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Scientific Reports Volume 11, Article Number: 17067 (2021) Cite this article
This study aims to determine the spatial distribution characteristics of Cu and Zn adsorption by sediments in the Dianchi estuary, and the composite adsorption law of Cu and Zn on sediment organic matter, metal oxides, and organic-inorganic composites. . The relationship between the adsorption contribution of each component of the substance. A static adsorption experiment was carried out on the sediments in the estuary of Dianchi Lake. Through correlation analysis and redundancy analysis, the relationship between adsorption capacity and sediment composition is analyzed. The results show that along the flow direction and vertical depth of the river, the amount of adsorption presents a more obvious spatial distribution law; the change trend of the sediment composition content is different from the change trend of the adsorption amount of Cu and Zn. The change trend of sediment component content is different from the change trend of Cu and Zn adsorption capacity. The compound effect between the components affects the adsorption capacity. The adsorption of Cu by the four groups of sediments after different treatments is more consistent with the Freundlich isotherm adsorption model; when Zn is adsorbed, the untreated and removed organics and iron-aluminum oxide groups are in good agreement with the Freundlich model, while the organic removal groups and iron-aluminum The oxide removal group is more in line with the Langmuir isotherm adsorption model; the adsorption contribution rate of the organic-inorganic composite in the sediment is not a simple addition of organic matter and iron-aluminum oxide, but a more complex quantitative relationship.
Estuary is the transition zone between lakes and rivers, with strong energy flow and material circulation. The estuary circulation leads to the redistribution of river sediments, water salinity, redox processes and pH values, which affect the mobility (including dissolution, deposition and diffusion) and spatial distribution of metals1. Due to the limited surface runoff in the dry and dry seasons, the surface runoff increased significantly during the rainy season and heavy rains, and the amount of heavy metals entering Dianchi Lake varies greatly with the seasons. In addition, as the urbanization of rivers flowing into Dianchi Lake increases year by year, pollution sources are also increasing. A large amount of heavy metals carried into Dianchi Lake can easily accumulate in the estuary. In the past, the spatial distribution, morphological analysis and ecological risk assessment of heavy metals in Dianchi Lake mostly focused on the adsorption direction of heavy metals on sediments. Adsorption is the main process for the transfer of pollutants to sediments4,5, which directly affects the migration, transformation, bioavailability, solubility and activity of heavy metals in the environment, as well as the concentration and bioavailability of heavy metal ions in sediments6. Therefore, exploring the adsorption mechanism and distribution characteristics of heavy metals in estuary sediments will help to formulate corresponding prevention and control measures according to local conditions, and will also help improve the understanding of the filtering and purification of heavy metal pollutants in wetland ecosystems and their mechanism of action. 7. Role in secondary pollution
Natural water sediments are mainly composed of minerals, with clay minerals (illite, kaolinite, and montmorillonite) as the core material. Metal oxides (iron oxide, aluminum oxide, manganese oxide) and organic matter (OM, mainly humic acid and tannic acid) combine with the surface of core mineral particles to form flocculent aggregates, which play an indispensable role in the adsorption process of metal pollution The lack of role8,9. Therefore, related scholars have conducted a lot of research on the role of sediment components in the process of adsorbing heavy metals. Generally, the role of a single component in adsorption is studied by artificially synthesizing a single sediment component 10, 11 or by selectively removing certain components (such as OM or iron oxide) from the sediment 11, 12. However, single-component studies ignore the influence of organic-inorganic composites in multi-component sediments. It is necessary to consider the role of each potentially influencing component to fully characterize sediment adsorption. In this research, we are committed to further exploring the adsorption mechanism of multi-component interactions and improving the understanding of the theory of multi-component complex adsorption systems.
This study will explore the vertical depth of the estuary and the spatial distribution characteristics of Cu(II) and Zn(II) adsorption in river sediments, as well as the impact of sediment organic matter, metal oxides, and organic-inorganic composites on sediments. The adsorption of Cu(II) and Zn(II) in sediments, especially the contribution rate of heavy metal adsorption between organics, metal oxides and organic-inorganic composites, to understand the deposition law of heavy metals in natural water and reveal wetland deposition in depth The adsorption mechanism of heavy metals by substances, and obtaining a combination of adsorption influencing factors with stronger adsorption capacity, is the preparation of the key underlying matrix material for wetland construction and restoration. Provide theoretical basis, especially in accordance with the adsorption characteristics of heavy metals in the lake mouth sediments, and take remediation measures according to local conditions to form a project implementation technical plan for the prevention and control of heavy metals in natural water.
