
Citation: | Ya-ci Liu, Lin Wu, Guo-wei Shi, Sheng-wei Cao, Ya-song Li, 2022. Characteristics and sources of microplastic pollution in the water and sediments of the Jinjiang River Basin, Fujian Province, China, China Geology, 5, 429-438. doi: 10.31035/cg2022051 |
Microplastic pollution is widely distributed from surface water to sediments to groundwater vertically and from land to the ocean horizontally. This study collected samples from surface water, groundwater, and sediments from upper to lower reaches and then to the estuary in 16 typical areas in the Jinjiang River Basin, Fujian Province, China. Afterward, it determined the components and abundance of the microplastics and analyzed the possible microplastic sources through principal component analysis (PCA). As a result, seven main components of microplastics were detected, i.e., polyethylene (PE), polypropylene (PP), polyvinyl chloride (PVC), polyethylene terephthalate (PET), polyformaldehyde (POM), nylon 6 (PA6), and polystyrene (PS). Among them, PE and PP were found to have the highest proportion in the surface water and sediments and in the groundwater, respectively. The surface water, groundwater, and sediments had average microplastic abundance of 1.6 n/L, 2.7 n/L and 33.8 n/kg, respectively. The microplastics in the sediments had the largest particle size, while those in the groundwater had the smallest particle size. Compared with water bodies and sediments in other areas, those in the study area generally have medium-low-level microplastic abundance. Three pollution sources were determined according to PCA, i.e., the dominant agriculture-forestry-fishery source, domestic wastewater, and industrial production. This study can provide a scientific basis for the control of microplastics in rivers.
Plastics are ubiquitous in our daily life. The annual global production of plastics soared from 234×106 t in 2000 to 460×106 t in 2019, and accordingly, the plastic waste increased from 156×106 t in 2000 to 353×106 t in 2019 (OECD, 2022). While plastic supplies bring convenience to our lives, improper plastic waste management leads to severe ecological problems (Song B et al. 2013; Zhang YS et al., 2017). It is estimated that 48×103‒12.7×106 t of plastic waste enters the sea from land every year (Jambeck JR et al., 2015). The top 20 rivers with the most severe plastic pollution, mostly located in Asia, account for 67% of the global total and 74% of plastics are mainly emitted in the wet season from May to October (Lebreton L et al., 2017).
Microplastics refer to plastic particles with sizes less than 5 mm. Because of their exceptional transmissibility, microplastics have been found in oceans, lakes, rivers, and even drinking water (Makhdoumi P et al., 2021). Microplastics in oceans mainly originate from land, with rivers serving as important transfer media. Moreover, 88%‒95% of microplastics is transported to estuaries by rivers (Schmid C et al., 2017). As transitional zones between freshwater and marine systems, estuaries witness the accumulation of high concentrations of microplastics (Xiong W et al., 2022). For instance, the Pearl River Delta has an estimated annual flux of microplastics into the sea of 2.4×103‒3.8×103 t (Mai L et al., 2019). Microplastics in oceans can be enriched and transferred into human bodies via the food chain consisting of phytoplankton, zooplankton, and mammals. After entering an organism, microplastics will be transported to and accumulate in many organs. Dutch scientists (Leslie HA et al. 2022) recently published a paper stating that they first discovered microplastics in human blood and that these microplastics were also able to enter human organs. This paper attracted global attention, once again bringing microplastic pollution to the public. In addition, owing to their high specific surface area and colloidal fluidity, microplastics can easily adsorb pollutants and carry them over long distances, posing a potential threat to ecosystems and human health.
The Jinjiang River, which is the largest river in Quanzhou City, Fujian Province, China, eventually flows from the Quanzhou Bay into the sea. Since river inflow is an important source of marine plastics, this study focused on the abundance and composition of microplastics in river surface water, sediments, and groundwater from the Jinjiang River Basin to the estuary of the Quanzhou Bay. The study analyzed the vertical distribution of microplastics from surface water to sediments and then to groundwater, as well as the horizontal distribution from land to the sea, aiming to provide a scientific basis for river management.
The Jinjiang River has a length of 182 km and a drainage area of 5629 km2. It flows through cities such as Yongchun, Anxi, Nan’an, Jinjiang, Licheng, and Fengze from northwest to southeast. The Jinjiang River has two tributaries in its upper reaches, namely the East River and the West River. The East River originates in Yunlu Village, Chengxiang Township, Yongchun County, with a drainage area of 1917 km2. The West River originates in Tiaozhou Village, Gande Township, Anxi County. The two tributaries meet at Shuangxikou, Jingdou Village, Fengzhou Town, Nan'an City and are then collectively called the Jinjiang River, which eventually enters the sea at Jinjiang City (Fig. 1). The Jinjiang River Basin has landforms of low hills of volcanic rocks in central Fujian and the granite hills and plains along the southeastern coast. Its terrain is high in the northwest and low in the southeast. The soil in the basin mainly consists of red soil and red laterite soil. Most of the mountains in the basin are covered by vegetation, with a forest cover of 51.15%. The basin has a south subtropical climate, with an average annual temperature of 17 ‒21 °C and average annual precipitation of 1651.6 mm, of which the precipitation from May to September accounts for 60%‒70%.
The Jinjiang River Basin is the main source of drinking water in Quanzhou City. The lower reaches of the Jinjiang River are one of the most economically developed areas in Fujian Province, and thus the Jinjiang River plays a particularly important role in the sustainable development of the Jinjiang River Basin. According to the Quanzhou Monthly Report on Water Environment Quality (January 2022), the 19 provincially controlled sections in the Jinjiang River Basin consist of 10 sections with Class-II water quality, eight sections with Class-III water quality, and one section with Class-V water quality, with sections with class-II and -III water quality accounting for 94.7%. The main water pollution in the Jinjiang River Basin originates from chemical, residential, coal, iron, manganese, and agricultural production (Ma L et al., 2012) and the pollutants mainly include CODMn, NH3-N and TP (Ma L et al., 2015).
This study selected 16 evenly spaced sampling sites along the Jinjiang River Basin, at which 16 sets of samples of surface water (SW1‒SW16), groundwater (GW1‒GW16), and sediments (S1–S16) were collected from June to July, 2020 (Fig. 1, Table 1). The sampling sites covered the areas from the upper to the lower reaches (including the West River and the East River) and then to the estuary of the Quanzhou Bay. The sampling sites were located in the lower reaches of domestic and industrial effluent discharges. Surface water and sediments were sampled at the same sampling sites, and groundwater samples were taken from domestic wells in villages near the surface water sampling sites. Each set of samples comprises 4 L of surface water, 4 L of groundwater, and at least 100 g of sediments. All water and sediment samples were placed in brown glass bottles stored in an incubator containing ice and then sent to the laboratory for testing as soon as possible.
