1 Introduction

Plastic materials are widely employed in our daily lives, provide convenience while simultaneously accumulating in the environment (Mohamed Nor and Obbard, 2014). These plastic wastes disintegrate into small plastic particles, ultimately forming microplastics, which are defined as plastics with sizes ≤ 5 mm (Thompson et al., 2004). Microplastics are categorized into primary and secondary types. Primary microplastics are particles initially produced with sizes < 5 mm for use in cosmetics, pharmaceutical carriers, cleaning products, resin pellets, and industrial sandblasting (Napper and Thompson, 2016; Horton et al., 2017b). Secondary microplastics originate from the fragmentation of large plastics due to constant abrasion, biodegradation and weathering (Duis and Coors, 2016). Additional sources of microplastics include textile laundering facilities and sandblasting operations (Browne et al., 2011).

Microplastics, due to their small size, hydrophobicity, and larger surface area-to-volume ratio, have the ability to absorb environmental pollutants like organic pollutants and metals (Abbasi et al., 2020, 2021; Zhou et al., 2020; ). Despite being different type of contaminants, microplastics and heavy metals can have synergistic effects. Dobaradaran et al. (2018) found that Al, Mn, Ni, Fe, Pb, Cd, Cu, and Cr adsorbed on the surface of plastic particles collected from coastline sediment. In soil agroecosystems, plastic mulches, which eventually break down into microplastics, may increase Cd toxicity by enhancing its mobility (Zhang et al., 2020). The physical and chemical properties of microplastics affect their adsorption of heavy metals. The adsorption ability of the same microplastics for different heavy metals also varies. Fred-Ahmadu et al. (2022) found that foam plastic (PS (polystyrene), PUR (polyurethane), PEVA (polyethylene vinyl acetate)) associated more metals than hard plastic (PE (polyethylene), PP (polypropylene), PET (polyethylene terephthalate)) samples. Aged microplastics had relatively high adsorption capacities for heavy metals compared with virgin microplastics (Holmes et al., 2012; Gao et al., 2021). Li et al. (2023) reported that the adsorption capacity of PE, PET, and PA6 (polyamide6) microplastics to Pb was stronger than that to Cd under the same condition. The order of adsorption capacity for the same metal ion was PE > PET > PA6. The growth of biofilms on micro-plastic surfaces can enhance the accumulation of heavy metals (Tien and Chen, 2013; Rochman et al., 2014). Smaller-sized microplastics can be more ecotoxic than their large counterparts due to their higher surface area to volume ratio, providing more space for metal adsorption, and, therefore, have a greater capacity to adsorb heavy metals (Wang et al., 2019a; Wang et al., 2019b). A field experiment revealed strong correlations between the adsorbability of PP and polyvinyl chloride (PVC) microplastics for Pb and Mn and the concentration of these metals in seawater (Gao et al., 2020). The level of heavy metals accumulated on microplastic surfaces directly relates to the concentration of heavy metals in the surrounding environment. Akhbarizadeh et al. (2018) identified a positive correlation between the contents of heavy metals in microplastics and in coastal sediments. However, the concentrations of Cr, Ni, Cu, Zn, Pb, As, and Cd adsorbed in microplastics were not correlated with their contents in sediments, with the exception of Hg (Deng et al., 2020).

The current understanding of microplastics and heavy metals pollution largely focused on marine environments. However, the knowledge gaps concerning their interaction in terrestrial water environments remain significant. Given that terrestrial rivers sediments serve as temporary or permanent repositories for microplastics and heavy metals (via mechanisms such as sorption, co-precipitation, and density differences) and can also act as secondary pollutants sources in aquatic ecosystems (Dang et al., 2015; Schintu et al., 2015; Alomar et al., 2016), they play a crucial role in transferring microplastics and heavy metals from inland water to marine environments (Zhang et al., 2019). It is estimated that rivers transport 70% – 80% of plastics that ultimately reach the oceans, with primary inputs from mishandled debris either during manufacturing and usage, agriculture and land waste, and wastewater treatment plant effluents (Alimi et al., 2018).

Therefore, it is urgent to develop monitoring programs for heavy metals in microplastics in terrestrial water environments. The objectives of the this study are to investigate the spatial distribution and abundance of microplastics, the contents of heavy metals in microplastics and river sediments, and explore the interaction between microplastics and heavy metals.

