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Article

Occurrence and Removal Efficiency of Microplastics in Four Drinking Water Treatment Plants in Zhengzhou, China

by
Yang Li
1,*,
Yinghui Meng
1,
Liwen Qin
1,
Minghui Shen
1,
Tongtong Qin
1,
Xudong Chen
1,
Beibei Chai
2,
Yue Liu
1,
Yanyan Dou
1 and
Xuejun Duan
1
1
School of Energy and Environment, Zhongyuan University of Technology, Zhengzhou 450007, China
2
Innovation Center for Intelligent Regulation & Comprehensive Management of Water Resources, College of Water Resources and Hydropower, Hebei University of Engineering, Handan 056038, China
*
Author to whom correspondence should be addressed.
Water 2024, 16(1), 131; https://doi.org/10.3390/w16010131
Submission received: 1 November 2023 / Revised: 21 December 2023 / Accepted: 27 December 2023 / Published: 29 December 2023
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Abstract

:
As an emerging contaminant, the presence of microplastics is widespread in the environment. However, current research regarding the removal of microplastics by drinking water treatment plants (DWTPs) remains insufficient. This study aims to investigate microplastics in water and sludge in four DWTPs in Zhengzhou; these DWTPs have different water sources. The results revealed that the abundance of microplastics in raw water ranged from 12.80 ± 0.80 to 25.07 ± 1.67 n/L. Overall, fibers and fragments ranging from 10 to 100 μm constituted the primary components. The proportion of white and transparent microplastics was the highest. Among the ten polymer types detected, polyvinyl chloride, polyphenylene oxide, and polyethylene terephthalate were the predominant ones in raw water; polyethylene terephthalate emerged as the prevalent polymer type in treated drinking water, with both polyethylene terephthalate and polyvinyl chloride being primarily present in sludge. The removal rate of microplastics ranged from 45.8% to 74.5%. Furthermore, the removal rates at the sedimentation tank outlet accounted for more than 50.0% of the total removal rate. The abundance of microplastics in sludge was significantly higher than that in water, indicating a concentrated environment for the persistence of microplastics. The proper disposal of sludge has emerged as one of the challenges requiring our attention.

1. Introduction

In recent years, the ecological and environmental pollution caused by microplastics (MPs) has garnered increasing attention from researchers worldwide [1,2,3]. The term MPs typically refers to plastic solids with a size smaller than 5 mm [4], which are extensively detected in oceans, freshwater, soil, air, and even the human body [5,6,7,8]. Over an extended duration, the investigation of MPs in marine environments has been a primary research focus [9,10], while the study of MPs in freshwater remains relatively inadequate. The significance of freshwater in relation to human livelihoods should not be overlooked, and it is imperative to gain a comprehensive understanding of the magnitude of MPs within it. Although the pollution and ecotoxicology issues associated with MPs have not been extensively investigated, the available evidence shows their potential impacts on human health [11,12] and other organisms [13]. Meanwhile, the exposure of MPs to environmental media, such as water, can lead to the adsorption of organic matter and heavy metals on their surfaces, resulting in aggregation effects [14,15]. Furthermore, the findings of Yu et al. suggest that MPs may serve as a conducive environment for specific pathogens subsequent to their absorption of antibiotics in the aquatic system [16]. The transportation of a substantial number of MPs via water may facilitate the dissemination of pathogenic bacteria and genes associated with antibiotic resistance in the surrounding environment [17]. MPs are widely prevalent in aquatic environments and encompass various polymer types, such as polyethylene, polypropylene, polystyrene, polyvinyl chloride, and so on [18]. The range of abundance exhibits significant variation, which may be attributed to the absence of standardized protocols for sampling, pretreatment, and detection methods. For example, the abundance of MPs ranges between 1.77 and 14.33 n/L in Chishui River in China [19]. In Vembanad Lake in India, however, the abundance value was between 26.79 ± 3.74 and 52.70 ± 5.43 n/L [20]. In order to establish a research consensus on MPs in the aquatic environment, it is imperative to conduct further investigations into the extent of MP pollution and its impacts and to emphasize the need for enhanced research efforts in this field.
Wastewater treatment plants (WWTPs) and drinking water treatment plants (DWTPs) serve as key points in the intricate cycle of water exchange between human society and nature. Previous studies have demonstrated that WWTPs exhibit a certain level of efficacy in the removal of MPs; however, a significant quantity of MPs still persists in the outlet discharged into freshwater, such as rivers and lakes [21,22,23]. Simultaneously, the provision of potable water that adheres to usage standards is imperative for human productivity and sustenance, with freshwater serving as the primary source. In this regard, DWTPs play a pivotal role in purifying raw water to ensure its quality. However, the current outlet standard of DWTPs does not yet have an established limit for MPs [24], and it is noteworthy that MPs exhibit distinct differences in terms of density, size, and morphology when compared to sediment particles and algae, despite the fact that they are all solid substances present in freshwater environments. Therefore, researchers are currently directing their attention towards DWTPs as a pivotal barrier for the removal of MPs, aiming to effectively address the public’s water supply demands [25]. The research conducted on the Indira Gandhi Water Treatment Plant in India indicates that pulse clarification and sand filtration are crucial steps for effectively removing MPs, with a removal efficiency of up to 80.0% [26]. A study conducted a comparison between DWTP Milence and DWTP Plzeň in the Czech Republic and revealed that DWTP Plzeň, which employs more complex treatment processes (coagulation/flocculation, sedimentation, sand filtration, and granular activated carbon filtration), exhibited a higher removal rate of 88.0% for MPs. In contrast, DWTP Milence, which relies solely on simple treatment processes (flocculation and sand filtration), achieved a lower removal rate of only 40.0% for MPs [27]. The research conducted by Jung et al. demonstrated that pre-ozonation combined with sedimentation can achieve a removal rate of 70.0–80.0%, with a relatively good removal efficiency for PP and PE [28]. However, the limited research data on the efficiency of MP removal in DWTPs hamper our understanding of the background levels of MPs in water supply systems and the risk assessment of MPs in relation to drinking water safety, and further related studies should be carried out to tackle this challenge in the future.
In this investigation, four urban DWTPs in Zhengzhou city were selected as the research objects, based on their diverse water sources and treatment processes. The abundance, size, morphology, color, and polymer type of the MPs were quantified in raw water, sedimentation tank outlet, treated drinking water, and sludge. Our research findings can contribute to the existing knowledge on the occurrence and presence of MPs in DWTPs and thereby facilitate a preliminary discussion on the efficacy of different treatment processes for the removal of MPs. This provides essential initial support for future investigations into the removal mechanisms of MPs by various treatment units.

