰ were assigned to SSB1, SSB2, SSB3, and SSB4, respectively, as input variables for PCA. The flow velocity of 3.0 cm/s was estimated as half of the lower measurement limit of the mechanical flow meter.

3.2. Numerical Abundance of MPs

MP abundances from triplicate samplings at SSB1–SSB4 followed normal distributions, with p-values of 0.637, 0.999, 0.299, and 0.632, respectively (Shapiro–Wilk test, p > 0.050). The mean MP abundances from triplicate samplings (Figure 3) were 94.2 ± 15.4 items/m3 (range: 80.7–111.0 items/m3) at SSB1, 70.6 ± 60.5 items/m3 (10.1–131.1 items/m3) at SSB2, 47.1 ± 64.9 items/m3 (0.0–121.1 items/m3) at SSB3, and 117.7 ± 15.4 items/m3 (100.9–131.1 items/m3) at SSB4 (Table S1). Across all sampling points (SSB1–SSB4, n = 12), MP abundances ranged from 0.0 to 131.1 items/m3, with a mean of 82.4 ± 47.7 items/m3. However, no statistically significant differences were observed between sampling points (one-way ANOVA, p = 0.332).

3.3. Overall Distributions of MP Polymer Types, Shapes, and Sizes

Ten polymer types were identified: PP, PE, PS, PA, PVC, alkyd resin, PMMA, PVA, PAS, and epoxy resin. PP (41%) and PE (41%) were the dominant polymers, together accounting for 82% of all identified types (Figure 4a). Only fragments and fibers were observed across all sampling points; no other shapes, consisting of pellets, foams, or films, were detected (Figure 4b). Fragments accounted for 76% of the total shape composition, making them the dominant type (Figure 4b).
Fragment sizes ranged from 37 μm to 2128 μm, with particles smaller than 700 μm comprising the majority (Figure 5a). Fragment abundance gradually increased as particle size decreased. In contrast, fiber sizes ranged from 108 μm to 5163 μm, and particles smaller than 700 μm exhibited low abundance (Figure 5b).

3.4. MP Polymer and Shape Distributions by Sampling Points

Seven polymer types—PP, PE, PS, PA, PVC, alkyd resin, and PAS—were detected in SSB1 (Figure 6a). The number of detected polymer types decreased in SSB2 (PP, PE, PA, alkyd resin, and PMMA) and SSB3 (PP and PE). However, the number increased again at SSB4, where six polymer types—PP, PE, PS, alkyd resin, PVA, and epoxy resin—were detected.
The proportion of PE decreased from SSB1 to SSB4; however, a mean PE abundance at each sampling point showed no statistically significant difference (n = 3, one-way ANOVA, p = 0.861). In contrast, the proportion of PP increased, and the mean PP abundance at SSB4 (n = 3, 74.0 ± 15.4 items/m3) was significantly higher than at SSB1 (16.8 ± 15.4 items/m3, p = 0.025), SSB2 (20.2 ± 17.5 items/m3, p = 0.033), and SSB3 (23.5 ± 25.4 items/m3, p = 0.045), as determined by a one-way ANOVA (p = 0.018) with a Tukey HSD post hoc test.
The proportion of fibers tended to gradually decrease from SSB1 to SSB4, while the proportion of fragments increased (Figure 6b). However, no statistically significant differences were observed in the median fiber abundances (Kruskal–Wallis test, p = 0.372) and the mean fragment abundances (one-way ANOVA, p = 0.184) among the sampling points.

3.5. Principal Component Analysis (PCA)

Two principal components (PCs) were extracted through PCA, with PC1 accounting for 43.6% and PC2 for 36.2% of the total variance (Figure 7, Table 1). PC1 was primarily related to flow velocity conditions, as indicated by a strong negative association with water flow velocity. In contrast, PC2 showed a strong positive association with salinity, reflecting the salinity gradient from freshwater to seawater.
Several types of MPs exhibited distinct relationships with each PC. PVC fragments and fibers, PAS fragments, PA fibers, Alkyd resin fragments, PE fibers, and PA fragments were predominantly associated with PC1, suggesting a stronger link to flow velocity conditions. Conversely, epoxy resin fragments, PVA fibers, PE fragments, PP fibers and fragments, and PS fragments were strongly aligned with PC2, indicating a stronger relationship with the salinity gradient.
Based on their coordinates along the PC1–PC2 axes, the sampling points were divided into three groups.
  • Group A (positive PC1, negative PC2) included only SSB1, characterized by stagnant freshwater conditions. A wide variety of polymer types and shapes was present in this area, likely due to the limited water movement.
  • Group B (negative PC1, negative PC2) included SSB2 and SSB3, marked by high water velocity and reduced diversity and abundance of MPs. PMMA fragments and fibers, uniquely detected at SSB2, contributed modestly and negatively to the PCs.
  • Group C (negative PC1, positive PC2) corresponded to SSB4, where low water velocity and elevated salinity were observed. The MPs in this area, particularly those positively associated with PC2, might be affected by seawater.

4. Discussions

4.1. Microplastic Distribution Patterns in the Aquatic System of Sasebo City

MP distribution patterns in the present study were primarily influenced by flow velocity conditions (PC1, 43.6%) and the salinity gradient (PC2, 36.2%). At the upstream SSB1, stagnant water conditions likely impeded downstream MP transport, thereby concentrating local MP abundance. In contrast, the midstream of the Sasebo River was characterized by the convergence of several small tributaries, which facilitated the rapid downstream transport of MPs through SSB2 and SSB3. At SSB4, tidal dynamics might have caused localized estuarine mixing, potentially introducing marine-derived MPs into the lowermost part of the river.
Contrary to expectations, the upstream SSB1 was not pristine and exhibited high MP abundance (94.2 ± 15.4 items/m3), likely due to stagnant conditions. The diversity of detected polymer types—PP, PE, PS, PA, alkyd resin, PVC, and PAS—at SSB1 suggests direct anthropogenic input from adjacent residential areas. For instance, PS is widely utilized globally for packaging materials [52], PA for garments [47,53], alkyd resin and PAS for paints [54,55,56], and PVC for household products [57].
In contrast, the relatively high water velocity influenced the MP distribution in Group B (SSB2 and SSB3). Fragments and fibers of PMMA, which are widely used in building materials and general consumer products [58,59], were detected at SSB2 and contributed modestly to the composition of Group B (Figure 6). The smaller variety of polymer types detected in this area compared to Groups A and C likely reflects limitations inherent to the bulk water sampling method under rapid water flow [60].
Bulk water sampling is appropriate for determining MP sources, abundances, and characteristics, and it is particularly advantageous in slow or stagnant water flows or heavily polluted aquatic environments [61]. Previous studies that used bulk water sampling collected water volumes of 300 mL [36], 1 L [30,35,62], 5 L [63,64], 30 L [25], and 50 L [65,66]. Some researchers have suggested that 100 L of water is sufficient to determine MP distribution [67,68]. The present study collected 300 L of surface water, which is a much larger volume than that used in the previous studies. However, bulk water sampling is vulnerable to high water velocity because it filters a smaller volume of water compared to the volume-reduction method [60,61]. This study identified a statistically significant negative correlation between mean MP abundances and water flow velocity (Pearson correlation, r = −0.934, p = 0.033, Figure S2). Additionally, greater standard deviations in SSB2 (±60.5 items/m3) and SSB3 (±64.9 items/m3) compared to SSB1 (±15.4 items/m3) and SSB4 (±15.4 items/m3) suggest unstable sampling results under high water flow velocity (Figure 3).
Meanwhile, in Group C (SSB4), characterized by high salinity, the PP fragment, PE fragment, PS fragment, epoxy resin fragment, PP fiber, and PVA fiber positively contributed. Epoxy resin is well known as one of the primary polymers for ship paints [54,55]. PVA fiber serves as fiber-reinforced concrete (FRC) for marine construction [69]. PP, PE, and PS have relatively lower densities of 0.9–0.91, 0.917–0.965, and 1.04–1.1 g/cm3, respectively, compared to other polymers [60]. Their low-density characteristics and versatile uses allow them to occupy vast portions of the detected MP polymers in surface water, regardless of the sampling methods and aquatic environments [8,21,27,47]. Indeed, PP and PE were detected across all sampling points in the present study. Notably, the mean abundance of PP at SSB4 was significantly higher than at other sampling points (one-way ANOVA, p = 0.018; Tukey HSD test, p < 0.050). This may imply the enrichment of PP polymers in the surface seawater in Sasebo Bay, as shown in previous marine studies that reported the dominant PP polymer types [23,25]. Further understanding of their distribution characteristics in the expanded study area of Sasebo Bay is necessary.
Additionally, fragment-shaped secondary MPs, derived from weathered larger plastics predominate over artificially manufactured primary MPs [2]. PP and PE are susceptible to physical and chemical degradation due to weathering, and they have low tensile strength [37,70]. These characteristics may cause them to break down easily into smaller particles (Figure 5a), thereby increasing the number of particles in the water body [2]. These small particles pose an increased risk of bioaccumulation [56,71] and can exert adverse ecological effects through intrinsic physical impacts [72,73,74], as well as by acting as vectors for heavy metals [75,76] and harmful chemicals [77,78].
Meanwhile, a notably low abundance of short fibers <700 μm is observed in Figure 5b. This result may be attributed to mesh selectivity based on particle shape. Fiber-shaped MPs are more prone to entanglement or bending, which makes them less likely to be captured by mesh filters than rigid fragments [47,61,79,80]. The tendency observed in the present study aligns with earlier findings from previous studies that also employed mesh sizes of 100 μm or larger and reported fragment-dominated compositions [21,47], indicating that larger mesh sizes inherently bias the captured fiber shape. In contrast, studies using non-mesh filtration methods [30,35] or finer mesh sizes (e.g., 10 μm [81]) have tended to report higher proportions of fibers.

