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Article

Vertical Binding Characteristics Between Dissolved Organic Matter and Heavy Metals in the Upper Reaches of the Yangtze River Using EEM-PARAFAC and 2D-FTIR-COS

by
Xihuan Wang
1,2,†,
Tiansen Zou
1,2,†,
Weibo Zhang
2,
Yili Fan
1,2 and
Yingchen Bai
1,2,*
1
College of Water Sciences, Beijing Normal University, Beijing 100875, China
2
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Water 2025, 17(9), 1359; https://doi.org/10.3390/w17091359
Submission received: 3 April 2025 / Revised: 24 April 2025 / Accepted: 29 April 2025 / Published: 30 April 2025
(This article belongs to the Special Issue Water Environment Pollution and Control, 4th Edition)
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Abstract

:
Dissolved organic matter (DOM) exerts a significant influence on the environmental behavior of heavy metals in water. This study investigated the spatial distribution characteristics of DOM in the upper reaches of the Yangtze River and its vertical (0–10 m) binding behavior with heavy metals. The results indicated that humic acid-like substances dominated the DOM composition in the river water, exhibiting spatial variability horizontally, with a higher proportion of protein-like components observed at the depth of 8 m. The DOM showed complexation affinity (LogK) values were 4.71–6.38 for Cu2+ and 4.27–6.26 for Hg2+, with the protein-like component C3 exhibiting higher LogK values when binding with Cu2+ or Hg2+ compared to humic-like components. The LogKCu and LogKHg varied distinctly with water depth, and at 8 m depth, humus-like component C1 exhibited stronger binding affinity for Hg2+, whereas protein-like component C3 showed greater affinity for Cu2+. The 2D-FTIR-COS analysis revealed that, in the DOM-Cu complexes, DOM from surface water preferentially bound to O-H groups of carbohydrates, phenols, and carboxylic acids, while deep water DOM favored C=O groups in amides; for DOM–Hg complexes, the active binding sites varied distinctly with depth. This study provides novel insights into the migration and transformation mechanisms of heavy metals in rivers.