2 Materials and Methods 2.1 Study Area

Surface sediment samples were collected from seven sites across various urban rivers within Zhengzhou City (shown in Fig. 1). Zhengzhou, characterized by a dense population, is a typical inland city adjacent to the Yellow River. The microplastics and heavy metals investigated in this study are presumed to primarily originate from industrial and domestic wastewater, aquaculture activities, and other urban activities.

2.2 Sampling Methods

In June 2020, sediment samples were collected in triplicate from the center of the river at a sediment depth of 0 – 3 cm using a stainless-steel grab sampler. At each site, the three sediment samples were combined and stored in an aluminum foil bag as a single sample. All collected sediment samples were transported to the laboratory in insulated ice-boxes and stored at −20℃ until further analysis was conducted.

2.3 Microplastics Extraction and Identification

Microplastics were extracted from each sediment replicate utilizing the density separation method, as detailed by Thompson et al. (2004). To briefly summarize the process, wet sediment samples were first oven-dried at 60℃ until a constant weight was achieved over a span of 48 – 72 h. The dried sediment samples were then sieved through 5 mm stainless steel sieves to eliminate impurities. From each sediment sample, 50 g (dried weight) was randomly selected and weighed into a pre-cleaned glass beaker – this process was repeated in triplicate. The flotation of microplastics were carried out in a saturated NaCl solution. Each sample was covered with watch glass, stirred for 30 min on a magnetic mixer, and then allowed to stabilize for 24 h to enable density separation. The supernatant was carefully collected and the floatation procedure was repeated with a second floatation using a ZnCl₂ solution (1.5 g cm⁻³). Subsequently, the supernatant liquid was vacuum filtered using GF/C filters with a pore size of 0.45 μm. The fractions collected were then digested with 2 mL of hydrogen peroxide (30%, GR) and nitric acid (65%–68%, GR) in a 1:2 ratio at 60℃. Following digestion, the samples were once again floated in a ZnCl₂ solution. Microplastics were subsequently separated from organic debris and filtered onto nitrocellulose filters. Post filtration, all membranes were allowed to dry at room temperature. These filters were then examined and photographed using a stereoscopic microscope (SZX7, Olympus, Japan). Characteristics of particles, such as shape, size, and color, were recorded and analyzed using a high-resolution camera unit connected to computer software and Nano Measurer software. To chemically characterize the representative samples of microplastics, Microscopy Fourier Transform Infrared (μ-FTIR) spectroscopic analysis was performed using a NICOLET In10 MX equipped with a built-in ATR module. To avoid airborne contamination of microplastics, a glass Petri dish was placed in the laboratory cabinet as a control prior to commencing the experiment. Additionally, while performing laboratory work, lab coats made of 100% cotton were worn.

2.4 Heavy Metal Analysis

Microplastics of size 1 – 5 mm were collected for the analysis of heavy metals. Approximately 0.1 – 0.5 g of microplastic samples were collected from each site and weighed into glass tube. These samples were subsequently digested with a solution comprising 5 mL of hydrogen peroxide and 5 mL of nitric acid in a microwave digestion vessel for 45 min. The digested samples were analyzed for heavy metals – Cr, Cu, Ni, Pb, Cd, As, and Zn – using collision-inductively coupled plasma-mass spectrometry (ICP-MS, Agilent 7700x Series, USA).

Meanwhile, heavy metals in the sediment were assessed by analyzing sediment samples in triplicate using acid digestion, as described by Duodu et al. (2015). For quality assurance and quality control, standard reference materials for sediment (GBW07304) were also analyzed. The relative standard deviation (RSD) was found to be less than 5%, and the recovery rate of seven heavy metals ranged between 95% and 105%.

2.5 Data Analysis

Statistical analyses were conducted utilizing SPSS 22.0. All original figures were crafted with Origin 2018. Correlation analysis and principal component analysis (PCA) were employed to estimate the sources of heavy metal contamination in the sediments.

2.6 Sediments Quality Assessment

To assess the risk of heavy metals contamination, the potential ecological risk index (RI) was used. The values were calculated based on the formulas presented in Table 1.

