Next Article in Journal
Public Policies for Territorial Cohesion and Sustainability in Europe: An Overview
Previous Article in Journal
Study on Physical Properties, Rheological Properties, and Self-Healing Properties of Epoxy Resin Modified Asphalt
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 15
Issue 8
10.3390/su15086888
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Physicochemical Properties and Environmental Effects of Suspended Sediment Particles in the Largest Freshwater Lake, China

by
Fang Cui
1,2,
Hua Wang
1,2,*,
Zilin Shen
1,2,
Yuanyuan Li
1,2,
Siqiong Li
1,2 and
Xueqi Tian
1,2
1
Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing 210098, China
2
College of Environment, Hohai University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(8), 6888; https://doi.org/10.3390/su15086888
Submission received: 6 March 2023 / Revised: 15 April 2023 / Accepted: 17 April 2023 / Published: 19 April 2023
Browse Figures
Review Reports Versions Notes

Abstract

:
Suspended sediment particles (SSPs) act as a potential source of and sink for aquatic pollution. This study sampled six sites in Poyang Lake in August and November 2019. Changes in the physicochemical properties of SSPs were analyzed using scanning electron microscope energy-dispersive spectrometry (SEM-EDS). The results showed that SSPs consisted mainly of clay and chalk, with an average content of 39.71% and 57.52%, respectively. The average particle size distribution of SSPs in the study area ranged from 5.54 to 15.97 μm and the spatial distribution pattern showed the north lake area (I) > west lake area (II) > east lake area (III). The angle (K) of morphological indicators varied widely, with coefficients of variation between 0.25 and 1.23. Water-flow velocity was negatively correlated with SSP size, while suspended-solid concentration was positively correlated with SSP surface roughness. Morphological parameters, chemical composition, and correlation between each SSP form were analyzed to identify morphological distribution characteristics. Linear regression equations estimated endogenous phosphorus load in zones I, II, and III as 1027.202 mg/kg, 1265.343 mg/kg, and 1013.111 mg/kg respectively. Therefore, we conclude that the morphological differences in particulate matter, the interaction between chemical fractions, and the aqueous environment affecting the distribution of phosphorus fugitive forms, may contribute to endogenous lake pollution. These results are essential for revealing the intrinsic relationship between SSP physicochemical properties and lake eutrophication and studying other water–sediment interface processes of lake pollutants.

1. Introduction

Suspended sediment particles (SSPs) are ubiquitous in aquatic ecosystems and their surface properties are strongly influenced by biochemical and biological processes [1,2]. These SSPs are the primary media and reservoirs [3] for these pollutants during water migration due to their surface charges, which tend to adsorb compounds such as PAHs, nutrients, heavy metals, etc. [4,5,6] and are the second-most abundant source of pollution following pathogens [7]. SSPs primarily carry inorganic minerals and organic matter [8]. For example, organic matter such as p-nitrophenol covering the surface of the particles can undergo phase changes under altered hydrodynamic conditions [9] and inorganic matter attached to the surface increases the attenuation of light radiation and affects the light transmission of the water column [10]. Some algae microbes are similarly important mediators of particulate matter [11], causing black-odorous waters through cell rupture and bio-metabolism [12]. In addition, there are discrepancies in the sorption-desorption behavior of nutrients between shallow and deep water lakes, such as the unstable interface between sediment and overlying water in shallow lakes, which is vulnerable to significant suspension by wind, waves, and lake currents [13], resulting in elevated concentrations of soluble phosphorus in the overlying water [14] and deterioration in the photosynthetic function of submerged plants [15]. This suggests a complex coupling between SSPs and the water column, which can be used as an emerging indicator for evaluating environmental water pollution.
Recent studies have focused on the particle size characteristics of SSPs. For example, particle size is tightly linked to the presence, content, and transport of organic carbon [16,17], which trend towards facilitating the fugacity and deposition of dissolved phosphorus [18]. Furthermore, the sizing distribution of suspended matter, to a certain extent, reflects the degree of enrichment of surface-adhered pollutants, hydrodynamic strength, surface wetting, and dryness [19,20,21]. Based on the above, some scholars have studied in depth the effects of particle–turbulence intermodulation mechanisms on particulate transport [22], streambed morphology [23], and nitrogen and phosphorus loading [24,25]. At most stages of research on suspended sediments, these scholars analyzed the environmental effects of interaction between the particulate matter and the carrier liquid. More research is required to investigate variability in the physicochemical properties of SSPs and the causes of variability, along with environmental effects (e.g., biodegradability, contaminant loading, sediment accumulation, etc.) of variability. Within the lake hydro-ecosystem, nutrient phosphorus tends to incorporate with particulate matter in granular form [26], primarily owing to the micromorphology, mineral composition, and high Fe/Al oxide content of SSPs [27], rendering them into phosphorus accumulation reservoirs [28,29]. The susceptibility of particles to external disturbances leads to variations in particle structure, pore size, and other aspects [30] concomitant with the migration transformation of pollutants [31]. Furthermore, the retention and transport of particulates perform essential functions in the phosphorus cycle [32] and still participate in interface exchange [33], the return of fugitive nutrients to the covering waters through resolution and dissolution [34], thereby forming the lake nutrients’ endogenous load [35,36] and directly affecting primary productivity and hydro-environmental quality [37,38]. Moreover, various forms and concentrations of phosphorus in SSPs contribute differently to lake eutrophication [39], making it essential further to explore pollutant water–sediment interface processes in lakes and to gain insight into the transport dynamics of SSPs [40].
Poyang Lake, a fluvial lake on the mid- and downstream plains of the Yangtze River [41], presents high dynamics and multiple sediments. Considering that SSP characteristics involve various disciplinary fields, the aims of this study are: (1) analyze the leading physicochemical indicators of the particulate matter (including material composition, particle size, chemical fraction, etc.); (2) investigate the driven mechanisms underlying the differences in the micro-morphology of SSPs and in its chemical properties; (3) probe the environmental effects of differences in physicochemical properties of SSPs on the distribution of phosphorus fugacity patterns. This study’s results help deepen awareness of sediment particle sources, multi-dimensional particle properties, their behavior in lakes and streams, and their influence on the transport and transformation of pollutants, providing a renewed scientific basis for endogenous pollution in shallow lakes to be effectively controlled and water ecosystem balance maintained.

