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Article

Source Identification and Ecological Risk of Potentially Harmful Trace Elements in Lacustrine Sediments from the Middle and Lower Reaches of Huaihe River

by
Min Xu
1,2,
Rong Wang
1,*,
Weiwei Sun
1,
Dianchang Wang
3 and
Xinghua Wu
3
1
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
2
State Key Laboratory of Palaeobiology and Stratigraphy, Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing 210008, China
3
China Three Gorges Corporation, Wuhan 430010, China
*
Author to whom correspondence should be addressed.
Water 2023, 15(3), 544; https://doi.org/10.3390/w15030544
Submission received: 16 January 2023 / Revised: 25 January 2023 / Accepted: 27 January 2023 / Published: 30 January 2023
(This article belongs to the Special Issue Geochemistry of Water and Sediment III)
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Abstract

:
Sediment pollution caused by potentially harmful trace elements (PHTEs) has attracted a great deal of attention, due to the persistent risks it poses to human beings and ecosystems. However, the pollution status and source identification of PHTEs from the middle and lower reaches of Huaihe River remains unclear. In this study, arsenic, cadmium, chromium, copper, nickel, zinc, lead and isotopic ratios in the lacustrine sediments of this river are investigated to determine the source of, and ecological risk posed by, these PHTEs. The results show that the concentrations of chromium, copper, nickel and zinc are generally close to the background values in the lacustrine sediments, and are assessed as representing a low degree of contamination. By contrast, significantly higher concentrations of arsenic and cadmium are commonly measured in the upper sediments, which are mainly derived from the agricultural application of fertilizers, pesticides and wastewater. Meanwhile, possible atmospheric lead deposition is identified by the isotopic analysis. Among these PHTEs, adverse biological effects of arsenic, chromium, and nickel may occur in lakes according to consensus-based sediment quality guidelines, but cadmium is selected as a PHTE for priority control according to potential ecological risk index. Our study highlights that developing regional sediment quality guidelines and soil restoration in the catchment are crucial for the freshwater ecosystem in the middle and lower reaches of Huaihe River.

1. Introduction

Lakes are one of the most important natural resources, and are crucial in freshwater supply, irrigation, aquaculture, and maintaining regional biodiversity. However, lake ecosystems are directly threatened by anthropogenic activities and climate change, and securing the supply of ecosystem services to support human well-being is one of the great environmental challenges of the 21st century [1,2,3]. Previous studies have confirmed that a large amount of potential harmful trace elements (PHTEs) enter into the lake ecosystems through wastewater discharge, surface runoff and atmospheric deposition resulting from rapid industrialization and agricultural intensification [4,5]. On one hand, PHTEs can be strongly accumulated in sediments, thus lowering their concentration in the water column [6]. On the other hand, PHTEs could also be released into the water in response to certain disturbances, posing a potential threat to the health of human well-being [7,8]. Therefore, understanding the source of, and ecological risk posed by, PHTEs in sediments is necessary in order to evaluate lake ecosystem safety [9,10].
Geochemical analyses and related indices such as geo-accumulation index (Igeo), potential ecological risk index (PERI) and sediment quality guidelines (SQGs) were proposed to assess anthropogenic impact and ecological risk in the lacustrine setting [4,11,12,13]. However, results might vary significantly in relation to the reference natural background due to the influence of local geochemical properties and natural variability [4]. In addition, stable isotopic compositions of PHTEs have also been useful to trace and quantify the natural and anthropogenic sources among complex environmental matrices because these isotopes are not significantly affected by fractionation processes [14,15,16,17,18,19]. Therefore, results are more reasonable when multiple analyses are combined to identify the pollution source and assess the ecological risk of PHTEs.
The reach of Huaihe River is an important agricultural base with high population density, providing ~20% of the grain yield in China [20]. Intensive anthropogenic activities have significant impacts on freshwater eutrophication through untreated wastewaters as well as non-point sources from aquaculture and agriculture [21,22,23,24,25,26]. The freshwater and sediment quality of the reach of Huaihe River is of particular concern due to the eastern route of South-to-North Water Transfer Project, which links a chain of natural lakes such as Lake Gaoyou, Lake Hongze and Lake Nansihu [21,26]. However, the pollution of PHTEs has been less well addressed compared with eutrophication, and the influence of anthropogenic activity is not well known. In this study, seven critical PHTEs, including arsenic (As), chromium (Cr), copper (Cu), cadmium (Cd), nickel (Ni), zinc (Zn), lead (Pb) and its isotopic ratios in the lacustrine sediments from the middle and lower reaches of Huaihe River (MLRHR) are analyzed. Specific aims of the study included: (1) characterization of geochemistry and Pb isotopes; (2) identification of PHTE sources; and (3) evaluation of the ecological risk in these lacustrine sediments.

2. Materials and Methods

2.1. Study Region

The Huaihe River is one of the seven major rivers in China. It has a total drainage area of ~2.7 × 105 km2, and is situated between the Yellow River and the Yangtze River (Figure 1). The mean annual precipitation is 920 mm; more than 60% falls during the season from April to October [20,27]. The Huaihe River basin mostly consists of plains and swales, except for some mountainous and hilly terrain in the northern and southwestern areas. Gneiss migmatite and schist are primarily distributed in the mountains, and unconsolidated Quaternary sediments are distributed over the plains and swales [27,28]. The Yellow River invaded the Huaihe River many times throughout history, and discharged abundant silt from the Chinese Loess Plateau to the alluvial plain [29].