Surface water | Groundwater | Sediments | |||||||||
Sample No. | Sampling site | Temperature of surface water /°C | Sample No. | Depth/m | Groundwater level/m | Well wall | Groundwater type | Sample No. | Organic matter content /(g/kg) | ||
SW1 | River | 29.6 | GW1 | 8.0 | 3.8 | Stones | Pore water | S1 | 13 | ||
SW2 | River | 33.4 | GW2 | 13.4 | 9.8 | Cement | Pore water | S2 | 15 | ||
SW3 | River | 32.9 | GW3 | 11.0 | 7.9 | Cement | Pore water | S3 | 6 | ||
SW4 | River | 25.0 | GW4 | 7.0 | 2.1 | Cement | Pore water | S4 | 11 | ||
SW5 | River | 31.2 | GW5 | 6.0 | 5.1 | Cement | Pore water | S5 | 16 | ||
SW6 | River | 31.2 | GW6 | 10.0 | 0.9 | Cement | Pore water | S6 | 28 | ||
SW7 | Estuary | 31.1 | GW7 | 5.0 | 4.4 | Cement | Pore water | S7 | 22 | ||
SW8 | Estuary | 30.8 | GW8 | 3.5 | 2.3 | Bricks | Pore water | S8 | 27 | ||
SW9 | Bay | 28.7 | GW9 | 10.0 | 3.4 | Bricks | Pore water | S9 | 38 | ||
SW10 | Bay | 28.8 | GW10 | 10.0 | 1.6 | Bricks | Pore water | S10 | 20 | ||
SW11 | Bay | 25.6 | GW11 | 8.0 | 4.3 | Stones | Pore water | S11 | 2 | ||
SW12 | Bay | 30.5 | GW12 | 10.0 | 5.4 | Bricks | Pore water | S12 | 40 | ||
SW13 | Bay | 30.0 | GW13 | 6.0 | 2.8 | Stones | Pore water | S13 | 21 | ||
SW14 | Bay | 30.6 | GW14 | 8.0 | 2.3 | Cement | Pore water | S14 | 22 | ||
SW15 | Bay | 30.9 | GW15 | 10.0 | 2.3 | Cement | Pore water | S15 | 8 | ||
SW16 | Bay | 27.8 | GW16 | 6.0 | 1.6 | Cement | Pore water | S16 | 10 |
(i) Surface water
A sample of 4 L surface water was filtered using a 1500-mesh SS316 filter, and then the filter was put into a beaker. Afterward, 50 mL of 30% H2O2 solution was added to the beaker to soak the filter, and then the beaker was placed into a water bath. After ultrasonic treatment for 20 mins, the filter was taken out and rinsed with a small amount of 30% H2O2 solution. Subsequently, a cleaning solution was added to the soaking solution in the beaker, which was then placed into a 60°C water bath. After 12 hours, the mixture was taken out and passed through a 1500-mesh SS316 filter. The sides of the beaker and the filter were washed with pure water. The filter was then put into 100 mL of saturated NaCl solution. The NaCl cleaning solution and the soaking solution were mixed and covered with aluminum foil, followed by standing for 12 hours. The supernatant was filtered out using a 1500-mesh SS316 filter. Then, the filter was rinsed repeatedly with ultra-pure water to remove NaCl residues and placed in a glass Petri dish to dry before tests.
(ii) Groundwater
A sample of 4 L groundwater was filtered using a 1500-mesh SS316 filter, and then the filter was put into a beaker. Afterward, 50 mL of 30% H2O2 solution was added to the beaker to soak the filter, and then the beaker was put into a water bath. After ultrasonic treatment for 20 mins, the filter was taken out and rinsed with a small amount of 30% H2O2 solution. Subsequently, a cleaning solution was added to the soaking solution in the beaker, which was then covered with aluminum foil and placed into a 60°C water bath. After 12 hours, the mixture was taken out and filtered using a 1500-mesh SS316 filter. Afterward, the sides of the beaker and the filter were washed with ultra-pure water, and then the filter was placed in a glass Petri dish to dry before tests.
(iii) Sediments
A sample of 100±1 g sediments was placed in a beaker, and then 300 mL of saturated NaCl solution was added to it. Afterward, the beaker was covered with aluminum foil and then placed in a heated magnetic agitator for 1 h at the temperature of 60°C and a rotation speed of 800 rpm. After that, the beaker was allowed to stand for 12 hours. The supernatant was then placed into another beaker, and a saturated NaCl solution was again added to the sediments. These steps of heating, stirring, standing, and taking the supernatant were repeated twice more. The supernatants obtained after conducting these steps three times were mixed and allowed to stand for 12 hours. The upper layer of the supernatant was taken and filtered using a 500-mesh SS316 filter. Afterward, the supernatant was repeatedly cleaned using ultra-pure water to remove NaCl residues. The filter was placed into a beaker, and then 50 mL of 30% H2O2 solution was added to soak the filter. After ultrasonic treatment for 20 mins, the filter was taken out and rinsed with a small amount of 30% H2O2 solution. Subsequently, a cleaning solution was added to the soaking solution in the beaker, which was then covered with aluminum foil and placed into a 60°C water bath. After 12 hours, the mixture was taken out and passed through a 1500-mesh SS316 filter. The sides of the beaker and the filter were rinsed with ultra-pure water, and then the filter was placed in a glass Petri dish to dry before tests.
Test instrument: A Confocal Laser Raman Spectrometer (Horiba LabRAM Aramis).
Operating conditions of the instrument: Laser wavelength: 532 nm; laser power: 11 mW; spectral range: 100–3500/cm; grating: 300, and microscope lens: 10×.
Test process: The filter was stuck to the slide. A positioning mark was made on the edge of the filter, and then the filter was placed on the loading platform, which was then moved point by point to identify the materials intercepted by the filter. The Raman spectra of the materials were collected and compared with the standard spectra to determine the composition of the materials. Meanwhile, the sizes of the materials were recorded.
The microplastic abundance in surface water and groundwater was expressed as the microplastic particle number per liter (n/L), and that in sediments was expressed as the microplastic particle number per kg (n/kg). The possible sources of microplastics were analyzed through PCA in software SPSS version 19.