2. Materials and Methods

2.1. Study Area

Poyang Lake (28°24′–29°26′ N, 115°49′–116°46′ E) is located in northern Jiangxi Province on the south side of the middle and lower reaches of the Yangtze River, which is the most extensive fluvial lake in the Yangtze River basin and the largest shallow lake in China [42]. Poyang Lake contains the waters of the Ganjiang River, Fei River, Rao River, Xiu River, and Xinjiang River, as well as water from the Tongjin River and Liao River, constituting the complete water system of Poyang Lake [43]. Its watershed covers an area of 162,200 km2, with an average of 145.7 billion m3 of multi-year water injected into the Yangtze River, occupying about 15.6% of the water entering the Yangtze River, playing a vital role in maintaining the water equilibrium of the middle and lower reaches of the Yangtze River and the eco-balance of the waters [44]. Poyang Lake’s basin has a sub-tropical monsoon climate with warm and humid weather and abundant rainfall and the average annual rainfall is 1400–1600 mm [45,46]. The soil types in the Poyang Lake basin are diverse, of which red loam, the most significant soil resource, accounts for 70.69% of the total soil area in the province distributed in the south of Poyang Lake (III), followed by yellow loam, which is a weakly acidic soil with high fertility [47], primarily distributed in the middle and north of Poyang Lake (I, II). Distinctive hydrological characteristics of the river–lake linkage of Poyang Lake, large-scale lakeshore grass oases, and wetland-rich biological resources support many endangered birds, such as whooping cranes, trumpeter swans, and wild geese, when overwintering. Meanwhile, it is an essential habitat for the Yangtze finless porpoise, accounting for roughly 1/4-1/3 of their population [48].
With Poyang Lake as the core, the eco-economic zone of Poyang Lake occupies 30.7% of the land area of Jiangxi Province, containing nearly 50% of the provincial population and generating more than 60% of its GDP [49], which has an excellent active foundation. Given that the eco-economic development of this basin has the most prototypical and investigative significance among the Ton Jiang lakes, we have selected six sites in Wucheng (S1), Sheshan (S2), Longkou (S3), Kangshan (S4), Duchang (S5), and Shaling (S6) respectively as the research area. Based on lake flow, with Songmen Mountain (S7) as the boundary, it was further divided into the northern lake area (I), the western lake area (II), and the eastern lake area (III) (Figure 1).

2.2. Collect Samples

The survey samplings were collected in seasons and dry periods (August, and November 2019) corresponding to water level changes in Poyang Lake. In situ water samples were collected at 6 points at 0.5 m from the water’s surface in the Poyang Lake area. Sealed samples were stored in airtight jars and then transferred to the laboratory, where 500–100 mL of them were filtered using a Brinell funnel with a 0.45 m acetic acid membrane. After filtering, membranes were dried at 105 °C, sifted through 100 layers of mesh (150 μm) to remove bulky particles and impurities, sieved off in tin foil, placed in a sealed bag, and stored for testing. Scanning electron microscopy (SEM; S4800) was performed at the Modern Analysis Centre of Nanjing University to obtain the electron microscopic images of the suspended particles. Using an energy-dispersive X-ray spectrometer (EDS; EX-250) equipped with the SEM, qualitative results were obtained following JY/T 0584-2020, GB/T 17359-2012, and GB/T 16594-2008 standards. The water velocity (V) of SSPs was determined with an electromagnetic flowmeter (ACM3-RS). Suspended solids concentration (SSC) was measured by electromagnetic measurement. Quality data (TP) came from the Jiangxi Hydrographic Bureau.

2.3. Data Processing Method

SEM-EDS could be employed to research sediment sources, transport processes, and deposition patterns [50]. It is a method for non-destructive surface elemental analysis [51] with potential detection limits of 0.1 to 0.5 wt.% for most elements [52]. Spatial resolutions of <10 nm could be attained by employing this technique, which provided the basis for generating quantitative and qualitative elemental data for single particles [53]. Additionally, SEM-EDS allows for multiple measurements of microscopic morphology and its chemical composition to be observed without destroying samples.
To ensure the accuracy of the sediment particle measurements, a magnification of roughly 100× for 20–30 particles per image and a single particle diameter pixel of roughly 25 pixels [54] were studied in accordance with US material testing standards, along with the minimum number of pixel points contained in the measured object. We processed the particle images acquired via scanning electron microscopy with the image processing software Image-Pro-Plus 6.0 (abbreviated as IPP). After editing the boundary shapes of all the particles, geometric parameters (e.g., area, perimeter, diameter, etc.) were selected for statistics and data output (Figure 2b). Mean value was obtained for the exact particle measurement three times to manage the errors created by the manual depiction of the boundary. As actual particles possess differing and sophisticated morphologies, geometric parameters derived from IPP alone are insufficient to entirely reflect the micro-morphology of the particles, thereby necessitating construction of secondary parameters to quantify (Angularity) K, (Roundness) R, Fractal Dimension FD) and characterize the 2D features of particulates (Figure 2c). K denotes the angularity of the particles. R measured the degree of object shape close to the circle [55]. FD gauged the degree of irregularity of fractal objects, which was positively correlated with the coarseness of the particle surface at the same dimensional level. Hence, it would be characterized by FD [56].
Although tedious, it could reveal fuller shape information about the particles than the automated particulate detector. In addition, micro-plastics, algae, organic matter, and other fugitive particle surface materials could be prevented from influencing the results. Therefore, we have adopted SEM-EDS to examine the physicochemical properties and quantified the particle morphology of SSPs via IPP.

3. Results and Discussion

3.1. Physical Properties of Suspended Sediment Particles

The physical properties of suspended particles were significant factors affecting their settling, transfer, and accumulation. The physical properties of the surface of suspended particulate matter were mainly described in this paper in relation to two aspects: particulate size composition and 2D morphology index.
The granular composition of SSPs was dominated by clay (39.71%) and chalk (57.45%) (Figure 2a and Figure 3a). It was similar to the outcome of the studies by Xu [57] and Moayeri Kashani et al. [58]. There were no significant seasonal variations in the suspension particle size composition based on the lake’s identical material sources and subsurface conditions. Unlike in the flood and dry seasons, no differences were found in the particle size composition of S1 and S4, with new sand grains in S3 (6.06%) and a substantial increase in clay in S6 (31.85%). Throughout the lake area, clay particles increased in I and II (15.19% and 21.3%, respectively), whereas silt increased by 20.67% in III. Minor sand particles (10.79–13%) were present in II and III. Levels of clay, silt, and coarse sand in Poyang Lake tended to decrease from northwest to southeast. Several factors may account for this. On the one hand, considering that the incoming upstream sand passed through the estuary delta, flow velocity abruptly dropped, materialization characteristics occurred between two phases of current and sediment, and coarse particles accumulated in the area around S2; on the other hand, this was probably caused by wind disturbance on the lake surface, where lesser particles would migrate and aggregate with the current to form larger particles.
Suspended particle dimensions were selected as a measure of mean particle size (D), whose dimensional variation features mirrored the sedimentary environment of the lake basin [59]. Floating particle mass D ranged from 5.54 to 15.97 μm within the lake basin (Figure 3b). The uneven distribution of water in flood and dry periods led to hydrodynamic disparities, resulting in particle size differences in SSPs. The average particle size of SSPs in the lake area (2.82–8.52 μm) was greater in the flood period than in the drought period (2.69–6.59 μm). Zone I was more remarkable than the rest of the lakes in terms of mean particle size (10.53 μm), due on the one hand to the fact that S5 was in a narrow inlet channel and was subject to substrate resuspension induced by lake currents and wind and wave disturbances, and on the other hand that S6 was affected by human-made sand mining in the S7 area with fine particles in the riverbed being scoured. Zone III was the area with the smallest average particle size value of SSPs (7.85 μm). This region was a stagnant area, influenced less by influent sediment (mainly from the Rao River and the Fu River) and weak hydrodynamic conditions [60,61], and therefore the particle size variation was minor in scope.
Based on the coefficient of variation (CV) characterizing the sensitivity of morphological indicators to variation in particle outlines [62], we evaluated and analyzed three 2D indicators of K, R, and FD in particles. In the flood season, the distribution patterns of CVK, CVR, and CVFD in SSPs were consistent among sites, with CVK (0.36) higher than CVR (0.26) and CVFD (0.02). In the dry season, CVK in the SSPs fluctuated more (0.25–0.65), with higher values in III than in the other zones. CVR ranged from 0.12 to 0.70, declining sharply in S3 and S4 (Figure 3c). It might be attributed to the weak mobility of water flow in III and the uniform distribution and globular shape of the particles. CVFD varied from 0.01 to 0.30. S1, S3, and S4 fluctuated considerably compared with the flood season, while S5 and S6 regions did not differ much. It probably was that the scheduling of Poyang Lake Water Conservancy Hub reduced the flow velocity north of S7. However, the other three sites were suspended in sediment by gravity flow owing to the interaction of the surrounding river flow, making the variation in SSP coarseness between sites even larger. Through analyzing the space-time distribution pattern of the coefficient of variation of each morphological index, CVK at each spot was the most typical to characterize the sensitivity of SSP contour variance.