3 Results and Discussion 3.1 Microplastics Abundance

The abundance of microplastics ranged from (2412 ± 187.5) to (7638 ± 1312) items kg⁻¹ dry sediment (Fig. 2), and the average abundance of microplastics in sediments of the studied urban rivers was (4388 ± 713) items kg⁻¹ dry sediment. Analysing the findings further, the researchers noted a hierarchical sequence of microplastic abundance across the various river stations. The Dongfeng River was found to be the most heavily polluted, followed by the Chao River, Jialu River, Shibali River, Suoxu River, Xionger River, and finally the Qili River. Interestingly, the distribution of microplastics pollution among the rivers was not in accordance with the expected trend of high pollution in downtown and low pollution in suburban locales. This anomaly could be attributed to the regular dredging practices implemented in the downtown river. For instance, dredging projects were carried in 2016, 2018, and 2020 on sections of the Xionger River, Jinshui River, Dongfeng River, Shibali River, Qili River, and Suoxu River, respectively. The high microplastic abundance seen at Dongfeng River could be a result of its close proximity to residential and scenic areas in the city's downtown. These regions frequently see large deposits of meso- and macro-plastics, which include a range of waste items such as food packaging, mineral water bottles, buoys, plastic bags, and various types of colored plastic packaging. The collected data suggests a notable correlation between the density of the human population and the number of microplastic debris. Currently, many studies worldwide have investigated the distribution of microplastics in rivers. Comparing the results of this study with those of other terrestrial river studies (as detailed in Table 2), it becomes evident that the urban rivers in the studied areas are experiencing a higher-than-average level of microplastic pollution relative to other locations globally.

3.2 Size, Morphology, Polymer Type, and Color Distribution

The distribution of microplastics according to size for the studied areas is shown in Fig. 3a. The majority of microplastics were found to be of a diameter between 0.038 – 1 mm. This particular size category accounted for over 90% of the total abundance in both the Chaohe River and Suoxu River. Meanwhile, over 80% of microplastics found in the Dongfeng River, Jialu River and Qili River also fell into this size range, with a slightly lower percentage of 78.4% in the Shibali River. Notably, the proportion of small-size microplastic (≤ 0.5 mm) was exceptionally high in sediments of the Chaohe River, Suoxu River and Jialu River. It was hypothesized that agricultural activities, specifically the usage plastic film mulching and application of sewage sludge in the surrounding farmlands, are significant sources of these tiny plastic particles (Zhang and Liu, 2018). In contrast, the Dongfeng River, Shibali River and Xionger River, which are heavily populated regions, microplastic pollution mainly originated from activities of industry, tourism, commerce, and domestic sewage. These results are consistent with the previous researches that most microplastics are typically found in smaller size fractions (Su et al., 2016; Peng et al., 2017). The ecological impact of these smaller microplastics is potentially greater (Lu et al., 2018) due to their higher surface area-to-volume ratio. This trait allows them to provides more space for POPs and heavy metals to adsorb (Bakir et al., 2014; Wang et al., 2019a; Wang et al., 2019b), resulting in a higher pollution concentration than larger microplastic particles.

The morphology distributions of microplastics in sediment samples are presented in Fig. 3b. The most prevalent form of microplastic was fragments. This was particularly the case in the Xionger River, Shibali River, Dongfeng River, and Chao River, where fragments accounted for 72.1%, 63.8%, 46.6%, and 44.2% of microplastics, respectively. In contrast, the Jialu River and Qili River show an abundance of fibers with 37.2% and 38.3%, respectively. Suoxu River shows an abundance of the film with 42.3%. Among all found microplastics, fragmented microplastics were the most common, followed by fibers, with membrane and spherical microplastics only accounting for a smaller proportion. These fragments are likely from larger plastic items that have degraded due to mechanical stress and UV radiation (Horton et al., 2017a; Salvador Cesa et al., 2017). Comparable findings have been reported in other stduies, such as those conducted in the sediment of Chao Phraya River in Tha Pra Chan area, Thailand (Ta and Babel, 2020), and the tributaries of the River Thames, UK, where fragment microplastics accounted for 91% of sedimentsamples (Horton et al., 2017a).