Dianchi Lake is the largest plateau lake in Yunnan and one of the urban lakes with serious water pollution. The rivers entering the lake have the characteristics of small flow, short flow, high pollution load, poor water quality, and relatively insufficient self-purification capacity of the river. The rivers with high pollution load in the basin have seriously threatened the ecological safety of Dianchi Lake14. Among them, Xinhe is the river that flows into the lake from the south of Dianchi Lake. It flows through urban and rural residential land and commercial land. Affected by human activities, the sediment pollution is serious, and the mud volume is large15. Therefore, this study chose Xinhe as the study area for the adsorption capacity of Cu and Zn by the sediments from the lakes and rivers at the entrance of Dianchi Lake.
The sampling point (Figure 1) is located in Xin Hanoi next to the positioning observation station of the National Plateau Wetland Research Center. Each sampling point is in the reflux section, the flow rate is slow, and the water depth is greater than 0.5m. According to Schiller [16], the water flow in the recirculation section is slow, organic matter is easy to deposit here, and Cu is fixed in the sediment. Therefore, the sediments in this profile can better reflect the influence of human activities on the adsorption capacity of sediments. The sediment samples were collected using fixed depth peat drills at 10 cm intervals along the direction of the water flow. Three depths are sampled at each interval: (1) 0-10 cm, (2) 10-20 cm, and (3) 20-30 cm. After removing impurities, air drying and grinding, the samples pass through a 0.2-mm sieve and are stored in sealed ziplock bags.
The pH value of the sediment was measured by the glass electrode method, and the water-soil ratio was 1:2.5. The sediment OM is obtained by using a total organic carbon (TOC) analyzer to obtain the TOC content, and then converting the value to a coefficient. Cation exchange capacity (CEC) was measured by hexaammine cobalt trichloride extraction spectrophotometry. The content of iron and alumina was determined by extraction with oxalic acid-ammonium oxalate solution. Table 1 shows the main physical and chemical properties of the sediments studied.
Prepare four groups of samples: (1) untreated, group A, (2) removal of OM, group B, (3) removal of iron and alumina, group C, and (4) removal of OM and iron and alumina, group D.
To prepare group B, 30% hydrogen peroxide was added to the sample and the mixture was placed in a water bath at 90 °C. To prepare group C, a solution of 16 g of ammonium oxalate and 10.88 g of oxalate was added to 5 g of soil in a 50 ml centrifuge tube. The mixture was stirred in a constant temperature shaker at 300 RPM/min for 48 hours. The liquid was changed every 24 hours, and the soil sample was washed with 0.01 mol/L sodium chloride (NaCl) to remove iron and alumina in the soil sample. To prepare the D group, two methods were applied.
A series of experiments were performed on each of the four groups using a series of Cu and Zn concentrations: 3 mg/L, 5 mg/L, 10 mg/L, 20 mg/L, 40 mg/L, and 60 mg/LL And 25 mg/L, 50 mg/L, 80 mg/L, 100 mg/L, 160 mg/L and 200 mg/L. For each experimental condition, put 0.5 g of soil sample in a 50 ml plastic centrifuge tube, add 15 ml of sodium nitrate (0.01 mol/L NaNO3) as a background electrolyte, and 1 ml of potassium chloride (2 mol/L added KCl) to Maintain the ionic strength, add Cu and Zn at the target concentration, adjust the pH to 4-8 with nitric acid and sodium hydroxide, and place the tube in a constant temperature oscillator at a speed of 300 r/min. Then, the tube was centrifuged at 4000 rpm for 5 minutes, and the concentration of Cu and Zn in the supernatant and precipitate were measured by inductively coupled plasma emission spectrometry (ICP-OES). The original copper and zinc content in the sediment plus the added copper and zinc minus the copper and zinc content in the supernatant gives the adsorption capacity.
Freundlich (1) and Langmuir (2) isotherm adsorption models are used to fit experimental data:
Where Qe is the equilibrium adsorption concentration (mg/g), Ce is the equilibrium concentration (mg/L), Kf is the equilibrium adsorption coefficient, and 1/n is the linearity of the adsorption isotherm:
Where Qe is the equilibrium adsorption concentration (mg/g), Qmax is the maximum adsorption capacity (mg/g), Kl is the equilibrium adsorption coefficient, and Ce is the equilibrium concentration (mg/L).