2. Materials and Methods

2.1. Sample Collection

Four urban DWTPs in different locations in Zhengzhou were selected as the research object (Table 1). For confidentiality reasons, the DWTPs were not named and were referred to as DWTP-A, DWTP-B, DWTP-C, and DWTP-D. The sampling points for the water samples were strategically designated at the intake, sedimentation tank outlet, and DWTP outlet (Figure 1). However, since DWTP-C only had a liquid chlorine disinfection tank, raw water and treated drinking water were collected for detection. The water sample, comprising 2.5 L, was collected using a stainless steel bucket and subsequently stored in a glass bottle [29]. To ensure the scientific rigor of the study, three sets of water samples were obtained from each sampling point to conduct parallel experiments. The sludge (500 g) from each DWTP, excluding DWTP-C, was encapsulated in aluminum foil bags to facilitate the detection of MPs. Subsequently, all the samples were promptly transported back to the laboratory for further experimentation.

2.2. Sample Pretreatment

In this study, the methods used to pretreat the water and sludge samples were those employed in previous research, and some steps were optimized and adjusted according to the different conditions of the samples [29,30]. Because the target water samples in this study were raw water and treated drinking water, which exhibits relatively good water quality, only 30% H2O2 was added during the digestion process to form Fenton’s reagent, without the addition of Fe(II). The main difference was that this study did not use Fenton’s reagent in the reference for the process of sample digestion. First, for the water samples, 2.5 L of water was slowly passed through a stainless steel wire sieve with a pore size of 10 μm; then, the retained materials on the sieve were rinsed with ultrapure water (50 mL) into a 200 mL glass beaker; 50 mL of 30% H2O2 was added; then, it was placed in a water bath at 50 °C for 6 h for the digestion of the organic matter. Second, excess sodium chloride was added to the glass beaker to form a supersaturated solution, which then stood for 12 h for density separation. Third, the supernatant was pumped through the vacuum filter by a glass fiber filter membrane with a pore size of 0.45 μm, and the filtered membrane was stored in glass culture dishes. Three parallel experiments were conducted on the water samples at each sampling point.
First, for the sludge samples, 30 g of sludge sample was put into a beaker (1 L) and 600 mL of saturated sodium chloride solution was added simultaneously. The solution was thoroughly mixed by stirring it at a speed of 200 r/min with a magnetic stirrer for a duration of 30 min. Then, the beaker was placed in an ultrasonic water bath for 20 min to further separate MPs from the sludge. Second, the supernatant in the beaker was passed through a stainless steel wire sieve with a pore size of 10 μm after standing for 12 h. Third, the retained materials on the sieve were rinsed with ultrapure water (50 mL) into a 500 mL glass beaker. In order to ensure the extraction effect of the MPs in the sludge samples, the first, second, and third steps were repeated three times for one sludge sample. One hundred and fifty milliliters of 30% H2O2 was added to the glass beaker; then, it was placed in a water bath at 50 °C for 12 h for digestion. Finally, the vacuum filter was used to filter the supernatant with a glass fiber filter membrane with a pore size of 0.45 μm, and the filtered membranes were stored in glass culture dishes. Three parallel experiments were conducted on the sludge samples for every DWTP. In addition, 200 g of sludge samples was used to measure the moisture content in each DWTP by oven drying at 105 °C for 12 h.