1. Introduction

Dissolved organic matter (DOM) is a crucial component of aquatic systems, playing a significant role in carbon cycling, pollutant transport, and ecological risk regulation in water environments [1,2]. DOM in aquatic environments primarily originates from terrestrial inputs, the decomposition of aquatic plant residues, the release of phytoplankton metabolites, and microbial degradation [3]. Depending on its source, DOM exhibits significant differences in composition and structure, which in turn affect its environmental behavior and ecological functions [4,5]. Through mechanisms such as complexation, adsorption, and solubilization, DOM plays a crucial role in regulating the migration, transformation, bioavailability, and ecotoxicity of pollutants, especially heavy metals (HMs) [6]. The study of the complexation between DOM and HMs in surface water remains a focus [7,8]. However, research on the influence of DOM with depths on heavy metals in rivers remains limited.
Copper and mercury from industrial emissions, mining, agricultural activities, and other sources enter aquatic environments, posing potential hazards to ecosystems and human health, with their ecotoxicity, bioavailability, and migration and transformation largely determined by their chemical forms [9,10]. Copper and mercury primarily exist in free, complexed, and particulate forms, with the free forms typically being more readily absorbed by aquatic organisms and exhibiting higher biotoxicity [11,12]. DOM is rich in active functional groups, such as carboxyl and phenolic hydroxyl groups, which can form stable complexes with copper and mercury, thereby significantly altering their speciation and influencing their ecological behavior and toxic effects [13]. Due to human activities and natural processes, the properties of DOM exhibit dynamic temporal and spatial heterogeneity, resulting in significant variations in its binding capacity and the bioavailability of heavy metals across different regions and depths of aquatic environments [14]. Previous studies have shown that DOM sources vary significantly across different areas of rivers, with surface waters typically dominated by terrestrial inputs and phytoplankton metabolites, while deep waters are primarily influenced by microbial degradation products [15,16]. These differences in DOM origin and composition may directly impact the complexation mechanisms between DOM and heavy metals [6]. However, the complexation mechanisms between DOM and heavy metals with depth in rivers remain unclear. Therefore, it remains essential to further investigate the depth-dependent characteristics of DOM in water and their influence on the complexation behavior of copper and mercury in order to more accurately predict the migration, transformation, and fate of heavy metals in real aquatic environments.
DOM in river water at different depths is rich in functional groups such as phenols, aliphatics, aromatics, and polysaccharides, which are capable of forming complexes with HMs [17,18,19]. Currently, most research focuses on the binding sequence, sites, and capacity between DOM and HMs in surface waters of rivers and lakes, while studies on the functional group characteristics and complexation mechanisms of DOM at different depths in river waters remain limited [20,21,22]. In addition, the molecular structure and properties of DOM at different depths undergo dynamic changes due to photochemical degradation, microbial transformation, adsorption–desorption, and aggregation-sedimentation processes, further influencing its complexation behavior with HMs [23,24]. EEM-PARAFAC effectively separates different fluorescent components and quantifies their binding affinity with heavy metals, and 2D-FTIR-COS reveals the binding sequence and sites of DOM functional groups interacting with HMs, demonstrating that spectroscopic techniques are essential tools for analyzing the composition and environmental behavior of DOM [25,26]. The combined application of these spectroscopic techniques provides key parameters for constructing more accurate heavy metal migration and transformation models and offers an effective method for revealing the active binding sites of DOM and its binding characteristics with heavy metals in river water at different depths. This approach can be applied in water quality assessment and pollution control planning, aiding the development of more precise strategies to mitigate heavy metal pollution and protect river ecosystem health.
The upper reaches of the Yangtze River have complex ecosystems that are sensitive to environmental changes and serve as a critical source for water environment protection and ecological risk prevention in the Yangtze River Basin [27,28]. Studying the complexation mechanisms between DOM and copper and mercury in water with depths in this region is crucial for understanding the environmental behavior of HMs in the basin, assessing ecological risks, and formulating effective pollution control strategies. Therefore, fluorescence analysis and fluorescence titration experiments were conducted on water samples from different depths in the upper reaches of the Yangtze River using methods such as EEM-PARAFAC and 2D-FTIR-COS. The objectives of this study are (1) to investigate the fluorescent components and spatial characteristics of aquatic DOM in the upper reaches of the Yangtze River; (2) to analyze the binding capacity of DOM with copper and mercury with depths (0–10 m); and (3) to elucidate the binding sequence of DOM functional groups with these heavy metals across different depths. This provides a crucial foundation for watershed ecological risk assessment and pollution control, while offering a new perspective on understanding biogeochemical processes in complex aquatic environments.

2. Materials and Methods

2.1. Study Area and Sample Collection

The Yangtze River is the longest river in Asia and the third longest river in the world, with a total length of 6300 km [29]. In the past few decades, with the continuous development of cities, industry, and agriculture in the upper reaches of the Yangtze River, a large number of pollutants have entered the water environment, increasing the water pollution load of the river [30]. The upper reaches of this river were selected as the study area, which flows through several cities, including Leshan, Yibin, Luzhou, and Chongqing, from upstream to downstream in the studied river.
A total of 19 surface water samples were collected in August 2022 in the study area (Figure 1), and 12 water samples from various depths (0, 2, 4, 6, 8, and 10 m) were collected at S2 and S9. Among the sampling sites, S1–S8, S9–S12, S13–S16, S17–S19 are located in Chongqing, Luzhou, Yibin, and Leshan areas, respectively. After collection, all samples were passed through a 0.45 µm pore-size filter, stored in pre-cleaned polyethylene bottles treated with nitric acid, and preserved at −4 °C in the dark.

2.2. Fluorescence Quenching Titration

Fluorescence-quenching titrations were conducted to evaluate the binding ability of DOM with Cu2+ and Hg2+ [22,31]. Stock solutions of Cu2+ (0.02 M) and Hg2+ (0.01 M) were prepared using analytical-grade reagents and diluted with ultrapure water to create ten concentration gradients. Subsequently, varying volumes of Cu2+ and Hg2+ solutions were added to 10 mL DOM samples to achieve final concentrations of 0–160 μM and 0–100 μM, respectively, with 10 mL ultrapure water serving as the blank control. In order to ensure the complexation effect of DOM and HMs, KCl solution was added to all samples with a final concentration of 10 Mm [32]. Finally, all solution samples were shaken in the dark at room temperature for 24 h to attain complexation equilibrium [33].