Excel 2013 and SPSS 20.0 were used to organize and analyze the experimental data, Origin 2018 software was used for chart analysis and isotherm adsorption model fitting, and Canoco 5 was used for redundancy analysis.
Along the river into the estuary, the change trend of Cu(II) and Zn(II) in sediments at a depth of 0-10 cm shows that the positions 1, 2, 6, 7, and 8 are higher than other positions. At 10-20 cm, both Cu and Zn absorption decrease. At 20-30 cm, the amount of Cu adsorption gradually increased, while the amount of Zn adsorption gradually decreased with the distance from the river (Figure 2). Generally speaking, the adsorption of Cu(II) and Zn(II) by sediments in the direction of water flow is quite different. According to Tukey's test (Table 2), the amount of Cu(II) and Zn(II) adsorbed by the sediments changed significantly (P <0.05).
The effect of position along the flow direction and different depths on Cu(II) and Zinc(II) adsorption changes. (a) The adsorption capacity of Cu in the direction of flow, N=8; (b) The adsorption capacity of Zn in the direction of flow, N = 8; (c) The vertical change of the adsorption capacity of sediments to copper, N = 3; (d) The vertical change of the zinc adsorption capacity of the sediment, N=3. Different lowercase letters represent the difference of Tukey's test at 5% probability.
From the depths in Figure 2c, d and Table 3, the adsorption amount of Cu(II) at different depths of the three groups of sediments has no statistical difference (P> 0.05), and the change trend is not significant. The adsorption amount of Zn(II) has changed significantly, except for 0-10 cm and 10-20 cm, there is no significant difference (P = 0.73), the other depths are all P <0.05, the difference is large, and the change trend is 0~10 cm ≈ 10~20 cm> 20~30 cm, indicating that the adsorption capacity for surface and middle layer sediments is higher, but the adsorption capacity for middle layer sediments is lower.
The content of each component of the sediment is linearly fitted to the distance from the river (Table 4). The slope of the fitted line is used to characterize the changing trend of each component. A positive slope indicates an increase in concentration, and a negative slope indicates a decrease. At 0-10 cm, OM and CEC increase with the distance from the river, while the oxides of iron and aluminum decrease. At 10-20 cm and 20-30 cm, all components except CEC decreased as the distance from the river increased.
Except for OM, each component in the sediment has a large difference at depths of 10-20 cm and 20-30 cm (Figure 3), while the other components have relatively small differences (P <0.05), which is similar to the distribution of Zn adsorption.
The vertical distribution of each sediment component. (a) Vertical distribution of OM content and CEC at three depths, (b) Vertical distribution of adsorption capacity of iron and aluminum oxide at three depths. Different lowercase letters represent the difference under 5% probability through Tukey's test, N = 3.
As shown in Figure 4 and Table 5, the difference in Cu adsorption of group A is much greater than that of the other three groups. The adsorption of Cu for group A increased to 1.54 mg/g, while the highest adsorption capacities of groups B, C and D were 0.17, 0.22 and 0.18 mg/g, respectively. The adsorption isotherm curve gradually stabilized, and the adsorption process tended to equilibrium. The untreated group A did not reach the adsorption equilibrium.
Adsorption isotherm curve. (a) Copper, (b) Zinc.
The correlation coefficient (R2) shows that the four groups all fit the Freundlich isotherm adsorption model well, indicating that Cu adsorption is dominated by multilayer heterogeneous adsorption. The adsorption capacity of the four samples follows the order of A>C>B>D, and the order of the K value (representing the adsorption force in the Freundlich model) is also A(6.72)>C(0.17)>B(0.13))> D (0.1 ).
The 1/n>1(1.02) in the adsorption isotherm curve of group D indicates that group D follows a linear adsorption process, and the adsorption process is difficult to carry out. In addition, considering that 1/n> 1 (1.29) of group A, group A may be far from reaching the adsorption equilibrium, making the adsorption isotherm present a similar linear adsorption process. For the other two groups, 1/n <1 (0.47 and 0.76), indicating that the adsorption process is nonlinear adsorption.
As shown in Figure 4 and Table 6, the isotherm adsorption curves of groups A, B, C, and D for Zn gradually become stable, and the adsorption process tends to be balanced. The Freundlich model provides consistent results for the A and D groups, indicating that their adsorption process is dominated by multilayer heterogeneous adsorption, while the B and C groups are more consistent with the Langmuir isotherm adsorption model. The four groups of samples showed values of 1/n <1 (0.04, 0.03, 0.03, 0.63) in the Freundlich model, indicating that the adsorption process is nonlinear. Nevertheless, the adsorption results of Zn and Cu show similar trends, and the K value follows the order of group A> C> B> D.