2.2. Sample Collection and Geochemical Analysis

In September 2019, seven gravity cores were recovered using a gravity corer from Lake Huayuan, Lake Tuohu, Lake Nüshan, Lake Hongze, Lake Baima, Lake Gaoyou and Lake Shaobo. Each core had length ranging from 25 to 35 cm. The cores were sliced at intervals of 1 cm in the field, then sealed into polyethylene bags until they were freeze-dried in the laboratory.
Elemental concentrations and lead isotope ratios (206Pb/207Pb and 208Pb/206Pb) were measured at 5 cm intervals, and a total of 50 samples were analyzed. The freeze-dried samples were homogenized and then completely digested by HCl-HNO3-HF-HClO4 in Teflon beakers. The concentrations of aluminum (Al), phosphorus (P), titanium (Ti) and zinc (Zn) were measured by inductively coupled plasma-atomic emission spectrometry, while the concentration of As, Cu, Cd, Cr, Ni and Pb were measured by inductively coupled plasma mass spectrometry. All chemical reagents were analytically pure and prepared with ultrapure water. Quality assurance and quality control were ensured by measuring blanks and standard reference materials (GBW07358; Chinese geological reference materials). No detectable concentrations of the studied PHTEs were found in blank samples; the recoveries of various PHTEs from the samples ranged from 93% to 106%, and the relative standard deviations of each PHTE were less than 5% in all batches determined multiple times.
The Pb isotopic ratios in samples were also determined by inductively coupled plasma mass spectrometry. Certified reference material SRM 981 from the National Institute of Standards and Technology was used for calibration and for isotope correction factors. The standard reference material was used to check accuracy and repeatability in isotopic ratios internal standards. The relative standard deviations of the 206Pb/207Pb and 208Pb/206Pb ratios related to the repeated measurements of the standard material were less than 0.2%.

2.3. Risk Assessment and Statistical Analysis

To determine the degree of anthropogenic impact, the Igeo of every PHTE was calculated:
Igeo = log2 (Cn/1.5/Bn)
where Cn and Bn are the measured content of element n in the sediments and the background level, respectively. The value of 1.5 was used as the background matrix correction factor due to lithospheric effects [30]. The median values for PHTEs in the sediments at 150–180 cm depth from Lake Hongze were referenced as the background level of PHTEs in the MLRHR [31]. According to the values of Igeo, different pollution levels were categorized as follows: Igeo ≤ 0, no pollution; 0 < Igeo ≤ 1, low pollution; 1 < Igeo ≤ 2, moderate pollution; 2 < Igeo ≤ 3, moderate to high pollution; 3 < Igeo ≤ 4, high pollution; 4 < Igeo ≤ 5, high to very high pollution; Igeo > 5, very high pollution.
The conventional ecological risk (Er) factor was used to assess the ecological risk level of PHTEs in sediments according to the following equation:
Ern = Trn × (Cn/Bn)
where Trn is the toxic-response factor of element n in the sediments, and the factors were 30 for Cd; 10 for As; 5 for Cu, Ni and Pb; 2 for Cr and 1 for Zn [32]. The Er giving an evaluation of single metal pollution was classified into five grades: low risk (Er ≤ 40), moderate risk (40 < Er ≤ 80), considerable risk (80 < Er ≤ 160), high risk (160 < Er ≤ 320) and very high risk (Er > 320).
The consensus-based sediment quality guidelines (SQGs) were also applied to evaluate the potential ecological risk of the freshwater ecosystems [33]. Concentrations below the threshold effect concentration (TEL) represent a minimal effect, while concentrations at or above the probable effect concentration (PEL) indicate that adverse biological effects are likely to frequently occur. Additionally, a varimax rotated principal component analysis (PCA) was conducted to identify potential sources of PHTEs.

3. Results

3.1. Descriptive Statistics of Element Composition in Sediments

The element composition of the lacustrine sediments from the MLRHR is given in Figure 2, and the basic statistics regarding the element concentrations are listed in Table 1. Cd, As, Cu and Zn generally show large variability in concentrations, with coefficients of variation (CVs) of 0.65, 0.41, 0.32 and 0.30, respectively. P and Pb have moderate variability, with CVs of 0.26 and 0.21, respectively, while Al, Ti, Cr and Ni are relatively uniform in the seven lakes, with CVs no larger than 0.20.
For the surface sediments (the top 0–1 cm), the highest concentrations of As (33.4 mg/kg), Cd (0.89 mg/kg), Cu (61.5 mg/kg), P (997.0 mg/kg) and Zn (162.5 mg/kg) were measured in Lake Baima, while the highest concentrations of Al (92.4 mg/g), Cr (101.1 mg/kg), Ni (50.6 mg/kg) and Pb (43.2 mg/kg) were measured in Lake Huayuan and the highest concentration of Ti (5.2 mg/g) was measured in Lake Gaoyou. By contrast, the lowest concentrations of Al (61.6 mg/g), Cr (69.4 mg/kg), Cu (28.8 mg/kg), Ni (34.9 mg/kg), Pb (26.3 mg/kg), Ti (2.7 mg/g) and Zn (76.0 mg/kg) were measured in Lake Tuohu, while the lowest concentrations of As (14.9 mg/kg), Cd (0.17 mg/kg) and P (603.6 mg/kg) were measured in Lake Gaoyou, Lake Nüshan and Lake Huayuan, respectively.
The results of Kaiser–Meyer–Olkin measure of sampling adequacy (0.71) and Bartlett’s test of sphericity (χ2 = 755.4, p < 0.001) suggest that the element composition of the lacustrine sediments from the MLRHR is suitable for PCA. The results show that the first two principal components (PCs) explain 81.0% of the total variance. The first PC represents 46.0% of the total variance, and is characterized by large positive loadings of Al (0.96), Cr (0.96) and Ni (0.95) concentration, and moderate loadings of Pb (0.78), Zn (0.75), Cu (0.55) and Ti (0.48) concentration (Figure 3). The second PC explains 35.0% of the total variance, and is mainly dominated by Cd (0.87) and As (0.79), as well as moderate loadings of P (0.78), Ti (−0.68), Cu (0.66), Zn (0.59) and Pb (0.43).

