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Article

Particulate and Dissolved Metals in the Pearl River Estuary, China—Part 2: Partitioning Characteristics and Influencing Factors

by
Hongyan Ma
1,2,
Yunpeng Wang
1,2,*,
Chuqun Chen
3 and
Yuanzhi Zhang
4
1
State Key Laboratory of Deep Earth Processes and Resources, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
4
School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
*
Author to whom correspondence should be addressed.
Water 2025, 17(10), 1436; https://doi.org/10.3390/w17101436
Submission received: 6 April 2025 / Revised: 3 May 2025 / Accepted: 7 May 2025 / Published: 9 May 2025
(This article belongs to the Section Water Quality and Contamination)
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Abstract

:
Metals in the Pearl River Estuary are potentially significant pollutants influenced by the region’s high population density and rapid industrial growth, but their distribution and impacts have not yet been thoroughly investigated. This study investigates the spatial distribution and environmental impacts of particulate and dissolved metals (including Cr, Mn, Fe, Co, Ni, Cu, Zn, Mo, Cd, Tl, and Pb) in the Pearl River Estuary using a combination of statistical methods and spatial analysis techniques. This is Part 2 of a series of papers. In Part 1, we mainly focused on the spatial characteristics of particulate and dissolved metals and the water environment factors influencing them. In Part 2, we mainly focus on the partitioning of metals between their particulate and dissolved forms and its influencing factors. The results show that the distribution of metals in the estuary is predominantly in the dissolved phase, except for Mn, which is more associated with particulates. Environmental factors such as temperature, oxygen content, and water depth exert a substantial impact on the metals’ partitioning behavior. In contrast, the pH value, salinity, and concentration of suspended matter have a minor influence. The results of this study highlight the importance of understanding metal partitioning in the estuary for effective water quality management and pollution control, which also provides valuable insights for pollution source tracking in this area.

1. Introduction

This is Part 2 of a series of papers about the particulate and dissolved metals in the Pearl River Estuary, China. In Part 1, we mainly focused on the distribution characteristics of particulate and dissolved metals and their influencing factors [1]. In the current paper, we mainly focus on the partitioning of metals between their particulate and dissolved forms and its influencing factors.
Metals in water occur in various states, such as a dissolved state, suspended particle state, and sediment state. Metals in an environmental can enter the solid medium (suspended matter, sediment) through adsorption and other means, and when the environmental conditions of the water body change, the metals in the solid medium can also re-enter the water environment through desorption, dissolution, and other means, resulting in secondary pollution [2]. The water dynamic conditions in the Pearl River Estuary are complex, and the partitioning behavior of metals between particulate and dissolved phases, as well as the factors influencing this partitioning, remain unclear, which hinders the effective evaluation and mitigation of metal pollution.
Metals in estuaries exhibit complex and varied environmental behavior, with their partitioning governed by numerous factors, including suspended substances, temperature, salinity, pH, and hydrodynamic conditions [3,4,5,6,7,8]. In addition, the environmental behavior of different metals is also different [7].
Metal partitioning between particulate and dissolved phases plays a key role in their transport within water bodies. The study of metal partitioning in particulate and dissolved phases can provide information on the content of biologically available trace metals in water. Therefore, investigating the partitioning of metals between their particulate and dissolved phases, along with the factors influencing this process, is crucial for understanding the migration of trace metals and for the management of estuarine pollution [9].
Previous studies on metal partitioning have mainly focused on the partitioning of metals between sediments and water bodies. Kuang Zexing et al. (2022) selected a typical marine shellfish farming area around Shangchuan Island in the South China Sea as the study area, calculated the partition coefficients (Kd) of heavy metals between seawater and sediments, and ranked the metals according to their partition coefficients [10]. Similarly, Ashayeri and Keshavarzi (2019) conducted a similar study in the Shadegan Wetland in southwestern Iran [11]. Li Guolian et al. (2011) calculated and compared the partition coefficients of heavy metals between the water and sediments at three major river estuaries flowing into Lake Chaohu—the Nanfei River, the Yuxi River, and the Hangbu River [12]. Wang Yuhao et al. (2025) calculated the partitioning of heavy metals between sediments and surface water in the Golmud River-Dabusun Salt Lake ecosystem in northwestern China [13]. The results showed that certain heavy metals, such as Cu, Co, Pb, and As, had lower Kd values in Dabusun Salt Lake than in the Golmud River and freshwater regions. It was also noted that the release of heavy metals from sediments into the water column was more pronounced due to high salinity [13]. Jakomin et al. (2015) compared the partition coefficients of Pb, Cd, and Zn in the Pano Aquifer and the Puelche Aquifer and found that the Kd values were generally higher in the Pano Aquifer than in the Puelche Aquifer [14]. They suggested that the higher Kd values in the Pano Aquifer were mainly due to its higher content of clay and organic matter, as well as its stronger pH stability [14]. Xu Xinrong et al. (2019) investigated the effects of pH and time on the release of heavy metals from sediments [15]. The study showed that heavy metals that remain in the natural environment for long periods of time can be continuously released due to changes in pH, thereby increasing the health risks [15].
Research on the partitioning of metals between water bodies and suspended particulate matter is limited [16,17,18,19,20]. Trinh Anh et al. (2013) investigated the variations in the partition coefficients of various heavy metals between suspended particulate matter and the dissolved phase in the Day River Basin of the Red River Delta in northern Vietnam [16]. The study aimed to identify the key factors controlling these partition coefficients. Particular attention was paid to five water quality parameters, redox potential, total organic carbon, pH, electrical conductivity, and suspended solids, which were considered to play a controlling role in the partitioning of heavy metals in the water column. The study found that redox potential and urban waste influenced the partitioning of heavy metals [16]. Zhang Jin et al. (2022) investigated the partitioning of metals between suspended particulate matter and the dissolved phase in the Taihu Basin of China and explored the effects of flow rate and total suspended solids (TSS) on metal partitioning [21]. The results showed that the partition coefficients of metals between the particulate phase (suspended solids) and the dissolved phase (colloidal and dissolved phases) increased in the transition from low to high flow when the TSS concentration and particle median diameter decreased. The concentration of metals in suspended solids was negatively correlated with the TSS concentration [21].
Research on metal partitioning in the Pearl River Estuary has also mainly focused on the partitioning of metals between sediments and water bodies [22], with the classification of metal forms mainly based on chemical perspectives [23,24]. Studies on the partitioning of metals between their particulate and dissolved forms and their influencing factors are very limited [25].
In this study, metals are categorized into their particulate and dissolved forms from a physical perspective, which provides insights into their partitioning dynamics and transport processes in the aquatic environment. Therefore, in January 2022, we surveyed the Pearl River Estuary. We collected water samples and recorded the environmental parameters at the sampling sites, including water depth, temperature, salinity, oxygen content, and pH. Laboratory analyses were then conducted to determine the concentrations of total suspended matter (TSM), as well as dissolved and suspended metals (Cr, Mn, Fe, Co, Ni, Cu, Zn, Mo, Cd, Tl, and Pb). Based on these data, we investigated the partitioning of metals between their solid and liquid phases and identified the factors that influence this distribution. Both the heavy metals in the suspended matter and water samples and the recordings of the physicochemical field parameters were determined, as described in Part 1 of the work published in [1].