The study provides a detailed visual representation of different kinds of microplastics collected from the studied areas in Fig. 3c. The primary polymer types identified within these microplastics were PP, PE and PET. Most notably, PP was the dominant composition in the majority of fragment microplastics gathered in this study. Fibershaped microplastics, which primarily originated from textile materials, plastic woven bags, and fishing nets, were predominantly composed of PE, PP and their copolymers. Films, another form of microplastic, are likely derived from plastic bags, packaging materials, and plastic film mulching (Ta and Babel, 2020). In this study, these film microplastics were also primarily composed of PP. Pellets, too, were discovered in all the studied areas. These microplastics were found to have smooth surfaces with predominantly clear or semi-opaque colors. PE or PP were the primary polymer types detected within these pellet microplastics. This finding aligns with previous research conducted on plastic microbeads in the coastal waters of Hong Kong, where the dominant microbeads were transparent and composed of PE/PP (So et al., 2018). The study suggests that cosmetics and personal care products are the major source of pellet microplastics.

The distribution of microplastics according to their colors is illustrated in Fig. 3d. Transparent microplastics were the most prevalent, accounting for 40.02% of the total microplastics discovered. This was closely followed by white (28.39%) and yellow (20.25%) microplastics. Conversely, blue, red and black microplastics accounted for significantly smaller fractions at 8.64%, 1.79% and 0.91% respectively. This observation aligns with a finding by Dobaradaran et al. (2018), which reported that white and colourless microplastics constituted the majority of microplastics in coastline sediment along the Persian Gulf. Generally, plastics are produced in transparent and white base colors, with chromatic colors being exclusive to specific products. The color of microplastics is inherited from the original plastic products which they originate. Over time, the colors of plastics can fade due to aging, and transparent and white plastics may turn yellow or grey due to surface physico-chemical precipitation (Ashton et al., 2010).

3.3 Heavy Metal in Sediments

The heavy metal concentrations of the sediment samples are shown in Table 3. The background value is the geochemical background value of the surface soil in the Henan section of the Yellow River. It was discovered that the average concentrations of certain heavy metals (Cu, Cd, Cr, Pb, and Zn) exceeded their corresponding background values. Specifically, 28.6% of the tested points revealed elevated concentrations of Cu and Cr, 71.4% for Cd and Zn, and Pb was found to be in excess in all tested points. However, the average concentrations of Ni and As fell within their background values. The spatial distribution of these heavy metals shows that along the Dongfeng River, a location characterized by high human activities, exhibited relatively high concentrations of heavy metals. In contrast, stations along the suburban Jialu River presented lower heavy metals concentration. Furthermore, Xionger River, Chaohe River, Qili River, Shibali River and Suoxu River were all found to be polluted to varying extents. Compared with reported values from other world regions (Table 3), the concentrations of heavy metals discovered in this study are comparable with those found in East and West Lake of Wuhan, China. However, they were lower than those in the Pearl River Estuary and rivers in urbanization area of South China, as well as rivers in the main city zone of Chongqing, China. This may be attributed to the high populations and associated increase in human activities, such as industrial and municipal wastewater discharge, in these large modern cities, along with non-ferrous mining and smelting activities in Chongqing.

The study further utilized the Potential Ecological Risk Index (RI), a widely accepted measure used to assess the degree of potential ecological risks of heavy metals in sediment. The RI values, calculated according to proposed equation by Hakanson (1980) (Table 1), are shown in Fig. 4. The potential ecological risks were found to be in the order of Cd > Pb > Cu > As > Ni > Zn > Cr. Spatially, the RI distribution followed the order of Dongfeng River > Chao River > Xionger River > Shibali River > Qili River > Qialu River > Suoxu River. The E_rⁱ values of Cd in the sediments ranged from 26.3 to 149, suggesting a very broad range of risk from low to considerable. The E_rⁱ and RI values of Pb, Cu, As, Ni, Zn, and Cr were mostly < 40 and < 150 (except for Dongfeng River), indicating low ecological risks for these heavy metals in the studied urban rivers. However, the E_rⁱ and RI values of Cd and of Dongfeng River were recorded at 149 and 187, respectively, pointing to moderate contamination with considerable risk posed by Cd. Cd has also been identified as a significantly ecological risk in the the Shuangtaizi Estuary (Li et al., 2015), underlining the need to pay close attention to its presence in the sediments of the studied areas.