3.2. Lead Isotopic Ratios

As shown in Figure 4, the samples have similar Pb isotopic ratios. The mean 206Pb/207Pb ratio is 1.18 for Lake Huayuan, 1.19 for Lake Tuohu, 1.18 for Lake Nüshan, 1.18 for Lake Baima, 1.18 for Lake Hongze, 1.18 for Lake Gaoyou and 1.19 for Lake Shaobao, respectively. The 208Pb/206Pb ratios significantly correlate with the corresponding 206Pb/207Pb ratios (Figure 4, R2 = 0.78, p < 0.001), with a mean of 2.09 for Lake Huayuan, 2.09 for Lake Tuohu, 2.10 for Lake Nüshan, 2.09 for Lake Baima, 2.10 for Lake Baima, 2.09 for Lake Gaoyou and 2.10 for Lake Shaobo.

3.3. Ecological Risk Assessment of Potentially Harmful Trace Elements

All Igeo values of Cr and Ni are below 0, and all Igeo values of As, Cu, Pb and Zn are below 1, indicating that the sediments are unpolluted or slightly polluted by these PHTEs (Figure 5). Among them, Igeo values of Cu and Zn between 0 and 1 only occur in the upper sediments from Lake Baima, and Igeo value of Pb between 0 and 1 only occur in the upper sediments from Lake Huayuan. Igeo values of As between 0 and 1 are found in the sediments from Lake Baima, Lake Huayuan and Lake Tuohu. For Igeo values of Cd, moderate Cd pollution occurs in Lake Baima and Lake Huayuan, slight pollution occurs in Lake Gaoyou, Lake Hongze and Lake Tuohu, while there is no Cd pollution in Lake Shaobo or Lake Nüshan.
Based on the ecological risk assessment method proposed by Hakanson (1980), most PHTEs are low-risk, except the risk posed by Cd varies significantly (Figure 6). The Cd risk in surface sediment from Lake Baima has reached a high level, and that from Lake Huayuan is also considerable. By contrast, all Cd concentrations in the lacustrine sediments are below the TEL from consensus-based SQGs, suggesting that Cd risk would not occur in the lacustrine sediments from the MLRHR. Instead, all Cr and Ni concentrations in the sediments exceed the TEL from consensus-based SQGs; As and Cu concentrations in the sediments also commonly exceed the TEL, and sporadic samples even exceed the PEL.

4. Discussion

4.1. Source Identification of the Potentially Harmful Trace Elements

PHTEs in lacustrine sediments not only contain products of natural processes, but also continuously receive contaminants from anthropogenic pollution [13]. The similar PC loading between Cr, Ni and Al suggests that these PHTEs mainly originate from the natural detritus in the catchment, such as the metamorphic rocks and mineral weathering. In addition, the Igeo values of Cr and Ni in the sediments also suggest that the anthropogenic contribution of Cr and Ni can be ignored in the MLRHR. Lower accumulations of anthropogenic Cr and Ni in freshwater sediments have also been reported by other similar studies from China [5,9,34,35]. Therefore, small variability of Cr and Ni in the sediments could result from changes in grain size, organic matter and carbonate content [4,11].
The distinct PC loadings between Cd, As, P and other elements, as well as the common positive Igeo values of Cd and As in the lacustrine sediments, suggest that these elements are influenced by anthropogenic sources. Although organic species of P in the sediment would undergo diagenetic processes, sedimentary profiles of P can quantify the sediment nutrient accumulation rates and reflect the lake trophic status [36,37,38,39]. The significant increase in P concentration in lacustrine sediments is mainly due to NaOH-P relating to the intensification of anthropogenic activities during the recent decades in east China [36,39,40]. Similar chemical partitioning of P was also found in surface sediments from Lake Hongze [41]. Agricultural non-point-source pollution is an important factor for water quality deterioration, due to the intensive use of industrial fertilizers in this region [5,39]. The phosphate fertilizer application rate increased to 99.4 kg/ha in the year 2016 [42]. However, only a small part of the applied phosphate fertilizer is absorbed by crops, while most is transported with rainfall or irrigation water to aquatic ecosystems, the same being true for other PHTEs, such as Cd [5]. In addition, Cd and As are closely linked to pesticides and wastewater irrigation [12,43,44]. In the MLRHR, land use is intensively distributed by agriculture around lakes, and thus anthropogenic Cd and As may mainly result from agricultural activities.
Cu, Pb and Zn are less influenced by agricultural sources, and the main source and transport pathway of Pb in the lacustrine sediment can be traced by Pb isotopic ratios [16,45]. Bedrock and the products of chemical weathering are the important natural sources of Pb in the sediments. The Cenozoic basalts in the MLRHR have 206Pb/207Pb ratios ranging from 1.08 to 1.12 with a mean of 1.11, while the Mesozonic granitoids have 206Pb/207Pb ratios ranging from 1.07 to 1.16 with a mean of 1.12 [46,47]. In contrast, the average 206Pb/207Pb ratio of the upper continental crust is ~1.20, which is close to that of the sediments from the Chinese Loess Plateau [48,49,50]. In one study, a fluvial sediment core had 206Pb/207Pb ratio of around 1.18 from the middle reach of the Huaihe River, where no obvious pollution sources were observed [51]. Considering that abundant sediments from the Chinese Loess Plateau had been discharged to the floodplain due to frequent floods, the reworked loess might be the dominant natural source of Pb in the lacustrine sediments from the MLRHR.
Because of the possible influence from anthropogenic pollution, we further compared the Pb isotopic ratios in the lacustrine sediments from the MLRHR with some potential Pb sources, such as gasoline, diesel, coal and Pb-Zn ores [14]. It was obvious that 206Pb/207Pb and 208Pb/206Pb ratios in the lacustrine sediments from the MLRHR are significantly different from those of vehicle exhaust and metallurgy dust (Figure 4). However, the range of the Pb isotopic ratios in this study is similar to that of coal, which has a 206Pb/207Pb ratio range from 1.17 to 1.19 (Figure 4). Coal burning was considered the major source of aerosol Pb pollution in the surrounding Nanjing and Shanghai in [52,53,54,55,56]. The 206Pb/207Pb ratios in the atmospheric particles ranged from 1.15 to 1.19 for total suspended particulates, and from 1.15 to 1.18 for PM2.5 from Nanjing [54]. Similar ratios were reported in Shanghai, which ranged from 1.16 to 1.17 for total suspended particulates, and had an average of 1.16 for PM2.5 [52,53]. In addition, the 206Pb/207Pb ratios ranged from 1.15 to 1.17 in the sediment core sampled near the Huaihe Bridge in the Huainan City, representing the influence of coal mining activities [51]. Furthermore, we compared the Pb isotopic ratios with other surface sediment from the delta of Yangtze River, where the 206Pb/207Pb ratios are generally lower than that from the MLRHR. For example, the average ratio of 206Pb/207Pb was 1.18 for Lake Xuanwu sediments, and 1.17 for Lake Mochou sediments from Nanjing [57]; the 206Pb/207Pb ratios ranged from 1.17 to 1.18 for Lake Taihu sediments [58,59]; the 206Pb/207Pb ratios were much lower in the lacustrine sediments from the waterscape parks in Shanghai, which had a mean of ~1.17 [60]. The 206Pb/207Pb ratios are slightly higher in the sediments from the Yangtze River intertidal zone, ranging from 1.18 to 1.19 [61]. Therefore, the input of anthropogenic Pb may be attributed to atmospheric pollution in this region.