2.3. Detection of MPs

First, the membranes after filtration were placed on the stage of a digital optical microscope (Motic BA310Digital, Motic Industrial Group Ltd., Xiamen, China) connected to computer by a camera; image acquisition software (Motic Images Plus 3.0 ML, Motic Industrial Group Ltd., Xiamen, China) was used to collect the suspected substance on the membranes. The amount, size, morphology, and color of the suspected substance were recorded, and photos were taken. The location of the suspected substance could be determined due to the used membranes marked with grids. Second, the polymer types of the MPs were detected using a confocal Raman microscopy spectrometer (gora-Lite, Ideaoptics Co., Ltd., Shanghai, China). The experimental parameters of this spectrometer were set to a wavenumber range of 60–3500/cm, with a resolution of less than 5/cm and a laser excitation wavelength of 785 nm. For the water samples, the suspected substances on the membranes were detected one by one, and the results were analyzed with the corresponding software (gora. Dawn v1.0). However, due to the excessive presence of suspected substances in the sludge samples, a random selection of some particles from each membrane was made for the detection [31]. In order to enhance the accuracy of the detection, we employed a random selection method to choose 80 particles from each membrane, aiming for maximum diversity in terms of sizes, shapes, and colors. This approach ensures more robust and scientifically sound experimental outcomes. The measured spectrum was considered to be the same as a standard spectrum only when the spectral similarity was greater than 70.0% [32]. After detection, the substances ultimately identified as MPs were counted, and the results were further analyzed. The electron microscope images of MPs can be seen in Figure S1.

2.4. Quality Control

The glass bottles and aluminum foil bags for storing water samples and sludge samples were thoroughly cleaned with ultrapure water and subsequently dried in an oven before the sampling process. In the course of the laboratory experiments, the operator donned a cotton lab coat and utilized disposable nitrile gloves. All laboratory vessels used in the experiment were washed with ultrapure water and dried by the oven. To prevent contamination from external sources, various items were wrapped in aluminum foil between each step of the experimental operation. Additionally, all the laboratory operations, such as digestion, extraction, and filtration, were conducted within a fume hood. Simultaneously, three blank experiments were conducted on the ultrapure water utilized in the laboratory, with each experiment employing 2 L of ultrapure water. The findings revealed the detection of only two MPs in the whole 6 L of ultrapure water, suggesting that the contamination in ultrapure water may be considered negligible.

2.5. Data Analysis

In this study, Microsoft Office 2010 software was utilized for data collation and calculation, while SPSS Statistics 24 software was employed to conduct a one-way analysis of variance (ANOVA). The abundance values of the MPs obtained from the three parallel experiments at each sampling point were grouped together to examine the significance of the differences between the four DWTPs.