Six microplastic components were detected in the surface water samples (Table 2), namely PE (57%), PP (23%), PVC (7%), PET (7%), PA6 (4%), and PS (3%), revealing that PE accounts for the highest proportion in surface water and that PE and PP accounted for 80% in the surface water in total. The microplastics corresponding to different sampling sites along the Jinjiang River Basin had different compositions, but they mainly comprised PE. PE was also detected in the surface water samples SW12 and SW13.
Type | Sample No. | PE | PP | PVC | PET | PA6 | PS | POM |
Surface water | SW1 | 56 | 22 | 11 | 11 | 0 | 0 | 0 |
SW2 | 63 | 25 | 6 | 0 | 6 | 0 | 0 | |
SW3 | 50 | 13 | 0 | 13 | 25 | 0 | 0 | |
SW4 | 83 | 0 | 0 | 17 | 0 | 0 | 0 | |
SW5 | 50 | 10 | 30 | 0 | 0 | 10 | 0 | |
SW6 | 50 | 0 | 0 | 50 | 0 | 0 | 0 | |
SW7 | 33 | 33 | 0 | 33 | 0 | 0 | 0 | |
SW8 | 50 | 33 | 0 | 0 | 17 | 0 | 0 | |
SW9 | 44 | 33 | 11 | 0 | 0 | 11 | 0 | |
SW10 | 50 | 25 | 0 | 0 | 0 | 25 | 0 | |
SW11 | 60 | 20 | 0 | 20 | 0 | 0 | 0 | |
SW12 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | |
SW13 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | |
SW14 | 50 | 50 | 0 | 0 | 0 | 0 | 0 | |
SW15 | 38 | 50 | 13 | 0 | 0 | 0 | 0 | |
SW16 | 67 | 33 | 0 | 0 | 0 | 0 | 0 | |
Groundwater | GW1 | 0 | 0 | 50 | 0 | 0 | 50 | 0 |
GW2 | 0 | 0 | 100 | 0 | 0 | 0 | 0 | |
GW3 | 0 | 75 | 0 | 0 | 0 | 0 | 25 | |
GW4 | 0 | 75 | 25 | 0 | 0 | 0 | 0 | |
GW5 | 0 | 0 | 0 | 100 | 0 | 0 | 0 | |
GW6 | 25 | 25 | 25 | 25 | 0 | 0 | 0 | |
GW7 | 0 | 0 | 0 | 0 | 0 | 0 | 100 | |
GW8 | 75 | 0 | 25 | 0 | 0 | 0 | 0 | |
GW9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW10 | 0 | 90 | 5 | 0 | 0 | 5 | 0 | |
GW11 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW12 | 0 | 67 | 0 | 33 | 0 | 0 | 0 | |
GW13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW14 | 60 | 20 | 0 | 10 | 10 | 0 | 0 | |
GW15 | 73 | 0 | 27 | 0 | 0 | 0 | 0 | |
GW16 | 38 | 62 | 0 | 0 | 0 | 0 | 0 | |
Sediment | S1 | 67 | 33 | 0 | 0 | 0 | 0 | 0 |
S2 | 0 | 67 | 33 | 0 | 0 | 0 | 0 | |
S3 | 33 | 0 | 33 | 0 | 0 | 33 | 0 | |
S4 | 33 | 67 | 0 | 0 | 0 | 0 | 0 | |
S5 | 0 | 25 | 50 | 0 | 0 | 25 | 0 | |
S6 | 25 | 50 | 0 | 0 | 0 | 25 | 0 | |
S7 | 75 | 25 | 0 | 0 | 0 | 0 | 0 | |
S8 | 75 | 0 | 0 | 25 | 0 | 0 | 0 | |
S9 | 0 | 50 | 50 | 0 | 0 | 0 | 0 | |
S10 | 60 | 20 | 0 | 20 | 0 | 0 | 0 | |
S11 | 50 | 0 | 0 | 0 | 0 | 50 | 0 | |
S12 | 29 | 57 | 14 | 0 | 0 | 0 | 0 | |
S13 | 0 | 0 | 100 | 0 | 0 | 0 | 0 | |
S14 | 50 | 50 | 0 | 0 | 0 | 0 | 0 | |
S15 | 75 | 0 | 25 | 0 | 0 | 0 | 0 | |
S16 | 100 | 0 | 0 | 0 | 0 | 0 | 0 |
A total of 102 microplastics were detected in 16 surface water samples, with average abundance of 1.6 n/L. The results indicated that the microplastic abundance gradually decreased from the upper to the lower reaches and then to the bay (Fig. 2a). Sample SW2 located in the West River in Nan'an City yielded the highest microplastic abundance of 4 n/L, and the urban source was an important source of microplastics of SW2. Sample SW13 located on the northern bank of the estuary had the lowest abundance (0.5 n/L). The sampling site of SW13 was far from cities and farmland and thus was less affected by the artificial input of microplastics. The microplastics in the surface water samples had small particle sizes, including 40‒100 µm (45%), 150‒500 µm (44%), and > 500 µm (11%).
Seven microplastic components were detected in the groundwater samples (Table 2), namely PP (54%), PE (33%), PVC (6%), PET (2%), POM (2%), PA6 (1%), and PS (1%), revealing that PP accounted for the highest proportion in the groundwater and that PE and PP accounted for 87% in total. The microplastics corresponding to different sampling sites had different compositions. The microplastic compositions of the East and West rivers in the upper reaches were significantly different from that in the lower reaches. Specifically, the microplastics in groundwater of the East River consisted of PVC and PS, while those in groundwater of the West River comprised PVC. By contrast, PP and POM were recorded for the sampling sites at the intersection of the East River and West rivers. The microplastics in groundwater of the northern and southern coasts of the Quanzhou Bay also had different compositions and were dominated by PE and PP, respectively. Trace microplastics (0.25 n/L) were detected in the groundwater samples GW9, GW11, and GW13, but their compositions were uncertain.
A total of 173 microplastics were detected in 16 groundwater samples, with average abundance of 2.7 n/L. The upper reaches of the basin had low microplastic abundance (
Five microplastic components were detected in sediments (Table 2), namely PE (43%), PP (30%), PVC (17%), PS (7%), and PET (4%), revealing that PE accounted for the highest proportion in the sediments and that PE and PP accounted for 73% in total. The microplastics corresponding to different sampling sites had different compositions. For instance, the microplastics detected in the coastal sediments of the Quanzhou Bay were mainly composed of PE.