4.2. Baseline MP Abundance in a Small-Scale Aquatic System with Limited Anthropogenic Influence

Kataoka et al. [21] noted that numerical and mass abundances of MPs were not statistically correlated with the basin area, while population density showed significance. They employed a 335 µm mesh net due to sampling difficulties arising from suspended solids in surface water [21,82]. However, the use of a volume-reduced sampling method with a relatively large mesh size (e.g., 355 μm) may underestimate 97% of MP distributions [47,61]. Indeed, the hydrological parameters of freshwater have recently been recognized as key factors in determining the distribution and fate of MPs [27,30,35,61]. Notably, precipitation may result in heightened water volumes in water bodies [31,32,33,34]. This causes a dilution effect on MP abundance, which is typically measured in items per liter or per cubic meter. In the same context of water volume and dilution effects, MP abundance tends to be relatively higher in small-scale aquatic systems compared to larger ones [35,77,83,84,85,86,87].
In addition, MP sources have long been considered a key driver of MP contamination in aquatic environments. There are two types of MP sources—point and nonpoint sources—which contribute to water quality deterioration and the MP input into aquatic environments [88]. Domestic and industrial wastewater are commonly classified as point sources [88]. The former includes laundry [48,89], personal care products [89,90,91], and household dust removal activities [89,92], while the latter encompasses chemical manufacturing, electroplating [93], textile production [94], and eyeglass polishing industries [95]. Although some wastewater reaches wastewater treatment plants (WWTPs), MP removal efficiency ranges from 64% to 99% [22,29,96]. This suggests that WWTPs continuously emit tiny microplastics that are difficult to remove through treatment processes [21,22,29,96,97]. Nonpoint sources include atmospheric deposition of MPs [98] and resuspension from riverbeds [99]. Precipitation plays a significant role in transporting unspecified MP loads from diverse sources, including urban areas [34], roads [100], and agricultural settings [101], into the aquatic environment.
These hydrological parameters and MP sources act synergistically to elevate MP abundance in small-scale freshwater systems with insufficient wastewater treatment [30,35]. Consequently, many studies have reported significant MP contamination under these conditions [30,33,34,35,37,102,103]. Comparing heavily polluted sites with reference sites as the baseline level can help contextualize the severity of pollution [30,35]. However, these comparisons are meaningful when based on controlled and comparable conditions. Therefore, establishing the baseline abundance of MPs in small-scale freshwater systems with limited anthropogenic influence is essential.
Summaries of contextual characteristics associated with this study area are presented below to support the potential of the present findings as a baseline reference. The population density in Sasebo City—a significant factor of MP abundance [21]—was 547.5 people/km2, with 233,227 people as of 2023 [104]. This population density ranks in the top 27% compared to ninety sampling points across seventy Japanese rivers (0–7161 people/km2; mean, 970 ± 1815 people/km2; median, 212 people/km2) where MPs were collected in a previous study [82]. In contrast, the total river length is merely 5.2 km, and the basin area of the Sasebo River (14.69 km2 [40]) ranks in the bottom 5% compared to thirty-seven Japanese rivers (14–13,019 km2; mean, 1596 ± 2620 km2; median, 705 km2) as reported in another study [21]. These records suggest that Sasebo City has a moderate population density, and it represents an extremely compact freshwater system.
As of 2021, Sasebo City had only 529 manufacturing enterprises, accounting for approximately 5.2% of the total 10,172 enterprises [104]. The majority of enterprises in this city are wholesale and retail trade, accommodation and food services, and medical and welfare services [104]. Notably, micro enterprises (with 1–9 employees) accounted for 61.6% of the manufacturing industry, and small enterprises (with 10–29 employees) made up 25.6% [104]. These figures imply that the majority of manufacturing enterprises in the city are small in size. Given this industrial structure, the potential impact of industrial activities on the river environment is likely to be limited.
Notably, the Chubu STP, which had treated 119,364 metric tons as of 2019, operates within the study area, and its effluent is discharged directly into Sasebo Bay rather than the river [41]. This operational setting indicates that treated sewage does not significantly affect the Sasebo River system or contribute to water quality deterioration, thereby reinforcing the suitability of the region as a baseline environment with limited anthropogenic influence.
Regarding water quality in the Sasebo River, dissolved oxygen (DO), biological oxygen demand (BOD), total nitrogen (TN), and total phosphorus (TP), which are water quality parameters significantly correlated with MP abundance [21], fell within ranges of 5.7–12 mg/L (mean 9.0 mg/L), <0.5–1.6 mg/L (mean 0.9 mg/L), 0.49–0.83 mg/L (mean 0.66 mg/L), and 0.040–0.073 mg/L (mean 0.057 mg/L), respectively, as of 2022 [105]. For reference, Japanese freshwater guidelines specify that A-grade water must have a DO above 7.5 mg/L and a BOD below 2 mg/L [105]. The TN and TP levels in the study area fall within the lowest 15% and 33%, respectively, compared to the ranges of 0.33–6.82 mg/L (mean, 1.72 ± 1.39 mg/L) for TN and 0.010–0.390 mg/L (mean, 0.103 ± 0.085 mg/L) for TP across thirty-three Japanese rivers [21]. Such comparisons demonstrate that the Sasebo River can be classified as having good water quality. Based on Japanese freshwater guidelines and inter-river comparisons, the river water quality falls within the range typically associated with well-preserved or low-impact freshwater environments.
In addition, the sampling in the present study was conducted during the representative dry season in May in Japan. In May 2022, only 33.0 mm of rainfall was recorded, representing only 2.1% of the total annual precipitation of 1581.0 mm [106]. Insignificant precipitation (12.0 mm) was recorded on May 12, and no rainfall occurred for ten days, including the sampling day [106]. This dry-weather condition helped reduce external variability, such as stormwater runoff or re-suspension, providing a snapshot of MP abundance under stable hydrological conditions.
Of particular note, the absence of significant variation in MP abundance across the sampling points indicates a scarcity of significant MP sources within the aquatic environment. Collectively, the combination of moderate population density, a small basin area, limited industrial activities, a sewage treatment system that discharges directly into the bay, good water quality, minimal rainfall-related variation, and the insignificant variation of MP abundance strongly reinforces that the present findings appropriately represent a baseline condition for small-scale freshwater systems with limited MP sources.
Severe MP contamination has been reported in small-scale aquatic environments, including the Tsurumi River [37], the Awano River, the Ayaragi River, the Asa River, the Majime River [35], the Shimaji River, the Koya River, the Fushino River, and the Nishiki River [30] in Japan; the Tijuana semiarid region in Mexico [34]; the Sean Saep Canal in Thailand [102]; the Lis River in Portugal [33]; and the Biała River and the Czarna Hańcza River in Poland [103]. These elevated MP levels are primarily attributed to high MP emissions from WWTPs driven by poor treatment systems [30,33,34,35,37,102,103]. The comparison underscores that the MP abundance levels reported in the present study are one to five orders of magnitude lower than those observed in heavily contaminated small-scale rivers (Table 2). Notably, the mean MP abundance in the present study was 82.4 items/m3, which is considerably lower than the baseline levels of PLI of 86,000 and 38,730 items/m3 used in previous studies [30,35]. This discrepancy suggests that MP pollution may have been underestimated in previous assessments that used these higher values as baselines.
Meanwhile, the Saigon River in Vietnam [36]; the Nakdong River in Republic of Korea [67]; the Wei River [63], the Manas River [64], the Ganjian River [65], the West River [107], the Yangtze River [108], and the Han River in China [109]; the Citarum River in Indonesia [27]; and the Weser River in Germany [32] have been reported as large-scale freshwater systems with substantial anthropogenic sources of MPs, including domestic, industrial, agricultural, and WWTP effluents. The abundances of MPs in these previous reports were recorded to be one to four orders of magnitude greater than the mean abundance of MPs in the present study (Table 2). This suggests that MP sources may play a more critical role in determining MP abundance than the scale of the aquatic system. Accordingly, the present study may serve as a baseline for comparison with those environments, even when variations in MP abundance occur due to the intensity or magnitude of MP sources, regardless of the aquatic system’s scale.
However, the mean abundance in the Sasebo River was approximately sixfold that of the anonymous Japanese 1st-grade river using a 100 μm mesh size [47] (Table 2). There are approximately 42-fold and 346-fold differences in river length and basin area, respectively, between the two rivers [47]. The mean abundance in the Yulin River in China, which has a river length 4-fold longer and a basin area 262-fold broader than the Sasebo River, was approximately one-sixth that reported in the present study [66]. The Yulin River has a relatively lower contaminant load because it is located in an underdeveloped region where anthropogenic activities such as tourism, industry, and commerce are limited in intensity [66]. Similarly, the low abundances in the Amazon catchment in Brazil were attributed to the substantial dilution factor and sparse population density [110]. This indicates that when anthropogenic influence is similarly sparse, dilution effects resulting from larger water volumes may play a critical role in determining MP abundance.
Collectively, the abundance of MPs in aquatic environments appears to adhere to the following trend: small-scale systems with intense anthropogenic influence > large-scale systems with intense anthropogenic influence > small-scale systems with limited anthropogenic influence (the present study) > large-scale systems with limited anthropogenic influence. Therefore, this study provides a useful baseline for comparison with both small-scale and large-scale systems with intense anthropogenic influence.
However, though MP abundance expressed in numerical terms (items/m3) is widely used to indicate pollution levels in aquatic environments, it does not represent the absolute number of emitted MP particles due to the discharged water volume. To better reflect the environmental load, future studies should quantify the daily MP load (items/day) by multiplying the abundance by the daily water discharge volume (m3/day) [38,82,111]. This approach may help clarify why certain MP abundance patterns show statistical insignificance in the present study.
Several additional approaches can be suggested to address the absence of statistical significance, such as identifying MP transport pathways in upstream areas [83,102,112,113]; evaluating potential contamination from the upper catchment, such as the Yamanota Reservoir [19,20,87]; and assessing MP inputs from tributaries [37,47].