The correlation analysis between the content of each component and the adsorption capacity of the sediment in the direction of the water flow was carried out. The correlation between adsorption capacity and OM content, CEC, iron and aluminum oxide content does not correspond to the change trend of adsorption capacity. It can be seen from Table 7 that the adsorption amount of Cu in the sediment at 0-10 cm has a high correlation with alumina (0.907), but the change trend of the adsorption amount is not significant. At 0-10 cm, the correlation between adsorption capacity and CEC is 0.943, but the adsorption capacity does not increase with the increase of CEC. At 10-20 cm, the adsorption of Zn is related to OM (0.604), but does not increase with the increase of OM.
These results indicate that the high content of certain sediment components does not mean that this component is the only factor driving the adsorption process. The overall effect may be due to changes in the surface potential of sediment particles. Studies have shown that (17) After removing iron and aluminum oxides from the soil, the amount of soil adsorption of Pb2 and Cd2 increases. This increase occurs because Pb2 and Cd2 can interact with the remaining citrate in the solution to form an acid complex The complex is adsorbed on the surface of soil particles and increases the negative potential. Another factor may be that even if the content of a certain component is high, other interwoven components may block or overlap the adsorption site. A study found that iron oxide can mask the charge sites of some soil particles.
In order to further explore the relationship between OM content, CEC, iron and alumina content and adsorption capacity in the direction of water flow, Cu and Zn are used as species, as well as OM content, CEC, and oxidation of iron and aluminum in sediments by Redundant Analysis (RDA) Material content as an environmental factor. The analysis results show that the adsorption amount of Cu and Zn has different correlations with the components of the sediment.
Figure 5 shows Cu, iron oxide, and aluminum oxide at an angle less than 90°, indicating that iron oxide and aluminum oxide have a stronger correlation with Cu adsorption than other components of the deposit, while OM and iron oxide may be adsorbed with zinc.
Redundant analysis graph of sediment composition and adsorption capacity.
Table 8 and Table 9 show that the contribution rate of OM and alumina in the adsorption process is higher than that of CEC and iron oxide. The contribution rate of OM in the entire adsorption process reached 72%, and the largest significant difference was 0.002. According to the distribution characteristics of the adsorption amount increasing with the distance of the river and the redundant analysis results of the sediment composition and adsorption amount, the adsorption of Cu at the Dianchi estuary is greatly affected by iron and aluminum oxides, while Zn is more affected by OM and CEC. Big.
Different sediment components adsorb different amounts of copper and zinc. It is reported that 19 OM and iron and manganese oxides have relatively high levels of Cu adsorption. Feng Jun et al. 20 also found that iron oxide strongly adsorbs Zn.
In summary, the various components of the sediment entangle with each other, shield or overlap the adsorption sites, so the adsorption amount at each depth is inconsistent with the OM content, CEC, iron, aluminum oxide content or adsorption amount change trend. The adsorption capacity does not increase with the increase of OM content, CEC or Fe-Al oxide content. The sediment components show a differential adsorption of heavy metals: iron-aluminum oxide contributes more to the adsorption of Cu(II), and OM and iron oxide contribute more to the adsorption of Zn(II).
Different components of the bottom mud have different adsorption characteristics for heavy metals; iron and alumina contribute more to Cu adsorption than other components, while OM and iron oxide contribute more to Zn adsorption.
Previous research results show that there is a certain linear positive correlation between the OM content, CEC, metal oxide content and the adsorption amount in the sediment 21, 22, 23. The results are shown in Table 10. The R2 between each component and the adsorption capacity is not high, indicating that the adsorption capacity does not depend on a single component, but is the result of the joint action of multiple components.
In the adsorption of Cu and Zn, as the equilibrium adsorption concentration increases, the competition for adsorbate molecules to occupy adsorption sites becomes more intense. When the high binding energy adsorption site approaches its full capacity, the non-specific adsorption increases and the adsorption speed gradually slows down. The iron-aluminum oxides and OM in groups B, C, and D mask the adsorption sites; therefore, the K values of these groups are much lower than those of group A (400.3). With the increase of adsorption equilibrium concentration, the adsorption sites of groups B, C, and D decreased faster than group A, and the growth rate of adsorption capacity was slower than that of group A. Relevant studies have shown that the equilibrium concentration of 25 increases, the adsorption capacity increases, and the adsorption curve shows a sharp increase trend at low concentrations. But the adsorption potential is limited. When the concentration of heavy metal ions is high, the electromotive force and electrical properties of the colloidal particles decrease, which reduces the stability of the heavy metal-colloid-soil aggregates, and the curve gradually becomes flat. The adsorption capacity decreases with the increase of the adsorption equilibrium concentration, which may be caused by the reduction of adsorption sites and the limited adsorption capacity.