2.3. Measurements of Optical Properties

The UV–visible absorption spectra of water samples were measured using a UV-2550 spectrophotometer across the wavelength range of 200–800 nm, with data collected at 1 nm intervals. Dissolved organic carbon (DOC) of all samples was measured using a TOC-Vcph analyzer (Kyoto, Japan, Shimadzu). Excitation–emission matrix (EEM) spectroscopy of water samples was conducted at room temperature using an F-7000 fluorescence spectrometer (Kyoto, Japan, Shimadzu). EEM spectra were obtained by scanning emission (Em) and excitation (Ex) wavelengths both in 2 nm intervals, ranging from 250–550 nm and 230–400 nm, respectively. The slit widths for both Ex and Em were set to 5 nm, and the scanning rate and voltage were configured at 2400 nm min−1 and 650 V, respectively. The PARAFAC model was applied using the DOMFluor toolbox in MATLAB R2017b to analyze the fluorescence EEMs of 137 water samples from the upper reaches of the Yangtze River, with the results validated through residual and split-half analysis [34,35]. The freshness index (β:α), fluorescence index (FI), biological index (BIX), and humification index (HIX) were derived from the EEM data to assess the source and humification degree of DOM.
The titrated DOM samples were freeze-dried, finely ground, and mixed with spectral-grade KBr at a 1:100 ratio. The mixture was then pressed under a pressure of 10–12 kPa to form crystal wafers. Fourier transform infrared spectra were measured with baseline correction over 30 scans in the range of 4000–500 cm−1 at a resolution of 4 cm−1.

2.4. Metal-DOM Binding Modeling

To evaluate the binding ability of DOM with Cu2+ and Hg2+ using the modified Ryan–Weber equation as Equation (1) [36]:
F = 100 + F e n d − 100 2 K C L K C L + K C Q + 1 − K C L + K C Q + 1 2 − 4 K 2 C L C Q
where F is the percentage of Fmax at the metal concentration CQ and without added metal, respectively. Fend represents the limiting value below which fluorescence intensity remains unchanged despite further addition of metal. K and CL denote the conditional binding constant and total concentration of binding sites, respectively. SigmaPlot 14.0 was used to solve for Fend, K, and CL.