4.2. Ecological Risk and Implication for Lake Management

As a whole, Cu, Pb and Zn have a consistent low ecological risk level from the consensus-based SQGs and Er assessments in the lacustrine sediments from the MLRHR, which likely pose low toxic effect on aquatic organisms. However, the ecological risk levels for As, Cd, Cr and Ni are somewhat different between the consensus-based SQGs and Er indices, which might be partially explained by the discrepancy in the principles of the two methods [13]. The consensus-based SQGs provide a risk based on empirically toxic experiments and total concentrations, which do not consider the differences in regional PHTE background values [26,31,33]. However, the background values of As, Cr and Ni in the lacustrine sediments from the MLRHR are 16.2 mg/kg, 88 mg/kg and 48.9 mg/kg, respectively, all higher than the TEL from the consensus-based SQGs [33]. The ecological risk of As, Cr and Ni thus would be considered high even without contribution of anthropogenic sources. By contrast, the Cd background value in this region is much lower than the TEL from consensus-based SQGs [33]. When the regional PHTE background values are taken into consideration using the Er method, the high toxic effect of Cd thus results in the calculated Er values being much higher than those of the other PHTEs. The uncertainty in the risk assessment of As, Cd, Cr, Cu and Ni by the consensus-based SQGs may relate to the different background values of these PHTEs in Canadian and Chinese freshwater sediments [31].
According to the pollution assessment using Igeo, we identify Cd as the priority PHTE for control in future environmental management in the MLRHR; in particular, the lacustrine sediment from Lake Baima has been moderately contaminated. As mentioned before, the primary anthropogenic sources of Cd in the lacustrine compartments may be fertilizers, wastewater irrigation and pesticides from agricultural soils. Meanwhile, Cd pollution is also the most urgent regarding agricultural soil contamination [44,62]. Thus, the most effective approach to migrate PHTE risk in lake ecosystems is soil remediation and erosion control in the catchment [44,63]. Furthermore, eutrophication can result in the release of Cd in lacustrine sediments because anthropogenic Cd is mainly in the exchangeable and/or carbonate fraction in the study region [7]. Therefore, secondary Cd pollution should also be paid more attention under anaerobic conditions when algae grow in these eutrophic lakes in the MLRHR.

5. Conclusions

The source and risk of PHTEs in the lacustrine sediments from the MLRHR in East China were investigated in this study. The results show that the concentrations of PHTEs in the sediments vary spatially, with the highest concentration of As, Cd, Cu and Zn in the surface sediments measured in Lake Baima, and the highest concentrations of Cr, Ni and Pb in the surface sediments measured in Lake Huayuan. As, Cd, Cu, Pb and Zn are found to be slightly to moderately polluting in some lakes, while the Igeo values suggest that there is no Cr and Ni pollution in this region. The main contribution of Cr, Cu, Ni, Pb and Zn is from natural origin, however, significant agricultural contribution of As and Cd is identified. Overestimated risk level of As, Cr and Ni but underestimated risk of Cd using the consensus-based SQGs results from the differences in regional PHTE background value. Our study provides detailed PHTE information that can be used to establish rational ecological protection measures on a catchment scale.

Author Contributions

M.X.: Conceptualization, Fieldwork, Methodology, Investigation, Data Curation, Writing—Original Draft, Writing—Review & Editing, Funding acquisition; R.W. and W.S.: Methodology, Writing—Original Draft, Writing—Review & Editing, Funding acquisition; D.W. and X.W.: Writing—Original Draft, Writing—Review & Editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the National Natural Science Foundation of China (No. 42107508), China Three Gorges Corporation (No. 201903144), the Provincial Natural Science of Jiangsu, China (No. BK20221558), and the High-level Innovation and Entrepreneurship Talent Programme of Jiangsu, China (No. JSSCBS20211397).