5. Conclusions

The spatial distribution of MPs in the Sasebo aquatic system was found to be governed primarily by flow velocity conditions and the salinity gradient. Stagnant freshwater conditions at upstream SSB1 appeared to impede downstream transport, causing localized accumulation of MPs such as PVC fragments and fibers, PAS fragments, PA fibers, alkyd resin fragments, PE fibers, and PA fragments. In contrast, midstream SSB2 and SSB3 experienced high water velocities from converging tributaries, facilitating downstream MP transport. At SSB4, the detection of epoxy resin fragments, PVA fibers, and fragments of PE and PP may indicate a potential influence of seawater intrusion on the local MP composition. The Sasebo aquatic system investigated in the present study, characterized by its compact basin area, moderate population density, limited industrial activity, restricted discharges of STP effluent, good water quality, and insignificant differences in MP abundance between sampling points, experienced minimal external disturbances due to a lack of significant rainfall before the sampling event. Collectively, these conditions indicate that the present finding in the Sasebo aquatic system is representative of a small-scale freshwater environment with limited anthropogenic influence. Given its markedly lower MP abundance compared to previously reported small- and large-scale aquatic systems with intense anthropogenic influence, this study provides a robust baseline for future comparative assessments.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microplastics4030055/s1, Table S1: Numerical abundances of microplastics (MPs), salinity, and water flow velocity measured at each sampling site in Sasebo City, Nagasaki, Japan; Figure S1. Representative spectra of seven reference polymer types obtained using micro FT-IR; Figure S2: Correlation between average MP abundances and water flow velocity at sampling sites in Sasebo City, Nagasaki, Japan.

Author Contributions

Conceptualization, Y.I.; methodology, H.J., B.K.M., and H.S.C.; software, H.J. and B.K.M.; validation, H.J., T.A., and Y.I.; formal analysis, H.J., D.F., and B.K.M.; investigation, H.J., D.F., and Y.I.; resources, H.S.C. and Y.I.; data curation, H.J., D.F., and Y.I.; writing—original draft preparation, H.J. and D.F.; writing—review and editing, H.J., A.E., Q.T.N., P.S.S., T.A., and Y.I.; visualization, H.J., D.F., and A.E.; supervision, H.S.C., T.A., and Y.I.; project administration, Y.I.; funding acquisition, Y.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author(s).

Acknowledgments

The authors appreciate every Sasebo City Nagasaki Prefecture stakeholder and the laboratory members—particularly Nana Hirota—for their dedication and help. This article was supported by the MOU between the Faculty of Environmental and Symbiotic Sciences (Prefectural University of Kumamoto, Japan) and the College of Fisheries and Ocean Science (Chonnam National University, Republic of Korea).