The relationship between heavy metals and microplastic pollution in the sediments was investigated. The spatial distribution of heavy metals was consistent with the distribution of microplastics, with areas of high human activitiy showing more pollution. A significant linear correlation between the heavy metals' RI and the abundance of microplastics in sediments was observed (R² = 0.7296, Pearson's r = 0.854, p < 0.05) (Fig. 5). Similar findings have also been reported in the sediments of Lagoon of Venice, Italy (Vianello et al., 2013) and Iran's main oil terminal (Akhbarizadeh et al., 2017). The strong positive correlation suggests that these pollutants may share the same anthropogenic sources.

3.4 Source Identification

Table 4 provides the Pearson correlation coefficients between the concentrations of heavy metals found in urban river sediments. A very significant positive correlations (p < 0.01) was found between Ni and As, Cu, Cd, Cr, and Pb to Zn, Cr and Pb to Cd, and a significant positive correlations (p < 0.05) was found between Cd, Cr, and Pb to Cu; Pb and As to Cr. This suggests that these main contaminants largely originated from common sources. Similar correlation patterns were observed in a study that found strong positive correlations between Cu, Cd, Cr, and Pb in the sediments of the Tiaozi River, a typical tributary of Liao River in Jilin Province (Li et al., 2018). Significant positive correlations between Zn, Cu, and Cd were also found in sediments of the Caoqiao River in the Taihu basin (Fang et al., 2012). According to the results discussed above, Cu, Cd, Cr, and Pb share similar sources. However, Ni and As did not correlate with any other heavy metals, which suggests that there might be a different source for Ni and As.

PCA has been widely used to identify relationships between heavy metals and to distinguish between natural and anthropogenic sources of heavy metals (Akhbarizadeh et al., 2017). Two principal components (noted as PC1 and PC2) were identified in this study, accounting for 94.22% of the cumulative variance with eigenvalues > 1 (Table 5). PC1, which accounted for 61.24% of the total variance, had high loading on Cu, Cd, Cr, Pb, and Zn, suggesting that these heavy metals were mainly influenced by anthropogenic activities (Xiao et al., 2021). PC2, which included Ni and As and accounted for 32.98% of the total variance. According to the results that the abundance of Ni and As in all stations were lower than the soil background values (Table 3). Thus, PC2 was little enrichment and less influenced by anthropogenic activities, indicating geogenic sources. The loading of heavy metals on PCA components was consistent with the significant correlation coefficients between heavy metals.

Moreover, the factor scores biplot of the PCA analysis (Fig. 6) demonstrates the spatial distribution of the sampling sites based on their similarity. Atations were classified into three categories. The Dongfeng River station, located in the city center with high concentrations of heavy metals, was classified separately. The Qili River, Shibali River, and Xionger River stations, which showed similar concentrations of heavy metals, were clustered into one group. Meanwhile, the suburban stations of Jialu River, Suoxu River, and Chao River were clustered into another group. The results indicate that the abundance of heavy metals was significantly correlated with human population density and industrial activity.

3.5 Relationship Between Heavy Metals in Microplastics and Sediments

The same targeted heavy metals identified in the sediments were also measured in the microplastics. Results are available in Table 6. The concentrations of heavy metals present in the analyzed microplastics were as follows: Ni: 1.47 – 5.86 mg kg⁻¹, Cu: 6.16 – 132 mg kg⁻¹, Cd: 0.08 – 0.61 mg kg⁻¹, Cr: 4.85 – 27.72 mg kg⁻¹, Pb: 3.61 – 57.40 mg kg⁻¹, Zn: 31.36 – 176.40 mg kg⁻¹, and As: 3.29 – 6.17 mg kg⁻¹, respectively. An illustrative comparison of heavy metal levels in both microplastics and sediments is shown in Fig. 7. Interestingly, the concentrations of Ni, Cu, Cd, Cr, Pb, Zn, and As that accumulated in microplastics were not dependent on their corresponding contents in sediments. Similar results were also found by Deng et al. (2020) regarding the relationship between heavy metal contents in microplastics and sediments of the Jinjiang Estuary in Fujian, China. In most stations, the concentrations of heavy metals including Ni, Cr, Zn, and Pb in the sediments were higher than those found in the microplastics (Dobaradaran et al., 2018; Deng et al., 2020). This could be attributed to the sediments' greater porosities and their densities of charged surface sites, which facilitate metal ion exchange and electrostatic attraction (Ashton et al., 2010). However, in some stations, the concentrations of Cu, Cd, and As in microplastics were higher than their contents in sediments. Examples include the concentrations of Cu in microplastics at Shibali River, Cd and As concentrations in microplastics at the Dongfeng River and Xionger River. Deng et al. (2020) also reported that the concentrations of some heavy metals (Cd and Zn) in microplastics surpassed their contents in sediments. This suggests that these heavy metals accumulated in microplastics could be both inherent and derived from the sediment environment.