3. Result and Discussion

3.1. Characteristics of DOM in the Upstream of the Yangtze River

The DOC concentration in the upper reaches of the Yangtze River was 1.18–2.46 mg/L, with an average of 1.79 mg/L. The horizontal distribution of DOC showed a trend of initially decreasing and then increasing from upstream to downstream, with Chongqing City exhibiting the highest concentration at 2.00 ± 0.38 mg/L and Yibin City the lowest at 1.53 ± 0.13 mg/L (Figure S1). Compared to the previous year, the DOC concentration observed in this study was higher, which may be attributed to the extremely dry weather conditions [37]. In terms of vertical distribution, the DOC concentrations at sites S2 and S9 (0–10 m) were 1.61 ± 0.06 mg/L and 1.26 ± 0.05 mg/L, respectively, showing minimal variation with depth.
The spectral characteristics of the three components were identified by EEM-PARAFAC analysis in the upper Yangtze River (Figure 2, Table S1). Based on the OpenFluor database, components C1 and C2 had Ex/Em maxima at (265, 345)/450 nm and (255, 310)/395 nm, resembling humic-like matters [38,39,40]. The component C3 with Ex/Em maxima at 275/325 nm was categorized as the protein-like (tryptophan-like) substance [41,42]. Components C1 and C2 accounted for 61.72% ± 6.02% of the DOM (Figure S2), indicating that DOM was primarily dominated by humic-like substances. The a250/a365 value was 4.14–12.08, with an average value of 6.74 ± 1.81 (Figure 3a). The a250/a365 ratios of water samples from Chongqing and Yibin exhibited a relatively wider range, suggesting more complex sources of DOM in these regions [43]. The lower a253/a203 (0.05 ± 0.01) in the river (Figure 3b) suggested that DOM primarily contains non-polar substituents on benzene rings, such as aliphatic chains and esters [44]. For horizontal distribution, the values of FI, BIX, β:α, and HIX were as follows: 2.31 ± 0.12, 0.83 ± 0.06, 0.80 ± 0.07, and 0.77 ± 0.09 for Chongqing; 2.18 ± 0.03, 0.83 ± 0.07, 0.80 ± 0.06, and 0.83 ± 0.02 for Luzhou; 2.21 ± 0.06, 0.78 ± 0.05, 0.77 ± 0.05, and 0.84 ± 0.10 for Yibin; and 2.56 ± 0.38, 1.00 ± 0.10, 0.92 ± 0.08, and 0.74 ± 0.03 for Leshan, respectively (Figure 3c–f). And FI, BIX, and β:α values were significantly higher in Leshan. However, HIX showed an opposite trend to these fluorescence indices, indicating that the downstream region exhibits stronger humification characteristics.
The Fmax of DOM components at different depths is shown in Figure 4a. For both sites S2 and S9, the Fmax of DOM was lowest in the surface layer, a pattern consistent with observations from Lake Baihua [45]. Photodegradation of DOM by solar radiation is generally considered the dominant process at the water surface [46,47], which may explain the lower abundance of DOM components in the surface layer compared to deeper waters. Humic acid-like components (C1 and C2) showed no significant variation with depth, whereas the protein-like substance (C3) exhibited distinguishable differences across depths. The Fmax of component C3 reached its maximum at a depth of 8 m at both S2 and S9, and its marked variation with depth highlights the higher instability and bioavailability of this protein-like component [48,49].
The ranges of FI, BIX, β:α, and HIX were 2.15–2.42, 0.71–0.90, 0.71–0.87, and 0.66–0.99, respectively (Figure 4b). The FI values of DOM at both S2 and S9 were above 1.4, indicating a predominant contribution from microbial sources [50]. Notably, DOM at S2 exhibited higher BIX values (0.85–0.90) compared to S9 (0.72–0.77), indicating a greater contribution of autochthonous sources at S2 [51]. The β:α values of DOM at S2 (0.80–0.87) were higher than those at S9 (0.71–0.75), suggesting a higher proportion of fresh DOM at S2 [32]. The HIX values of DOM at S2 (0.66–0.79) were lower than those at S9 (0.81–0.99) within the 0–10 m depth range, indicating a higher degree of humification at S9 [37]. Overall, variations in the fluorescence indices revealed distinct depth-dependent heterogeneities in the aromaticity and spectral properties of riverine DOM. These differences may influence metal-binding abilities, as aromaticity and spectral characteristics are key factors governing metal-DOM complexation [52,53].