Data Availability Statement

Datasets related to this article are available from the corresponding author on reasonable request.

Acknowledgments

We thank the two anonymous reviewers for their constructive comments.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Carpenter, S.R.; Stanley, E.H.; Vander Zanden, M.J. State of the World’s Freshwater Ecosystems: Physical, Chemical, and Biological Changes. Annu. Rev. Env. Resour. 2011, 36, 75–99. [Google Scholar] [CrossRef] [Green Version]
  2. Pekel, J.-F.; Cottam, A.; Gorelick, N.; Belward, A.S. High-resolution mapping of global surface water and its long-term changes. Nature 2016, 540, 418–422. [Google Scholar] [CrossRef] [PubMed]
  3. Poff, N.L.; Brown, C.M.; Grantham, T.E.; Matthews, J.H.; Palmer, M.A.; Spence, C.M.; Wilby, R.L.; Haasnoot, M.; Mendoza, G.F.; Dominique, K.C.; et al. Sustainable water management under future uncertainty with eco-engineering decision scaling. Nat. Clim. Chang. 2016, 6, 25–34. [Google Scholar] [CrossRef] [Green Version]
  4. Birch, G.F. Determination of sediment metal background concentrations and enrichment in marine environments—A critical review. Sci. Total Environ. 2017, 580, 813–831. [Google Scholar] [CrossRef] [PubMed]
  5. Zhang, H.; Shan, B. Historical records of heavy metal accumulation in sediments and the relationship with agricultural intensification in the Yangtze-Huaihe region, China. Sci. Total Environ. 2008, 399, 113–120. [Google Scholar] [CrossRef]
  6. Yi, Y.; Yang, Z.; Zhang, S. Ecological risk assessment of heavy metals in sediment and human health risk assessment of heavy metals in fishes in the middle and lower reaches of the Yangtze River basin. Environ. Pollut. 2011, 159, 2575–2585. [Google Scholar] [CrossRef]
  7. Chen, M.; Ding, S.; Li, C.; Tang, Y.; Fan, X.; Xu, H.; Tsang, D.C.W.; Zhang, C. High cadmium pollution from sediments in a eutrophic lake caused by dissolved organic matter complexation and reduction of manganese oxide. Water Res. 2021, 190, 116711. [Google Scholar] [CrossRef]
  8. Malferrari, D.; Brigatti, M.F.; Laurora, A.; Pini, S. Heavy metals in sediments from canals for water supplying and drainage: Mobilization and control strategies. J. Hazard. Mater. 2009, 161, 723–729. [Google Scholar] [CrossRef]
  9. Guo, W.; Huo, S.; Xi, B.; Zhang, J.; Wu, F. Heavy metal contamination in sediments from typical lakes in the five geographic regions of China: Distribution, bioavailability, and risk. Ecol. Eng. 2015, 81, 243–255. [Google Scholar] [CrossRef]
  10. Yang, J.; Chen, L.; Liu, L.-Z.; Shi, W.-L.; Meng, X.-Z. Comprehensive risk assessment of heavy metals in lake sediment from public parks in Shanghai. Ecotoxicol. Environ. Saf. 2014, 102, 129–135. [Google Scholar] [CrossRef]
  11. Lin, Q.; Liu, E.; Zhang, E.; Nath, B.; Shen, J.; Yuan, H.; Wang, R. Reconstruction of atmospheric trace metals pollution in Southwest China using sediments from a large and deep alpine lake: Historical trends, sources and sediment focusing. Sci. Total Environ. 2018, 613, 331–341. [Google Scholar] [CrossRef] [PubMed]
  12. Pratte, S.; Bao, K.; Shen, J.; De Vleeschouwer, F.; Le Roux, G. Centennial records of cadmium and lead in NE China lake sediments. Sci. Total Environ. 2019, 657, 548–557. [Google Scholar] [CrossRef]
  13. Yu, Z.; Liu, E.; Lin, Q.; Zhang, E.; Yang, F.; Wei, C.; Shen, J. Comprehensive assessment of heavy metal pollution and ecological risk in lake sediment by combining total concentration and chemical partitioning. Environ. Pollut. 2021, 269, 116212. [Google Scholar] [CrossRef] [PubMed]
  14. Bi, X.-Y.; Li, Z.-G.; Wang, S.-X.; Zhang, L.; Xu, R.; Liu, J.-L.; Yang, H.-M.; Guo, M.-Z. Lead Isotopic Compositions of Selected Coals, Pb/Zn Ores and Fuels in China and the Application for Source Tracing. Environ. Sci. Technol. 2017, 51, 13502–13508. [Google Scholar] [CrossRef] [PubMed]
  15. Bing, H.; Wu, Y.; Zhou, J.; Li, R.; Wang, J. Historical trends of anthropogenic metals in Eastern Tibetan Plateau as reconstructed from alpine lake sediments over the last century. Chemosphere 2016, 148, 211–219. [Google Scholar] [CrossRef] [PubMed]
  16. Wan, D.; Yang, H.; Jin, Z.; Xue, B.; Song, L.; Mao, X.; Yang, J. Spatiotemporal trends of atmospheric Pb over the last century across inland China. Sci. Total Environ. 2020, 729, 138399. [Google Scholar] [CrossRef]
  17. Wang, L.W.; Jin, Y.L.; Weiss, D.J.; Schleicher, N.J.; Wilcke, W.; Wu, L.H.; Guo, Q.J.; Chen, J.B.; O’Connor, D.; Hou, D.Y. Possible application of stable isotope compositions for the identification of metal sources in soil. J. Hazard. Mater. 2021, 407, 124812. [Google Scholar] [CrossRef]