3.2. Chemical Characteristics of Suspended Sediment Particles

The chemical properties of sediment particles were fundamental to investigating the physicochemical interactions occurring during sediment transport [63]. Alumino-silicates dominated SSPs. By SEM-EDS qualitative analysis, it was found that the material phase composition of sediment particles in the region has remarkable similarity, yet differs in their relative contents [64,65,66] (Figure 4a). The alkali metal elements such as Ca and Mg were not detected in the area and might be restricted by the detection limit. Suspended sediments in Poyang Lake were high in C and may contain large amounts of organic matter. Six points of SSP all contained four constant elements: O, C, Al, and Si. Moreover, the percentage of elemental content was over 90%. Trace elements K and Fe occur in the delta area formed by S1, S2, and S5. Probably the supplementation of transportation activities and tributary input led to the growth of water contamination sources, creating favorable conditions for accumulating trace elements on the surface of SSPs. The average contents of essential elements in the region were O (57.41%), C (41.05%), Si (1.03%), and Al (0.64%) in order from high to low (Figure 4b).
Among the SSPs of Poyang Lake, Fe was mainly distributed in clay, about 51%. Al was predominantly in clay and silt, with a small gap (38–42%). The amount of Ca was immense in silt and sand, reaching more than 95% (Figure 4c). This could be explained by the fact that the surface of the fine particles was less coarse. Fe and Al were adsorbed and bound to the surface of the particles in their oxidized state underwater [67,68], further promoting their enrichment in SSPs. By contrast, Ca was more soluble in the water mass and mainly in ionic mode. Since the coarse particles possessed more sorption sites on the surface and sank faster, elements of Ca were quickly deposited to the lake bottom along the particles and spread in the thicker ones. Differences in the distribution of these elemental concentrations in the particulate matter might be influenced by various particle diameters, presumably correlating between them. It has been shown that Fe and Al were positively related to clay grains and Ca elements negatively correlated with sand grains [69]. Thus, there was a “grain control effect” of trace element content in SSPs. The findings by [70,71,72] also prove it.

3.3. Drive Mechanism for Differences in Physicochemical Properties

Hydrological exchanges frequently occurred between rivers and lakes within the Poyang Lake basin [73], with solid interactions between water flow and SSP movement [31]. Complicated hydrodynamic and hydro-environmental circumstances trigger a sophisticated response of SSPs in terms of micro-morphological and kinematic characteristics [74]. Increased odds of collision between particles may exist to influence their morphological properties. The correlation analysis of the physical characteristics parameters of particles (D, K, R, FD) with flow velocity (V), suspended particle concentration (SSC), and total phosphorus (TP) in this study was shown in Figure 5a. K and R in SSPs were not significantly related to SSC and TP. K, R, and FD were correlated considerably with V. D was negatively associated with it (r1 = 0.503, r2 = 0.831, and r3 = 0.542, r4 = −0.328, p < 0.01, n = 12), i.e., within the more vital perturbed region, coarse particles were continually eroded making the particles rounded and smooth [75]. FD was statistically positively related to SSCs, TP (r1 = 0.657, r2 = 0.467), consistent with the results of former studies [76,77] that were essentially analogous. The higher the surface roughness of the particulates, the more the surface pore space favors the attachment of organic coatings, resulting in particles being suspended in the overlying aqueous column and increasing concentrations. In part, the morphology of SSPs exhibits a dynamic process influenced by hydrodynamics and the water environment.
Suspended sediment was mainly derived from solid-phase minerals in the soil, and soil erosion can impact particulate matter chemistry [78]. Suspended sediment was broadly consistent with the chemical components between red and yellow loam (Figure 5b), with SiO2 dominating [79]. The chemical components of the sediment particles were soil-traceable. Native minerals in red and yellow soils underwent leaching during soil formation [80], resulting in Si depletion and Al- and Fe-enrichment, which made the SSP fraction significantly higher in Fe2O3 and Al2O3 than in other oxides. Therefore, soil formation processes have influenced the chemical composition of SSPs. Additionally, the massive leakage of alkali metal elements from the soil particles in the process whereby Fe and Al were comparatively aggregated can be explained by the notable absence of Ca and Mg content in the particulate matter, which contributed to the relatively homogeneous elemental composition of the particulate matter. Note that the elemental composition of SSPs varied considerably, yet the relative content of SSPs varied inconsequentially depending on the soil type. Consequently, corresponding links between the soil fraction and the chemical properties of the particles could be seen.