In practical applications, the surface of the sediment particles is uneven, resulting in an uneven number and distribution of adsorption sites. The adsorption isotherm of Cu and Zn by the sediment is more in line with the Freundlich adsorption isotherm model than the Langmuir model, indicating that the adsorption process follows multilayer adsorption. The surface of the sediment particles is not uniform, and the Freundlich isotherm adsorption model fits in accordance with reality; the results of Mustapha et al. 27 are similar. The order of the adsorption amount of the sample corresponds to the order of its K value (because some samples cannot be fitted by the Langmuir isotherm adsorption model, the Freundlich adsorption isotherm model K value is used for comparison), similar to most samples. The research results 28. The K value is used as a measure of adsorption Ability indicator: the greater the value, the greater the adsorption capacity of the sediment on Cu and Zn. Among groups B, C, and D, the K value (0.17 and 0.83) of group C is the largest, and the K value (0.09 and 0.27) of group D is the smallest, indicating that iron-aluminum oxides and OM are important factors in the adsorption process, iron-aluminum The adsorption capacity of oxides for heavy metals is stronger than that of OM.
Previous studies on changes in adsorption characteristics before and after the removal of soil and sediment components mainly focused on changes in the isotherm adsorption equation or kinetic adsorption equation of each single component, but did not consider the combined effect. Individual compound effects and isolated studies of inorganic colloids (minerals) or organic colloids (OM) cannot reflect the true sediment system.
The contribution rate of each component to the adsorption of Cu and Zn in the sediment is calculated according to formula (1). (3):
Where G is the rate of a specific component, (Q not removed) is the adsorption without removing the component, and (Q removal) is the adsorption removing the component. In order to obtain the quantitative relationship between the fitting curve and GOM-IAO, GOM and GIAO, the X axis is the OM contribution rate (GOM) plus the iron aluminum oxide contribution rate (GIAO), and the OM-iron aluminum oxide is used as the X axis. The contribution rate of GOM-IAO is taken as the Y axis. The obvious positive linear correlation between GOM-IAO, GOM and GIAO indicates that the OM-iron-aluminum oxide composite material plays a role in the adsorption of Cu and Zn. The simple addition of iron and aluminum oxide leads to a certain quantitative relationship of Cu adsorption (4):
And the adsorption of Zn (5):
The content of organic/inorganic composites is not equal to the sum of OM and metal oxides, which may be due to hydrogen bonding, ion exchange and hydrophobic forces, such as anion adsorption mechanisms, which embed the composites between the mineral surface and the expanded clay mineral crystal layer. ,31, affect the degree of mineral cementation, thereby affecting the stability of the colloid 32. In addition to directly participating in the formation of complexes, the strong surface activity of iron and alumina can form a bridge with OM and stabilize colloids through coordination exchange or the formation of ionic bonds. In this way, these components combine to form organic and inorganic compounds that form the core and structure of the soil 34, 35, 36.
Quantitative relationship between OM, iron-aluminum oxides and organic-inorganic composites' contribution to Cu(II) and Zn(II) adsorption. (a) Copper, (b) Zinc.
In order to further compare the adsorption capacity of OM-iron-aluminum oxide composite material, OM and iron-aluminum oxide, we compared four sets of sediment samples under different pH values and changes in adsorption capacity (Figure 7). We found that under different pH values, the adsorption performance of the A group to the sediment Cu and Zn is greater than the other three groups. Perez-Novo et al. 37 reported similar results.
The relationship between adsorption capacity and pH. (a) The adsorption capacity of the four groups of samples at different pH values for Cu; (b) the adsorption of Zn by the four groups of samples at different pH values.
In group A, OM forms organic-inorganic composites with iron and aluminum oxides, increasing the surface area and surface activity of the deposits, and enhancing the adsorption capacity38. In addition, the Mg(II) and Fe(II) compounds in the sediment may be dissolved due to the presence of a large amount of H in a low pH environment, thereby competing for adsorption sites, or Cu may form hydroxyl compounds with the increase of pH 24 and 39. 40. Group D removes OM, iron and alumina at the same time, greatly reducing the number of active sites on the surface of the sediment, exposing the siliceous framework of the sediment, and the adsorption is more easily affected by pH.