  18. Xu, D.; Gao, B.; Peng, W.; Qu, X.; Zhang, M.; Wang, J. Novel insights into Pb source apportionment in sediments from two cascade reservoirs, North China. Sci. Total Environ. 2019, 689, 1030–1036. [Google Scholar] [CrossRef]
  19. Zhong, Q.; Yin, M.; Zhang, Q.; Beiyuan, J.; Liu, J.; Yang, X.; Wang, J.; Wang, L.; Jiang, Y.; Xiao, T.; et al. Cadmium isotopic fractionation in lead-zinc smelting process and signatures in fluvial sediments. J. Hazard. Mater. 2021, 411, 125015. [Google Scholar] [CrossRef]
  20. Dai, C.; Qin, X.S.; Lu, W.T.; Huang, Y. Assessing adaptation measures on agricultural water productivity under climate change: A case study of Huai River Basin, China. Sci. Total Environ. 2020, 721, 137777. [Google Scholar] [CrossRef]
  21. Guo, C.; Chen, Y.; Xia, W.; Qu, X.; Yuan, H.; Xie, S.; Lin, L.-S. Eutrophication and heavy metal pollution patterns in the water suppling lakes of China’s south-to-north water diversion project. Sci. Total Environ. 2020, 711, 134543. [Google Scholar] [CrossRef] [PubMed]
  22. Wang, Y.; Xie, X.; Liu, C.; Wang, Y.; Li, M. Variation of net anthropogenic phosphorus inputs (NAPI) and riverine phosphorus fluxes in seven major river basins in China. Sci. Total Environ. 2020, 742, 140514. [Google Scholar] [CrossRef] [PubMed]
  23. Wu, W.; Qu, S.; Nel, W.; Ji, J. The influence of natural weathering on the behavior of heavy metals in small basaltic watersheds: A comparative study from different regions in China. Chemosphere 2021, 262, 127897. [Google Scholar] [CrossRef] [PubMed]
  24. Yang, G.; Ma, R.; Zhang, L.; Jiang, J.; Yao, S.; Zhang, M.; Zeng, H. Lake status, major problems and protection strategy in China. J. Lake Sci. 2010, 22, 799–810. [Google Scholar]
  25. Zhang, Q. The South-to-North Water Transfer Project of China: Environmental Implications and Monitoring Strategy. J. Am. Water Resour. Assoc. 2009, 45, 1238–1247. [Google Scholar] [CrossRef]
  26. Zhuang, W.; Ying, S.C.; Frie, A.L.; Wang, Q.; Song, J.; Liu, Y.; Chen, Q.; Lai, X. Distribution, pollution status, and source apportionment of trace metals in lake sediments under the influence of the South-to-North Water Transfer Project, China. Sci. Total Environ. 2019, 671, 108–118. [Google Scholar] [CrossRef]
  27. Zhang, L.; Song, X.; Xia, J.; Yuan, R.; Zhang, Y.; Liu, X.; Han, D. Major element chemistry of the Huai River basin, China. Appl. Geochem. 2011, 26, 293–300. [Google Scholar] [CrossRef]
  28. Han, L.; Hao, Q.; Qiao, Y.; Wang, L.; Peng, S.; Li, N.; Gao, X.; Fu, Y.; Xu, B.; Gu, Z. Geochemical evidence for provenance diversity of loess in southern China and its implications for glacial aridification of the northern subtropical region. Quat. Sci. Rev. 2019, 212, 149–163. [Google Scholar] [CrossRef]
  29. Zhang, L.; Qin, X.; Liu, J.; Sun, C.; Mu, Y.; Gao, J.; Guo, W.; An, S.; Lu, C. Geochemistry of sediments from the Huaibei Plain (east China): Implications for provenance, weathering, and invasion of the Yellow River into the Huaihe River. J. Asian Earth Sci. 2016, 121, 72–83. [Google Scholar] [CrossRef]
  30. Loska, K.; Wiechuła, D.; Korus, I. Metal contamination of farming soils affected by industry. Environ. Int. 2004, 30, 159–165. [Google Scholar] [CrossRef]
  31. Cheng, H.; Li, M.; Zhao, C.; Yang, K.; Li, K.; Peng, M.; Yang, Z.; Liu, F.; Liu, Y.; Bai, R.; et al. Concentrations of toxic metals and ecological risk assessment for sediments of major freshwater lakes in China. J. Geochem. Explor. 2015, 157, 15–26. [Google Scholar] [CrossRef]
  32. Hakanson, L. An ecological risk index for aquatic pollution control. a sedimentological approach. Water Res. 1980, 14, 975–1001. [Google Scholar] [CrossRef]
  33. MacDonald, D.D.; Ingersoll, C.G.; Berger, T.A. Development and Evaluation of Consensus-Based Sediment Quality Guidelines for Freshwater Ecosystems. Arch. Environ. Contam. 2000, 39, 20–31. [Google Scholar] [CrossRef]
  34. Tang, W.; Shan, B.; Zhang, H.; Mao, Z. Heavy metal sources and associated risk in response to agricultural intensification in the estuarine sediments of Chaohu Lake Valley, East China. J. Hazard. Mater. 2010, 176, 945–951. [Google Scholar] [CrossRef]
  35. Xu, M.; Wang, R.; Yang, X.; Yang, H. Spatial distribution and ecological risk assessment of heavy metal pollution in surface sediments from shallow lakes in East China. J. Geochem. Explor. 2020, 213, 106490. [Google Scholar] [CrossRef]
  36. Liu, E.; Shen, J.; Yang, X.; Zhang, E. Spatial distribution and human contamination quantification of trace metals and phosphorus in the sediments of Chaohu Lake, a eutrophic shallow lake, China. Environ. Monit. Assess. 2012, 184, 2105–2118. [Google Scholar] [CrossRef] [PubMed]
  37. Moyle, M.; Boyle, J.F. A method for reconstructing past lake water phosphorus concentrations using sediment geochemical records. J. Paleolimnol. 2021, 65, 461–478. [Google Scholar] [CrossRef]