2. Materials and Methods

2.1. Study Area, Sample Collection, and Analysis

The Pearl River Estuary, situated along the southeastern coast of China between approximately 21° N–23° N and 113° E–115° E, serves as an outlet through which the Pearl River—the largest river system in southern China—flows into the South China Sea. The current study builds on the results presented in Part 1 [1]. Details of the study area, sampling, and analytical procedures can be found in Part 1 and are not repeated here [1]. The distribution of the sampling sites is shown in Figure 1.

2.2. Statistical and Spatial Methods

In the current study, the spatial distribution patterns of metal partition coefficients in the Pearl River Estuary were analyzed using a combination of Global Moran’s I and Local Moran’s I. Additionally, a correlation analysis and multiple regression analysis were used to investigate the influence of water environmental parameters on metal partitioning. A detailed description of these methods can be found in Part 1 [1].

2.3. Partition Coefficient

The metal partition coefficient (Kd) is an important index to reflect the partitioning relationship between the dissolved phase and suspended particulate phase of metals in water. The equation for the calculation of Kd is as follows [26]:
Kd = P/D × 1000,
where P is the suspended particulate metal concentration (μg/g) and D is the dissolved metal concentration (μg/L). The log(Kd) value is effective for assessing the distribution of trace metals between the dissolved and particulate phases. A higher log(Kd) suggests a greater affinity of the metal for suspended particles, while a lower log(Kd) indicates that the metal is more prevalent in the dissolved phase [19].

3. Results and Discussion

3.1. Comparison of Dissolved and Suspended Particulate Metal Contents

To facilitate a comparison of the metal content in suspended particulate matter with that in the dissolved fraction, the metal content in the suspended particles was converted from μg/g to μg/L. The concentrations of particulate and dissolved metals in the Pearl River Estuary can be found in Part 1 of this series of articles. The comparison of metal contents in particulate and dissolved forms is shown in Table 1. Among the metal elements analyzed in the particulate phase, Fe exhibited the highest concentration, averaging 227.31 μg/L. Following Fe, Mn and Zn had the next highest concentrations, with average levels of 10.26 μg/L and 1.37 μg/L, respectively. The average concentrations of Pb, Cr, Ni, Cu, and Co ranged from 0 to 1 μg/L, while Mo, Tl, and Cd had average concentrations ranging from 0.001 to 0.01 μg/L. A comparison of the metals in suspended particles with those in filtered water shows that most metals in the Pearl River Estuary are mainly found in the dissolved fraction, including Cr, Ni, Cu, Zn, Mo, Cd, Tl, and Pb. Mn is predominantly present in the particulate form, while Fe and Co have similar concentrations, with slightly higher values in the dissolved fraction.
The primary forms of metal deposits vary in different waters. In Zhanjiang Bay and Jiaozhou Bay, Pb occurs mainly in particulate form [27,28], while in the Pearl River Estuary, it occurs mainly in dissolved form. The variability in the sample data indicates that the concentration ranges of all metals in the particulate form are greater than those in the dissolved fraction, with more pronounced spatial heterogeneity.
The tendency for metals to primarily exist in the dissolved form in the Pearl River Estuary, compared to Zhanjiang Bay and Jiaozhou Bay, can be explained by several factors. Firstly, the hydrodynamic conditions in the Pearl River Estuary, influenced by strong tidal action and significant water flow, facilitate the transition of metals from their particulate to dissolved forms [17]. Secondly, the chemical characteristics of the water in the Pearl River Estuary may also favor the dissolution of metals. The water in this estuary likely has higher solubility and lower concentrations of suspended particulate matter, creating favorable conditions for metals to remain dissolved. Lastly, the difference in pollution sources is another contributing factor. The industrial and urban pollution in the Pearl River Estuary may lead to a higher prevalence of metals in their dissolved form, particularly heavy metal ions, due to wastewater discharge and agricultural runoff.

3.2. Comparison of Spatial Distribution of Dissolved and Particulate Metals

Based on the results of Part 1, a comparison of the spatial variation in suspended particulate and dissolved metal forms was conducted. The spatial distribution patterns of particulate metals, including Mn, Co, Ni, Cu, Mo, Cd, Tl, and Zn, exhibit clustering behavior, while the dissolved forms of Cr, Cd, Cu, Fe, Ni, Mo, and Tl show clustered distributions. The remaining metals do not deviate significantly from a random pattern. It can be observed that metals such as Ni, Cu, Cd, Mo, and Tl are clustered in both phases, while Pb shows a random distribution. Mn, Co, and Zn show spatial clustering in the particulate phase, but their spatial distribution patterns in the dissolved phase show no significant deviation from the random distribution. Cr and Fe, in contrast, show clustering in the dissolved phase, but a random distribution in the particulate phase. The Pearl River Estuary, as a typical estuarine ecosystem, shows spatial distribution patterns of dissolved and particulate metals, which are jointly controlled by multiple sources of input and hydrological–geochemical processes. The significant clustering of particulate metals such as Mn, Co, and Zn is likely closely related to the surrounding industrial activities in the Pearl River Estuary, such as electronics manufacturing and metallurgy, as well as atmospheric deposition, including traffic-related particulate matter. Some researchers have suggested that particulate Zn and Co from industrial emissions in the Pearl River Delta region are enriched primarily by atmospheric deposition in estuarine surface sediments and form spatial hotspots [29]. The enrichment of dissolved metals, such as Cr and Fe, is more driven by hydrological–geochemical processes. The complex hydrodynamic conditions at the freshwater–saltwater interface of the Pearl River Estuary, such as the tidal effects and salinity gradients, may promote the migration and redistribution of dissolved Fe and Cr. It is worth noting that Ni, Cu, Cd, Mo, and Tl show significant clustering in both dissolved and particulate forms, suggesting that these metals may be influenced by various input sources (such as industrial effluents and agricultural runoff) and morphological transformations. The biphasic clustering of Cu in estuarine environments may be related to the synergistic effects of complexation with organic matter (dissolved phase) and adsorption to minerals (particulate phase) [30]. In contrast, the spatially random distribution of Pb may reflect the diversity of its sources (such as industrial emissions and natural weathering) and the effects of long-distance transport [31]. Within the Pearl River Estuary, the high clustering of particulate metals (including Co, Cu, Mn, Mo, and Tl) is mainly observed in the north of Humen. Low–low clustering, such as Zn, Ni, Fe, and Cd, mainly occurs in a seaward direction, distancing from the coastline. Cr and Pb have a low–high distribution pattern to the northward of Wanshan Island; the pattern is also observed in Pb, which shows a low–low clustering pattern near the Hong Kong-Zhuhai-Macau Bridge. Spatial trends of Metals in their dissolved state in the Pearl River Estuary are more diverse compared to the particulate metals. The dissolved metals north of Humen show both high–high clustering (Cd, Co, Cu, Ni, and Tl) and low–low clustering for some metals such as Fe and Mo. Among the dissolved metals, low–low clustering tends to occur near Jiaomen and Hengmen, such as for Cr, Mo, Ni, and Pb. In addition, high–high clustering is also more common in the waters south of Wanshan Island, especially for Mo and Fe. The spatial distribution pattern of dissolved Zn differs significantly from that of the other metals. It shows a complex pattern that includes low–low clustering, low–high clustering, as well as a high and low clustering.
The local spatial distribution patterns of suspended particulate and dissolved metals in the Pearl River Estuary show the complex interactions between the spatial heterogeneity of pollution sources and environmental processes. The high clustering of suspended particulate metals (Co, Cu, Mn, Mo, and Tl) is mainly observed in the region north of Humen, which is closely related to the dense industrial activities (such as electronics manufacturers and metallurgical plants) and urban emissions in this area. Particulate Cu and Co released from the industrial areas in the Pearl River Delta are deposited in the northern part of Humen by atmospheric deposition and river transport, forming significant high-value clustering zones [29]. The high-value clustering of Mo and Tl may be related to the high concentrations contained in industrial effluents. In contrast, the low–low clustering of particulate Zn, Ni, Fe, and Cd inputs is mainly found in marine areas far from land, reflecting the significant influence of inputs from land on the distribution of particulate metals. The local spatial distribution patterns of dissolved metals are more diverse, reflecting the complexity of hydrological and geochemical processes. In the region north of Humen, a high clustering of dissolved Cd, Co, Cu, Ni, and Tl and a low–low clustering of Fe and Mo are observed. This could be related to the redox conditions in the mixing zone between fresh and salt water. Fe tends to be present in dissolved form in reducing environments, but in the freshwater–saltwater mixing zone, oxidation may cause the formation of particulate oxides, leading to the low-value clustering of dissolved Fe [32]. Mo tends to be present in dissolved form under alkaline conditions, but in the freshwater–saltwater mixing zone, it may form particulate matter due to adsorption, which explains the occurrence of its low-value clustering [33]. The low–low clustering near Jiaomen and Hengmen (such as Cr, Mo, Ni, and Pb) may be related to the strong water exchange and dilution effects in these areas. The high clustering of dissolved Mo and Fe in the waters south of Wanshan Island may be influenced by local pollution sources (such as ship emissions and aquaculture) and sediment resuspension. In addition, the complex spatial distribution pattern of dissolved Zn (low–low, low–high, and high–low clustering) may reflect the dynamic balance between its multiple sources (such as industrial effluents and atmospheric deposition) and transformation processes. The spatial heterogeneity of dissolved Zn suggests that it is influenced by hydrological conditions (such as flow velocity and salinity gradient) and the input of pollutants (such as industrial effluents), which may lead to considerable spatial heterogeneity [34].

3.3. Comparison of Correlation Between Dissolved and Particulate Metals

Based on the results of Part 1, a comparison of the correlation between particulate and dissolved metals was conducted. Overall, the correlation between particulate metals is stronger than that between dissolved metals. In general, the particulate metals show a significant positive correlation with each other, with only a few exceptions. Pb shows the weakest correlation and only shows a significant positive relationship with Cr. Cr and Fe also show relatively weak correlations with other metals. Fe shows no significant correlation with Zn or Cd, and Cr shows no significant correlation with Mn, Ni, or Cd. However, other particulate metals show significant positive correlations with each other. In contrast, the correlations between dissolved metals are less widespread than those observed for particulate metals. Pb shows weak correlations with other metals, and Cr, Mn, Co, Ni, and Zn each show significant correlations with only one other metal. Among the dissolved metals, Fe, Mo, Cd, and Tl show stronger correlations with four significant pairs. Dissolved Cu shows the closest correlations with other metals with five significant correlations. Interestingly, the correlations between the dissolved metals are both positive and negative. For example, Fe shows remarkable negative correlations with Cu, Cd, and Tl, while Mo also shows significant inverse relationships with these elements.
The strong correlations between particulate metals are primarily due to their common sources (such as industrial emissions and soil erosion) and adsorption mechanisms (such as co-precipitation with iron and manganese oxides and organic matter) [35]. Correlations between dissolved metals are weaker and are largely determined by variables including salinity gradients, pH fluctuations, and complexation with organic matter [36]. The weak correlation between particulate Pb and other metals may be attributed to several factors: Pb contamination is largely attributed to legacy sources such as past coal combustion and leaded gasoline additives (such as tetraethyl lead), as well as industrial emissions (such as battery manufacturing and metallurgy). These sources of Pb may differ from those of other metals, leading to a weaker correlation [29]. These sources exhibit high spatiotemporal heterogeneity, resulting in a distribution pattern of Pb that differs from that of other metals. Particulate Pb in the Pearl River Estuary tends to associate with iron–manganese oxides and organic matter, while metals such as Cu, Zn, and Cd are primarily associated with sulfides or carbonates [37]. The adsorption behavior of particulate Pb is significantly influenced by the content of organic matter, while other metals tend to be controlled by mineral phases. This selective adsorption leads to a distribution pattern of particulate Pb that differs from that of other metals. The migration of particulate Pb is influenced by atmospheric deposition and riverine transport, while other metals are more influenced by riverine transport and industrial effluent discharges [29].
The relationship between particulate metals and environmental factors tends to be more pronounced compared to that of dissolved metals, particularly with factors such as temperature, salinity, oxygen concentration, and pH. Particulate metals often show negative correlations, while the correlations of dissolved metals are weaker and alternate between positive and negative. Overall, particulate metals are more strongly influenced by environmental factors and show clear associations with most environmental factors.

3.4. Metal Partition Coefficients

To further investigate the partitioning behavior of metals between their suspended particulate and aqueous phases in the Pearl River Estuary, Table 2 shows the logarithmic values of the partition coefficients of metals. A high log(Kd) value reflects a strong association of metals with particulate matter, while a low log(Kd) value reflects a preference for the dissolved phase in aquatic environments. According to Table 2, the mean log(Kd) value for Mo is the lowest at about 2, while Mn has the highest mean log(Kd) value at almost 6. Mean log(Kd) values for other metals in the Pearl River Estuary generally range between 3 and 5, with most around 4. The descending order of the mean partition coefficient (log(Kd)) for metals in the Pearl River Estuary is as follows: Mn, Fe, Co, Tl, Cu, Cd, Pb, Cr, Zn, Ni, and Mo. The low coefficient of variation indicates that the metal partitioning in the Pearl River Estuary has low variability. This low variability may reflect the stable water quality or environmental conditions in the estuary during the study period, suggesting that metal migration and partitioning were not significantly affected by drastic environmental fluctuations (such as extreme weather events or sudden pollution events). The low coefficient of variation may also indicate a high reliability of the experimental data, with consistent measurement methods or analytical procedures and minimal errors. This result indicates a high degree of consistency and stability in the partitioning of metals in the Pearl River Estuary and provides important clues for further studies on the environmental behavior of these metals.
It is known that the partition coefficient of metals depends on the environmental conditions. Therefore, the results reported in different publications are not always identical [38]. The logarithmic values of metal partition coefficients in the Pearl River Estuary and other regions are shown in Table 3. Compared to Zhanjiang Bay, the Day River, and the northern Australian coastal and estuarine areas, most metals in the Pearl River Estuary are mainly in dissolved form, including Fe, Cr, Ni, Zn, Cd, Pb, and Co. Only Mn tends to be associated with suspended solids in the Pearl River Estuary. The partition coefficient of Cu is between that of Zhanjiang Bay and Day River. Temperature is a critical factor to be considered when discussing the partition coefficients. The latitudes of the three regions are all at lower latitudes than the Pearl River Estuary. In addition, the dominance of dissolved metals in the Pearl River Estuary is likely closely related to the low concentration of suspended particulate matter. The range of logarithmic values of the partition coefficients also shows that the partition coefficients of Cu, Zn, Cd, and Pb are significantly higher in the Scheldt Estuary than in the Pearl River Estuary. Excessive concentrations of dissolved metals in the aquatic environment pose a significant threat to current aquatic ecosystems. If metals bind to particles and precipitate, they could pose a future threat to aquatic ecosystems. Compared to Jiaozhou Bay and the six Texas estuaries, the fluctuations of metal partition coefficients in the Pearl River Estuary are smaller [39].

3.5. Spatial Distribution Patterns of Metal Partitioning

A spatial autocorrelation analysis was performed to investigate the spatial distribution patterns of the metal partition coefficients. The results of the global autocorrelation analysis, in particular the Moran’s I index of the metal partition coefficients in the Pearl River Estuary, are shown in Table 4. Overall, the spatial distribution patterns of the partition coefficients for Cr, Cu, Cd, Tl, and Pb show no significant differences from the random pattern, suggesting that their distribution is relatively uniform and may be less affected by water mixing or environmental conditions. Fe and Mo show a clustered spatial distribution pattern within a 99% confidence interval. The probability that Mn and Ni exhibit this clustered pattern by chance is less than 5%. The probability that Co and Zn exhibit this clustered pattern by chance is less than 10%. The spatial patterns of Fe, Mo, Mn, Ni, Co, and Zn show a significant spatial clustering, which is likely influenced by local geochemical processes or anthropogenic activities.
Since the global Moran’s I index cannot reveal the specific locations or local characteristics of spatial autocorrelation, a local Moran’s I analysis was conducted to identify the precise locations and types of spatial clustering, providing data support for regional management. The results of this analysis are shown in Figure 2. Two prominent spatial distribution patterns of the metal partition coefficients in the Pearl River Estuary were observed. The first is a low-low clustering in areas farther from the land and closer to the ocean, particularly near Jimi Men and Huangmao Hai, where metals such as Cr, Fe, Mo, and Ni are present. In the direction toward the ocean, low log(Kd) anomalies (low–high clustering) are also observed, such as for Tl and Pb. The second pattern is a high–high clustering observed north of Humen, including Co, Fe, Mn, and Zn, with anomalies of high log(Kd) values for Cd and Cu near Dong’ao Island and the Hong Kong-Zhuhai-Macao Bridge.
The local Moran’s I analysis shows that the proportion of particulate metals is higher towards the land (Hu-men), while the proportion decreases towards the sea. This indicates that input from land is one of the main sources of metals in the particulate phase in the Pearl River Estuary.
The areas closer to land in the Pearl River Estuary are influenced by runoff from the Pearl River Basin, which carries large amounts of suspended particulate matter, such as sediments and organic matter that have a strong adsorption capacity for metals. Human activities, including industrial effluents, agricultural runoff, and urban runoff, also contribute to the increased input of metal particles. With increasing distance from land, the terrestrial input gradually decreases, leading to a reduction in the concentration of suspended particulate matter and, consequently, to a decrease in the proportion of particulate metals. Salinity is another decisive factor: close to land (Humen), the salinity is lower and the stability of suspended matter is higher, which facilitates the adsorption of metals onto these particles.
Towards the sea, the salinity gradually increases, which leads to the flocculation of the suspended particles. These particles aggregate and settle, reducing the proportion of particulate metals [44]. In high-salinity environments, the adsorption capacity of metal ions on the surface of particles decreases, causing some metals to be desorbed from the particulate phase and transition into the dissolved phase [45]. In addition, suspended particulate matter is an important carrier for the adsorption of particulate metals, and their concentration and composition have a direct effect on log(Kd) values [35]. High concentrations of suspended particulate matter can promote the adsorption of metals onto particles [46], leading to a higher proportion of particulate metals near Humen and the Hong Kong-Zhuhai-Macao Bridge.

3.6. Correlation Analysis of the Metal Partition Coefficient

The results of the correlation analysis between the log(Kd) values of the trace metals and the environmental factors are shown in Figure 3. Overall, the figure shows a similar trend to the particulate metals, but the correlations are less pronounced compared to the particulate metals. Particulate metals have a more direct and stronger influence on the partition coefficient.
The log(Kd) values of Mn, Fe, Co, Ni, Zn, and Mo are significantly correlated with the log(Kd) values of many other metals (≥5) and are strongly influenced by environmental factors. In contrast, the log(Kd) values of other metals (Cr, Cu, Cd, Tl, and Pb) are scarcely affected by environmental factors and show limited correlations with the log(Kd) values of other metals. The significant high correlation between the partition coefficients of metals may indicate the following phenomena: similar environmental behavior—these metals exhibit comparable behavior in aquatic systems due to the influence of similar environmental factors; similar physicochemical properties—they share similar physicochemical properties, such as electronegativity, solubility, and ionic radius, leading to comparable binding affinities with particulate matter, and, consequently, they may follow analogous partitioning patterns in water; common pollution sources—these metals may originate from the same or similar pollution sources, for example, industrial effluents, agricultural runoff, or urban sewage could simultaneously affect the distribution of multiple metals, resulting in consistent partitioning behavior; coexistence and interactions of metals—these metals may interact with each other on particles, influencing their distribution and transport in the aquatic environment; and stability of the environment—a high correlation may also indicate relatively stable environmental conditions during the study period, leading to similar partitioning behavior of the different metals. If the environmental factors remain unchanged, it is less likely that the partitioning patterns of the metals will show significant fluctuations.
The correlation between the total suspended matter (TSM) concentration and the metal partition coefficients was not as high as expected. The positive correlation between the TSM concentration and the log(Kd) values of metals indicates that higher TSM concentrations may enhance the adsorption of metals on particles. Studies in the Beijiang River indicate that higher particulate concentrations promote the prevalence of metals in the particulate phase. In addition, smaller particles have a larger specific surface area so that they can adsorb more metals [39]. In contrast, temperature, salinity, oxygen content, and pH have a significant influence on the log(Kd) values of metals. The negative correlation between temperature, salinity, oxygen content, pH, and the log(Kd) values of metals indicates that these environmental factors facilitate the desorption of metals and promote their transition from the particulate to the dissolved phase. Higher temperatures may improve the solubility of metals, while variations in pH and salinity can affect metal-particle interactions, such as binding to organic matter or inorganic particles. Changes in pH affect the hydrolysis, precipitation, and adsorption behavior of metals. In general, metal ions are more likely to be present in the dissolved phase at low pH values, while metals may form hydroxide precipitates at higher pH values, increasing their proportion in the particulate phase [43]. However, the results of this study are similar to those in Bulimba Creek [47], where an increase in pH (i.e., under alkaline conditions) unexpectedly led to an increased release of heavy metals. Changes in redox conditions affect the chemical speciation and solubility of metals. In general, oxidative conditions favor the adsorption of metals [39], while, under reducing conditions, certain metals (e.g., iron and manganese) can be released from oxides, increasing the proportion of dissolved metals [48,49]. However, this pattern is not consistent with observations in the Pearl River Estuary.

3.7. Multiple Regression Analysis

A multiple regression analysis between the log-transformed metal distribution coefficients and the aquatic environmental parameters was performed to evaluate the influence of environmental factors on metal distribution in more detail. The results of the multiple regression analysis are shown in Table 5. To facilitate a comparison of the relative significance of the aquatic environmental parameters, the coefficients in the table are standardized (Beta coefficients). For the coefficients and models that did not pass the significance test, this is, of course, only an indication. Overall, the metals that are most sensitive to environmental factors in terms of their partition coefficients are Mn, Fe, Co, and Mo (R2 > 0.8), followed by Ni and Zn (R2 > 0.6). Oxygen content, temperature, and water depth are the most important factors influencing metal partitioning. Surprisingly, pH, salinity, and suspended solids have no significant influence on metal partitioning in the Pearl River Estuary. Changes in salinity can affect the complexation and adsorption behavior of metals. With increasing salinity, metal ions may form complexes with chloride ions and other substances, increasing their dissolved concentration [35,50]. Salinity and the concentration of suspended solids can influence the flocculation process [44] and thus affect the partitioning of metals.
In particular, water depth has a significant negative influence on the partitioning of Fe and Co, while temperature and oxygen content have a highly significant negative influence on their partitioning. In deeper, high-temperature, and oxygen-rich environments, Fe and Co are more likely to be present in the dissolved phase. Although the environmental factors have no significant influence on the partitioning of Mn between the particulate and dissolved phase, the model (R2 = 0.838***) explains the distribution of Mn quite well. From the results of the factor analysis in Part 1, it can be concluded that the partitioning of Mn is influenced by environmental factors, although this factor is outside the scope of this study. The oxygen content has a significant negative effect on the Mo concentration, and the model (R2 = 0.921***) shows an extremely strong explanatory power for the Mo partitioning, indicating that the Mo distribution is strongly impacted by aquatic environmental factors. The partitioning of Ni and Zn is also significantly affected by environmental factors.
In addition to the environmental factors investigated in this work, the partitioning of metals is, of course, also influenced by a variety of other factors. The behavior of metals in estuaries is usually not conservative and is influenced by the interaction between environmental gradients and metal sources [51]. The sources of metals are often complex. For example, Fe, Cu, and Zn may originate from sources such as brake abrasion, road dust, and industrial emissions [52], while Cr, Fe, Cu, Zn, and Pb may be associated with the transportation industry [53]. The sources include natural processes such as rock weathering and human activities such as metallurgy, electroplating, and industrial processes such as tanning [33]. In the Jiao Men Channel of the Pearl River Estuary [54], the use of agricultural chemicals such as phosphorus fertilizers, fungicides, and pesticides is the main source of Cd and Cu contamination in sediments. Pb originates primarily from transportation, e.g., from vehicle emissions, the use of lead-acid batteries, and thermal power generation. Zn, Fe, and Mn are closely linked to industrial activities, particularly wastewater discharges from sectors such as steel production, mechanical engineering, electronics, chemicals, and manufacturing. Ni, Cr, and Co mainly originate from the natural weathering of the minerals in the source material.
The physicochemical properties of estuaries, such as salinity, density, current velocity, and the composition of suspended matter, have a considerable influence on the behavior of metals. Organic matter can form complexes with metals and thus increase the proportion of metals in the dissolved phase. In addition, the decomposition of organic substances can change the redox conditions, which further influences the partitioning of metals [55]. Hydrodynamic conditions such as flow velocity and turbulence intensity can affect the settling and resuspension of particles and thus the partitioning of metals between the particulate and dissolved phases [56]. The electrical conductivity (EC) has a considerable influence on the desorption behavior of heavy metals. An increase in conductivity (i.e., a rise in ion concentrations within the aquatic environment) generally promotes the dissolution and bioavailability of heavy metals [47]. In estuarine areas, total phosphorus (TP) has a greater influence on the adsorption of heavy metals than total organic carbon (TOC). In estuarine areas, the higher concentration of TP promotes the adsorption of heavy metals such as Pb and Cu [47]. In addition, mineral composition has a significant influence on the adsorption of metals [47].

4. Conclusions

In this two-paper series work, the authors analyze the concentrations, spatial distribution characteristics, partitioning, and relevant driving factors of metals (Cu, Cr, Pb) in both their particulate phase and dissolved phase in the Pearl River Estuary. In Part 1, the authors focused on the analysis of particulate and dissolved metals. In Part 2, we conduct a comprehensive comparison of particulate and dissolved metals and also analyzed the distribution behavior of metals between their particulate and dissolved phases in the Pearl River Estuary and the factors influencing this. The following conclusions were drawn:
(1)
Elevated concentrations of particulate metals are predominantly found towards the Humen area, and particulate metals tend to exhibit higher concentrations near the Hong Kong-Zhuhai-Macao Bridge. The distribution of dissolved metals is hardly affected by the bridge, although high concentrations of certain metals, including Fe, Mo, and Ni, are observed not only in the Humen direction, but also towards the ocean.
(2)
Significant correlations between metals and environmental factors are observed more frequently in the particulate form.
(3)
The metals in the Pearl River Estuary are predominantly present in their dissolved form, with the except of Mn, whose concentration in suspended particulate matter is higher than that in filtered water.
(4)
The spatial distribution of metal partition coefficients shows a distinct clustering pattern: In the Pearl River Estuary, the partition coefficients of metals such as Fe, Mo, Mn, Ni, Co, and Zn show a clear spatial clustering, possibly related to local geochemical processes or human activities. In particular, a high-value clustering of certain metals (such as Fe, Mo, Mn, and Zn) is observed in the vicinity of Humen and the Hong Kong-Zhuhai-Macao Bridge, while some metals (such as Tl and Pb) are mainly concentrated in the oceanic direction, further away from land.
(5)
The partition coefficients of metals (Mn, Fe, Co, Ni, Zn, and Mo) show significant correlations with those of other metals (≥5 metals) and are strongly influenced by environmental factors, indicating a strong sensitivity to these factors. In contrast, the partition coefficients of Cr, Cu, Cd, Tl, and Pb show lower correlations with both the partition coefficients of other metals and environmental factors.
(6)
Temperature, oxygen content, and water depth are the most important determinants of metal distribution dynamics in the Pearl River Estuary, while the effects of pH, salinity, and suspended solids concentration on metal partitioning are relatively small.
This study analyzes the distribution of metals in the particulate phase and dissolved phase in the Pearl River Estuary and identifies the main environmental factors influencing the partitioning of metals. The results provide scientific support for regional water quality management and metal pollution control. By thoroughly investigating the relationship between the spatial distribution of metals and aquatic environmental parameters, this study provides valuable insights for future environmental protection measures and pollution source tracking.

Author Contributions

Conceptualization, Y.Z., C.C. and Y.W.; methodology, Y.Z., C.C. and Y.W.; resources, Y.Z., C.C. and Y.W.; project administration, Y.W., C.C. and Y.Z.; funding acquisition, Y.W., C.C. and Y.Z.; software, H.M.; validation, Y.W.; formal analysis, H.M.; investigation, H.M. and C.C.; data curation, H.M.; writing—original draft preparation, H.M.; writing—review and editing, Y.W.; visualization, H.M.; supervision, Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The Natural Science Foundation of China, grant number U1901215, and the Natural Science Fund of Guangdong Province, grant number 2021A1515011375.

Data Availability Statement

Data available on request.

Acknowledgments

The authors express their gratitude to Ye Feng and Wei Gangjian’s team in GIGCAS for their support during the sampling process.

Conflicts of Interest

The authors confirm that there are no conflicts of interest.

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Water 17 01436 g001
Figure 1. Distribution of sampling stations in the Pearl River Estuary [1].
Figure 1. Distribution of sampling stations in the Pearl River Estuary [1].
Water 17 01436 g001
Water 17 01436 g002
Figure 2. The local spatial patterns of log(Kd) values for metals in the Pearl River Estuary. Subfigures (a–k) illustrate individual metals: (a) Cd, (b) Co, (c) Cr, (d) Cu, (e) Fe, (f) Mn, (g) Mo, (h) Ni, (i) Pb, (j) Tl, and (k) Zn.
Figure 2. The local spatial patterns of log(Kd) values for metals in the Pearl River Estuary. Subfigures (a–k) illustrate individual metals: (a) Cd, (b) Co, (c) Cr, (d) Cu, (e) Fe, (f) Mn, (g) Mo, (h) Ni, (i) Pb, (j) Tl, and (k) Zn.
Water 17 01436 g002
Water 17 01436 g003
Figure 3. Correlation between log(Kd) values of metals and environmental factors. WD: water depth; T: temperature; S: salinity; O: oxygen; TSM: total suspended matter.
Figure 3. Correlation between log(Kd) values of metals and environmental factors. WD: water depth; T: temperature; S: salinity; O: oxygen; TSM: total suspended matter.
Water 17 01436 g003
Table 1. Comparison of metal contents in the suspended particulate phase and dissolved phase in the Pearl River Estuary (ug/L).
Table 1. Comparison of metal contents in the suspended particulate phase and dissolved phase in the Pearl River Estuary (ug/L).
Particulate Dissolved
MetalsRangeMeanRangeMean
Cr0.055–1.2840.591.01–10.254.86
Mn0.19–57.1510.260.78–1.540.98
Fe16.24–659.60227.31190.9–472.09381.94
Co0.0024–0.31680.120.12–0.210.18
Ni0.017–1.8860.463.49–24.218.29
Cu0.020–0.8360.331.08–3.552.10
Zn0.20–3.311.3714.13–48.2821.78
Mo0.0013–0.02460.00904.61–10.638.74
Cd0.0002–0.01710.00360.006–0.0620.026
Tl0.0001–0.01060.00400.015–0.0450.025
Pb0.078–3.3530.652.43–9.644.66
Table 2. Logarithmic values of metal partitioning coefficients (log(Kd)) in the Pearl River Estuary.
Table 2. Logarithmic values of metal partitioning coefficients (log(Kd)) in the Pearl River Estuary.
MetalsRangeMeanCV
Cr3.73–4.774.180.06
Mn5.31–6.705.830.07
Fe4.52–5.304.810.04
Co4.33–5.244.790.05
Ni2.98–4.193.370.11
Cu3.73–4.654.250.04
Zn3.62–4.243.90.04
Mo1.77–2.732.060.12
Cd3.36–4.844.20.09
Tl3.74–4.614.260.04
Pb3.76–4.734.190.06
Note: CV: coefficient of variation.
Table 3. Overview of metal partitioning behavior (log(Kd)) in the Pearl River Estuary and other regions.
Table 3. Overview of metal partitioning behavior (log(Kd)) in the Pearl River Estuary and other regions.
AreasMetricFeMnCrNiCuZnCdPbCo
our resultsMean4.815.834.183.374.253.904.204.194.79
Zhanjiang Bay [19]Mean5.325.214.734.693.674.405.145.60
Day River [16]Mean5.8 5.0 5.5 5.3 5.4 5.1 5.7 5.3 5.6
our resultsRange4.52–5.305.31–6.703.73–4.772.98–4.193.73–4.653.62–4.243.36–4.843.76–4.734.33–5.24
Jiaozhou Bay [40]Range 3.8–4.91.9–4.72.2–5.02.8–5.4
Scheldt Estuary [41]Range 4.3–5.44.5–5.05.5–6.45.4–6.0
Six Texas Estuaries [42]Range4.7–7.2 3.0–5.13.8–6.0 3.8–6.8
North Australian [43]Range5.7–8.8 3.8–5.33.7–5.44.4–6.73.3–6.35.5–7.2
Table 4. Global Moran’s I for assessing spatial patterns in log(Kd) values of metals in the Pearl River Estuary.
Table 4. Global Moran’s I for assessing spatial patterns in log(Kd) values of metals in the Pearl River Estuary.
MetalsMoran’s I Indexz-Scorep-Value
Cr0.212 1.083 0.279
Mn0.523 2.271 0.023
Fe0.609 2.600 0.009
Co0.401 1.760 0.078
Ni0.559 2.347 0.019
Cu0.257 1.364 0.173
Zn0.418 1.785 0.074
Mo0.731 3.307 0.001
Cd0.269 1.230 0.219
Tl−0.067 −0.037 0.971
Pb−0.251 −0.720 0.471
Table 5. Multiple regression coefficients for metal log(Kd) values and aquatic environmental parameters in the Pearl River Estuary.
Table 5. Multiple regression coefficients for metal log(Kd) values and aquatic environmental parameters in the Pearl River Estuary.
Depth of WaterTemperature SalinityOxygenpHSuspended Solids R2
Cr−0.37 0.31 −0.03 0.16 −0.39 0.19 0.266
Mn−0.07 −0.33 −0.52 −0.42 0.24 −0.15 0.838 ***
Fe−0.45 * −1.08 ** 0.78 −1.58 *** 0.89 −0.23 0.870 ***
Co−0.45 * −1.07 ** 0.87 −1.35 ** 0.63 −0.18 0.849 ***
Ni0.01 0.43 −0.65 0.77 −1.17 0.13 0.708 **
Cu−0.14 −0.74 1.61 −0.94 −0.51 −0.41 0.235
Zn−0.18 0.08 −0.01 −1.07 0.32 −0.04 0.642 **
Mo0.06 −0.40 −0.55 −0.90 ** 0.72 −0.16 0.921 ***
Cd0.44 0.96 −1.31 1.01 −0.83 0.01 0.263
Tl−0.34 −1.47 * 1.97 −1.63 0.80 −0.03 0.334
Pb−0.26 −0.11 −0.27 −0.88 1.12 −0.34 0.185
Notes: The coefficients in the table are standardized. * Significance levels: p < 0.1 (*); p < 0.05 (**); p < 0.01 (***).
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Ma, H.; Wang, Y.; Chen, C.; Zhang, Y. Particulate and Dissolved Metals in the Pearl River Estuary, China—Part 2: Partitioning Characteristics and Influencing Factors. Water 2025, 17, 1436. https://doi.org/10.3390/w17101436

AMA Style

Ma H, Wang Y, Chen C, Zhang Y. Particulate and Dissolved Metals in the Pearl River Estuary, China—Part 2: Partitioning Characteristics and Influencing Factors. Water. 2025; 17(10):1436. https://doi.org/10.3390/w17101436

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Ma, Hongyan, Yunpeng Wang, Chuqun Chen, and Yuanzhi Zhang. 2025. "Particulate and Dissolved Metals in the Pearl River Estuary, China—Part 2: Partitioning Characteristics and Influencing Factors" Water 17, no. 10: 1436. https://doi.org/10.3390/w17101436

APA Style

Ma, H., Wang, Y., Chen, C., & Zhang, Y. (2025). Particulate and Dissolved Metals in the Pearl River Estuary, China—Part 2: Partitioning Characteristics and Influencing Factors. Water, 17(10), 1436. https://doi.org/10.3390/w17101436

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