3.4. Physico-Chemical Properties Differences Trigger Environmental Effects

Phosphorus was the most pivotal element among all biological sources in the eutrophication of shallow lakes [81]. Furthermore, the biological effectiveness of phosphorus in SSPs’ contribution to the eutrophication of the underlying water column is correlated closely with its deposition mode [82,83]. The geochemical morphology of SSPs as an endogenous source of phosphorus has been an influential criterion for distinguishing the transport capacity and eco-effects of phosphorus in particulates. Hence, this paper used P as an example to explore the distributional effects of the physicochemical properties of SSPs on phosphorus morphology.
A linear regression model was constructed in this study based on the relationship between the morphological parameters of the particulate matter and each form of phosphorus at different particle classes, thereby estimating the phosphorus load in the SSPs (Figure 6 and Figure S1). The table showed that TP and each morphological P in SSPs showed a positive correlation with clay and a negative correlation with silt and sand. The correlation between Fe/Al-P and OP at silt grain size was less than clay and sand. It could be noted that grain size had a significant influence on the TP load in SSPs as well as the distribution of each form of P and that D had the most significant impact on the Ca-P load, with R2 reaching over 0.78. However, there were lower relationships with Fe/Al-P, with the greatest R2 being merely 0.526, possibly related to the source of each form of phosphorus. Furthermore, we have observed discrepancies in the phosphorus state distribution between regions. Phosphorus content in all forms was higher in II than in I and III, with a maximum of 2421.68 mg/kg in TP and less distributed in OP, averaging 437.46 mg/kg, demonstrating that II was more affected by neighboring agricultural surface sources and industrial pollution sources. Comparatively, the state of phosphorus distribution was more similar in I and II, where Ca-P accounted for a more significant proportion (1073.643 mg/kg) and possibly appropriate treatment has been carried out in both areas (Figure 5d).
The contributions of quantitative chemical factors to explain the variation in total phosphorus and different phosphorus forms in particulates were analyzed in RDA (Figure 5c). Axes I and II interpreted 49.39% and 3.59%, with no apparent explanatory information in the other two axes. The chemical components explained, to some extent, the variation in phosphorus state content in the SSPs. SiO2 content in the SSPs was negatively correlated with the different phosphorus states and connected well with TP, Ca-P, and OP, indicating a significant influence by the sand content of SSPs on the phosphorus distribution. Slight correlations were found between TiO2 and Ca-P and Fe/Al-P, probably linked to its source and the detrital minerals that adsorbed specific metal ions. MnO showed minor dependence on all forms of phosphorus. It was assumed that MnO mainly oxidized with certain metal ions or organic matter in aqueous bodies [84] in different ways from each form of phosphorus. Al2O3 showed significant positive correlations with all forms of phosphorus apart from Ca-P. TFe2O3 was also well-correlated with all forms of phosphorus and influenced Fe/Al-P and OP more. CaO had positive correlations with Ca-P, TP, and OP, speculating that CaO neutralized the acidity of the water column and promoted phosphate precipitation. A weaker correlation was found with Fe/Al-P. Given the limited surface zone of the particulate matter, the adsorption processes of Fe/Al ions bound to P may compete with Ca for adsorption [85]. It may be inferred that the interactions between the distinct chemicals in SSP affected the phosphorus adsorption capacity. Additionally, the particulate and chemical fractions affected S2, S3, and S4 (III) more than the other areas. The smaller particle size distribution and larger specific surface area in Zone III were known to predispose ions and organic matter in aquatic environments to interact with the surface chemical fraction of SSPs, thus explicating the regional differences. Thereby it emerged that varying chemical components of SSPs further complicated their impacts on phosphorus distribution.
The above analysis allowed us to better understand the distributional features of phosphorus in the SSP of shallow lakes and the regional differences. It would be facilitative in formulating more effective management measures regarding lake eutrophication.

4. Conclusions

As the primary carrier of water pollutants, their surface properties are affected by the complicated water–sediment conditions and further for pollutants in the water migration and transformation of indirect impact. To uncover the relationship between SSPs and the water–sediment environment, we sampled six sites in Poyang Lake. We measured the SSP-related data based on SEM-EDS, then analyzed the 2-dimensional morphological characteristics and chemistry of SSPs among different areas and explored the driving mechanisms and triggering environmental effects of the differences in their physicochemical properties. Results indicated that most SSPs were composed of clay and silt. Comparison of the coefficients of variation based on 2-D morphometric indicators (K, R, FD) revealed the most pronounced variation of CVK among the sites, characterizing the sensitivity of particle profile variability. As shallow-lake hydrodynamics and aquatic environments have extreme variability, they triggered a complicated SSP microscopic morphological response. Under high-intensity disturbance, coarse particles were gradually rounded by abrasion. Particles in high-concentration water bodies tended to be suspended in the superimposed water and had rougher profiles. Moreover, there was self-similarity in the physical phase composition of SSPs among the points. By establishing linear regression models and RDA analysis, we discussed the morphological parameters of SSPs, the intrinsic connection between chemical components, and each form of phosphorus. We separately estimated the endogenous phosphorus load in zones I, II, and III. With our research results, we have highlighted the differences in the physicochemical properties of SSPs triggering environmental effects and provided novel thoughts for remediating endogenous pollution in lakes. The follow-up will explore the interrelationship between the three phases of SSPs, aquatic and biological, and research the dynamic coupled environmental system formed between the three.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su15086888/s1, Figure S1: Correlation analysis between morphological parameters and TP and each morphological phosphorus at different particle size classes of the granules. D means particle size content (%) in the order of clay, silt, and sand; K means angle; R means roundness; FD means roughness.

Author Contributions

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

Funding

This research was funded by the National Natural Science Foundation of China, grant number 52179064, A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions and National Nature Science Foundation of China, grant number 51479064, and Water conservancy science and technology project of Jiangxi Province, grant number 202023ZDKT12. And The APC was funded by Prof. Hua Wang.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data and material are available from the corresponding author.

Acknowledgments

Many thanks to my teacher, Wang Hua, and my partners for their support of this research.

Conflicts of Interest

We declare that we have no financial or personal relationships with others or organizations that can inappropriately influence our work. There is no professional or other personal interest of any nature or kind in any product, service, or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.