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Andrady, A.L. Microplastics in the Marine Environment. Mar. Pollut. Bull. 2011, 62, 1596–1605. [Google Scholar] [CrossRef]
  2. GESAMP Guidlines for the Monitoring and Assessment of Plastic Litter in the Ocean. Available online: http://www.gesamp.org/publications/guidelines-for-the-monitoring-and-assessment-of-plastic-litter-in-the-ocean (accessed on 31 October 2024).
  3. Akoueson, F.; Sheldon, L.M.; Danopoulos, E.; Morris, S.; Hotten, J.; Chapman, E.; Li, J.; Rotchell, J.M. A Preliminary Analysis of Microplastics in Edible versus Non-Edible Tissues from Seafood Samples. Environ. Pollut. 2020, 263, 114452. [Google Scholar] [CrossRef] [PubMed]
  4. Yuan, Z.; Nag, R.; Cummins, E. Human Health Concerns Regarding Microplastics in the Aquatic Environment—From Marine to Food Systems. Sci. Total Environ. 2022, 823, 153730. [Google Scholar] [CrossRef]
  5. Barboza, L.G.A.; Lopes, C.; Oliveira, P.; Bessa, F.; Otero, V.; Henriques, B.; Raimundo, J.; Caetano, M.; Vale, C.; Guilhermino, L. Microplastics in Wild Fish from North East Atlantic Ocean and Its Potential for Causing Neurotoxic Effects, Lipid Oxidative Damage, and Human Health Risks Associated with Ingestion Exposure. Sci. Total Environ. 2020, 717, 134625. [Google Scholar] [CrossRef] [PubMed]
  6. Bessa, F.; Barria, P.; Neto, J.M.; Frias, J.; Otero, V.; Sobral, P.; Marques, J.C. Occurrence of Microplastics in Commercial Fish from a Natural Estuarine Environment. Mar. Pollut. Bull. 2018, 128, 575–584. [Google Scholar] [CrossRef]
  7. Gündoğdu, S.; Çevik, C.; Temiz Ataş, N. Occurrence of Microplastics in the Gastrointestinal Tracts of Some Edible Fish Speciealong the Turkish Coast. Turk. J. Zool. 2020, 44, 312–323. [Google Scholar] [CrossRef]
  8. Park, T.J.; Lee, S.H.; Lee, M.S.; Lee, J.K.; Lee, S.H.; Zoh, K.D. Occurrence of Microplastics in the Han River and Riverine Fish in South Korea. Sci. Total Environ. 2020, 708, 134535. [Google Scholar] [CrossRef]
  9. Daniel, D.B.; Ashraf, P.M.; Thomas, S.N.; Thomson, K.T. Microplastics in the Edible Tissues of Shellfishes Sold for Human Consumption. Chemosphere 2021, 264, 128554. [Google Scholar] [CrossRef] [PubMed]
  10. Danopoulos, E.; Jenner, L.C.; Twiddy, M.; Rotchell, J.M. Microplastic Contamination of Seafood Intended for Human Consumption: A Systematic Review and Meta-Analysis. Environ. Health Perspect. 2020, 128, 126002. [Google Scholar] [CrossRef]
  11. Maneechan, W.; On Prommi, T. Occurrence of Microplastics in Edible Aquatic Insect Pantala Sp. (Odonata: Libellulidae) from Rice Fields. PeerJ 2022, 10, e12902. [Google Scholar] [CrossRef] [PubMed]
  12. Blackburn, K.; Green, D. The Potential Effects of Microplastics on Human Health: What Is Known and What Is Unknown. Ambio 2022, 51, 518–530. [Google Scholar] [CrossRef]
  13. Zhou, Y.; Wu, Q.; Li, Y.; Feng, Y.; Wang, Y.; Cheng, W. Low-Dose of Polystyrene Microplastics Induce Cardiotoxicity in Mice and Human-Originated Cardiac Organoids. Environ. Int. 2023, 179, 108171. [Google Scholar] [CrossRef]
  14. Jenner, L.C.; Rotchell, J.M.; Bennett, R.T.; Cowen, M.; Tentzeris, V.; Sadofsky, L.R. Detection of Microplastics in Human Lung Tissue Using ΜFTIR Spectroscopy. Sci. Total Environ. 2022, 831, 154907. [Google Scholar] [CrossRef]
  15. Goodman, K.E.; Hare, J.T.; Khamis, Z.I.; Hua, T.; Sang, Q.X.A. Exposure of Human Lung Cells to Polystyrene Microplastics Significantly Retards Cell Proliferation and Triggers Morphological Changes. Chem. Res. Toxicol. 2021, 34, 1069–1081. [Google Scholar] [CrossRef] [PubMed]
  16. Ragusa, A.; Svelato, A.; Santacroce, C.; Catalano, P.; Notarstefano, V.; Carnevali, O.; Papa, F.; Rongioletti, M.C.A.; Baiocco, F.; Draghi, S.; et al. Plasticenta: First Evidence of Microplastics in Human Placenta. Environ. Int. 2021, 146, 106274. [Google Scholar] [CrossRef]
  17. Fournier, E.; Etienne-Mesmin, L.; Grootaert, C.; Jelsbak, L.; Syberg, K.; Blanquet-Diot, S.; Mercier-Bonin, M. Microplastics in the Human Digestive Environment: A Focus on the Potential and Challenges Facing in Vitro Gut Model Development. J. Hazard. Mater. 2021, 415, 125632. [Google Scholar] [CrossRef] [PubMed]
  18. Tan, H.; Yue, T.; Xu, Y.; Zhao, J.; Xing, B. Microplastics Reduce Lipid Digestion in Simulated Human Gastrointestinal System. Environ. Sci. Technol. 2020, 54, 12285–12294. [Google Scholar] [CrossRef]
  19. Österlund, H.; Blecken, G.; Lange, K.; Marsalek, J.; Gopinath, K.; Viklander, M. Microplastics in Urban Catchments: Review of Sources, Pathways, and Entry into Stormwater. Sci. Total Environ. 2023, 858, 159781. [Google Scholar] [CrossRef] [PubMed]
  20. Schell, T.; Hurley, R.; Nizzetto, L.; Rico, A.; Vighi, M. Spatio-Temporal Distribution of Microplastics in a Mediterranean River Catchment: The Importance of Wastewater as an Environmental Pathway. J. Hazard. Mater. 2021, 420, 126481. [Google Scholar] [CrossRef]
  21. Kataoka, T.; Nihei, Y.; Kudou, K.; Hinata, H. Assessment of the Sources and Inflow Processes of Microplastics in the River Environments of Japan. Environ. Pollut. 2019, 244, 958–965. [Google Scholar] [CrossRef] [PubMed]
  22. Park, H.J.; Oh, M.J.; Kim, P.G.; Kim, G.; Jeong, D.H.; Ju, B.K.; Lee, W.S.; Chung, H.M.; Kang, H.J.; Kwon, J.H. National Reconnaissance Survey of Microplastics in Municipal Wastewater Treatment Plants in Korea. Environ. Sci. Technol. 2020, 54, 1503–1512. [Google Scholar] [CrossRef]
  23. Min, B.-K.; Cho, C.-R.; Cheon, H.-S.; Soh, H.-Y.; Cho, H.-S. A Study on the Distribution of Microplastics in the South Coast of Korea and Gwangyang Bay. Microplastics 2024, 3, 355–372. [Google Scholar] [CrossRef]
  24. Kim, K.Y.; Jeong, H.H.; Kim, J.H.; Min, B.K.; Cho, C.R.; Soh, H.Y.; Ishibashi, Y.; Cho, H.S. Microplastic Distribution Characteristics Considering the Marine Environment Based on Surface Seawater Quality Parameters in Southern Sea of Korea, 2019. Sustainability 2024, 16, 6272. [Google Scholar] [CrossRef]
  25. Min, B.K.; Jeong, H.H.; Ju, M.J.; Ko, U.; Dae, K.H.; Kim, H.J.; Cho, C.R.; Soh, H.Y.; Ishibashi, Y.; Cho, H.S. Baseline Study on Microplastic Distribution in the Open Surface Waters of the Korean Southwest Sea. Water 2023, 15, 2393. [Google Scholar] [CrossRef]
  26. Zheng, Y.; Li, J.; Cao, W.; Liu, X.; Jiang, F.; Ding, J.; Yin, X.; Sun, C. Distribution Characteristics of Microplastics in the Seawater and Sediment: A Case Study in Jiaozhou Bay, China. Sci. Total Environ. 2019, 674, 27–35. [Google Scholar] [CrossRef]
  27. Jeong, H.; Novirsa, R.; Cahya Nugraha, W.; Addai-Arhin, S.; Dinh, Q.P.; Fukushima, S.; Fujita, E.; Bambang, W.; Kameda, Y.; Ishibashi, Y.; et al. The Distributions of Microplastics (MPs) in the Citarum River Basin, West Java, Indonesia. J. Environ. Saf. 2021, 12, 33–43. [Google Scholar] [CrossRef]
  28. Miller, R.Z.; Watts, A.J.R.; Winslow, B.O.; Galloway, T.S.; Barrows, A.P.W. Mountains to the Sea: River Study of Plastic and Non-Plastic Microfiber Pollution in the Northeast USA. Mar. Pollut. Bull. 2017, 124, 245–251. [Google Scholar] [CrossRef]
  29. Sugiura, M.; Takada, H.; Takada, N.; Mizukawa, K.; Tsuyuki, S. Microplastics in Urban Wastewater and Estuarine Water: Importance of Street Runoff. Environ. Monit. Contam. Res. 2021, 1, 54–65. [Google Scholar] [CrossRef]
  30. Kabir, A.H.M.E.; Sekine, M. Wastewater Treatment Plants Elevating Microplastic Abundances, Ecological Risks, and Loads in Japanese Rivers: A Source-to-Sink Perspective. Environ. Sci. Pollut. Res. 2023, 30, 96499–96514. [Google Scholar] [CrossRef] [PubMed]
  31. Xia, W.; Rao, Q.; Deng, X.; Chen, J.; Xie, P. Rainfall Is a Significant Environmental Factor of Microplastic Pollution in Inland Waters. Sci. Total Environ. 2020, 732, 139065. [Google Scholar] [CrossRef] [PubMed]
  32. Moses, S.R.; Löder, M.G.J.; Herrmann, F.; Laforsch, C. Seasonal Variations of Microplastic Pollution in the German River Weser. Sci. Total Environ. 2023, 902, 166463. [Google Scholar] [CrossRef]
  33. Sá, B.; Pais, J.; Antunes, J.; Pequeno, J.; Pires, A.; Sobral, P. Seasonal Abundance and Distribution Patterns of Microplastics in the Lis River, Portugal. Sustainability 2022, 14, 2255. [Google Scholar] [CrossRef]
  34. Piñon-Colin, T.J.; Rodriguez-Jimenez, R.; Rogel-Hernandez, E.; Alvarez-Andrade, A.; Wakida, F.T. Microplastics in Stormwater Runoff in a Semiarid Region, Tijuana, Mexico. Sci. Total Environ. 2020, 704, 135411. [Google Scholar] [CrossRef]
  35. Kabir, A.; Sekine, M.; Imai, T.; Yamamoto, K.; Kanno, A.; Higuchi, T. Assessing Small-Scale Freshwater Microplastics Pollution, Land-Use, Source-to-Sink Conduits, and Pollution Risks: Perspectives from Japanese Rivers Polluted with Microplastics. Sci. Total Environ. 2021, 768, 144655. [Google Scholar] [CrossRef] [PubMed]