A total of 54 microplastics were detected in the 16 sediment samples from the basin, with average abundance of 33.8 n/kg. The detection results show that the microplastic abundance in the sediments is stable from the upper reaches of the basin to the estuary. The microplastic abundance was 30 n/kg in samples S1–S4 and 40 n/kg in samples S5–S8 (Fig. 2c). The sediment samples from different sampling sites around the Quanzhou Bay had greatly different microplastic abundance. Specifically, samples S10, S12 and S15 had higher microplastic abundance than other sediment samples, suggesting that microplastic pollution in coastal sediments was severe. Among the 16 sediment samples, sample S12 from the southern bank of the Quanzhou Bay had the highest microplastic abundance of 70 n/kg. This sample was collected from a dock with many large fishing boats, household garbage, and fishing nets, which led to increased microplastic pollution. Sample S12 also had the highest organic matter content of 40 g/kg (Table 1), which led to the easy interception of microplastics. This may be the reason for the highest microplastic abundance of this sample. The microplastics had small particle sizes, including 50‒100 µm (13%), 150‒500 µm (74%), and >500 µm (13%).
The microplastics in the surface water from the upper to the lower reaches had similar main components dominated by PE. By contrast, the microplastics in the groundwater at different locations from the upper to lower reaches had greatly different main compositions. The groundwater has poorer connectivity than the surface water, leading to significant differences in the microplastic composition in groundwater at different locations. The components and particle sizes of microplastics detected in surface water, groundwater, and sediments were compared (Figs. 3a, b). According to the comparison results, PE had the largest proportion in the microplastic components in the surface water and sediments, while PP accounted for the largest proportion in the microplastic components in the groundwater. PE in surface water is prone to precipitate into the sediments and is also easy to migrate a long way and finally reach the bay. POM was only detected in groundwater. The different microplastic compositions in surface water, groundwater, and sediments indicate that the microplastic composition is highly correlated with the bearing media.
Type | Study area | Microplastic abundance/(n/L) |
Surface water | Jinjiang River, China | 0.5–4 (this study) |
Shuangtaizi River of Liaoning, China | 1.33±0.67–7.33±3.93 (Li JN et al., 2021) | |
Daliao River of Liaoning, China | 3.00±1.15–11.00±3.51 (Li JN et al., 2021) | |
Manas River, Xinjiang, China | 24±4–48±9 (Wang GL, 2020) | |
Yangtze estuary, China | 0.24–1.35 (Luo W, 2019) | |
Qinghai-Tibet Plateau, China | 0.247–2.686 (Liu RP et al., 2021a) | |
Yellow River, China | 5.358–654 (Liu RP et al., 2021b) | |
Ciwalengke River, Indonesia | 5.85±3.28 (Alam FC et al., 2019) | |
Itchen River, Britain | 1.15 (Gallagher A et al., 2015) | |
Hudson River, USA | 0.98 (Miller RZ et al., 2017) | |
San Gabriel River, USA | 0.41 (Moore CJ et al., 2011) | |
Groundwater | Jinjiang River, China | 0.25–5.25 (this study) |
Shallow aquifer, Bacchus Marsh, Australia | 16–97 (Samandra S et al., 2022) | |
Karst aquifer of Illinois, USA | 0.86–15.2 (Panno SV et al., 2019) | |
Northern Germany | 0–7 (Mintenig SM et al., 2019) | |
Coastal areas of southern India | 0–4.3 (Selvam S et al., 2021) | |
Southeast coast of the Bay of Bengal | 2–80 (Ramakrishnan R et al., 2021) | |
Sediment | Jinjiang River, China | 20–70 (this study) |
Liaohe river, China | (20.00±34.64)–(193.33±172.43) (Han LH et al., 2020) | |
Yangtze River estuary, China | 20–340 (Peng G et al., 2017b) | |
Yellow River, China | 43.57-615 (Liu RP et al., 2021b) | |
Urban freshwater rivers, Shanghai, China | 53–723 (Peng G et al., 2017a) | |
Wei River, China | 360–1320 (Ding L et al., 2019) | |
Rhine River, Germany | 228–3763 (Klein S et al., 2015) | |
Atoac River in Puebla, Mexico | (833.33±80.79)–(1633.34±202.56) (Shruti VC et al., 2019) |
The microplastics in groundwater generally have smaller particle sizes than those in surface water and sediments. The results of this study show that 84% of microplastics in groundwater have a particle size of 10‒100 μm and only 1% of them have particle sizes greater than 500 μm. Because the hydrodynamic condition is the key factor controlling the microplastic distribution in river water and sediments, microplastics with large particle sizes are more likely to precipitate into sediments. Therefore, the microplastics in sediments generally have larger particle sizes than those in surface water and groundwater, with 74% of microplastics in sediments having a particle size of 150‒500 μm.
The microplastic abundance of samples of surface water, groundwater, and sediments collected at 16 sets of different sampling sites was compared (Fig. 3c). The microplastic abundance in surface water was greater than or equal to that in groundwater at the sampling sites except for sites 10, 14, 15 and 16 near the coastal zone of the Quanzhou Bay, at which the microplastic abundance in groundwater was higher than that in surface water. In particular, the groundwater at sampling site 16 had the highest microplastic abundance of 25 n/L. There was no significant correlation (p > 0.05) between the microplastic abundance of surface water, groundwater, and sediments.
The microplastic abundance in surface water obtained in this study was compared with that in previous studies, yielding the following results (Table 3). The microplastic abundance in the surface water in the study area is significantly lower than that in the Yellow River and Manas River in China, and is lower than that in the Daliao River, China and the Ciwalengke River, Indonesia. It approximates that in the Shuangtaizi River, China and the Itchen River, Britain, but is higher than that in the Yangtze Estuary, Qinghai-Tibet Plateau, the Hudson River and the San Gabriel River. Overall, the microplastic abundance in the surface water of the Jinjiang River Basin is at a medium-low level, and the microplastic distribution in coastal zones of the basin may be affected by coastal waves, tides, and flows. Microplastics in surface water are harmful and are prone to enter soil through surface runoff and agricultural irrigation, leading to microplastic pollution in the soil. Groundwater may be polluted due to its connection with surface water. Microplastics may be transmitted to human bodies through accumulation in fish.