References

  1. Borthakur, A.; Wang, M.; He, M.; Ascencio, K.; Blotevogel, J.; Adamson, D.T.; Mahendra, S.; Mohanty, S.K. Perfluoroalkyl acids on suspended particles: Significant transport pathways in surface runoff, surface waters, and subsurface soils. J. Hazard. Mater. 2021, 417, 126159. [Google Scholar] [CrossRef] [PubMed]
  2. Liu, M.Y.; Huai, W.X.; Chen, B. Predicting the effective diffusivity across the sediment-water interface in rivers. J. Clean. Prod. 2021, 292, 126085. [Google Scholar] [CrossRef]
  3. Zhao, Y.; Zou, L.; Niu, Z.; Luo, X.; Li, X. Advances in the Analysis of Organic Contaminants in Sediments and Particu-late Matters by Liquid Chromatography-High Resolution Mass Spectrometry. J. Instrum. Anal. 2021, 40, 1396–1408. [Google Scholar]
  4. Adhikari, P.L.; Maiti, K.; Bam, W. Fate of particle-bound polycyclic aromatic hydrocarbons in the river-influenced continental margin of the northern Gulf of Mexico. Mar. Pollut. Bull. 2019, 141, 350–362. [Google Scholar] [CrossRef] [PubMed]
  5. Chen, C.; Kong, M.; Wang, Y.Y.; Shen, Q.S.; Zhong, J.C.; Fan, C.X. Dredging method effects on sediment resuspension and nutrient release across the sediment-water interface in Lake Taihu, China. Environ. Sci. Pollut. Res. 2020, 27, 25861–25869. [Google Scholar] [CrossRef] [PubMed]
  6. Fan, J.Y.; Jian, X.; Shang, F.; Zhang, W.; Zhang, S.; Fu, H.J. Underestimated heavy metal pollution of the Minjiang River, SE China: Evidence from spatial and seasonal monitoring of suspended-load sediments. Sci. Total Environ. 2021, 760, 142586. [Google Scholar] [CrossRef]
  7. Drummond, J.; Schmadel, N.; Kelleher, C.; Packman, A.; Ward, A. Improving Predictions of Fine Particle Immobilization in Streams. Geophys. Res. Lett. 2019, 46, 13853–13861. [Google Scholar] [CrossRef]
  8. Walch, H.; von der Kammer, F.; Hofmann, T. Freshwater suspended particulate matter-Key components and processes in floc formation and dynamics. Water Res. 2022, 220, 118655. [Google Scholar] [CrossRef]
  9. Wang, T.; Qu, G.; Sun, Q.; Liang, D.; Hu, S. Evaluation of the potential of p-nitrophenol degradation in dredged sediment by pulsed discharge plasma. Water Res. 2015, 84, 18–24. [Google Scholar] [CrossRef]
  10. Wang, M.J.; Wang, Z.Y.; Huang, C.J. Scattering Characteristics of Marine Mixed Suspended Particles to Blue and Green Lasers. Spectrosc. Spectr. Anal. 2022, 42, 1749–1754. [Google Scholar]
  11. Sanchez, N.; Bizsel, N.; Iriarte, J.L.; Olsen, L.M.; Ardelan, M.V. Iron cycling in a mesocosm experiment in a north Patagonian fjord: Potential effect of ammonium addition by salmon aquaculture. Estuar. Coast. Shelf Sci. 2019, 220, 209–219. [Google Scholar] [CrossRef]
  12. Wu, S.; Liufu, W.; Xu, Z.; Zhong, M.; Pu, J.; Su, Y.; Su, L.; Yang, X. Mechanism and application of in situ remediation of black and smelly sediment by calcium nitrate sustained-release particles. Chin. J. Environ. Eng. 2022, 16, 2198–2207. [Google Scholar]
  13. Niu, J.W.; Xu, J.S.; Li, G.X.; Dong, P.; Shi, J.H.; Qiao, L.L. Swell-dominated sediment re-suspension in a silty coastal seabed. Estuar. Coast. Shelf Sci. 2020, 242, 106845. [Google Scholar] [CrossRef]
  14. Geng, X.; Li, D.P.; Xu, C.T.; Sun, P.R. Using sediment resuspension to immobilize sedimentary phosphorus. Environ. Sci. Pollut. Res. 2021, 28, 1837–1849. [Google Scholar] [CrossRef] [PubMed]
  15. Li, D.; Yang, Z.H.; Guo, M. Study of Suspended Sediment Diffusion Coefficients in Submerged Vegetation Flow. Water Resour. Res. 2022, 58, e2021WR031155. [Google Scholar] [CrossRef]
  16. Wu, Y.; Fang, H.; Huang, L.; Cui, Z. Particulate organic carbon dynamics with sediment transport in the upper Yangtze River. Water Res. 2020, 184, 116193. [Google Scholar] [CrossRef]
  17. Liu, L.; Li, Z.W.; Li, Z.J.; Liu, E.F.; Nie, X.D.; Liu, C.; Xiao, H.B. Effect of aggregate breakdown on the unevenly enriched organic carbon process in sediments under a rain-induced overland flow. Soil Tillage Res. 2020, 204, 104752. [Google Scholar] [CrossRef]
  18. Xing, X.L.; Chen, M.S.; Wu, Y.X.; Tang, Y.Z.; Li, C. The decomposition of macrozoobenthos induces large releases of phosphorus from sediments. Environ. Pollut. 2021, 283, 117104. [Google Scholar] [CrossRef]
  19. Wang, S.; Pan, C.; Li, H.; Han, C. Distribution and influence factor of Cu, Pb, Hg in surficial sediments and suspended sediments of Hangzhou Bay. China Environ. Sci. 2017, 37, 4701–4709. [Google Scholar]
  20. Ehn, J.K.; Reynolds, R.A.; Stramski, D.; Doxaran, D.; Lansard, B.; Babin, M. Patterns of suspended particulate matter across the continental margin in the Canadian Beaufort Sea during summer. Biogeosciences 2019, 16, 1583–1605. [Google Scholar] [CrossRef]
  21. Nguyen, T.T.H.; Zhang, W.G.; Li, Z.; Li, J.; Ge, C.; Liu, J.Y.; Bai, X.X.; Feng, H.; Yu, L.Z. Assessment of heavy metal pollution in Red River surface sediments, Vietnam. Mar. Pollut. Bull. 2016, 113, 513–519. [Google Scholar] [CrossRef] [PubMed]
  22. Ben Hamza, S.; Ben Kalifa, R.; Said, N.M.; Bournot, H.; Le Palec, G. Numerical study of sediment transport in turbulent two-phase flows around an obstacle. Appl. Math. Model. 2017, 45, 97–122. [Google Scholar] [CrossRef]
  23. Vazquez-Tarrio, D.; Piegay, H.; Menendez-Duarte, R. Textural signatures of sediment supply in gravel-bed rivers: Revisiting the armour ratio. Earth-Sci. Rev. 2020, 207, 103211. [Google Scholar] [CrossRef]
  24. Zhao, B.; Hu, Y.S.; Yu, H.R.; Chen, S.K.; Xing, T.; Guo, S.S.; Zhang, H. A method for researching the eutrophication and N/P loads of plateau lakes: Lugu Lake as a case. Sci. Total Environ. 2023, 876, 162747. [Google Scholar] [CrossRef] [PubMed]
  25. Ha, M.E.; Zhang, Z.L.; Wu, M. Biomass production in the Lower Mississippi River Basin: Mitigating associated nutrient and sediment discharge to the Gulf of Mexico. Sci. Total Environ. 2018, 635, 1585–1599. [Google Scholar] [CrossRef] [PubMed]
  26. Jin, X.; Zhang, W.Q.; Li, S.M. Complex responses of suspended particulate matter in eutrophic river and its indicative function in river recovery process. Ecol. Indic. 2020, 115, 106397. [Google Scholar] [CrossRef]
  27. Wang, X.X.; Zhou, J.; Wu, Y.H.; Bol, R.; Wu, Y.; Sun, H.Y.; Bing, H.J. Fine sediment particle microscopic characteristics, bioavailable phosphorus and environmental effects in the world largest reservoir. Environ. Pollut. 2020, 265, 114917. [Google Scholar] [CrossRef]