3.2. Evolution of Binding Ability of HMs and DOM

The fluorescence intensity of each DOM component at different depths changed following the addition of Cu2+ or Hg2+, indicating that DOM interacted with the heavy metals in the river (Figure 5 and Figure 6). For component C1, Cu2+ exhibited a strong quenching effect (55.8%), whereas Hg2+ showed a comparatively weaker quenching effect (33.0%), which is consistent with findings from the previous study [54]. Both heavy metals showed strong quenching effects with the component C3 (over 60%), due to the aromatic rings and oxygen-containing functional groups (e.g., phenolic hydroxyl and carboxyl) in protein-like components, which provide multiple binding sites for stable coordination with metal ions, thereby enhancing their metal-binding affinity [55,56]. In addition, at a depth of 10 m, the fluorescence intensity of component C3 increased with increasing concentrations of Cu2+ and Hg2+, which was because the metal ions stimulated the chromophore of DOM [36,57]. The a253/a203 increased with the addition of Cu2+, indicating a reduction in aliphatic chain substituents and an increase in carbonyl, carboxyl, and ester group substituents on aromatic compounds within DOM at different depths [58]. In contrast, the addition of Hg2+ led to a decreasing trend, suggesting a distinct binding mechanism compared to Cu2+.
During the addition of Cu2+ or Hg2+, the fluorescence intensity of most components progressively decreased, suggesting significant fluorescence quenching of DOM (Figure 5 and Figure 6). The quenching constant (LogK) for each component was calculated using the modified Ryan–Weber equation to assess the quenching capacity. The values of LogKCu and LogKHg were 4.71–6.38 and 4.27–6.26, respectively, aligning with the ranges reported in previous studies [8,59]. DOM can form complexes with metal ions, thereby enhancing their mobility and reducing the associated environmental risks, which aligns with the findings observed in river sediments [60]. The LogK value of DOM–Hg was comparable to that of DOM–Cu, suggesting that Hg2+ exhibited a similar stability to Cu2+ in aquatic environments, and their potential environmental risks were also of a similar magnitude.
The orders of LogKCu and LogKHg for DOM components at different depths were C3 > C2 > C1 (5.55 ± 0.36 > 5.53 ± 0.37 > 5.16 ± 0.30) and C3 > C1 > C2 (5.79 ± 0.32 > 5.11 ± 0.19 > 4.77 ± 0.22), respectively (Figure 4c,d, Table 1). The order of LogKHg values for the components remained consistent between the downstream area (S2) and the upstream area (S9), while the LogKCu values exhibited variations between the two locations. The LogKCu of the protein-like component C3 was highest for S2, while the humic acid-like component C2 exhibited the greatest LogKCu for S9. This difference was attributed to spatial variations in DOM composition, with the downstream area being enriched in protein-like substances from biological sources, whereas the upstream area contains a higher proportion of humic substances derived from terrestrial inputs [61]. The LogKCu of components C1 and C3 in the downstream area (S2) were higher than those in the upstream area (S9), whereas the LogKHg values showed no significant difference between the two locations. Overall, copper and mercury displayed notable differences in their binding affinities with DOM, with Cu2+ primarily forming inner-sphere complexes, whereas Hg2+ more commonly forms outer-sphere complexes [54,62].
The affinity of protein-like substances (C3) for Cu2+ and Hg2+ was stronger than that of humic-like substances (C1 and C2), indicating that C3 played a key role in the environmental behavior of HMs [63]. The markedly higher binding constant of Cu2+ with component C2, compared to that of Hg2+, was attributed to the smaller ionic radius and paramagnetism of Cu(II), along with its strong coordination ability with organic ligands [64]. Variations in the LogKCu and LogKHg values of each DOM component with depth may be associated with hydrodynamic disturbances induced by shipping [65]. At the depth of 8 m, the humus-like component C1 demonstrated stronger binding with Hg2+, while the protein-like component C3 exhibited greater affinity for Cu2+, which was attributed to the distinct coordination preferences of Hg2+ and Cu2+ for different DOM functional groups [20,66].

3.3. Analysis of Binding Sequence of HMs and DOM Combined with FTIR

The Fourier transform infrared (FTIR) spectra of DOM following the addition of Cu2+ or Hg2+ exhibited seven distinct absorption bands, with characteristic peaks observed at 3420, 1636, 1430, 1140, 870, 660, and 600 cm−1 (Figure 7). The absorption band at 3420 cm−1 was attributed to O–H stretching vibrations from carbohydrates, phenols, and carboxylic acid compounds [67]. The peak at 1636 cm−1 corresponded to the C=O stretching vibration characteristic of the amide [68]. The signal at 1430 cm−1 was assigned to the deformation vibration of aromatic N=O groups [8,69]. The absorption bands observed at 1140 and 870 cm−1 were attributed to the stretching vibration of aliphatic C–OH and aromatic C–H, respectively [68,70]. The peaks at 660 and 600 cm−1 corresponded to alkyl halides and carboxyl –OH, respectively [70,71].
To investigate the binding order between HMs and functional groups of DOM, 2D-FTIR-COS analysis in the 4000–400 cm−1 region was performed on water samples collected from different depths at the site S9 (Figure 8). The results showed that both the synchronous and asynchronous spectra of the water samples exhibited noticeable variations with depth, indicating that the binding sequence between DOM and heavy metals differed across depth gradients. According to the previous study [72], the binding sequence of DOM functional groups in surface water with Cu2+ followed the order: O–H groups from carbohydrates, phenols, and carboxylic acids > C=O in the amide > aromatic C–H > C–OH of alkyl halides > C–OH of carboxyl groups > aromatic N=O > aliphatic C–OH (3420 > 1636 > 870 > 660 > 600 > 1430 > 1140 cm−1). At the depth of 4 m, the binding sequence was C=O in the amide > aromatic C–H > O–H from carbohydrates, phenols, and carboxylic acids > aromatic N=O > C–OH of alkyl halides > –OH of carboxyl groups > aliphatic C–OH (1636 > 870 > 3420 > 1430 > 660 > 600 > 1140 cm−1). At the depth of 8 m, the affinity sequence was C=O in the amide > aliphatic C–OH > aromatic C–H > C–OH of alkyl halides > aromatic N=O > –OH of carboxyl groups (1636 > 1140 > 870 > 660 > 1430 > 600 cm−1).
As for DOM-Hg, the binding sequence in surface water was as follows: O–H groups from carbohydrates, phenols, and carboxylic acids > aromatic C–H > C=O in the amide > aliphatic C–OH > C–OH of alkyl halides > –OH in carboxyl groups > aromatic N=O (3420 > 870 > 1636 > 1140 > 660 > 600 > 1430 cm−1). At the depth of 4 m, the binding sequence was C–OH of alkyl halides > –OH in carboxyl groups > C=O in the amide and aliphatic C–OH > aromatic C–H and aromatic N=O (660 > 600 > 1636, 1140 > 870, 1430 cm−1). At the depth of 8 m, the binding sequence was aromatic C–H and aliphatic C–OH > –OH in carboxyl groups > C–OH of alkyl halides and aromatic N=O > C=O in the amide (870, 1140 > 600 > 660, 1430 > 1636 cm−1).
In surface water, Cu2+ and Hg2+ preferentially bound to O–H groups from polysaccharides, phenols, and carboxylic acids. In deep water (4 and 8 m), copper preferentially combined with the amide C=O, while mercury preferentially bound to alkyl halides at the depth of 4 m and to aromatic C–H and aliphatic C–OH groups at the depth of 8 m. These changes may be attributed to variations in redox conditions or ionic strength with depth [73]. Overall, the binding order of Cu2+, Hg2+, and DOM functional groups in water samples exhibited depth dependence, suggesting that the interaction mechanisms between DOM and heavy metals vary with depth. This variation may be closely linked to factors such as the chemical environment of the water body and the source and composition of DOM [45,74]. These results highlight the important role of water depth in the combination between DOM and heavy metals.

4. Conclusions

The study employed EEM-PARAFAC and 2D-FTIR-COS to investigate the spatial distribution characteristics of DOM in the upper reaches of the Yangtze River and its binding behavior with Cu2+ and Hg2+ at varying water depths (0–10 m). The results indicated that DOM was predominantly humic acid-like; however, significant compositional variations were observed across both vertical and horizontal gradients, particularly in the protein-like component C3. The protein-like component C3 exhibited a higher binding affinity for both Cu2+ and Hg2+, with the metal-binding behavior of DOM displaying a distinct depth-dependent pattern. In addition, the active binding sites involved in DOM–Cu and DOM–Hg complexation shifted with changes in water depth. These findings enhance our understanding of the migration and transformation of heavy metals in riverine environments and highlight the critical role of DOM in regulating their environmental behavior. This provides support for water environment quality assessment and pollution control, effectively ensuring the ecological health of rivers. In the future, mass spectrometry and nuclear magnetic resonance techniques should be applied to explore the binding mechanisms of DOM and heavy metals at the molecular level.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w17091359/s1. References [34,35,38,39,40,41,42,43,58,75] are cited in Supplementary Materials.