  36. Lahens, L.; Strady, E.; Kieu-Le, T.C.; Dris, R.; Boukerma, K.; Rinnert, E.; Gasperi, J.; Tassin, B. Macroplastic and Microplastic Contamination Assessment of a Tropical River (Saigon River, Vietnam) Transversed by a Developing Megacity. Environ. Pollut. 2018, 236, 661–671. [Google Scholar] [CrossRef] [PubMed]
  37. Kameda, Y.; Yamada, N.; Fujita, E. Source- and Polymer-Specific Size Distributions of Fine Microplastics in Surface Water in an Urban River. Environ. Pollut. 2021, 284, 117516. [Google Scholar] [CrossRef]
  38. Kudo, K.; Takaoka, T.; Nihei, Y.; Kitaura, F. Estimation of Temporal Variations and Annual Flux of Microplastics in Rivers under Low- and High-Flow Condistions. J. Jpn. Soc. Civ. Eng. Ser. B1 (Hydraul. Eng.) 2018, 74, I_529–I_534. [Google Scholar] [CrossRef]
  39. Sankoda, K.; Yamada, Y. Occurrence, Distribution, and Possible Sources of Microplastics in the Surface River Water in the Arakawa River Watershed. Environ. Sci. Pollut. Res. 2021, 28, 27474–27480. [Google Scholar] [CrossRef]
  40. Nagasaki Prefecture in Japan Annaul Stastics in Nagasaki Prefecture. Volume 47. Available online: https://www.pref.nagasaki.jp/bunrui/kenseijoho/toukeijoho/kankoubutsu/nenkan/33937.html (accessed on 31 October 2024).
  41. Nagasaki Prefecture in Japan Annual Stastics in Nagasaki Prefecture. Volume 69. Available online: https://www.pref.nagasaki.jp/bunrui/kenseijoho/toukeijoho/kankoubutsu/nenkan/599095.html (accessed on 31 October 2024).
  42. General Oceanics Inc. 2030 and 2031 Series Mechanical and Electronic Digital Flowmeter Operators Manual. Available online: https://www.generaloceanics.com/media/hexaattachment/products/attachments/2030_MANUAL.pdf (accessed on 11 June 2024).
  43. Masura, J.; Baker, J.; Foster, G.; Arthur, C. Laboratory Methods for the Analysis of Microplastics in the Marine Environment: Recommendations for Quantifying Synthetic Particles in Waters and Sediments. Available online: https://doi.org/10.25607/OBP-604 (accessed on 11 June 2024).
  44. Michida, Y.; Chavanich, S.; Chiba, S.; Cordova, M.R.; Cózar, C.A.; Galgani, F.; Hagmann, P.; Hinata, H.; Isobe, A.; Kershaw, P.; et al. Guidelines for Harmonizing Ocean Surface Microplastic Monitoring Methods. Version 1.1. Available online: https://doi.org/10.25607/OBP-867 (accessed on 31 October 2024).
  45. Prata, J.C.; Da Costa, J.P.; Duarte, A.C.; Rocha-Santos, T. Methods for Sampling and Detection of Microplastics in Water and Sediment: A Critical Review. TrAC Trends Anal. Chem. 2019, 110, 150–159. [Google Scholar] [CrossRef]
  46. Tagg, A.S.; Harrison, J.P.; Ju-Nam, Y.; Sapp, M.; Bradley, E.L.; Sinclair, C.J.; Ojeda, J.J. Fenton’s Reagent for the Rapid and Efficient Isolation of Microplastics from Wastewater. Chem. Commun. 2017, 53, 372–375. [Google Scholar] [CrossRef]
  47. Jeong, H.; Kusano, T.; Addai-Arhin, S.; Nugraha, W.C.; Novirsa, R.; Phan Dinh, Q.; Shirosaki, T.; Fujita, E.; Kameda, Y.; Cho, H.S.; et al. Differences in Microplastic Distributions on the Surface Freshwater Collected Using 100– and 355–μm Meshes. Environ. Monit. Contam. Res. 2022, 2, 22–34. [Google Scholar] [CrossRef]
  48. Corami, F.; Rosso, B.; Bravo, B.; Gambaro, A.; Barbante, C. A Novel Method for Purification, Quantitative Analysis and Characterization of Microplastic Fibers Using Micro-FTIR. Chemosphere 2020, 238, 124564. [Google Scholar] [CrossRef]
  49. Walton, W.H. Feret‘s Statistical Diameter as a Measure of Particle Size. Nature 1948, 162, 329–330. [Google Scholar] [CrossRef]
  50. Jeong, H.; Jung, H.; Lee, J.; Cho, H. The Characteristics of Methylsiloxane Distribution in the Marine Surface Sediment, Masan Bay, Korea, in August 2018 and Suggesting Directions for Further Studies. Water 2024, 16, 3514. [Google Scholar] [CrossRef]
  51. Jeong, H.; Choi, S.-D.; Cho, H.-S. Characteristics of Hypoxic Water Mass Occurrence in the Northwestern Gamak Bay, Korea, 2017. J. Korean Soc. Mar. Environ. Saf. 2021, 27, 708–720. [Google Scholar] [CrossRef]
  52. Gelbke, H.P.; Banton, M.; Block, C.; Dawkins, G.; Eisert, R.; Leibold, E.; Pemberton, M.; Puijk, I.M.; Sakoda, A.; Yasukawa, A. Risk Assessment for Migration of Styrene Oligomers into Food from Polystyrene Food Containers. Food Chem. Toxicol. 2019, 124, 151–167. [Google Scholar] [CrossRef] [PubMed]
  53. Peng, C.; Tang, X.; Gong, X.; Dai, Y.; Sun, H.; Wang, L. Development and Application of a Mass Spectrometry Method for Quantifying Nylon Microplastics in Environment. Anal. Chem. 2020, 92, 13930–13935. [Google Scholar] [CrossRef] [PubMed]
  54. Duis, K.; Coors, A. Microplastics in the Aquatic and Terrestrial Environment: Sources (with a Specific Focus on Personal Care Products), Fate and Effects. Environ. Sci. Eur. 2016, 28, 2. [Google Scholar] [CrossRef]
  55. Song, Y.K.; Hong, S.H.; Jang, M.; Han, G.M.; Shim, W.J. Occurrence and Distribution of Microplastics in the Sea Surface Microlayer in Jinhae Bay, South Korea. Arch. Environ. Contam. Toxicol. 2015, 69, 279–287. [Google Scholar] [CrossRef]
  56. Neves, D.; Sobral, P.; Ferreira, J.L.; Pereira, T. Ingestion of Microplastics by Commercial Fish off the Portuguese Coast. Mar. Pollut. Bull. 2015, 101, 119–126. [Google Scholar] [CrossRef]
  57. Kawakami, T.; Isama, K.; Matsuoka, A. Analysis of Phthalic Acid Diesters, Monoester, and Other Plasticizers in Polyvinyl Chloride Household Products in Japan. J. Environ. Sci. Health Part A 2011, 46, 855–864. [Google Scholar] [CrossRef]
  58. Harper, C.A. Modern Plastics Handbook, 1st ed.; Harper, C.A., Ed.; McGraw-Hill Professional: New York, NY, USA, 2000; ISBN 0070267146. [Google Scholar]
  59. Zeng, W.R.; Li, S.F.; Chow, W.K. Preliminary Studies on Burning Behavior of Polymethylmethacrylate (PMMA). J. Fire Sci. 2002, 20, 297–317. [Google Scholar] [CrossRef]
  60. Hidalgo-Ruz, V.; Gutow, L.; Thompson, R.C.; Thiel, M. Microplastics in the Marine Environment: A Review of the Methods Used for Identification and Quantification. Environ. Sci. Technol. 2012, 46, 3060–3075. [Google Scholar] [CrossRef]
  61. Jeong, H. A Study on the Proper Sampling Method for Microplastic Distributions in the Surface Freshwater: From Case Studies in Japan and Indonesia. Ph.D. Thesis, Prefectural University of Kumamoto, Kumamoto, Japan, 2021. Available online: http://rp-kumakendai.pu-kumamoto.ac.jp/dspace/bitstream/123456789/2099/3/2021-kan-zenbun-jeong.pdf (accessed on 31 October 2024).
  62. Capparelli, M.V.; Molinero, J.; Moulatlet, G.M.; Barrado, M.; Prado-Alcívar, S.; Cabrera, M.; Gimiliani, G.; Ñacato, C.; Pinos-Velez, V.; Cipriani-Avila, I. Microplastics in Rivers and Coastal Waters of the Province of Esmeraldas, Ecuador. Mar. Pollut. Bull. 2021, 173, 113067. [Google Scholar] [CrossRef] [PubMed]
  63. Ding, L.; fan Mao, R.; Guo, X.; Yang, X.; Zhang, Q.; Yang, C. Microplastics in Surface Waters and Sediments of the Wei River, in the Northwest of China. Sci. Total Environ. 2019, 667, 427–434. [Google Scholar] [CrossRef] [PubMed]
  64. Wang, G.; Lu, J.; Tong, Y.; Liu, Z.; Zhou, H.; Xiayihazi, N. Occurrence and Pollution Characteristics of Microplastics in Surface Water of the Manas River Basin, China. Sci. Total Environ. 2020, 710, 136099. [Google Scholar] [CrossRef] [PubMed]
  65. Hu, H.; Jin, D.; Yang, Y.; Zhang, J.; Ma, C.; Qiu, Z. Distinct Profile of Bacterial Community and Antibiotic Resistance Genes on Microplastics in Ganjiang River at the Watershed Level. Environ. Res. 2021, 200, 111363. [Google Scholar] [CrossRef]
  66. Mao, Y.; Li, H.; Gu, W.; Yang, G.; Liu, Y.; He, Q. Distribution and Characteristics of Microplastics in the Yulin River, China: Role of Environmental and Spatial Factors. Environ. Pollut. 2020, 265, 115033. [Google Scholar] [CrossRef]
  67. Eo, S.; Hong, S.H.; Song, Y.K.; Han, G.M.; Shim, W.J. Spatiotemporal Distribution and Annual Load of Microplastics in the Nakdong River, South Korea. Water Res. 2019, 160, 228–237. [Google Scholar] [CrossRef]
  68. Jiang, Y.; Zhao, Y.; Wang, X.; Yang, F.; Chen, M.; Wang, J. Characterization of Microplastics in the Surface Seawater of the South Yellow Sea as Affected by Season. Sci. Total Environ. 2020, 724, 138375. [Google Scholar] [CrossRef]
  69. Ito, H.; Watanabe, K.; Todoroki, S.; Suemori, H.; Shinjyo, R. Study on Performance of PVA Fiber Reinforced Concrete Exposed for 10 Years to Seawater Spray. J. Adv. Concr. Technol. 2018, 16, 159–169. [Google Scholar] [CrossRef]