  28. Fan, W.; Ao, L.; Zhang, S. Sedimentary phosphorus fractions in typical lacustrine wetland of Changshou Lake flowing into the Three-Gorges Reservoir. Bull. Environ. Contam. Toxicol. 2022, 109, 706–712. [Google Scholar] [CrossRef]
  29. Que, Z.; Wang, X.; Yuan, X.; Wu, S.; Yu, L.; Li, H.; Zhang, Y.; Wang, J. Spatial-temporal distribution of carbon, nitrogen and phosphorus concentrations and eutrophication evaluation of mountainous small river in a cascaded damming. J. Lake Sci. 2022, 34, 1949–1967. [Google Scholar]
  30. An, C.G.; Fu, X.D. Theory of delayed response in river morphodynamics: Applicability and limitations. Int. J. Sediment Res. 2022, 37, 162–172. [Google Scholar] [CrossRef]
  31. Dallmann, J.; Phillips, C.B.; Teitelbaum, Y.; Sund, N.; Schumer, R.; Arnon, S.; Packman, A.I. Impacts of Suspended Clay Particle Deposition on Sand-Bed Morphodynamics. Water Resour. Res. 2020, 56, e2019WR027010. [Google Scholar] [CrossRef]
  32. Ji, N.N.; Liu, Y.; Wang, S.R.; Wu, Z.H.; Li, H. Buffering effect of suspended particulate matter on phosphorus cycling during transport from rivers to lakes. Water Res. 2022, 216, 118350. [Google Scholar] [CrossRef]
  33. Su, X.M.; Steinman, A.D.; Zhang, Y.L.; Ling, H.; Wu, D. Significant Temporal and Spatial Variability in Nutrient Concentrations in a Chinese Eutrophic Shallow Lake and Its Major Tributaries. Water 2022, 14, 217. [Google Scholar] [CrossRef]
  34. Cheng, X.L.; Huang, Y.N.; Li, R.; Pu, X.C.; Huang, W.D.; Yuan, X.F. Impacts of water temperature on phosphorus release of sediments under flowing overlying water. J. Contam. Hydrol. 2020, 235, 103717. [Google Scholar] [CrossRef] [PubMed]
  35. Juez, C.; Garijo, N.; Hassan, M.A.; Nadal-Romero, E. Intraseasonal-to-Interannual Analysis of Discharge and Suspended Sediment Concentration Time-Series of the Upper Changjiang (Yangtze River). Water Resour. Res. 2021, 57, e2020WR029457. [Google Scholar] [CrossRef]
  36. Rhoads, B.L. River Dynamics: Geomorphology to Support Management; Cambridge University Press: Cambridge, UK, 2020. [Google Scholar]
  37. Choudhary, S.; Nayak, G.; Tiwari, A.K.; Khare, N. Sediment composition and its effect on the productivity in Larsemann Hills, East Antarctica. Arab. J. Geosci. 2018, 11, 416. [Google Scholar] [CrossRef]
  38. Pavoni, E.; Crosera, M.; Petranich, E.; Faganeli, J.; Klun, K.; Oliveri, P.; Covelli, S.; Adami, G. Distribution, Mobility and Fate of Trace Elements in an Estuarine System Under Anthropogenic Pressure: The Case of the Karstic Timavo River (Northern Adriatic Sea, Italy). Estuaries Coasts 2021, 44, 1831–1847. [Google Scholar] [CrossRef]
  39. Fink, G.; Alcamo, J.; Florke, M.; Reder, K. Phosphorus Loadings to the World’s Largest Lakes: Sources and Trends. Glob. Biogeochem. Cycles 2018, 32, 617–634. [Google Scholar] [CrossRef]
  40. Liang, J.; Liu, J.; Xu, G.; Chen, B. Grain-size characteristics and net transport patterns of surficial sediments in the Zhejiang nearshore area, East China Sea. Oceanologia 2020, 62, 12–22. [Google Scholar] [CrossRef]
  41. Qi, L.Y.; Huang, J.C.; Huang, Q.; Gao, J.F.; Wang, S.G.; Guo, Y.Y. Assessing Aquatic Ecological Health for Lake Poyang, China: Part II Index Application. Water 2018, 10, 909. [Google Scholar] [CrossRef]
  42. Wang, Y.; Molinos, J.G.; Shi, L.L.; Zhang, M.; Wu, Z.S.; Zhang, H.; Xu, J. Drivers and Changes of the Poyang Lake Wetland Ecosystem. Wetlands 2019, 39, S35–S44. [Google Scholar] [CrossRef]
  43. Huang, A.; Liu, X.; Peng, W.; Dong, F.; Ma, B.; Li, J.; Wang, W. Spatiotemporal characteristics, influencing factors and evolution laws of water exchange capacity of Poyang Lake. J. Hydrol. 2022, 609, 127717. [Google Scholar] [CrossRef]
  44. Xu, C.; Yang, G.; Wan, R.; Ou, W.; Wang, P. Toward ecological function zoning and comparison to the Ecological Redline Policy: A case study in the Poyang Lake Region, China. Environ. Sci. Pollut. Res. 2021, 28, 40178–40191. [Google Scholar] [CrossRef] [PubMed]
  45. Liu, W.L.; Zhu, S.N.; Huang, Y.P.; Wan, Y.F.; Wu, B.; Liu, L. Spatiotemporal Variations of Drought and Their Teleconnections with Large-Scale Climate Indices over the Poyang Lake Basin, China. Sustainability 2020, 12, 3526. [Google Scholar] [CrossRef]
  46. Song, Y.Y.; Zhang, Q.; Melack, J.M.; Li, Y.L. Groundwater dynamics of a lake-floodplain system: Role of groundwater flux in lake water storage subject to seasonal inundation. Sci. Total Environ. 2023, 857, 159414. [Google Scholar] [CrossRef]
  47. Li, Y.; Zhang, Q.; Tao, H.; Yao, J. Integrated model projections of climate change impacts on water-level dynamics in the large Poyang Lake (China). Hydrol. Res. 2019, 52, 43–60. [Google Scholar] [CrossRef]
  48. Liu, X.; Mei, Z.; Zhang, J.; Sun, J.; Zhang, N.; Guo, Y.; Wang, K.; Hao, Y.; Wang, D. Seasonal Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis) movements in the Poyang Lake, China: Implications on flexible management for aquatic animals in fluctuating freshwater ecosystems. Sci. Total Environ. 2022, 807, 150782. [Google Scholar] [CrossRef]
  49. Zhao, Z.; Yu, D.; Han, C.; Wang, K. Ecosystem services value prediction and driving forces in the Poyang Lake Eco-economic Zone. Acta Ecol. Sin. 2017, 37, 8411–8421. [Google Scholar]
  50. Li, T.; Sun, G.H.; Yang, C.P.; Liang, K.; Ma, S.Z.; Huang, L.; Luo, W.D. Source apportionment and source-to-sink transport of major and trace elements in coastal sediments: Combining positive matrix factorization and sediment trend analysis. Sci. Total Environ. 2019, 651, 344–356. [Google Scholar] [CrossRef]
  51. Aramendia, J.; Gomez-Nubla, L.; Castro, K.; de Vallejuelo, S.F.O.; Arana, G.; Maguregui, M.; Baonza, V.G.; Medina, J.; Rull, F.; Madariaga, J.M. Overview of the techniques used for the study of non-terrestrial bodies: Proposition of novel non-destructive methodology. Trac-Trends Anal. Chem. 2018, 98, 36–46. [Google Scholar] [CrossRef]
  52. Barnes, M.; McLeod, C.L.; Chappell, C.; Faraci, O.; Gibson, B.; Krekeler, M.P.S. Characterizing the geogenic background of the Midwest: A detailed mineralogical and geochemical investigation of a glacial till in southwestern Ohio. Environ. Earth Sci. 2020, 79, 1–22. [Google Scholar] [CrossRef]