Author Contributions

Conceptualization, X.W., T.Z. and Y.B.; Methodology, Y.F.; Software, W.Z.; Validation, W.Z.; Formal analysis, X.W. and T.Z.; Investigation, X.W.; Writing—original draft, X.W. and T.Z.; Writing—review & editing, Y.B.; Visualization, X.W., T.Z., W.Z. and Y.F.; Funding acquisition, Y.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The Yangtze River Joint Research Phase II Program (No. 2022-LHYJ-02-0402) and National Key Research and Development Program of China (No. 2022YFC3204103–01, No. 2023YFC3208401).

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Conflicts of Interest

The authors declare no conflict of interest.

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Water 17 01359 g001
Figure 1. Water sampling sites in the upstream of the Yangtze River.
Figure 1. Water sampling sites in the upstream of the Yangtze River.
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Figure 2. Three fluorescent components were derived from the PARAFAC analysis, with C1, C2, and C3 representing components 1, 2, and 3, respectively. Red signifies high fluorescence intensity, white indicates a value of zero, and blue denotes the absence of a value.
Figure 2. Three fluorescent components were derived from the PARAFAC analysis, with C1, C2, and C3 representing components 1, 2, and 3, respectively. Red signifies high fluorescence intensity, white indicates a value of zero, and blue denotes the absence of a value.
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Figure 3. Distribution characteristic of fluorescent indexes across different region (a–f). CQ, LZ, YB, and LS refer to DOM samples in Chongqing, Luzhou, Yibin, and Leshan city, respectively.
Figure 3. Distribution characteristic of fluorescent indexes across different region (a–f). CQ, LZ, YB, and LS refer to DOM samples in Chongqing, Luzhou, Yibin, and Leshan city, respectively.
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Figure 4. Values of Fmax of PARAFAC components (a), fluorescence parameters (b), logKCu (c), and logKHg (d) of DOM in Yangtze River with depth. Solid line and dotted lines represented the PARAFAC components of S2 and S9, respectively.
Figure 4. Values of Fmax of PARAFAC components (a), fluorescence parameters (b), logKCu (c), and logKHg (d) of DOM in Yangtze River with depth. Solid line and dotted lines represented the PARAFAC components of S2 and S9, respectively.
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Figure 5. Changes in fluorescence intensity for three components identified by the PARAFAC model after adding different amounts of Cu2+, (a–f) and (h–m) refer to Fmax in S2 and S9, respectively.
Figure 5. Changes in fluorescence intensity for three components identified by the PARAFAC model after adding different amounts of Cu2+, (a–f) and (h–m) refer to Fmax in S2 and S9, respectively.
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Figure 6. Changes in fluorescence intensity for three components identified by the PARAFAC model after adding different amounts of Hg2+, (a–f) and (h–m) refer to Fmax in S2 and S9, respectively.
Figure 6. Changes in fluorescence intensity for three components identified by the PARAFAC model after adding different amounts of Hg2+, (a–f) and (h–m) refer to Fmax in S2 and S9, respectively.
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Figure 7. Fourier transform infrared spectra (FTIR) (4000–400 cm−1) of DOM with different depth after adding Cu2+ and Hg2+, (a,d) refer to FTIR of DOM with depth at 0 m, (b,e) refer to FTIR of DOM with depth at 4 m, (c,f) refer to FTIR of DOM with depth at 8 m.
Figure 7. Fourier transform infrared spectra (FTIR) (4000–400 cm−1) of DOM with different depth after adding Cu2+ and Hg2+, (a,d) refer to FTIR of DOM with depth at 0 m, (b,e) refer to FTIR of DOM with depth at 4 m, (c,f) refer to FTIR of DOM with depth at 8 m.