  70. Rodrigues, M.O.; Abrantes, N.; Goncalves, F.J.M.; Nogueira, H.; Marques, J.C.; Goncalves, A.M.M. Spatial and Temporal Distribution of Microplastics in Water and Sediments of a Freshwater System (Antuã River, Portugal). Sci. Total Environ. 2018, 633, 1549–1559. [Google Scholar] [CrossRef]
  71. Lusher, A.L.; McHugh, M.; Thompson, R.C. Occurrence of Microplastics in the Gastrointestinal Tract of Pelagic and Demersal Fish from the English Channel. Mar. Pollut. Bull. 2013, 67, 94–99. [Google Scholar] [CrossRef]
  72. Wright, S.L.; Thompson, R.C.; Galloway, T.S. The Physical Impacts of Microplastics on Marine Organisms: A Review. Environ. Pollut. 2013, 178, 483–492. [Google Scholar] [CrossRef]
  73. Jovanović, B. Ingestion of Microplastics by Fish and Its Potential Consequences from a Physical Perspective. Integr. Environ. Assess. Manag. 2017, 13, 510–515. [Google Scholar] [CrossRef] [PubMed]
  74. Ahrendt, C.; Perez-Venegas, D.J.; Urbina, M.; Gonzalez, C.; Echeveste, P.; Aldana, M.; Pulgar, J.; Galbán-Malagón, C. Microplastic Ingestion Cause Intestinal Lesions in the Intertidal Fish Girella Laevifrons. Mar. Pollut. Bull. 2020, 151, 110795. [Google Scholar] [CrossRef]
  75. Bradney, L.; Wijesekara, H.; Palansooriya, K.N.; Obadamudalige, N.; Bolan, N.S.; Ok, Y.S.; Rinklebe, J.; Kim, K.H.; Kirkham, M.B. Particulate Plastics as a Vector for Toxic Trace-Element Uptake by Aquatic and Terrestrial Organisms and Human Health Risk. Environ. Int. 2019, 131, 104937. [Google Scholar] [CrossRef]
  76. Maity, S.; Biswas, C.; Banerjee, S.; Guchhait, R.; Adhikari, M.; Chatterjee, A.; Pramanick, K. Interaction of Plastic Particles with Heavy Metals and the Resulting Toxicological Impacts: A Review. Environ. Sci. Pollut. Res. 2021, 28, 60291–60307. [Google Scholar] [CrossRef] [PubMed]
  77. Yamahara, S.; Nakata, H. Road Dust-Associated Microplastics as a Carrier of Plastic Additives in Urban Small-Scale River Sediment. Environ. Monit. Contam. Res. 2025, 5, 10–25. [Google Scholar] [CrossRef]
  78. Bakir, A.; Rowland, S.J.; Thompson, R.C. Transport of Persistent Organic Pollutants by Microplastics in Estuarine Conditions. Estuar. Coast. Shelf Sci. 2014, 140, 14–21. [Google Scholar] [CrossRef]
  79. Tokai, T.; Uchida, K.; Kuroda, M.; Isobe, A. Mesh Selectivity of Neuston Nets for Microplastics. Mar. Pollut. Bull. 2021, 165, 112111. [Google Scholar] [CrossRef]
  80. Barrows, A.P.W.; Neumann, C.A.; Berger, M.L.; Shaw, S.D. Grab: Vs. Neuston Tow Net: A Microplastic Sampling Performance Comparison and Possible Advances in the Field. Anal. Methods 2017, 9, 1446–1453. [Google Scholar] [CrossRef]
  81. Imbulana, S.; Tanaka, S.; Yukioka, S.; Oluwoye, I. Occurrence and Distribution of Plastic Particles (10–25,000 Μm) and Microfibers in the Surface Water of an Urban River Network in Japan. Environ. Monit. Assess. 2024, 196, 92. [Google Scholar] [CrossRef]
  82. Nihei, Y.; Yoshida, T.; Kataoka, T.; Ogata, R. High-Resolution Mapping of Japanese Microplastic and Macroplastic Emissions from the Land into the Sea. Water 2020, 12, 951. [Google Scholar] [CrossRef]
  83. An, L.; Cui, T.; Zhang, Y.; Liu, H. A Case Study on Small-Size Microplastics in Water and Snails in an Urban River. Sci. Total Environ. 2022, 847, 157461. [Google Scholar] [CrossRef]
  84. Zhang, J.; Zhang, C.; Deng, Y.; Wang, R.; Ma, E.; Wang, J.; Bai, J.; Wu, J.; Zhou, Y. Microplastics in the Surface Water of Small-Scale Estuaries in Shanghai. Mar. Pollut. Bull. 2019, 149, 110569. [Google Scholar] [CrossRef]
  85. Zhuang, L.; Zhang, Y.; Xue, Y.; Ren, Y.; He, J.; Sun, H. Influence of Ongoing Discharge from Multiple Wastewater Treatment Plants on Microplastic Patterns in Small-Scale Receiving Rivers. Sci. Total Environ. 2024, 932, 172880. [Google Scholar] [CrossRef]
  86. Büngener, L.; Schäffer, S.-M.; Schwarz, A.; Schwalb, A. Microplastics in a Small River: Occurrence and Influencing Factors along the River Oker, Northern Germany. J. Contam. Hydrol. 2024, 264, 104366. [Google Scholar] [CrossRef] [PubMed]
  87. Matjašič, T.; Mori, N.; Hostnik, I.; Bajt, O.; Viršek, M.K. Microplastic Pollution in Small Rivers along Rural–Urban Gradients: Variations across Catchments and between Water Column and Sediments. Sci. Total Environ. 2023, 858, 160043. [Google Scholar] [CrossRef]
  88. US EPA Basic Information about Nonpoint Source (NPS) Pollution. Available online: https://www.epa.gov/nps/basic-information-about-nonpoint-source-nps-pollution (accessed on 11 June 2024).
  89. Siegfried, M.; Koelmans, A.A.; Besseling, E.; Kroeze, C. Export of Microplastics from Land to Sea. A Modelling Approach. Water Res. 2017, 127, 249–257. [Google Scholar] [CrossRef] [PubMed]
  90. Guerranti, C.; Martellini, T.; Perra, G.; Scopetani, C.; Cincinelli, A. Microplastics in Cosmetics: Environmental Issues and Needs for Global Bans. Environ. Toxicol. Pharmacol. 2019, 68, 75–79. [Google Scholar] [CrossRef]
  91. Sharma, S.; Basu, S.; Shetti, N.P.; Nadagouda, M.N.; Aminabhavi, T.M. Microplastics in the Environment: Occurrence, Perils, and Eradication. Chem. Eng. J. 2021, 408, 127317. [Google Scholar] [CrossRef]
  92. Webster, T.F.; Harrad, S.; Millette, J.R.; Holbrook, R.D.; Davis, J.M.; Stapleton, H.M.; Allen, J.G.; McClean, M.D.; Ibarra, C.; Abdallah, M.A.E.; et al. Identifying Transfer Mechanisms and Sources of Decabromodiphenyl Ether (BDE 209) in Indoor Environments Using Environmental Forensic Microscopy. Environ. Sci. Technol. 2009, 43, 3067–3072. [Google Scholar] [CrossRef]
  93. Wang, F.; Wang, B.; Duan, L.; Zhang, Y.; Zhou, Y.; Sui, Q.; Xu, D.; Qu, H.; Yu, G. Occurrence and Distribution of Microplastics in Domestic, Industrial, Agricultural and Aquacultural Wastewater Sources: A Case Study in Changzhou, China. Water Res. 2020, 182, 115956. [Google Scholar] [CrossRef]
  94. Alam, F.C.; Sembiring, E.; Muntalif, B.S.; Suendo, V. Microplastic Distribution in Surface Water and Sediment River around Slum and Industrial Area (Case Study: Ciwalengke River, Majalaya District, Indonesia). Chemosphere 2019, 224, 637–645. [Google Scholar] [CrossRef]
  95. Lee, J.; Choi, Y.; Jeong, J.; Chae, K.J. Eye-Glass Polishing Wastewater as Significant Microplastic Source: Microplastic Identification and Quantification. J. Hazard. Mater. 2021, 403, 123991. [Google Scholar] [CrossRef] [PubMed]
  96. Edo, C.; Gonzalez-Pleiter, M.; Leganes, F.; Fernandez-Pinas, F.; Rosal, R. Fate of Microplastics in Wastewater Treatment Plants and Their Environmental Dispersion with Effluent and Sludge. Environ. Pollut. 2020, 259, 113837. [Google Scholar] [CrossRef] [PubMed]
  97. Imbulana, S.; Tanaka, S.; Oluwoye, I. Quantifying Annual Microplastic Emissions of an Urban Catchment: Surface Runoff vs Wastewater Sources. J. Environ. Manag. 2024, 360, 121123. [Google Scholar] [CrossRef]
  98. Dris, R.; Gasperi, J.; Rocher, V.; Saad, M.; Renault, N.; Tassin, B. Microplastic Contamination in an Urban Area: A Case Study in Greater Paris. Environ. Chem. 2015, 12, 592–599. [Google Scholar] [CrossRef]
  99. Hurley, R.; Woodward, J.; Rothwell, J.J. Microplastic Contamination of River Beds Significantly Reduced by Catchment-Wide Flooding. Nat. Geosci. 2018, 11, 251–257. [Google Scholar] [CrossRef]
  100. Verschoor, A.; de Pooter, L.; Dröge, R.; Kuenen, J.; Valk, E. Emission of Microplastics and Potential Mitigation Measures Abrasive Cleaning Agents, Paints and Tyre Wear. Available online: https://rivm.openrepository.com/server/api/core/bitstreams/a53256d6-26bb-47bd-86e3-e3671a85b491/content (accessed on 11 June 2024).
  101. Katsumi, N.; Kusube, T.; Nagao, S.; Okochi, H. The Role of Coated Fertilizer Used in Paddy Fields as a Source of Microplastics in the Marine Environment. Mar. Pollut. Bull. 2020, 161, 111727. [Google Scholar] [CrossRef]
  102. Eamrat, R.; Taweesan, A.; Pussayanavin, T. Assessment of Microplastics Distribution and Related Water Quality in an Urban Canal, Thailand. Pollution 2022, 8, 1172–1184. [Google Scholar] [CrossRef]
  103. Pol, W.; Żmijewska, A.; Stasińska, E.; Zieliński, P. Spatial–Temporal Distribution of Microplastics in Lowland Rivers Flowing through Two Cities (Ne Poland). Water Air Soil Pollut. 2022, 233, 140. [Google Scholar] [CrossRef]
  104. Sasebo City in Japan The Raywa 5-Year Edition of Sasebo City Statistics (34th). Available online: https://www.city.sasebo.lg.jp/kikaku/seisak/r5toukeisyo.html (accessed on 11 June 2024).
  105. Nagasaki Prefecture in Japan The Results of Water Quality Measurement of Public Water Area and Groundwater in Reiwa 4-Year. Available online: https://www.pref.nagasaki.jp/shared/uploads/2024/04/1712911053.pdf (accessed on 11 June 2024).