Brown, red and black fragment microplastics were identified at the sites of the Shibali River, Dongfeng River and Xionger River, respectively. These locations also contained microplastics with higher concentrations of most heavy metals than those in other sites (Fig. 7). It is common for metals to be used as catalysts, colourants, additives, and stabilizers during the manufacture of plastics (Wäger et al., 2012; Fries et al., 2013; Nakashima et al., 2016). Certain studies have sought to establish a relationship between the color of plastic polymers and their metal concentrations. It was found that black pellets contained higher concentrations of metals compared to white or colored ones, mainly due to the relatively high levels of hazardous additives in black plastics, which include pigments with metal-based components (Acosta-Coley et al., 2019; Santos-Echeandía et al., 2020). It is important to note that procedures for extracting and analyzing heavy metals in microplastics did not discriminate between inherent metal additives and those adsorbed from the environment. Consequently, the results represent the sum of both sources of metals in the microplastics. The amount of heavy metals enriched in microplastics varies greatly. This variation depends not only the concentration of heavy metals in the surrounding environment (Khalid et al., 2020), but also on the physical and chemical properties of the microplastics themselves. Comparing the heavy metals in microplastics collected from urban rivers sediments with unused plastic (Wang et al., 2004; Munier and Bendell, 2018; Vedolin et al., 2018), it is observed that Cu, Cd, and Pb concentrations in microplastics collected from certain sites exceeded those in the original plastic debris. From the results discussed above, it can be concluded that microplastics could act as carriers for heavy metals, and there may be transfer of heavy metals between sediments and microplastics. This phenomenon poses an increased risk to organisms that inadvertently consume these microplastics, underscoring the need for more comprehensive research and targeted mitigation strategies in these areas.

4 Conclusions

The average abundance of microplastics in the sediments of the studied urban rivers was (4388 ± 713) items kg⁻¹ dry sediment. When compared with reported microplastic abundance from various other regions globally, it becomes evident that the urban river sediments in the studied areas suffer from a higher than average microplastic pollution. A deeper examination of the collected microplastics revealed that fragments and fibers were the dominant shapes, followed by film and pellet. In terms of color, the majority of microplastics were predominantly transparent and white, and most microplastics were less than 1 mm in size.

The E_rⁱ and RI values for Pb, Cu, As, Ni, Zn, and Cr were found to be less than 40 and 150 (except for the Dongfeng River), respectively. This suggests that these heavy metals posed a relatively low ecological risk in most of the studied urban rivers. Conversely, the Dongfeng River station, with frequent human activities, was moderately contaminated with Cd and possessed a considerable risk. Cd was identified as the main potential ecological risk factor in the sediments of the studied areas.

A relatively good significant linear relationship was found between the potential ecological risk index of heavy metals and the abundance of microplastics. This suggests common anthropogenic sources for these pollutants. The Pearson correlation and PCA analysis results revealed that anthropogenic activities (such as industrial operations, emissions from traffic, urban and agricultural wastewaters) as well as geogenic sources (like sediments pedogenesis) were primary sources of sediment contamination in the studied region.

The concentrations of heavy metals accumulated in the microplastics did not depend on their corresponding contents in sediments. The concentrations of Cu, Cd, and As in the microplastics were higher than those in the sediments. This discovery confirmed the significant role of microplastics as potential carrier of heavy metals. Heavy metals might be transferred between sediments and microplastics, possibly increasing the risks to organisms that inadvertently ingest these microplastics.

Acknowledgements

This work was supported by the Key Research and Development Program (Scientific and Technological Project) of Henan Province (Nos. 212102310080, 22210232 0294, and 232102231062), the Fundamental Research Funds for the Central Universities (No. 220602024), and the Major Focus Project of Henan Academy of Sciences (No. 220102002).