  38. Smoak, J.M.; Swarzenski, P.W. Recent increases in sediment and nutrient accumulation in Bear Lake, Utah/Idaho, USA. Hydrobiologia 2004, 525, 175–184. [Google Scholar] [CrossRef] [Green Version]
  39. Zhang, H.; Shan, B. Historical distribution and partitioning of phosphorus in sediments in a agricultural watershed in the Yangtze-Huaihe region, China. Environ. Sci. Technol. 2008, 42, 2328–2333. [Google Scholar] [CrossRef]
  40. Ni, Z.; Wang, S.; Wu, Y.; Pu, J. Response of phosphorus fractionation in lake sediments to anthropogenic activities in China. Sci. Total Environ. 2020, 699, 134242. [Google Scholar] [CrossRef] [PubMed]
  41. Yu, H.; Zhang, W.-B.; Lu, S.-Y.; Yan, S.-W.; Hu, R.-J.; Chen, L.; Zhang, L.-L.; Yu, J.-P. Spatial distribution characteristics of surface sediments nutrients in Lake Hongze and their pollution status evaluation. Environ. Sci. 2010, 31, 961–968. [Google Scholar]
  42. Li, H.; Yang, Z.; Dai, M.; Diao, X.; Dai, S.; Fang, T.; Dong, X. Input of Cd from agriculture phosphate fertilizer application in China during 2006-2016. Sci. Total Environ. 2020, 698, 134149. [Google Scholar] [CrossRef] [PubMed]
  43. Rodriguez Martin, J.A.; Lopez Arias, M.; Grau Corbi, J.M. Heavy metals contents in agricultural topsoils in the Ebro basin (Spain). Application of the multivariate geoestatistical methods to study spatial variations. Environ. Pollut. 2006, 144, 1001–1012. [Google Scholar] [CrossRef] [PubMed]
  44. Tang, X.; Li, Q.; Wu, M.; Lin, L.; Scholz, M. Review of remediation practices regarding cadmium-enriched farmland soil with particular reference to China. J. Environ. Manag. 2016, 181, 646–662. [Google Scholar] [CrossRef] [PubMed]
  45. Renberg, I.; Brännvall, M.-L.; Bindler, R.; Emteryd, O. Stable lead isotopes and lake sediments—A useful combination for the study of atmospheric lead pollution history. Sci. Total Environ. 2002, 292, 45–54. [Google Scholar] [CrossRef]
  46. Chen, F.; Lv, H.; Yu, G. Subdivision of tectonogeochemical provinces in Eastern Yangtze Plate. Geol. Miner. Resour. South China 1998, 3, 48–54. [Google Scholar]
  47. Zhang, L.; Xing, F. Lead isotope compositions of Mesozoic granitoids and lead isotopic provinces from Anhui Province. Acta Petrol. Sin. 1993, 9, 105–114. [Google Scholar]
  48. Choi, M.-S.; Yi, H.-I.; Yang, S.Y.; Lee, C.-B.; Cha, H.-J. Identification of Pb sources in Yellow Sea sediments using stable Pb isotope ratios. Mar. Chem. 2007, 107, 255–274. [Google Scholar] [CrossRef]
  49. Jones, C.E.; Halliday, A.N.; Rea, D.K.; Owen, R.M. Eolian inputs of lead to the North Pacific. Geochim. Et Cosmochim. Acta 2000, 64, 1405–1416. [Google Scholar] [CrossRef]
  50. Millot, R.; Allègre, C.-J.; Gaillardet, J.; Roy, S. Lead isotopic systematics of major river sediments: A new estimate of the Pb isotopic composition of the Upper Continental Crust. Chem. Geol. 2004, 203, 75–90. [Google Scholar] [CrossRef]
  51. Wang, J.; Liu, G.J.; Liu, H.; Lam, P.K.S. Tracking historical mobility behavior and sources of lead in the 59-year sediment core from the Huaihe River using lead isotopic compositions. Chemosphere 2017, 184, 584–593. [Google Scholar] [CrossRef] [PubMed]
  52. Chen, J.M.; Tan, M.G.; Li, Y.L.; Zhang, Y.M.; Lu, W.W.; Tong, Y.P.; Zhang, G.L.; Li, Y. A lead isotope record of shanghai atmospheric lead emissions in total suspended particles during the period of phasing out of leaded gasoline. Atmos. Environ. 2005, 39, 1245–1253. [Google Scholar] [CrossRef]
  53. Chen, J.; Tan, M.; Li, Y.; Zheng, J.; Zhang, Y.; Shan, Z.; Zhang, G.; Li, Y. Characteristics of trace elements and lead isotope ratios in PM2.5 from four sites in Shanghai. J. Hazard. Mater. 2008, 156, 36–43. [Google Scholar] [CrossRef] [PubMed]
  54. Hu, X.; Sun, Y.; Ding, Z.; Zhang, Y.; Wu, J.; Lian, H.; Wang, T. Lead contamination and transfer in urban environmental compartments analyzed by lead levels and Isotopic compositions. Environ. Pollut. 2014, 187, 42–48. [Google Scholar] [CrossRef]
  55. Liu, E.; Yan, T.; Birch, G.; Zhu, Y. Pollution and health risk of potentially toxic metals in urban road dust in Nanjing, a mega-city of China. Sci. Total Environ. 2014, 476, 522–531. [Google Scholar] [CrossRef]
  56. Mukai, H.A.; Tanaka, A.; Fujii, T.; Zeng, Y.Q.; Hong, Y.T.; Tang, J.; Guo, S.; Xue, H.S.; Sun, Z.L.; Zhou, J.T.; et al. Regional characteristics of sulfur and lead isotope ratios in the atmosphere at several Chinese urban sites. Environ. Sci. Technol. 2001, 35, 1064–1071. [Google Scholar] [CrossRef]
  57. Hu, X.; Wang, C.; Zou, L. Characteristics of heavy metals and Pb isotopic signatures in sediment cores collected from typical urban shallow lakes in Nanjing, China. J. Environ. Manag. 2011, 92, 742–748. [Google Scholar] [CrossRef]