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Figure 8. Synchronous (a–c) and synchronous (d–f) analysis of the 2D-COS-FTIR spectra of DOM with depth in the range of 4000 cm−1 to 400 cm−1 after the addition of Cu2+; synchronous (g–i) and synchronous (j–l) analysis of the 2D-COS-FTIR spectra of DOM with depth in the range of 4000 cm−1 to 400 cm−1 after the addition of Hg2+; (a,d,g,j) refer to spectra maps with depth at 0 m, (b,e,h,k) refer to spectra maps with depth at 4 m, (c,f,i,l) refer to spectra maps with depth at 8 m. Red and blue indicate positive and negative auto-/cross-peaks, respectively.
Figure 8. Synchronous (a–c) and synchronous (d–f) analysis of the 2D-COS-FTIR spectra of DOM with depth in the range of 4000 cm−1 to 400 cm−1 after the addition of Cu2+; synchronous (g–i) and synchronous (j–l) analysis of the 2D-COS-FTIR spectra of DOM with depth in the range of 4000 cm−1 to 400 cm−1 after the addition of Hg2+; (a,d,g,j) refer to spectra maps with depth at 0 m, (b,e,h,k) refer to spectra maps with depth at 4 m, (c,f,i,l) refer to spectra maps with depth at 8 m. Red and blue indicate positive and negative auto-/cross-peaks, respectively.
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Table 1. Binding constants (logK) of Cu and Hg with components C1, C2, and C3 across different depth.
Table 1. Binding constants (logK) of Cu and Hg with components C1, C2, and C3 across different depth.
SiteComponentsDeepth (m)Cu2+Hg2+
logKFend (%)R2logKFend (%)R2
S2C105.3851.410.924.9764.030.94
25.3551.850.945.2661.410.97
45.4446.170.954.9771.020.97
65.5647.290.895.0162.770.84
85.5051.100.925.5473.000.90
105.0448.380.955.0368.470.98
C205.8566.780.914.5248.210.95
25.0864.570.945.0054.310.97
45.7955.280.944.7356.390.98
65.5364.500.854.9465.570.84
85.1277.120.864.2753.460.97
105.7572.140.974.6756.170.90
C305.7641.270.995.2339.990.88
25.8844.710.976.0140.770.90
45.3430.520.885.4739.870.87
65.6141.360.776.2630.960.90
86.2737.380.975.6537.520.85
105.5339.540.975.8845.030.84
S9C104.8841.790.944.9369.490.86
24.7134.190.965.1368.150.83
44.7134.190.965.0365.840.97
64.8938.850.954.9662.130.87
85.0342.350.955.4268.960.91
105.4642.680.845.0869.180.88
C205.4867.590.944.9966.820.98
25.1567.700.964.8258.040.95
45.3568.000.884.9864.330.96
65.2162.480.964.9859.900.87
85.6556.150.934.7044.940.83
106.3866.920.774.6156.980.92
C304.8126.970.865.9842.370.91
25.5433.710.985.9726.800.92
45.1223.580.946.0537.490.91
65.5336.230.865.4035.170.82
85.6133.350.90-
10--
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Wang, X.; Zou, T.; Zhang, W.; Fan, Y.; Bai, Y. Vertical Binding Characteristics Between Dissolved Organic Matter and Heavy Metals in the Upper Reaches of the Yangtze River Using EEM-PARAFAC and 2D-FTIR-COS. Water 2025, 17, 1359. https://doi.org/10.3390/w17091359

AMA Style

Wang X, Zou T, Zhang W, Fan Y, Bai Y. Vertical Binding Characteristics Between Dissolved Organic Matter and Heavy Metals in the Upper Reaches of the Yangtze River Using EEM-PARAFAC and 2D-FTIR-COS. Water. 2025; 17(9):1359. https://doi.org/10.3390/w17091359

Chicago/Turabian Style

Wang, Xihuan, Tiansen Zou, Weibo Zhang, Yili Fan, and Yingchen Bai. 2025. "Vertical Binding Characteristics Between Dissolved Organic Matter and Heavy Metals in the Upper Reaches of the Yangtze River Using EEM-PARAFAC and 2D-FTIR-COS" Water 17, no. 9: 1359. https://doi.org/10.3390/w17091359

APA Style

Wang, X., Zou, T., Zhang, W., Fan, Y., & Bai, Y. (2025). Vertical Binding Characteristics Between Dissolved Organic Matter and Heavy Metals in the Upper Reaches of the Yangtze River Using EEM-PARAFAC and 2D-FTIR-COS. Water, 17(9), 1359. https://doi.org/10.3390/w17091359

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