  106. Japan Meteorological Agency Historical Weather Records for Sasebo City. Available online: https://www.data.jma.go.jp/stats/etrn/index.php?prec_no=84&block_no=47812&year=&month=&day=&view=h0 (accessed on 11 June 2024).
  107. Huang, D.; Li, X.; Ouyang, Z.; Zhao, X.; Wu, R.; Zhang, C.; Lin, C.; Li, Y.; Guo, X. The Occurrence and Abundance of Microplastics in Surface Water and Sediment of the West River Downstream, in the South of China. Sci. Total Environ. 2021, 756, 143857. [Google Scholar] [CrossRef]
  108. Yuan, W.; Christie-Oleza, J.A.; Xu, E.G.; Li, J.; Zhang, H.; Wang, W.; Lin, L.; Zhang, W.; Yang, Y. Environmental Fate of Microplastics in the World’s Third-Largest River: Basin-Wide Investigation and Microplastic Community Analysis. Water Res. 2022, 210, 118002. [Google Scholar] [CrossRef] [PubMed]
  109. Chen, C.; Deng, J.; Zhang, Q.; Cai, J. Microplastic Pollution and Characteristics in the Surface Waters of the Middle and Lower Reaches of the Han River along Hubei Province, China. Int. J. Environ. Sci. Technol. 2023, 20, 10205–10216. [Google Scholar] [CrossRef]
  110. Rico, A.; Redondo-Hasselerharm, P.E.; Vighi, M.; Waichman, A.V.; de Souza Nunes, G.S.; de Oliveira, R.; Singdahl-Larsen, C.; Hurley, R.; Nizzetto, L.; Schell, T. Large-Scale Monitoring and Risk Assessment of Microplastics in the Amazon River. Water Res. 2023, 232, 119707. [Google Scholar] [CrossRef]
  111. Otsuka, Y.; Takada, H.; Nihei, Y.; Kameda, Y.; Nishikawa, K. Current Status and Issues of Microplastic Pollution Research. J. Jpn. Sociery Water Environ. 2021, 44, 35–42. [Google Scholar] [CrossRef]
  112. Verma, C.R.; Pise, M.; Kumkar, P.; Gosavi, S.M.; Kalous, L. Microplastic Contamination in Ulhas River Flowing through India’s Most Populous Metropolitan Area. Water Air Soil Pollut. 2022, 233, 520. [Google Scholar] [CrossRef]
  113. Su, L.; Nan, B.; Craig, N.J.; Pettigrove, V. Temporal and Spatial Variations of Microplastics in Roadside Dust from Rural and Urban Victoria, Australia: Implications for Diffuse Pollution. Chemosphere 2020, 252, 126567. [Google Scholar] [CrossRef]
Microplastics 04 00055 g001
Figure 1. Land use map of Sasebo City, Nagasaki, Japan, showing surface water sampling points (SSB1–SSB4) for microplastic collection.
Figure 1. Land use map of Sasebo City, Nagasaki, Japan, showing surface water sampling points (SSB1–SSB4) for microplastic collection.
Microplastics 04 00055 g001
Microplastics 04 00055 g002
Figure 2. Examples of size measurements of fragment and fiber microplastics (a,b) using an SMZ25 microscope and NIS-Elements BR software version 5.30.00 [Build 1531] (Nikon Corp., Tokyo, Japan). The scale bar was created using the size measurement tool of the software.
Figure 2. Examples of size measurements of fragment and fiber microplastics (a,b) using an SMZ25 microscope and NIS-Elements BR software version 5.30.00 [Build 1531] (Nikon Corp., Tokyo, Japan). The scale bar was created using the size measurement tool of the software.
Microplastics 04 00055 g002
Microplastics 04 00055 g003
Figure 3. Box-and-whisker plot of MP abundances at each sampling point.
Figure 3. Box-and-whisker plot of MP abundances at each sampling point.
Microplastics 04 00055 g003
Microplastics 04 00055 g004
Figure 4. Composition of detected (a) polymers and (b) shapes across all sampling points.
Figure 4. Composition of detected (a) polymers and (b) shapes across all sampling points.
Microplastics 04 00055 g004
Microplastics 04 00055 g005
Figure 5. Size distribution of (a) fragment and (b) fiber microplastics across all sampling points.
Figure 5. Size distribution of (a) fragment and (b) fiber microplastics across all sampling points.
Microplastics 04 00055 g005
Microplastics 04 00055 g006
Figure 6. Composition of detected (a) polymers and (b) shapes at each sampling point.
Figure 6. Composition of detected (a) polymers and (b) shapes at each sampling point.
Microplastics 04 00055 g006
Microplastics 04 00055 g007
Figure 7. Principal component analysis: (a) loading plot and (b) score plot.
Figure 7. Principal component analysis: (a) loading plot and (b) score plot.
Microplastics 04 00055 g007
Table 1. Summary of principal component analysis parameters, including eigenvalues, explained variance, cumulative variance, loading factors, and eigenvectors.
Table 1. Summary of principal component analysis parameters, including eigenvalues, explained variance, cumulative variance, loading factors, and eigenvectors.
Principal Components (PCs)PC 1PC 2
Eigenvalue7.4166.154
Proportion (%)43.636.2
Accumulative Proportion (%)43.679.8
ParametersLoading FactorsEigenvectors
PC 1PC 2PC 1PC 2
PP fragment−0.4490.780−0.0480.104
PE fragment−0.0890.8880.0070.178
PS fragment0.6130.6940.0960.112
PA fragment0.647−0.1660.0880.024
PAS fragment0.989−0.1000.133−0.004
Alkyd resin fragment0.9910.1180.1380.043
PMMA fragment−0.242−0.092−0.0310.032
PAS fragment0.989−0.1000.133−0.004
Epoxy resin fragment−0.2820.901−0.0230.134
PP fiber0.2580.9220.0540.182
PE fiber0.836−0.5400.104−0.073
PA fiber0.989−0.1000.133−0.004
PVC fiber0.989−0.1000.133−0.004
PMMA fiber−0.242−0.092−0.0310.032
PVA fiber−0.2820.901−0.0230.134
Velocity−0.629−0.775−0.101−0.151
Salinity−0.2820.901−0.0230.134
PP: polypropylene; PE: polyethylene, PS: polystyrene; PA: polyamide 6; PAS: polyacrylate styrene; PMMA: polymethyl methacrylate; PVA: polyvinyl acetate; Velocity: water flow velocity.
Table 2. Comparison of aquatic environmental characteristics and microplastic abundances between the present study and previously reported aquatic systems.
Table 2. Comparison of aquatic environmental characteristics and microplastic abundances between the present study and previously reported aquatic systems.
Study AreaRiverMesh
Size		Filtered Water
Volume		Numerical Abundance of MPsReference
LengthBasin AreaMinMaxMeanSD
(km)(km2)(μm)(L)(items/m3)
Small-Scale Aquatic Environments with Limited Anthropogenic Influence
Sasebo River, Japan5.214.7100<3000.0131.182.447.7this study
Small-Scale Aquatic Environments with Intense Anthropogenic Influence *
Tsurumi River, Japan42.523510<202981240n/an/a[37]
Awano River, Japan29.317750<1102,000146,000132,80015,730[35]
Ayaragi River, Japan9.52086,000148,000111,88021,420
Asa River, Japan4423287,000172,000130,00027,840
Majime River, Japan8.31299,0001,061,000272,500299,150
Saba River–Shimaji River, Japan172.1746450–1000111,000256,00088,50046,410[30]
Koya River, Japan4426482,25072,530
Fushino River, Japan30322.487,80048,750
Nishiki River, Japan110884.238,73024,200
Semiarid region, Tijuana, Mexicon/a0.038–1.7525<188,000289,000n/an/a[34]
Sean Saep Canal, Bangkok, Thailand72n/a100–1000n/a3071113479 (300–1000 μm)
261 (100–300 μm)		n/a[102]
Lis River, Portugal39.5850150<n/a0.053422.22203.6727.8[33]
Biała River, Białystok City, Poland17.02 **102 ***40<50510023,60010,8303960[103]
Czarna Hańcza River, Suwałki City, Poland10.90 **65.5 ***40<50490025,20010,2903900
Large-Scale Aquatic Environments with Intense Anthropogenic Influence *
Saigon River, Vietnam250471750<0.3172,000519,000n/an/a[36]
Nakdong River Upstream, Republic of Korean/a933620<1002932167n/an/a[67]
Nakdong River Midstream, Republic of Korean/a599120<10014002613n/an/a
Nakdong River Downstream, Republic of Korean/a626120<1003601273n/an/a
Wei River, China818134,76675<5367010,700n/an/a[63]
Manas River, China45033,500100<500021,00049,000n/an/a[64]
Ganjian River, China76683,50050<50160720407n/a[65]
West River Down Stream, in Pearl River, China173 **353,120753029909870n/an/a[107]
Yangtze River, China6300n/a48<502025801270830[108]
Han River Middle and Lower Reaches, China940 **151,00025<n/a231584064218806[109]
Citarum River, Indonesian/a13,000100<0.050350,000210,000130,000[27]
Weser River, Germany74449,00010–500622 ± 16715714,536n/an/a[32]
Large-Scale Aquatic Environments with Limited Anthropogenic Influence *
The anonymous 1st-grade river, Japan2135090100<32003.238.814.110.7[47]
Yulin River, China20 **386164<5071713n/a[66]
Amazon River, Brazil1500n/a55<300–4600839n/an/a[110]
* The groups of minimal and intense microplastic sources were categorized following the discussion of each previous study. ** The distance investigated in the study area. *** City areas. n/a indicates that the data is not available.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jeong, H.; Fukuda, D.; Elwaleed, A.; Nguyen, Q.T.; Soe, P.S.; Min, B.K.; Cho, H.S.; Agusa, T.; Ishibashi, Y. Microplastic Distribution in a Small-Scale Aquatic System with Limited Anthropogenic Influence: A Case Study in Sasebo City, Japan. Microplastics 2025, 4, 55. https://doi.org/10.3390/microplastics4030055