At present, there are only a few studies of microplastic pollution in groundwater. The microplastic abundance in groundwater in this study was compared with that in existing studies (Table 3), yielding the following results. The microplastic abundance in groundwater in the study area is lower than that in the shallow aquifer of Bacchus Marsh, Australia, and approximates that in the coastal areas of southern India and northern Germany. The maximum microplastic abundance in groundwater in the study area is lower than that in the karst aquifer of Illinois, U.S., and the southeastern coast of the Bay of Bengal. Overall, the microplastic abundance in the groundwater of the Jinjiang River Basin is at a medium-low level.
The microplastic abundance in sediments in this study was compared with that in previous studies (Table 3), and the results are as follows. The microplastic abundance in sediments in the study area is significantly lower than that in the Wei River and Yellow River in China, the Rhine River in Germany, and the Atoac River in Puebla, Mexico. The lowest microplastic abundance in the sediments of the Jinjiang River Basin is similar to that in the Liaohe River, the Yangtze River estuary, and the Shanghai urban freshwater rivers in China, while the highest abundance in the sediments of the Jinjiang River Basin is significantly lower than that in these rivers. Overall, the microplastic abundance in the sediments of the Jinjiang River Basin is low.
PCA was carried out for the data on microplastics in the water bodies and sediments of the Jinjiang River Basin. As a result, three principal components were extracted (Table 4), and they had a cumulative contribution rate of 66.505%. The microplastics with a large load on principal component 1 consist of PE and PP, those with a large load on principal component 2 comprise PVC, PET, PA6, and PS, and those with a large load on principal component 3 consist of POM.
Microplastic component | Agriculture-forestry-fisheries | Domestic wastewater | Industrial production |
PE | 0.964 | 0.085 | 0.016 |
PP | 0.938 | 0.213 | −0.107 |
PVC | −0.156 | 0.644 | 0.312 |
PET | 0.008 | 0.715 | 0.300 |
PA6 | 0.169 | 0.464 | 0.364 |
PS | −0.164 | 0.657 | 0.191 |
POM | −0.116 | −0.091 | 0.867 |
Contribution rate/% | 27.180 | 23.340 | 15.985 |
Accumulative contribution/% | 27.180 | 50.520 | 66.505 |
More than one-half of PE is used for film products, followed by pipes, injection molding products, and wire wrapping layers. PP in China is mainly used for woven bags, packaging bags, and strapping ropes, which consume approximately 30% of the total PP (Tang QS, 2018). Agricultural activities are the main source of microplastics in soil owing to the plastic mulching, sewage irrigation, and sludge fertilization in farmland (Yan YC et al., 2022). However, the microplastics in farmland soil have relatively simple composition and mainly consist of PP (50.51%) and PE (43.43%), which account for more than 90% of the microplastics in soil (Liu M et al., 2018). This result indicates that PP and PE are the main components of microplastic pollution in farmland. Forestry and fisheries are well developed in the Jinjiang River Basin and the Quanzhou Bay, especially in the Quanzhou Bay, with fisheries for mariculture and marine capture have been established. Agriculture, forestry, and fisheries use plastics, fishing nets, and cages, which are mainly composed of PE and PP and all can cause plastic pollution. Therefore, the principal component 1 associated with PE and PP accounted for the source in agriculture, forestry, and fisheries.
PVC is closely related to daily life and can be found in items such as shoes, artificial leather, toys, mineral water bottles, and raincoats. PET can be used to manufacture polyester, bottles, and electronic appliances. PA6 is nylon and is mainly used in synthetic fibers to be employed in fields such as textile clothing. PS is frequently used to make foam plastic products, disposable plastic tableware, and transparent CD cases, all of which are common in daily life. Dutch researchers Leslie HA et al. (2022) discovered PET plastic in one-half of volunteers' blood samples and PS in more than one-third of volunteers' blood samples. They noted that PET plastic is widely used to manufacture beverage bottles and PS is used to produce many products such as disposable food containers. Jinjiang City, located in the Jinjiang River Basin, has a prosperous shoe-making industry, and a large market named Jinjiang International Shoes Spinning is located near the Jinjiang River. Textile washing in daily life, as well as the ubiquitous plastic bottles and packages, sheds large numbers of microplastics into domestic wastewater. More than 1900 fibers can be carried into wastewater from a single washing item and are then discharged into urban waterways (Browne MA et al., 2011). Wastewater treatment plants rarely carry out professional treatment of microplastics, enabling most of the microplastics to be discharged into watercourses (Falco FD et al. 2017). This study revealed that PVC, PET, PA6, and PS detected in the Jinjiang River mainly originate from domestic wastewater, which can be regarded as principal component 2.
POM, one of the five general engineering plastics, has excellent comprehensive performance and similar hardness, strength, and rigidity to metal. Therefore, principal component 3 associated with POM is interpreted as industrial production. POM was only detected in groundwater in this study, indicating that POM in groundwater did not originate from surface water and may be directly discharged into groundwater by factories. The groundwater sample GW7 collected from Chidian Town, Jinjiang City, had microplastic abundance of 3 n/L, and the microplastics in this sample consisted of only POM. Huang YY et al. (2015) revealed that multiple indexes of groundwater in Chidian Town exceeded those of Class-III groundwater stipulated in GB/T 14848-2017 Standard for Groundwater Quality—a national standard of China. The reason for this finding is that there are industrial enterprises in this area, and the discharged industrial sewage is an important source of groundwater pollution. In this study, POM was detected at the sampling site of GW7 probably due to the direct discharge of industrial wastewater in this area.
According to the above analysis, the microplastic sources in the Jinjiang River Basin mainly include the dominant agriculture-forestry-fishery source, domestic wastewater, and industrial production. However, there is a lack of targeted policies and systems at the national level for these microplastic sources. Moreover, current management in the basin fails to focus on microplastics, and the investment, monitoring, and impact assessment for microplastics in the basin are all insufficient. For these reasons, multi-party cooperation and effective supervision and control policies are yet to be established for the basin.
Microplastic pollution is widely distributed from surface water to sediments to groundwater vertically and from land to the ocean horizontally. Seven main microplastic components were detected in the water bodies and sediments of the Jinjiang River Basin. Among them, PE has the largest proportion in the surface water and sediments, and PP accounts for the largest proportion in the groundwater. The microplastic abundance in the surface water is greater than or equal to that in groundwater at most sampling sites. The microplastics in the groundwater have the smallest overall particle size, while those in the sediments have the largest particle size. Compared with other areas, the study area has medium-low-level microplastic abundance in general. Three pollution sources were determined according to PCA, i.e., the dominant agriculture-forestry-fishery source, domestic wastewater, and industrial production.