When OM forms an organic-inorganic composite with iron and aluminum oxides, the surface properties of iron oxide will change. First of all, the decrease of zeta potential indicates that the negative charge on the surface increases, which is beneficial to improve the adsorption of cations. Zhou et al. 41 found that a large amount of free humic acid may cover the surface of iron oxide, reducing its surface potential and lowering the zeta potential. Secondly, OM and iron aluminum oxide have a large number of adsorption sites. OM adsorbs heavy metals through ion exchange, surface complexation and precipitation with functional groups such as carboxyl and hydroxyl groups with a large number of negative charges in OM, while humic acid and fulvic acid in OM adsorb heavy metals through complexation11,43. The metal oxides represented by iron and alumina have variable charges, and can be substituted by H ions by surface -OH groups and adsorb to negatively charged sites 44 or react with surface groups to form complexes 45.
In short, the organic-inorganic composite in the sediment does not correspond to the simple addition of OM and iron-aluminum oxide. Their contribution to the adsorption of Cu and Zn is GOM-IAO = (GOM GIAO) * 0.4–2 and GOM-IAO = (GOM GIAO) * 1.18–3.35. When the organic-inorganic complex is formed, the zeta potential decreases, the negative surface charge increases, and the adsorption sites for functional groups and variable charges increase. This makes the adsorption capacity of the organic-inorganic complex for Cu and Zn significantly higher than that of OM, iron and aluminum.的oxide.
Along the direction of the water flow, with the increase of the distance from the river, the adsorption amount of Cu and Zn did not change significantly at 0-10 cm, and showed a downward trend at 10-20 cm and a downward trend at 20-20-20 cm. 30 cm. In terms of depth, the adsorption capacity shows a trend of 0-10 cm ≈10-20 cm> 20-30 cm.
The different components of sediments have different adsorption of heavy metals, so the contribution rate of iron and aluminum oxides to Cu(II) adsorption in sediments is greater than that of organic matter and CEC. Compared with CEC and alumina, organic matter and iron oxide contribute more to the adsorption of Zn(II). At the same time, adsorption does not depend on a single component, and adsorption is the result of the combined effects of multiple components.
In the samples of group A (without any treatment), group B (removing OM), group C (removing iron and alumina), group D (removing OM and iron alumina at the same time), the Freundlich isotherm adsorption model provides the adsorption of Cu Best fit. In the adsorption of Zn, groups A and D are in good agreement with the Freundlich model, and groups B and C are in good agreement with the Langmuir isotherm adsorption model.
The organic-inorganic composite in the sediment does not simply correspond to the sum of OM and iron-aluminum oxide. Their contribution to Cu and Zn adsorption are GOM-IAO = (GOM GIAO) * 0.4–2 and GOM-IAO = (GOM GIAO) * 1.18–3.35, respectively. The adsorption capacity of organic-inorganic composites is significantly higher than that of OM and iron-aluminum oxides.
Machado, AADS, Spencer, K., Kloas, W., Toffolon, M. & Zarfl, C. The fate and impact of metals in estuaries: a review and conceptual model for a better understanding of toxicity. science. Total environment. 541, 268–281 (2016).
ADS article CAS Google Scholar
Xiao, DD Characteristics of heavy metals in surface sediments of Baoxiang River and assessment of potential ecological risks (Yunnan Normal University, 2018).
Zhang, Y., Shi, T., Zhang, Y. & Tao, Y. Spatial distribution and risk assessment of heavy metals in the sediments of Dianchi Lake, China's hypertrophic plateau. environment. monitor. Evaluate. 186, 1219–1234 (2014).
Papelis, C., Roberts, PV & Leckie, JO Simulating the adsorption rate of cadmium and selenite on microporous and mesoporous transition alumina. environment. science. technology. 29, 1099–1108 (1995).
ADS CAS PubMed article PubMed Central Google Scholar
Li, P. etc. The influence of pH on the release of heavy metals (Zn, Cu) in the sediments of Xiawan Harbor[J]. Chin. J. Environment. Britain. 4, 2425–2428 (2010).
Bin, H. etc. The effect of soil particle size on the adsorption, distribution and migration of heavy metals (like) substances in soil: a review [J]. Environment. process. Impact 22, 1596-1615 (2020).