3. Results and Discussion

3.1. Abundance of the MPs

The presence of MPs was detected in the DWTP water and sludge samples, and the abundance exhibits variations across the different DWTPs (Figure 2); the specific data can be found in Tables S1 and S2. The raw water exhibited an abundance ranging from 12.80 ± 0.80 to 25.07 ± 1.67 n/L, while the treated drinking water demonstrated a range of abundance from 6.40 ± 0.80 to 8.80 ± 0.80 n/L. We performed an ANOVA on the abundance of MPs for each DWTP. The results of the calculations revealed significant differences in the raw water (p = 0.00042) and treated drinking water (p = 0.041). However, no significant differences were observed in the sedimentation tank outlet (p = 0.457). The findings indicate that the abundance of MPs in the raw water in DWTP-C was the lowest among all four DWTPs; this was possibly due to its use of groundwater as the raw water. Previous studies have shown that the abundance of MPs in groundwater is lower compared to that of surface water. In the Yunlong River region of China, the maximum abundance of MPs in the groundwater is merely 4 n/L [33], while the value is 10.1 n/L in the coastal region of southern India [34]. Compared with the aforementioned surface water, the maximum abundance of MPs is 14.33 n/L in Chishui River [19] and 52.70 ± 5.43 n/L in Vembanad Lake [20]. The quality of groundwater is generally superior to that of surface water due to its greater distance from anthropogenic activities.
It is evident that DWTP-B exhibits the highest abundance with a value of 25.07 ± 1.67 n/L. The finding was that the abundance of MPs in Yellow River water, which constitutes 100% of the raw water supply for DWTP-B, surpasses that of DWTP-D provided by the Middle Route Project of S-N Water Diversion (18.67 ± 2.01 n/L). Although comprehensive sampling analyses of various water sources have not yet been conducted in this study, analogous findings can be inferred from the existing studies. According to Qian et al.’s research results, the abundance range of MPs in the surface water of the Baotou section of the Yellow River during the dry season was 432.50 ± 240.54 n/L [35]. A study of Danjiangkou Reservoir, which serves as the water source for the Middle Route Project of S–N Water Diversion, indicates that the highest abundance of MPs was only 15.02 n/L [36].
The coagulation/flocculation and sedimentation process employed by the DWTPs exhibits a discernible efficacy in the removal of MPs. In the outlet from the sedimentation tanks of DWTP-A, -B, and -C, the abundance of MPs decreased to 11.47 ± 1.85 n/L, 13.33 ± 1.67 n/L, and 11.73 ± 2.01 n/L, respectively. Combined with the abundance of MPs present in treated drinking water, it can be inferred that the filters, activated carbon adsorption tanks, and liquid chlorine disinfection tanks also played an important role in effectively removing MPs. The research conducted by Sarkar et al. demonstrates that sand filtration exhibits an MP removal efficiency of approximately 23.0% [26]. The outlet from DWTP-C, which exclusively employs a liquid chlorine disinfection tank, still exhibits a reduction in MP content. This observation suggests the potential deposition of MPs within tanks or pipelines during the flow of water.
In contrast to the water samples, the sludge samples exhibit a higher abundance of MPs. Each membrane contains numerous suspected particles, from which we randomly selected 80 particles in a membrane for detection and extrapolated the detected proportion to estimate the total quantity of MPs present on the entire membrane. This quantification, which is relative to the weight of the dried sludge sample, serves as the abundance in the sludge samples (Figure 2b). Compared to the water samples, a higher accumulation of MPs was observed in the sludge samples. In this study, DWTP-C lacks the data on sludge due to its simple process; the abundance of MPs in the sludge samples of the other three DWTPs is 11,032.84 ± 1234.77 n/kg, 10,532.92 ± 1749.86 n/kg, and 8424.81 ± 263.32 n/kg, respectively. Similarly, one-way ANOVA was conducted to assess the abundance of MPs in the sludge samples collected from each DWTP. The results revealed no statistically significant difference between the DWTPs (p = 0.9). In addition, a study conducted on a DWTP in Barcelona, Spain, showed that the sludge samples exhibited a mean abundance of 14,360 n/kg [37]. The research findings on eight DWTPs in the UK were alarming, as the abundance of MPs in the sludge reached an astonishing 86,000 n/g [38]. Consequently, the sludge generated by the DWTPs acts as a focal point for the accumulation of MPs derived from water bodies. To effectively mitigate the re-entry of these MPs into the natural environment, we must confront the challenge of appropriately treating and disposing of this sludge.

3.2. Size and Morphology of the MPs

In this study, we categorized the sizes of the MPs into five distinct ranges: 10–50 μm, 50–100 μm, 100–500 μm, 500–1000 μm, and greater than 1000 μm (Table S3) and calculated the proportion of MPs within each size range (Figure 3). The size variation between the water and sludge samples is substantial. However, MPs predominantly occurred in sizes ranging from 10 to 50 μm or sizes that were smaller than 100 μm overall. Among all the detected MPs, those ranging in size from 10 to 100 μm constituted approximately half of the total detected particles.
Regarding the raw water, the MPs ranging from 10 to 50 μm in size exhibited a predominant presence, apart from those in DWTP-B. Notably, the MPs within this size range in DWTP-C constituted 47.9% of the total, accounting for nearly half. This phenomenon appeared to be correlated with the variations in the water sources; according to a review article by Ren et al., it was believed that MPs with smaller sizes were more prone to migration in groundwater [39]. Currently, there is a dearth of research on the presence of MPs in the Zhengzhou section of the Yellow River. However, given that a small fraction of Zhengzhou’s water source still originates from the Yellow River, it is imperative to give special attention to this issue in future research endeavors. A significant decrease in the proportion of larger MPs (>1000 μm) was observed at the sedimentation tank outlet and in the treated drinking water. Furthermore, no MP particles exceeding 1000 μm in size were detected in DWTP-A, -B, or -C, and only one MP particle larger than 1000 μm was detected in all the treated drinking water samples collected from DWTP-D. The movement of larger-sized MP particles in water exhibits similar characteristics to that of sediment particles, thereby facilitating their effective removal by conventional water treatment processes.
With the exception of DWTP-C, the proportions of MPs in the sludge samples from the remaining three DWTPs exhibit basic consistency with those observed in their respective raw water samples across all size ranges. The notable distinction lies in the discernible escalation of MPs exceeding 100 μm in size within the sludge samples. This proportion attained its pinnacle at 59.2% in DWTP-D. Moreover, the presence of MPs larger than 1000 μm in all the sludge samples provides additional evidence supporting the notion that sludge derived from DWTPs serves as a focal point for the accumulation of MPs.
The morphology categories that were distinguished included fibers, fragments, particles, and film (Figure 4 and Table S4). It is worth noting that microspheres were relatively scarce, whereas irregular granular MPs were more abundant; so, we uniformly specified them as particles. The distribution of morphology did not appear to exhibit a significant correlation with the variations in water sources; while the presence of microspheres remained limited, the abundance of primary MPs in these DWTPs was relatively low, with secondary MPs being predominantly present. The formation of secondary MPs occurs through the hydrodynamic fragmentation, weathering, and photodegradation of larger plastic waste, resulting in a diverse range of forms during their migration process. The findings of Fan et al. also indicated that secondary MPs were dominant in freshwater bodies in China [40].
Comparing these four DWTPs, it was evident that the proportion of fragments in both the water and the sludge samples from DWTP-A was consistently the highest, with values of 47.1%, 46.5%, 50.0%, and 40.7%, respectively. The proportion of fibers and fragments in the raw water of DWTP-C was equivalent, with both accounting for 33.3%. However, the percentage of fragments in the treated drinking water was higher at 42.3% compared to the fibers. And the proportion of fibers was relatively high in the case of DWTP-B and DWTP-D. Similarly, numerous studies have demonstrated that freshwater environments are predominantly characterized by the prevalence of MPs in the form of fibers and fragments [40,41,42]. However, based on the analysis of all the sludge sample data, it was evident that the MPs in fibers constituted a relatively high proportion, ranging from 38.7% to 60.8%. This observation suggests that DWTPs may be more effective at removing MPs in fibers; however, further rigorous experimentation is required to substantiate this claim.