Different from common pollutants, there is no targeted treatment or fast and convenient monitoring techniques for microplastics, which are prone to be discharged into the environment through wastewater and cannot be completely removed. Therefore, a sound regulatory system is yet to be established to enhance public understanding of the harm of microplastic pollution and to effectively curb microplastic pollution at source. The purpose is to reduce the threat of microplastics to the ecological environment and human health.
Ya-Ci Liu and Ya-Song Li conceived of the presented idea. Lin Wu and Guo-Wei Shi contributed to sample preparation. Sheng-Wei Cao verified the analytical methods. All authors discussed the results and contributed to the final manuscript.
The authors declare no conflicts of interest.
This research was funded by National Natural Science Foundation of China (41907175 and 41902259), and China Geological Survey project (DD20190303).
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Surface water | Groundwater | Sediments | |||||||||
Sample No. | Sampling site | Temperature of surface water /°C | Sample No. | Depth/m | Groundwater level/m | Well wall | Groundwater type | Sample No. | Organic matter content /(g/kg) | ||
SW1 | River | 29.6 | GW1 | 8.0 | 3.8 | Stones | Pore water | S1 | 13 | ||
SW2 | River | 33.4 | GW2 | 13.4 | 9.8 | Cement | Pore water | S2 | 15 | ||
SW3 | River | 32.9 | GW3 | 11.0 | 7.9 | Cement | Pore water | S3 | 6 | ||
SW4 | River | 25.0 | GW4 | 7.0 | 2.1 | Cement | Pore water | S4 | 11 | ||
SW5 | River | 31.2 | GW5 | 6.0 | 5.1 | Cement | Pore water | S5 | 16 | ||
SW6 | River | 31.2 | GW6 | 10.0 | 0.9 | Cement | Pore water | S6 | 28 | ||
SW7 | Estuary | 31.1 | GW7 | 5.0 | 4.4 | Cement | Pore water | S7 | 22 | ||
SW8 | Estuary | 30.8 | GW8 | 3.5 | 2.3 | Bricks | Pore water | S8 | 27 | ||
SW9 | Bay | 28.7 | GW9 | 10.0 | 3.4 | Bricks | Pore water | S9 | 38 | ||
SW10 | Bay | 28.8 | GW10 | 10.0 | 1.6 | Bricks | Pore water | S10 | 20 | ||
SW11 | Bay | 25.6 | GW11 | 8.0 | 4.3 | Stones | Pore water | S11 | 2 | ||
SW12 | Bay | 30.5 | GW12 | 10.0 | 5.4 | Bricks | Pore water | S12 | 40 | ||
SW13 | Bay | 30.0 | GW13 | 6.0 | 2.8 | Stones | Pore water | S13 | 21 | ||
SW14 | Bay | 30.6 | GW14 | 8.0 | 2.3 | Cement | Pore water | S14 | 22 | ||
SW15 | Bay | 30.9 | GW15 | 10.0 | 2.3 | Cement | Pore water | S15 | 8 | ||
SW16 | Bay | 27.8 | GW16 | 6.0 | 1.6 | Cement | Pore water | S16 | 10 |
Type | Sample No. | PE | PP | PVC | PET | PA6 | PS | POM |
Surface water | SW1 | 56 | 22 | 11 | 11 | 0 | 0 | 0 |
SW2 | 63 | 25 | 6 | 0 | 6 | 0 | 0 | |
SW3 | 50 | 13 | 0 | 13 | 25 | 0 | 0 | |
SW4 | 83 | 0 | 0 | 17 | 0 | 0 | 0 | |
SW5 | 50 | 10 | 30 | 0 | 0 | 10 | 0 | |
SW6 | 50 | 0 | 0 | 50 | 0 | 0 | 0 | |
SW7 | 33 | 33 | 0 | 33 | 0 | 0 | 0 | |
SW8 | 50 | 33 | 0 | 0 | 17 | 0 | 0 | |
SW9 | 44 | 33 | 11 | 0 | 0 | 11 | 0 | |
SW10 | 50 | 25 | 0 | 0 | 0 | 25 | 0 | |
SW11 | 60 | 20 | 0 | 20 | 0 | 0 | 0 | |
SW12 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | |
SW13 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | |
SW14 | 50 | 50 | 0 | 0 | 0 | 0 | 0 | |
SW15 | 38 | 50 | 13 | 0 | 0 | 0 | 0 | |
SW16 | 67 | 33 | 0 | 0 | 0 | 0 | 0 | |
Groundwater | GW1 | 0 | 0 | 50 | 0 | 0 | 50 | 0 |
GW2 | 0 | 0 | 100 | 0 | 0 | 0 | 0 | |
GW3 | 0 | 75 | 0 | 0 | 0 | 0 | 25 | |
GW4 | 0 | 75 | 25 | 0 | 0 | 0 | 0 | |
GW5 | 0 | 0 | 0 | 100 | 0 | 0 | 0 | |
GW6 | 25 | 25 | 25 | 25 | 0 | 0 | 0 | |
GW7 | 0 | 0 | 0 | 0 | 0 | 0 | 100 | |
GW8 | 75 | 0 | 25 | 0 | 0 | 0 | 0 | |
GW9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW10 | 0 | 90 | 5 | 0 | 0 | 5 | 0 | |
GW11 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW12 | 0 | 67 | 0 | 33 | 0 | 0 | 0 | |
GW13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW14 | 60 | 20 | 0 | 10 | 10 | 0 | 0 | |
GW15 | 73 | 0 | 27 | 0 | 0 | 0 | 0 | |
GW16 | 38 | 62 | 0 | 0 | 0 | 0 | 0 | |
Sediment | S1 | 67 | 33 | 0 | 0 | 0 | 0 | 0 |
S2 | 0 | 67 | 33 | 0 | 0 | 0 | 0 | |
S3 | 33 | 0 | 33 | 0 | 0 | 33 | 0 | |
S4 | 33 | 67 | 0 | 0 | 0 | 0 | 0 | |
S5 | 0 | 25 | 50 | 0 | 0 | 25 | 0 | |
S6 | 25 | 50 | 0 | 0 | 0 | 25 | 0 | |
S7 | 75 | 25 | 0 | 0 | 0 | 0 | 0 | |
S8 | 75 | 0 | 0 | 25 | 0 | 0 | 0 | |