Huang, XY, etc. The migration of heavy metal elements in the surface sediments of the wetland ecosystem in the Liaohe River Delta. Agere. bull. 38, 414–425 (2019).
Wang, W. The effect of doping additives on the adsorption of heavy metals in the surface sediments of the Inner Mongolia section of the Yellow River (Inner Mongolia Normal University, 2012).
Saeedi, M., Hosseinzadeh, M. and Rajabzadeh, M. Competitive heavy metal adsorption on natural bed sediments in the Jajrood River, Iran. environment. Earth Science. 62, 519–527 (2011).
Dong, X. et al. Adsorption of heavy metals on heat-treated deposits with high organic content. Biological resources. technology. 160, 123–128 (2014).
ADS CAS PubMed article PubMed Central Google Scholar
Li, Z. etc. The effect of removing organic matter and iron and manganese oxides on the adsorption of cadmium by aggregates in red rice fields. RSC Advanced 5, 90588–90595 (2015).
ADS CAS Article Google Scholar
Sarkar, D., De, DK, Das, R. & Mandal, B. The removal of organic matter and iron and manganese oxides from the soil affects the adsorption of boron in the soil. Geoderma 214–215, 213–216 (2014).
ADS article CAS Google Scholar
Franzblau, RE, Daughney, CJ, Moreau, M. & Weisener, CG In the process of Fe(II) addition, oxidation and hydrolysis, the adsorption of selenate on E. coli and iron oxide composite materials. Chemical Agere. 383, 180–193 (2014).
ADS CAS Article Google Scholar
Cloth, JM, etc. Release and source of dissolved organic matter into the lake from the Dianchi Lake Basin[J]. Chinese Journal of Science. Repeatedly. 40, 10 (2020).
Tian, WG, Wan, M. & Zhang, Y. Ecological survey of major rivers flowing into Yunnan. environment. science. Guide 35, 18–23 (2016).
Schiller, ADP, etc. The influence of hydrological flow in tropical watershed on the dynamics of copper and zinc in sediments. environment. monitor. Evaluate. 191, 86 (2019).
Lin, DS etc. The effects of soil pH, organic matter and water oxides on the competitive adsorption of cadmium and lead. J. Agricultural environment. science. 26, 510–515 (2007).
Liu, DB etc. Several soil surface charge characteristics in the central and southern regions 4: the influence of iron and alumina on the soil surface charge characteristics. Journal. crime. 38, 123–127 (2001).
Bradl, HB Adsorption of heavy metal ions to soil and soil components. J. Colloidal Interface Science. 277, 1-18 (2004).
ADS CAS PubMed article Google Scholar
Feng, J. et al. Analysis on the adsorption and desorption characteristics of copper and zinc in farmland black soil[J]. J. Northeast Agriculture. University 37, 60-62 (2009).
Lin, J.-G. & Chen, S.-Y. The adsorption relationship between heavy metals and organics in river sediments. Environment. internationality. 24, 345–352 (1998).
Jianliang et al. The quantitative relationship between the adsorption rate of Pb(II) by carbonaceous materials in the soil and the content of soil organic matter. science. Total environment. 572, 369–378 (2016).
Vega, A., Covelo, EF, Andrade, ML & Marcet, P. The relationship between heavy metal content in mineral soil and soil properties. anus. Humph. Journal 524, 141–150 (2004).
Wang, F., Wang, W., Wu, B., Bai, Q. and Perera, MSA mechanism, cause and control of water, solute and gas migration caused by mining activities. Geofluids 2019, 1–4 (2019).
Wang, KL, etc. Experimental study on the adsorption of zinc and cadmium on different texture soils in the presence of colloids[J]. Soil. 043, 239–246 (2011).
Wang, H. Nutrient transfer mechanism and simulation model of loess slope land under rainfall conditions (Northwest Sci-Tech University of Agriculture and Forestry, 2006).
Mustapha, AA, Abdu, N. & Jibrin, JM used freundlich, langmuir and dubinin-raduskevich models to adsorb cadmium, copper, lead, and zinc in organically modified soil components. internationality. J. Soil 12, 43–53 (2017).
Fang, YX etc. The influence of pig manure source DOM on soil Cd adsorption in the Three Gorges Water Fluctuation Zone[J]. J. Agricultural Environment. science. 39, 1240-1248 (2020).
Ling, C. The effect of organic matter removal on chromium (VI) adsorption by soil particle size in Mingshan River Basin (Master of Sichuan Agricultural University, 2011).