  58. Li, Y.; Zhou, S.L.; Zhu, Q.; Li, B.J.; Wang, J.X.; Wang, C.H.; Chen, L.; Wu, S.H. One-century sedimentary record of heavy metal pollution in western Taihu Lake, China. Environ. Pollut. 2018, 240, 709–716. [Google Scholar] [CrossRef]
  59. Yao, S.; Xue, B.; Tao, Y. Sedimentary lead pollution history: Lead isotope ratios and conservative elements at East Taihu Lake, Yangtze Delta, China. Quat. Int. 2013, 304, 5–12. [Google Scholar] [CrossRef]
  60. Li, H.-B.; Yu, S.; Li, G.-L.; Liu, Y.; Yu, G.-B.; Deng, H.; Wu, S.-C.; Wong, M.-H. Urbanization increased metal levels in lake surface sediment and catchment topsoil of waterscape parks. Sci. Total Environ. 2012, 432, 202–209. [Google Scholar] [CrossRef]
  61. Zhang, W.; Feng, H.; Chang, J.; Qu, J.; Yu, L. Lead (Pb) isotopes as a tracer of Pb origin in Yangtze River intertidal zone. Chem. Geol. 2008, 257, 257–263. [Google Scholar] [CrossRef]
  62. Zhao, F.-J.; Ma, Y.; Zhu, Y.-G.; Tang, Z.; McGrath, S.P. Soil Contamination in China: Current Status and Mitigation Strategies. Environ. Sci. Technol. 2015, 49, 750–759. [Google Scholar] [CrossRef] [PubMed]
  63. Huang, J.; Zhang, Y.; Arhonditsis, G.B.; Gao, J.; Chen, Q.; Wu, N.; Dong, F.; Shi, W. How successful are the restoration efforts of China’s lakes and reservoirs? Environ. Int. 2019, 123, 96–103. [Google Scholar] [CrossRef] [PubMed]
Water 15 00544 g001 550
Figure 1. The location of Huaihe River and seven sampling lakes.
Figure 1. The location of Huaihe River and seven sampling lakes.
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Figure 2. The concentration of main elements in the seven sampling sediment cores from the MLRHR.
Figure 2. The concentration of main elements in the seven sampling sediment cores from the MLRHR.
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Figure 3. Principal components analysis of the concentration of main elements in the seven sampling sediment cores from the MLRHR.
Figure 3. Principal components analysis of the concentration of main elements in the seven sampling sediment cores from the MLRHR.
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Figure 4. The comparison of Pb isotopes from the MLRHR with different sources, including Chinese ore, coal, fuel, aerosols and natural sediments [14].
Figure 4. The comparison of Pb isotopes from the MLRHR with different sources, including Chinese ore, coal, fuel, aerosols and natural sediments [14].
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Figure 5. Igeo values of critical PHTEs in the seven sampling sediment cores from the MLRHR.
Figure 5. Igeo values of critical PHTEs in the seven sampling sediment cores from the MLRHR.
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Figure 6. Er values of critical PHTEs in the seven sampling sediment cores from the MLRHR.
Figure 6. Er values of critical PHTEs in the seven sampling sediment cores from the MLRHR.
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Table
Table 1. Statistics of the element concentrations of the surface sediments, background concentrations, and guideline freshwater sediment quality values (mg/kg, dry weight).
Table 1. Statistics of the element concentrations of the surface sediments, background concentrations, and guideline freshwater sediment quality values (mg/kg, dry weight).
AlTiPAsCdCrCuNiPbZn
Minimum58527.32674.6288.16.90.0652.317.424.919.540.8
Maximum99199.25395.9997.035.00.89111.968.456.144.3168.4
Average 80637.04410.0587.817.50.2588.234.644.431.099.9
Coefficient of variation0.140.140.260.410.650.170.320.180.210.30
Background a 11.10.283.030.836.629.487.0
TEL 9.81.043.431.622.735.8121.0
PEL 33.05.0111.0149.048.6128.0459.0
Note: a Background: background concentrations of heavy metals in sediments from Chinese lakes [31].
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Xu, M.; Wang, R.; Sun, W.; Wang, D.; Wu, X. Source Identification and Ecological Risk of Potentially Harmful Trace Elements in Lacustrine Sediments from the Middle and Lower Reaches of Huaihe River. Water 2023, 15, 544. https://doi.org/10.3390/w15030544

AMA Style

Xu M, Wang R, Sun W, Wang D, Wu X. Source Identification and Ecological Risk of Potentially Harmful Trace Elements in Lacustrine Sediments from the Middle and Lower Reaches of Huaihe River. Water. 2023; 15(3):544. https://doi.org/10.3390/w15030544

Chicago/Turabian Style

Xu, Min, Rong Wang, Weiwei Sun, Dianchang Wang, and Xinghua Wu. 2023. "Source Identification and Ecological Risk of Potentially Harmful Trace Elements in Lacustrine Sediments from the Middle and Lower Reaches of Huaihe River" Water 15, no. 3: 544. https://doi.org/10.3390/w15030544

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