S9 | 0 | 50 | 50 | 0 | 0 | 0 | 0 | |
S10 | 60 | 20 | 0 | 20 | 0 | 0 | 0 | |
S11 | 50 | 0 | 0 | 0 | 0 | 50 | 0 | |
S12 | 29 | 57 | 14 | 0 | 0 | 0 | 0 | |
S13 | 0 | 0 | 100 | 0 | 0 | 0 | 0 | |
S14 | 50 | 50 | 0 | 0 | 0 | 0 | 0 | |
S15 | 75 | 0 | 25 | 0 | 0 | 0 | 0 | |
S16 | 100 | 0 | 0 | 0 | 0 | 0 | 0 |
Type | Study area | Microplastic abundance/(n/L) |
Surface water | Jinjiang River, China | 0.5–4 (this study) |
Shuangtaizi River of Liaoning, China | 1.33±0.67–7.33±3.93 (Li JN et al., 2021) | |
Daliao River of Liaoning, China | 3.00±1.15–11.00±3.51 (Li JN et al., 2021) | |
Manas River, Xinjiang, China | 24±4–48±9 (Wang GL, 2020) | |
Yangtze estuary, China | 0.24–1.35 (Luo W, 2019) | |
Qinghai-Tibet Plateau, China | 0.247–2.686 (Liu RP et al., 2021a) | |
Yellow River, China | 5.358–654 (Liu RP et al., 2021b) | |
Ciwalengke River, Indonesia | 5.85±3.28 (Alam FC et al., 2019) | |
Itchen River, Britain | 1.15 (Gallagher A et al., 2015) | |
Hudson River, USA | 0.98 (Miller RZ et al., 2017) | |
San Gabriel River, USA | 0.41 (Moore CJ et al., 2011) | |
Groundwater | Jinjiang River, China | 0.25–5.25 (this study) |
Shallow aquifer, Bacchus Marsh, Australia | 16–97 (Samandra S et al., 2022) | |
Karst aquifer of Illinois, USA | 0.86–15.2 (Panno SV et al., 2019) | |
Northern Germany | 0–7 (Mintenig SM et al., 2019) | |
Coastal areas of southern India | 0–4.3 (Selvam S et al., 2021) | |
Southeast coast of the Bay of Bengal | 2–80 (Ramakrishnan R et al., 2021) | |
Sediment | Jinjiang River, China | 20–70 (this study) |
Liaohe river, China | (20.00±34.64)–(193.33±172.43) (Han LH et al., 2020) | |
Yangtze River estuary, China | 20–340 (Peng G et al., 2017b) | |
Yellow River, China | 43.57-615 (Liu RP et al., 2021b) | |
Urban freshwater rivers, Shanghai, China | 53–723 (Peng G et al., 2017a) | |
Wei River, China | 360–1320 (Ding L et al., 2019) | |
Rhine River, Germany | 228–3763 (Klein S et al., 2015) | |
Atoac River in Puebla, Mexico | (833.33±80.79)–(1633.34±202.56) (Shruti VC et al., 2019) |
Microplastic component | Agriculture-forestry-fisheries | Domestic wastewater | Industrial production |
PE | 0.964 | 0.085 | 0.016 |
PP | 0.938 | 0.213 | −0.107 |
PVC | −0.156 | 0.644 | 0.312 |
PET | 0.008 | 0.715 | 0.300 |
PA6 | 0.169 | 0.464 | 0.364 |
PS | −0.164 | 0.657 | 0.191 |
POM | −0.116 | −0.091 | 0.867 |
Contribution rate/% | 27.180 | 23.340 | 15.985 |
Accumulative contribution/% | 27.180 | 50.520 | 66.505 |
Surface water | Groundwater | Sediments | |||||||||
Sample No. | Sampling site | Temperature of surface water /°C | Sample No. | Depth/m | Groundwater level/m | Well wall | Groundwater type | Sample No. | Organic matter content /(g/kg) | ||
SW1 | River | 29.6 | GW1 | 8.0 | 3.8 | Stones | Pore water | S1 | 13 | ||
SW2 | River | 33.4 | GW2 | 13.4 | 9.8 | Cement | Pore water | S2 | 15 | ||
SW3 | River | 32.9 | GW3 | 11.0 | 7.9 | Cement | Pore water | S3 | 6 | ||
SW4 | River | 25.0 | GW4 | 7.0 | 2.1 | Cement | Pore water | S4 | 11 | ||
SW5 | River | 31.2 | GW5 | 6.0 | 5.1 | Cement | Pore water | S5 | 16 | ||
SW6 | River | 31.2 | GW6 | 10.0 | 0.9 | Cement | Pore water | S6 | 28 | ||
SW7 | Estuary | 31.1 | GW7 | 5.0 | 4.4 | Cement | Pore water | S7 | 22 | ||
SW8 | Estuary | 30.8 | GW8 | 3.5 | 2.3 | Bricks | Pore water | S8 | 27 | ||
SW9 | Bay | 28.7 | GW9 | 10.0 | 3.4 | Bricks | Pore water | S9 | 38 | ||
SW10 | Bay | 28.8 | GW10 | 10.0 | 1.6 | Bricks | Pore water | S10 | 20 | ||
SW11 | Bay | 25.6 | GW11 | 8.0 | 4.3 | Stones | Pore water | S11 | 2 | ||
SW12 | Bay | 30.5 | GW12 | 10.0 | 5.4 | Bricks | Pore water | S12 | 40 | ||
SW13 | Bay | 30.0 | GW13 | 6.0 | 2.8 | Stones | Pore water | S13 | 21 | ||
SW14 | Bay | 30.6 | GW14 | 8.0 | 2.3 | Cement | Pore water | S14 | 22 | ||
SW15 | Bay | 30.9 | GW15 | 10.0 | 2.3 | Cement | Pore water | S15 | 8 | ||
SW16 | Bay | 27.8 | GW16 | 6.0 | 1.6 | Cement | Pore water | S16 | 10 |
Type | Sample No. | PE | PP | PVC | PET | PA6 | PS | POM |
Surface water | SW1 | 56 | 22 | 11 | 11 | 0 | 0 | 0 |
SW2 | 63 | 25 | 6 | 0 | 6 | 0 | 0 | |
SW3 | 50 | 13 | 0 | 13 | 25 | 0 | 0 | |
SW4 | 83 | 0 | 0 | 17 | 0 | 0 | 0 | |
SW5 | 50 | 10 | 30 | 0 | 0 | 10 | 0 | |
SW6 | 50 | 0 | 0 | 50 | 0 | 0 | 0 | |