Violante, A., Cristofaro, AD, Rao, MA & Gianfreda, L. Physicochemical properties of protein-montmorillonite and protein-al(oh)x-montmorillonite complexes. Clay miner. 30, 325–336 (1995).
ADS CAS Article Google Scholar
Huang, P., Wang, M. and Chiu, C. Soil mineral-organic matter-microbe interaction: basic principles and effects. Senior Agron. 82, 391–472 (2004).
Li, SB, etc. The role of ionic interface behavior in the formation of soil organic-inorganic complexes. science. agriculture. crime. 26, 1682–1691 (2018).
Xu, XR etc. Research progress on soil aggregates and organic carbon stabilization mechanism. Chin. J. Soil Science. 48, 1523–1529 (2017).
Ransom, BL, Bennett, RH, Baerwald, RJ & Shea, KF Transmission electron microscopy study of in-situ organic matter on continental margins: occurrence and "single layer" hypothesis. March. 138, 1-9 (1997).
ADS CAS Article Google Scholar
Jastrow, JD The formation of soil aggregates and the production of particulate matter and mineral-related organic matter. Soil organisms. Biochemical. 28, 676 (1996).
History, JP et al. The effect of long-term located fertilization on the soil organic-inorganic composite state. Plant Nutrition Fair. science. 2, 4-9 (2002).
Pérez-Novo, C. etc. The effect of organic matter removal on the competitive and non-competitive adsorption of copper and zinc in acid soils. J. Colloidal Interface Science. 322, 33-40 (2008).
ADS article CAS Google Scholar
Study on the adsorption and desorption characteristics of lead, copper, zinc and cadmium in the soils of Xuzhou and Suzhou. Master's thesis, Capital Normal University (2007).
OEzdemir, G. & Yapar, S. The adsorption and desorption behavior of copper ions on Na-montmorillonite: the effect of rhamnolipids and pH. J. Hazardous materials. 166, 1307–1313 (2009).
Shuang, X., Zhang, W., Hongbin, Z., Jin, M. & Perera, MSA Experimental study of Cu(II) adsorption and desorption in silty clay. Geofluids 2018, 1-12 (2018).
Zhou, Y., Zhang, Y., Li, P., Li, G. & Jian, T. Comparative study on the adsorption and interaction of humic acid on natural magnetite, hematite and quartz: the initial HA concentration Influence. Powder technology. 251, 1-8 (2014).
ADS CAS Article Google Scholar
Lalonde, K., Mucci, A., Ouellet, A. & Gélinas, Y. Iron promotes the preservation of organic matter in sediments. Nature 483, 198–200 (2012).
ADS CAS PubMed article PubMed Central Google Scholar
Yuan, M., Xu, ZP, Baumgartl, T. & Huang, L. Errata: The effect of organic surface properties on the adsorption of cations in the solution phase. Water, air, and soil pollution. 225, 2161 (2014).
ADS article CAS Google Scholar
Bin, H. Study on the adsorption, enrichment, migration characteristics and stability of heavy metals in paddy soil (Hunan University, 2016).
Gupta, SS & Bhattacharyya, KG Adsorption of heavy metals on kaolinite and montmorillonite: a review. Physical Chemistry Chemical Physics 14, 6698–6723 (2012).
PubMed article CAS PubMed Central Google Scholar
This research was funded by the National Natural Science Foundation of China (41463012).
Key Laboratory of Yunnan Plateau Wetland Protection, Restoration and Ecological Services, School of Wetland, Southwest Forestry University, Kunming 650224
Ma Xiangshu, Liu Leng, Fang Yichuan, Sun Xiaolong
National Plateau Wetland Research Center, Southwest Forestry University, Kunming 650224
Ma Xiangshu, Liu Leng, Fang Yichuan, Sun Xiaolong
Yunnan Dianchi National Wetland Ecosystem Research Station, Southwest Forestry University, Kunming 650224
Ma Xiangshu, Liu Leng, Fang Yichuan, Sun Xiaolong
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X.-sM: Conceptualization, supervision, formal analysis and editing. LL: Data management. Y.-cF: Visualization. X.-lS: Review. All authors reviewed the manuscript.
The author declares no competing interests.
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Ma, Xs., Liu, L., Fang, Yc. etc. The adsorption characteristics of Cu(II) and Zn(II) in the estuary sediments of a typical polluted river in Dianchi Lake——Taking Xinhe as an example. Science Report 11, 17067 (2021). https://doi.org/10.1038/s41598-021-96638-4
DOI: https://doi.org/10.1038/s41598-021-96638-4
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