AMA Style

Jeong H, Fukuda D, Elwaleed A, Nguyen QT, Soe PS, Min BK, Cho HS, Agusa T, Ishibashi Y. Microplastic Distribution in a Small-Scale Aquatic System with Limited Anthropogenic Influence: A Case Study in Sasebo City, Japan. Microplastics. 2025; 4(3):55. https://doi.org/10.3390/microplastics4030055

Chicago/Turabian Style

Jeong, Huiho, Daigo Fukuda, Ahmed Elwaleed, Quynh Thi Nguyen, Pyae Sone Soe, Byeong Kyu Min, Hyeon Seo Cho, Tetsuro Agusa, and Yasuhiro Ishibashi. 2025. "Microplastic Distribution in a Small-Scale Aquatic System with Limited Anthropogenic Influence: A Case Study in Sasebo City, Japan" Microplastics 4, no. 3: 55. https://doi.org/10.3390/microplastics4030055

APA Style

Jeong, H., Fukuda, D., Elwaleed, A., Nguyen, Q. T., Soe, P. S., Min, B. K., Cho, H. S., Agusa, T., & Ishibashi, Y. (2025). Microplastic Distribution in a Small-Scale Aquatic System with Limited Anthropogenic Influence: A Case Study in Sasebo City, Japan. Microplastics, 4(3), 55. https://doi.org/10.3390/microplastics4030055

Article Metrics

Back to TopTop