3.3. Color and Polymer Type of the MPs

In previous studies, the parameter of color was often overlooked by researchers when investigating MPs. However, it is crucial to consider that the color of MPs significantly influences fish feeding behavior [43]. Moreover, variations in color play a pivotal role in plastic photodegradation, MP formation, and the subsequent environmental impacts [44]. Therefore, it is imperative to differentiate and quantify colors in research pertaining to MPs. The MPs detected in the water and sludge samples exhibited distinct hues, including white, transparent, blue, yellow, red, pink, and black (Figure 5 and Table S5). Reiterating the fact, white and transparent MPs remained the predominant colors that were detected in all the water and sludge samples. Furthermore, while the yellow MPs exhibited a similar frequency of occurrence, their proportion was comparatively lower than that of the preceding two colors.
In addition, it was observed that the sludge samples did not detect MPs of colors such as blue, pink, red, and black; however, these colors were present in the water samples. Several assumptions could potentially explain this disparity: firstly, it may be attributed to the dynamic nature of the water flow at the operational DWTPs where our sampling took place, which resulted in variations between sampling locations. Secondly, chemical and biological processes occur in sludge during the fading of MPs. Thirdly, the limitations associated with the current methods for extracting MPs from sludge samples could result in incomplete extraction. Nonetheless, it is important to note that our study data only provide evidence for the presence of MPs at a specific time point; therefore, future research encompassing extended timelines is necessary for more accurate quantitative analysis.
A total of 10 polymer types were identified in this study (Figure 6), including polyvinyl chloride (PVC), polyethylene terephthalate (PET), polypropylene (PP), polystyrene (PS), polymethyl methacrylate (PMMA), polyethylene (PE), polyphenylene oxide (PPO), polyamide 6 (PA6), polytetrafluoroethylene (PTFE), and polyformaldehyde (POM). The corresponding proportion can be found in Table S6. Due to the wide variety of polymers, we included the spectroscopic images detected by the instrument in the supplementary materials (Figure S1).
For DWTP-A and DWTP-B, the predominant polymer type in the raw water was PVC, constituting 23.5% and 37.2%, respectively. In the raw water of DWTP-C, PPO accounted for a significant proportion of 37.5%. Lastly, PET emerged as the primary polymer type in the raw water of DWTP-D, reaching a substantial percentage of 24.3%. A recent review study showed that the most frequent polymer types reported in groundwater were PET, PE, PVC, PA, and PS [45]. Although these substances were identified in our research, their proportions were consistently lower than those of PPO. This observation appeared to be intricately linked to the lifestyle and industrial composition of the local residents. The results obtained for the remaining three DWTPs that utilize surface water as raw water still demonstrated similarities. In fact, the diversity of the polymer types present in MPs is extensive, and our detection findings may have merely scratched the surface. The migration and the distribution of MPs in the natural environment are influenced by multiple factors, and our understanding of their mechanisms remains limited.