SW7 | 33 | 33 | 0 | 33 | 0 | 0 | 0 | |
SW8 | 50 | 33 | 0 | 0 | 17 | 0 | 0 | |
SW9 | 44 | 33 | 11 | 0 | 0 | 11 | 0 | |
SW10 | 50 | 25 | 0 | 0 | 0 | 25 | 0 | |
SW11 | 60 | 20 | 0 | 20 | 0 | 0 | 0 | |
SW12 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | |
SW13 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | |
SW14 | 50 | 50 | 0 | 0 | 0 | 0 | 0 | |
SW15 | 38 | 50 | 13 | 0 | 0 | 0 | 0 | |
SW16 | 67 | 33 | 0 | 0 | 0 | 0 | 0 | |
Groundwater | GW1 | 0 | 0 | 50 | 0 | 0 | 50 | 0 |
GW2 | 0 | 0 | 100 | 0 | 0 | 0 | 0 | |
GW3 | 0 | 75 | 0 | 0 | 0 | 0 | 25 | |
GW4 | 0 | 75 | 25 | 0 | 0 | 0 | 0 | |
GW5 | 0 | 0 | 0 | 100 | 0 | 0 | 0 | |
GW6 | 25 | 25 | 25 | 25 | 0 | 0 | 0 | |
GW7 | 0 | 0 | 0 | 0 | 0 | 0 | 100 | |
GW8 | 75 | 0 | 25 | 0 | 0 | 0 | 0 | |
GW9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW10 | 0 | 90 | 5 | 0 | 0 | 5 | 0 | |
GW11 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW12 | 0 | 67 | 0 | 33 | 0 | 0 | 0 | |
GW13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
GW14 | 60 | 20 | 0 | 10 | 10 | 0 | 0 | |
GW15 | 73 | 0 | 27 | 0 | 0 | 0 | 0 | |
GW16 | 38 | 62 | 0 | 0 | 0 | 0 | 0 | |
Sediment | S1 | 67 | 33 | 0 | 0 | 0 | 0 | 0 |
S2 | 0 | 67 | 33 | 0 | 0 | 0 | 0 | |
S3 | 33 | 0 | 33 | 0 | 0 | 33 | 0 | |
S4 | 33 | 67 | 0 | 0 | 0 | 0 | 0 | |
S5 | 0 | 25 | 50 | 0 | 0 | 25 | 0 | |
S6 | 25 | 50 | 0 | 0 | 0 | 25 | 0 | |
S7 | 75 | 25 | 0 | 0 | 0 | 0 | 0 | |
S8 | 75 | 0 | 0 | 25 | 0 | 0 | 0 | |
S9 | 0 | 50 | 50 | 0 | 0 | 0 | 0 | |
S10 | 60 | 20 | 0 | 20 | 0 | 0 | 0 | |
S11 | 50 | 0 | 0 | 0 | 0 | 50 | 0 | |
S12 | 29 | 57 | 14 | 0 | 0 | 0 | 0 | |
S13 | 0 | 0 | 100 | 0 | 0 | 0 | 0 | |
S14 | 50 | 50 | 0 | 0 | 0 | 0 | 0 | |
S15 | 75 | 0 | 25 | 0 | 0 | 0 | 0 | |
S16 | 100 | 0 | 0 | 0 | 0 | 0 | 0 |
Type | Study area | Microplastic abundance/(n/L) |
Surface water | Jinjiang River, China | 0.5–4 (this study) |
Shuangtaizi River of Liaoning, China | 1.33±0.67–7.33±3.93 (Li JN et al., 2021) | |
Daliao River of Liaoning, China | 3.00±1.15–11.00±3.51 (Li JN et al., 2021) | |
Manas River, Xinjiang, China | 24±4–48±9 (Wang GL, 2020) | |
Yangtze estuary, China | 0.24–1.35 (Luo W, 2019) | |
Qinghai-Tibet Plateau, China | 0.247–2.686 (Liu RP et al., 2021a) | |
Yellow River, China | 5.358–654 (Liu RP et al., 2021b) | |
Ciwalengke River, Indonesia | 5.85±3.28 (Alam FC et al., 2019) | |
Itchen River, Britain | 1.15 (Gallagher A et al., 2015) | |
Hudson River, USA | 0.98 (Miller RZ et al., 2017) | |
San Gabriel River, USA | 0.41 (Moore CJ et al., 2011) | |
Groundwater | Jinjiang River, China | 0.25–5.25 (this study) |
Shallow aquifer, Bacchus Marsh, Australia | 16–97 (Samandra S et al., 2022) | |
Karst aquifer of Illinois, USA | 0.86–15.2 (Panno SV et al., 2019) | |
Northern Germany | 0–7 (Mintenig SM et al., 2019) | |
Coastal areas of southern India | 0–4.3 (Selvam S et al., 2021) | |
Southeast coast of the Bay of Bengal | 2–80 (Ramakrishnan R et al., 2021) | |
Sediment | Jinjiang River, China | 20–70 (this study) |
Liaohe river, China | (20.00±34.64)–(193.33±172.43) (Han LH et al., 2020) | |
Yangtze River estuary, China | 20–340 (Peng G et al., 2017b) | |
Yellow River, China | 43.57-615 (Liu RP et al., 2021b) | |
Urban freshwater rivers, Shanghai, China | 53–723 (Peng G et al., 2017a) | |
Wei River, China | 360–1320 (Ding L et al., 2019) | |
Rhine River, Germany | 228–3763 (Klein S et al., 2015) | |
Atoac River in Puebla, Mexico | (833.33±80.79)–(1633.34±202.56) (Shruti VC et al., 2019) |
Microplastic component | Agriculture-forestry-fisheries | Domestic wastewater | Industrial production |
PE | 0.964 | 0.085 | 0.016 |
PP | 0.938 | 0.213 | −0.107 |
PVC | −0.156 | 0.644 | 0.312 |
PET | 0.008 | 0.715 | 0.300 |
PA6 | 0.169 | 0.464 | 0.364 |
PS | −0.164 | 0.657 | 0.191 |
POM | −0.116 | −0.091 | 0.867 |
Contribution rate/% | 27.180 | 23.340 | 15.985 |
Accumulative contribution/% | 27.180 | 50.520 | 66.505 |
Location of the Jinjiang River Basin and the sampling sites
Microplastics abundance in surface water (a), groundwater (b) and sediment (c) of Jinjiang River Basin.
Comparison of microplastics composition (a), particle sizes (b) and abundance in surface water, groundwater and sediment of Jinjiang River Basin.