  53. Fahad, M.; Ali, S.; Iqbal, Y. Plasma diagnostics by optical emission spectroscopy on manganese ore in conjunction with XRD, XRF and SEM-EDS. Plasma Sci. Technol. 2019, 21, 085507. [Google Scholar] [CrossRef]
  54. Deng, J.J.; Drevet, T.; Penard, L.; Camenen, B. Fine sediment dynamics over a gravel bar. Part 1: Validation of a new image-based segmentation method. Catena 2023, 225, 106978. [Google Scholar] [CrossRef]
  55. Tao, J.; Zhang, C.; Guo, X.; Zhu, R.; Pan, J.; Tang, Y. Application of Quantitative Roundness Characterization to Identify Sedimentary Microfacies in Fan Delta Deposits: A case study of conglomerates in the Baikouquan Formation, Mahu Sag. Acta Sedimentol. Sin. 2020, 38, 956–965. [Google Scholar]
  56. Chen, R.; Feng, M.X.; Li, M.; Huang, Y. Size distribution and particle shape of iron ore powder based on the fractal theory. Mater. Res. Innov. 2015, 19, 405–409. [Google Scholar] [CrossRef]
  57. Xu, W.; Li, X.; Wai, O.W.H.; Huang, W.; Yan, W. Remobilization of trace metals from contaminated marine sediment in a simulated dynamic environment. Environ. Sci. Pollut. Res. 2015, 22, 19905–19911. [Google Scholar] [CrossRef]
  58. MoayeriKashani, M.; Lai, S.H.; Ibrahim, S.; Sulaiman, N.M.N.; Teo, F.Y. Tracking the hydrodynamic behavior of fine sediment using particle image velocimetry. Environ. Earth Sci. 2016, 75, 1–13. [Google Scholar] [CrossRef]
  59. Zhang, T.; Wen, Y.; Dong, D.; Wang, G. Grain size features and sedimentary environment of surficial sediments in the northwest Lake Taihu. J. Lake Sci. 2018, 30, 836–846. [Google Scholar]
  60. Wang, Z.; Yu, D.; Wang, W.; Luo, F.; Tang, J.; Yang, J. End-Member Analysis of Sedimentary Dynamics Indicated by the Grain-Size of Surface Sediments in the Quanzhou Bay. Trop. Geogr. 2021, 41, 975–986. [Google Scholar]
  61. Gao, W.; Liu, S.H.; Liu, J.; Xu, Y.Q.; Li, P. The sedimentary facies and dynamic environment of the Diaokou lobe in the modern Huanghe River Delta of China. Acta Oceanol. Sin. 2018, 37, 40–52. [Google Scholar] [CrossRef]
  62. Kinsyo, T.; Nakanishi, H.; Hirai, K.; Noda, H.; Takikawa, T.; Yahiro, S. Development of polyester resin particles for toner with a controlled particle size distribution and shape. Polym. J. 2017, 49, 593–600. [Google Scholar] [CrossRef]
  63. Ledieu, L.; Simonneau, A.; Cerdan, O.; Negrel, P.; Laperche, V.; Grosbois, C.; Laggoun-Defarge, F. Geochemical insights into spatial and temporal evolution of sediment at catchment scale (Egoutier stream, France). Appl. Geochem. 2020, 122, 104743. [Google Scholar] [CrossRef]
  64. Fernandes, E.; Vitorino, N.; Ribeiro, M.J.; Teixeira, C.; Bordalo, A.A. Spatial and seasonal dynamics of elemental composition and mineralogy of intertidal and subtidal sediments in the Lima estuary (NW Portugal). Arab. J. Geosci. 2019, 12, 412. [Google Scholar] [CrossRef]
  65. Shruti, V.C.; Jonathan, M.P.; Rodríguez-Espinosa, P.F.; Nagarajan, R.; Escobedo-Urias, D.C.; Morales-García, S.S.; Martínez-Tavera, E. Geochemical characteristics of stream sediments from an urban-volcanic zone, Central Mexico: Natural and man-made inputs. Geochemistry 2017, 77, 303–321. [Google Scholar] [CrossRef]
  66. Lipp, A.G.; Roberts, G.G.; Whittaker, A.C.; Gowing, C.J.B.; Fernandes, V.M. River Sediment Geochemistry as a Conservative Mixture of Source Regions: Observations and Predictions From the Cairngorms, UK. J. Geophys. Res.-Earth Surf. 2020, 125, e2020JF005700. [Google Scholar] [CrossRef]
  67. Jia, X.; Tian, Z.; Zhang, D.; Jiang, M. Physical and Chemical Characteristic and Phosphorus Adsorption Efficiency of Surface Sediment in Xiaoxingkai Lake. Wetl. Sci. 2021, 19, 577–584. [Google Scholar]
  68. Wang, Y.D.; Ouyang, W.; He, M.C.; Han, F.X.; Lin, C.Y. Sorption dynamics, geochemical fraction and driving factors in phosphorus transport at large basin scale. J. Clean. Prod. 2021, 294, 126111. [Google Scholar] [CrossRef]
  69. Wei, Z.; Xu, Y.; Zhao, Y.; Zhao, Y.; Bai, L.; Jiang, H.; Wang, C. The settling of resuspended lake sediment related to physicochemical properties of particles of different sizes: Implication for environmental remediation. Int. J. Sediment Res. 2021, 36, 542–554. [Google Scholar] [CrossRef]
  70. Takata, H.; Aono, T.; Tagami, K.; Uchida, S. A new approach to evaluate factors controlling elemental sediment-seawater distribution coefficients (K-d) in coastal regions, Japan. Sci. Total Environ. 2016, 543, 315–325. [Google Scholar] [CrossRef]
  71. Sims, D.B.; Hudson, A.C.; Keller, J.E.; Strange, M.; Buch, A.C.; Ferrari, D.; Fernandez, G.M.; Garcia-Hernandez, J.; Kesl, B.D.; Torres, S. Trace elements migrating from tailings to rock varnish laminated sediments in an old mining region from Nelson, Nevada, USA. Int. J. Sediment Res. 2022, 37, 202–213. [Google Scholar] [CrossRef]
  72. Haddout, S.; Priya, K.L.; Casila, J.C.C.; Samad, B. Assessment of heavy metal contamination in the surficial sediments from the Sebou River Estuary, Morocco. Environ. Forensics 2022, 23, 23–31. [Google Scholar] [CrossRef]
  73. Zhan, L.C.; Chen, J.S.; Zhang, S.Y.; Li, L.; Huang, D.W.; Wang, T. Isotopic signatures of precipitation, surface water, and groundwater interactions, Poyang Lake Basin, China. Environ. Earth Sci. 2016, 75, 1–14. [Google Scholar] [CrossRef]
  74. He, Q.; Qiu, Y.; Liu, H.; Sun, X.; Kang, L.; Cao, L.; Li, H.; Ai, H. New insights into the impacts of suspended particulate matter on phytoplankton density in a tributary of the Three Gorges Reservoir, China. Sci. Rep. 2017, 7, 1–11. [Google Scholar] [CrossRef]
  75. Lopez, M.; Lopez, I.; Aragones, L.; Serra, J.C.; Esteban, V. The erosion on the east coast of Spain: Wear of particles, mineral composition, carbonates and Posidonia oceanica. Sci. Total Environ. 2016, 572, 487–497. [Google Scholar] [CrossRef] [PubMed]
  76. Zhu, C.Y.; Guo, L.C.; Maren, D.S.; Wang, Z.B.; He, Q. Exploration of Decadal Tidal Evolution in Response to Morphological and Sedimentary Changes in the Yangtze Estuary. J. Geophys. Res.-Ocean. 2021, 126, e2020JC017019. [Google Scholar] [CrossRef]
  77. Zhang, R.R.; Li, M.; Yuan, X.; Pan, Z.C. Influence of rainfall intensity and slope on suspended solids and phosphorus losses in runoff. Environ. Sci. Pollut. Res. 2019, 26, 33963–33975. [Google Scholar] [CrossRef] [PubMed]