3.4. MP Removal Efficiency

Currently, there is no universally established specific threshold for MPs as an emerging contaminant in drinking water worldwide. Nevertheless, given their potential safety risks, the presence of MPs in drinking water remains a significant concern among consumers [46,47]. Therefore, this study can be useful as a raw quantification of the efficacy of the removal of MPs in various DWTPs (Table 2). The removal rate was separately determined at the sedimentation tank outlet and in the treated drinking water. The calculation method involved subtracting the mean abundance of MPs at each respective location from that in the raw water and then expressing it as a percentage relative to the mean abundance of MPs in the raw water. Hence, because DWTP-C relies solely on a liquid chlorine disinfection tank, its removal efficiency was comparatively lower than that of the other three DWTPs and was only 45.8%. The same scenario was observed in DWTP Milence, which is equipped with a simplistic process; it exhibited a removal efficiency of merely approximately 40.0% [27]. This may be due to the natural sedimentation of MPs as they flow with water in DWTP-C or to the limitations in our current sample processing methods, which still require improvement for enhanced accuracy. It is noteworthy that this value demonstrates a commendable performance when compared with the removal rates of the three other DWTPs.
The removal rates for the remaining three DWTPs ranged from 37.1% to 49.4% for the sedimentation tank outlet and from 52.9% to 74.5% for the treated drinking water. It was clear that the removal rate at the sedimentation tank outlet accounted for more than 50.0% of the total removal rate. Therefore, considering the inherent characteristics of MPs as solid particles, the significance of the sedimentation tank in DWTPs cannot be disregarded. A study conducted by Wang et al. on a DWTP with a water supply scale of 1.2 million m3/d demonstrated that the implementation of coagulation and sedimentation resulted in the removal of 40.5–54.5% of the total MPs [48]. The laboratory simulation conducted by Li et al. revealed that the coagulation and sedimentation process in DWTPs could effectively eliminate approximately 98.0% of PS beads [49]. This study underscores the significance of the sedimentation process for MP removal in DWTPs; however, achieving such high removal efficacy remains challenging during actual operational conditions.
After the sedimentation tanks in DWTP-A and DWTP-B, subsequent treatment processes, including V-type filters, activated carbon adsorption tanks, and liquid chlorine disinfection tanks, were employed. The removal rates of the MPs were determined to be 20.0% and 27.7%, respectively. As for DWTP-D, the subsequent treatment processes were the rapid filter and the liquid chlorine disinfection tank, resulting in a removal efficiency of 15.7%. In the study of DWTP Plzeň in the Czech Republic, the deep-bed filtration revealed a removal rate of 20.0% [27], and Wang et al.’s results indicate that the efficiency of the removal of MPs by sand filtration was 29.0–44.4% [48]. Similarly, Sarkar et al.’s study demonstrated a removal efficiency of approximately 23.0% for the sand filter [26]. The removal rate of this part in this study, however, exhibited a low value.
Here, we report the data collected from different studies on the MP removal efficiency in various DWTPs (Table 3). Generally, DWTPs with simple processes exhibit poor MP removal efficacy, as observed in the case of DWTP-C in this study. The removal efficiency of the majority of the DWTPs studied exceeds 80.0%, indicating a relatively high performance compared to the three surface water-based DWTPs investigated in this study. It is noteworthy that the DWTP situated in Barcelona, Spain, employed a highly intricate process, achieving an exceptional efficiency rate of 98.3% [33]; it is very difficult to achieve such a high MP removal efficiency in the actual operational DWTPs. Overall, numerous scholars have exhibited significant interest in investigating the MP removal efficiency in DWTPs. However, certain limitations still exist within the current findings. The MPs present in water exhibit diverse sizes, shapes, and polymer types, which can impact the efficiency of the processes used for their removal from raw water, such as coagulation, sedimentation, and filtration. In addition to examining macro removal rates, it is imperative to focus on comprehending the transport process of MPs within each water treatment unit and elucidating the microscopic mechanisms underlying the interaction between coagulants and MPs as well as the retention mechanisms of the filter media for trapping MPs. This will provide a more comprehensive theoretical foundation for future advancements in efficient technologies aimed at removing MPs in DWTPs.

4. Conclusions

This study investigated the occurrence of MPs and the MP removal efficiency in four DWTPs in Zhengzhou city. Due to the diverse water sources, there were variations in the abundance of MPs in the raw water, ranging from 12.80 ± 0.80 to 25.07 ± 1.67 n/L. Among these sources, DWTP-B obtained from the Yellow River exhibited the highest abundance of MPs in its raw water, while DWTP-C, sourced from groundwater, displayed the lowest abundance. The treated drinking water demonstrated a range of abundance from 6.40 ± 0.80 to 8.80 ± 0.80 n/L. The abundance for each DWTP was analyzed by one-way ANOVA and the results revealed significant differences in the raw water (p = 0.00042) and treated drinking water (p = 0.041). However, no significant differences were observed in the sedimentation tank outlet (p = 0.457). In general, fibers and fragments ranging from 10 to 100 μm in size were found to be the primary components of the MPs in all the water and sludge samples, with the exception of the treated drinking water sample from DWTP-D, where the dominant size range was between 100 and 500 μm. Furthermore, a total of seven different colors of MPs were detected, with white and transparent being predominant. The polymer types also demonstrated diversity as ten distinct polymer types were detected across all the samples; PVC emerges as the main polymer type in raw water at two DWTPs, while PPO and PET prevail in raw water in the other two DWTPs. Additionally, PET emerged as the most prevalent polymer type in treated drinking water, with both PET and PVC being primarily present in sludge.
The overall removal rates of the MPs in the four DWTPs ranged from 45.8% to 74.5%. Among them, DWTP-C exhibited the lowest removal rate, which was attributed to its simplified treatment process. The coagulation/flocculation and sedimentation process employed by the DWTPs exhibited a discernible efficacy in the removal of MPs, and the removal rates at the sedimentation tank outlet accounted for more than 50.0% of the total removal rate. The removal efficiency results in this study, when compared with some of the previous studies, do not meet the desired level of effectiveness. Additionally, it is crucial to pay attention to the significantly higher abundance of MPs found in sludge, with abundance ranging from 8424.81 ± 263.32 n/kg to 11,032.84 ± 1234.77 n/kg with no significant difference (p = 0.9). The sludge in DWTPs could serve as a focal point for the accumulation of MPs from water bodies. Therefore, we must confront the challenge of appropriately treating and disposing of this sludge to effectively mitigate the re-entry of MPs into the natural environment. Currently, the research on MPs still encounters numerous challenges. In order to comprehensively and systematically investigate the removal mechanisms of MPs in DWTPs, it is imperative to obtain more fundamental research data. This will establish a solid foundation for the establishment of regulations to limit MPs in drinking water, in order to effectively safeguard public health and safety.
Limitations: The scope of our study was limited to four DWTPs in Zhengzhou, which may impose regional and sample size constraints on the generalizability of our findings. However, these results can still serve as valuable points of comparison and reference for research conclusions in other regions. In addition, this investigation was based on a single-time sampling for each DWTP, which inevitably introduces potential research errors. Future investigations should focus on the seasonal and spatiotemporal distribution of MPs in DWTPs to comprehensively assess the removal efficiency of individual treatment units and to deeply analyze the underlying mechanisms involved. This aspect deserves attention from all scholars engaged in this field, and it will be a primary focus of our forthcoming series of studies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w16010131/s1, Figure S1: Electron microscope images of the MPs in this investigation ((a) fragment, transparent; (b) fragment, yellow; (c) fiber, white; (d) fiber, blue; (e) particle, transparent; (f) film, transparent), Figure S2: Raman spectral of 10 polymer types detected in water and sludge samples in present investigation, Table S1: Abundance of the MPs in water samples in each DWTP, Table S2: Abundance of the MPs in sludge samples in each DWTP, Table S3: Percentage of the MP size ranges in water and sludge samples in each DWTP, Table S4: Percentage of the MP shapes in water and sludge samples in each DWTP, Table S5: Percentage of the MP colors in water and sludge samples in each DWTP, Table S6: Percentage of the MP polymer types in water and sludge samples in each DWTP.

Author Contributions

Conceptualization, Y.L. (Yang Li) and B.C.; data curation, M.S., X.C. and Y.L. (Yue Liu); formal analysis, M.S., X.C. and Y.L. (Yue Liu); investigation, Y.M., L.Q. and T.Q.; methodology, Y.M., L.Q. and T.Q.; resources, Y.L. (Yang Li), B.C. and X.D.; writing—original draft, Y.L. (Yang Li) and Y.D.; writing—review and editing, B.C. and X.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key Research and Development Program of Henan Province (No. 222102320223), the Postgraduate Education Reform and Quality Improvement Project of Henan Province (No. YJS2023JD17), the Science Fund for Distinguished Young Scholars of Hebei Province (No. E2022402064), the Young Scholar Foundation of Zhongyuan University of Technology (No. 2021XQG04), and the Natural Science Foundation of Zhongyuan University of Technology (No. K2023QN009).

Data Availability Statement

The data are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Water 16 00131 g001
Figure 1. Location of water sampling points in different DWTPs.
Figure 1. Location of water sampling points in different DWTPs.
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Water 16 00131 g002
Figure 2. Abundance of MPs in water samples (a) and sludge samples (b) in each DWTP (RW: raw water; STO: sedimentation tank outlet; TDW: treated drinking water).
Figure 2. Abundance of MPs in water samples (a) and sludge samples (b) in each DWTP (RW: raw water; STO: sedimentation tank outlet; TDW: treated drinking water).
Water 16 00131 g002
Water 16 00131 g003
Figure 3. Percentage of the MP size ranges in water and sludge samples in each DWTP ((a): DWTP-A; (b): DWTP-B; (c): DWTP-C; (d): DWTP-D).
Figure 3. Percentage of the MP size ranges in water and sludge samples in each DWTP ((a): DWTP-A; (b): DWTP-B; (c): DWTP-C; (d): DWTP-D).
Water 16 00131 g003
Water 16 00131 g004
Figure 4. Percentage of the MP shapes in water and sludge samples in each DWTP ((a): DWTP-A; (b): DWTP-B; (c): DWTP-C; (d): DWTP-D).
Figure 4. Percentage of the MP shapes in water and sludge samples in each DWTP ((a): DWTP-A; (b): DWTP-B; (c): DWTP-C; (d): DWTP-D).
Water 16 00131 g004
Water 16 00131 g005
Figure 5. Percentage of the MP colors in water and sludge samples in each DWTP (RW: raw water, STO: sedimentation tank outlet, TDW: treated drinking water, S: sludge).
Figure 5. Percentage of the MP colors in water and sludge samples in each DWTP (RW: raw water, STO: sedimentation tank outlet, TDW: treated drinking water, S: sludge).
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Water 16 00131 g006
Figure 6. Percentage of the MP polymer types in water and sludge samples in each DWTP (RW: raw water, STO: sedimentation tank outlet, TDW: treated drinking water, S: sludge).
Figure 6. Percentage of the MP polymer types in water and sludge samples in each DWTP (RW: raw water, STO: sedimentation tank outlet, TDW: treated drinking water, S: sludge).
Water 16 00131 g006
Table 1. Relevant parameters of the four DWTPs.
Table 1. Relevant parameters of the four DWTPs.
DWTPSampling TimeScale (×104 m3)Water Source
A14 June 202315Yellow River (10%)
Middle Route Project of S-N Water Diversion (90%)
B16 June 202310Yellow River (95%)
Middle Route Project of S-N Water Diversion (5%)
C27 June 20236Fourteen underground water wells (100%)
D11 July 202310Middle Route Project of S-N Water Diversion (100%)
Table 2. MP removal efficiency in each DWTP.
Table 2. MP removal efficiency in each DWTP.
WDTPMean Abundance (n/L)Removal Rate 1 (%)Removal Rate 2 (%)
RWSTOTDW
A22.6711.476.9349.469.4
B25.0713.336.4046.874.5
C12.80/6.93/45.8
D18.6711.738.8037.152.9
Note: RW represents raw water; STO represents sedimentation tank outlet; TDW represents treated drinking water; removal rate 1 represents the removal rate of MPs at the sedimentation tank outlet; removal rate 2 represents the removal rate of MPs in the treated drinking water.
Table 3. Comparison of relevant parameters and MP removal efficiency of DWTPs.
Table 3. Comparison of relevant parameters and MP removal efficiency of DWTPs.
NameCountryRaw WaterCapacity (104 m3/d)Treatment ProcessRemoval Efficiency (%)Reference
MilenceCzech RepublicÚhlava River1.56Flocculation and sand filtration40.0[27]
PlzeňCzech RepublicÚhlava River3.46Coagulation/flocculation, sedimentation, filtration, ozonation, and GAC filtration88.0[27]
DWTP1Czech RepublicLarge reservoir31.97Coagulation/flocculation, sand filtration70.0[50]
DWTP2Czech RepublicSmall reservoir0.86Coagulation/flocculation, sedimentation, sand and granular activated carbon filtration81.0[50]
DWTP3Czech RepublicRiver0.78Coagulation/flocculation, flotation, sand filtration and granular activated carbon filtration83.0[50]
Sant Joan DespíSpainLlobregat River43.20Coagulation/flocculation, settling, sand filtration, ozonation, GAC filtration, and ultrafiltration93.0[51]
BarcelonaSpainLlobregat river27.65Coagulation/flocculation, clarifiers, sand filters, carbon filters, reversible electrodialysis98.3[37]
Indira GandhiIndiaGanga River34.85Pre-disinfection, coagulation/flocculation, pulse clarification, sand filtration, and post-disinfection84.6[26]
A total of 4 DWTPsKoreaNakdong River and two lakesNDPre-ozonation, coagulation, sedimentation, sand filtration>90.0[28]
/ChinaYangtze River120Coagulation/flocculation, sedimentation, sand filtration, ozonation, granular activated carbon (GAC) filtration82.1–88.6[48]
/China/20.00Coagulation/flocculation, settling, ozonation, biological activated carbon, sand filtration80.1[52]
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Li, Y.; Meng, Y.; Qin, L.; Shen, M.; Qin, T.; Chen, X.; Chai, B.; Liu, Y.; Dou, Y.; Duan, X. Occurrence and Removal Efficiency of Microplastics in Four Drinking Water Treatment Plants in Zhengzhou, China. Water 2024, 16, 131. https://doi.org/10.3390/w16010131

AMA Style

Li Y, Meng Y, Qin L, Shen M, Qin T, Chen X, Chai B, Liu Y, Dou Y, Duan X. Occurrence and Removal Efficiency of Microplastics in Four Drinking Water Treatment Plants in Zhengzhou, China. Water. 2024; 16(1):131. https://doi.org/10.3390/w16010131

Chicago/Turabian Style

Li, Yang, Yinghui Meng, Liwen Qin, Minghui Shen, Tongtong Qin, Xudong Chen, Beibei Chai, Yue Liu, Yanyan Dou, and Xuejun Duan. 2024. "Occurrence and Removal Efficiency of Microplastics in Four Drinking Water Treatment Plants in Zhengzhou, China" Water 16, no. 1: 131. https://doi.org/10.3390/w16010131

APA Style

Li, Y., Meng, Y., Qin, L., Shen, M., Qin, T., Chen, X., Chai, B., Liu, Y., Dou, Y., & Duan, X. (2024). Occurrence and Removal Efficiency of Microplastics in Four Drinking Water Treatment Plants in Zhengzhou, China. Water, 16(1), 131. https://doi.org/10.3390/w16010131

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