  78. Galy, V.; Peucker-Ehrenbrink, B.; Eglinton, T. Global carbon export from the terrestrial biosphere controlled by erosion. Nature 2015, 521, 204–207. [Google Scholar] [CrossRef] [PubMed]
  79. River, M.; Richardson, C.J. Suspended Sediment Mineralogy and the Nature of Suspended Sediment Particles in Stormflow of the Southern Piedmont of the USA. Water Resour. Res. 2019, 55, 5665–5678. [Google Scholar] [CrossRef]
  80. Cheng, B.; Yang, Q.; Shu, Z.; Miao, K.; Wang, M. Studies on the Degradation and Mobility of Iprodione in Soil. Asian J. Ecotoxicol. 2019, 14, 304–310. [Google Scholar]
  81. Tay, C.J.; Mohd, M.H.; Teh, S.Y.; Koh, H.L. Internal phosphorus recycling promotes rich and complex dynamics in an algae-phosphorus model: Implications for eutrophication management. J. Theor. Biol. 2022, 532, 110913. [Google Scholar] [CrossRef]
  82. Zou, Y.; Zhang, R.; Chen, J.A.; Wang, L.; Lu, D. Research Advance in the Application of Clay Minerals to Phosphorus Pollution Control in Eutrophic Water Bodies and Sediments. Adv. Earth Sci. 2018, 33, 578–589. [Google Scholar]
  83. Liu, C.; Du, Y.H.; Yin, H.B.; Fan, C.X.; Chen, K.N.; Zhong, J.C.; Gu, X.Z. Exchanges of nitrogen and phosphorus across the sediment-water interface influenced by the external suspended particulate matter and the residual matter after dredging. Environ. Pollut. 2019, 246, 207–216. [Google Scholar] [CrossRef] [PubMed]
  84. Hu, W.X.; Kang, X.; Cao, J.; Wang, X.L.; Fu, B.; Wu, H.G. Thermochemical oxidation of methane induced by high-valence metal oxides in a sedimentary basin. Nat. Commun. 2018, 9, 1–11. [Google Scholar] [CrossRef]
  85. Wang, Y.; Yu, Y.; Li, H.Y.; Shen, C.C. Comparison study of phosphorus adsorption on different waste solids: Fly ash, red mud and ferric-alum water treatment residues. J. Environ. Sci. 2016, 50, 79–86. [Google Scholar] [CrossRef] [PubMed]
Sustainability 15 06888 g001 550
Figure 1. Location of Poyang Lake (a); point map of Poyang Lake (b); point map of Poyang elevation map of Poyang Lake (c).
Figure 1. Location of Poyang Lake (a); point map of Poyang Lake (b); point map of Poyang elevation map of Poyang Lake (c).
Sustainability 15 06888 g001
Sustainability 15 06888 g002 550
Figure 2. Microscopic morphology and structure of suspended sediment particulate matter. Particulate matter classification (a); schematic diagram of measurement parameters (A: sum of pixels of the particle; C: sum of the distances of consecutive boundary pixels of the particle; L: long axis of the particle; W: short axis of the particle; R: particle roundness; FD: measurement of the irregularity of the surface) (b); morphological parameters of particulate matter (c).
Figure 2. Microscopic morphology and structure of suspended sediment particulate matter. Particulate matter classification (a); schematic diagram of measurement parameters (A: sum of pixels of the particle; C: sum of the distances of consecutive boundary pixels of the particle; L: long axis of the particle; W: short axis of the particle; R: particle roundness; FD: measurement of the irregularity of the surface) (b); morphological parameters of particulate matter (c).
Sustainability 15 06888 g002
Sustainability 15 06888 g003 550
Figure 3. Particle composition (a); particle size distribution (b); particulate matter two-dimensional index coefficient of variation distribution (c).
Figure 3. Particle composition (a); particle size distribution (b); particulate matter two-dimensional index coefficient of variation distribution (c).
Sustainability 15 06888 g003
Sustainability 15 06888 g004 550
Figure 4. Chemical fraction of suspended particulate matter. SEM image for EDS analysis (a); average content of atomic percentages of elements (A%) at monitoring sites (b); elemental content of Fe, Al, and Ca at different grain levels (c).
Figure 4. Chemical fraction of suspended particulate matter. SEM image for EDS analysis (a); average content of atomic percentages of elements (A%) at monitoring sites (b); elemental content of Fe, Al, and Ca at different grain levels (c).
Sustainability 15 06888 g004
Sustainability 15 06888 g005 550
Figure 5. Verification of correlation between physical parameters of particulate matter and hydrodynamics and water environment (a); comparison of chemical components between suspended sediment particles and soil (b); RDA analysis of chemical properties of total phosphorus and various forms of phosphorus in particulate matter (c); estimates of entire and multiple forms of phosphorus in each lake area of Poyang Lake, including OP and Fe/Al- P content is endogenous phosphorus load (d).
Figure 5. Verification of correlation between physical parameters of particulate matter and hydrodynamics and water environment (a); comparison of chemical components between suspended sediment particles and soil (b); RDA analysis of chemical properties of total phosphorus and various forms of phosphorus in particulate matter (c); estimates of entire and multiple forms of phosphorus in each lake area of Poyang Lake, including OP and Fe/Al- P content is endogenous phosphorus load (d).
Sustainability 15 06888 g005
Sustainability 15 06888 g006 550
Figure 6. Relationship between morphological parameters of particulate matter and various forms of phosphorus at diverse particle sizes.
Figure 6. Relationship between morphological parameters of particulate matter and various forms of phosphorus at diverse particle sizes.
Sustainability 15 06888 g006
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cui, F.; Wang, H.; Shen, Z.; Li, Y.; Li, S.; Tian, X. Physicochemical Properties and Environmental Effects of Suspended Sediment Particles in the Largest Freshwater Lake, China. Sustainability 2023, 15, 6888. https://doi.org/10.3390/su15086888

AMA Style

Cui F, Wang H, Shen Z, Li Y, Li S, Tian X. Physicochemical Properties and Environmental Effects of Suspended Sediment Particles in the Largest Freshwater Lake, China. Sustainability. 2023; 15(8):6888. https://doi.org/10.3390/su15086888

Chicago/Turabian Style

Cui, Fang, Hua Wang, Zilin Shen, Yuanyuan Li, Siqiong Li, and Xueqi Tian. 2023. "Physicochemical Properties and Environmental Effects of Suspended Sediment Particles in the Largest Freshwater Lake, China" Sustainability 15, no. 8: 6888. https://doi.org/10.3390/su15086888

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop