Effects of Oxygenation Resuspension on DOM Composition and Its Role in Reducing Dissolved Manganese in Drinking Water Reservoirs
Supporting Information
* These authors contributed equally to this work.
1 Key Laboratory of Environmental Aquatic Chemistry, State Key Laboratory of Regional Environment and Sustainability, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. No. 18 Shuangqing Road, Haidian, Beijing, 100085, China
2 School of Ecology and Environment, Inner Mongolia University. No.235 West College Road, Saihan, Hohhot, 010021, China
3 University of Chinese Academy of Sciences. No. 19A Yuquan Road, Shijingshan, Beijing, 100049, China
✉ Correspondence: Changwei Lü <lcw2008@imu.edu.cn>, Min Yang <yangmin@rcees.ac.cn>
Summary: 25 pages, 12 figures and 6 tables.
Fig. S1
Sediment resuspension experiments were conducted in six drinking water source reservoirs located in Zhejiang Province, China, designated as Reservoirs A, B, C, D, E, and F (Fig. S1). Reservoir F was identified to have a relatively higher manganese content in its sediments and was therefore selected as the source for sediment samples used in laboratory simulation experiments. To protect the confidentiality of the reservoirs, all reservoir names have been anonymized and represented using letter codes.
Specific sediment resuspension procedures were applied are: Reservoir A (5 days), Reservoir B (21 days), Reservoir C (39 days), Reservoir D (14 days), Reservoir E (11 days) and Reservoir F (29 days). For reservoir F, water and sediment samples were analyzed to evaluate the impact of sediment resuspension on Mn release and its control.
Fig. S2
A pre-experiment was conducted to determine the optimal solid-liquid ratio for the sediment-water mixture in the simulation system. Different solid-liquid ratios (20, 30, 40, 50, 60, 70 g L\(^{-1}\)) were tested to evaluate metal ion release. The solid-liquid ratio of 40 g L\(^{-1}\) was selected for the simulation system based on the release fraction, which was determined by comparing the final concentrations at 48 hours with the initial concentrations at 0.3 hours, when the maximum aqueous concentrations were observed.
The figure illustrates the maximum release amounts of metals at various solid-liquid ratios in the sediment from Reservoir F. Samples were placed in a constant-temperature water bath shaker at 20°C with a shaking frequency of 260 r min\(^{-1}\). Samples were collected at two time points: after 0.3 hours (early release concentration) and after 48 hours (equilibrium concentration). The maximum release amount was calculated as the difference between these two concentrations. The supernatant was then extracted by centrifugation at 3200 r min\(^{-1}\), and metal concentrations were measured after filtration through a 0.45 µm membrane.
Fig. S3
Fig. S4
In this study, sediment collected from Reservoir F was used for laboratory simulation experiments. A schematic diagram of the simulation system is shown in Fig. S4. Each system consisted of a sealed black polyethylene buckets connected to an external aeration system to regulate dissolved oxygen (DO) levels by introducing either nitrogen or oxygen gas. Additionally, a stirring module was included to simulate sediment disturbance.
A total of 10 systems were set up: 8 systems with both aeration and stirring, each adjusted to DO levels of 0, 2, 5, and 7 mg L\(^{-1}\), with two replicates per condition. Furthermore, one system was set up with aeration (DO level of 7 mg L\(^{-1}\)) but without stirring, and another served as a control system with neither aeration nor stirring.
Fig. S5
Fig. S6
Fig. S7
The composition and structural characteristics of DOM in overlying water were characterized using three-dimensional fluorescence spectroscopy. Parallel factor analysis (PARAFAC) modeling was conducted using the DOM Fluor toolbox in MATLAB 2022b. After removing Raman and Rayleigh–Tyndell scattering effects, outliers were identified and excluded based on leverage and loading plots. PARAFAC models with varying numbers of components were established, and a binary validation approach was applied to identify the optimal model.
Fluorescence datasets were compared using the OpenFluor online platform, where components were considered to have strong matching if the Tucker congruence coefficients (\(\theta\)) for both excitation and emission spectra exceeded 0.951. The final model identified three components: C1, C2, and C3.
- Component C1 (Ex = 225 nm, Em = 325 nm): Identified as protein-like matter, primarily associated with degraded proteins, particularly tryptophan-like compounds2.
- Component C2 (Ex = 230 nm, Em = 415 nm): Representing terrestrial humic-like substances, characterized by aromatic structures, large molecular size3, and significant hydrophobicity4,5.
- Component C3 (Ex = 263 nm, Em = 464 nm):Corresponding to terrestrially derived terrestrial humic-like substances6,it is highly likely to befulvic acid-like substances7,8.
The DOM-EEM spectra of the water samples were analyzed using Parallel Factor Analysis (PARAFAC), which mathematically decomposes the data into different fluorescence components with distinct spectral characteristics.
Fig. S8
Fig. S9
Fig. S10
In each simulation system, changes in manganese concentrations in the water were continuously monitored. Dissolved manganese (dissolved Mn) was determined by filtering water samples through a 0.22 µm filter. Colloidal manganese (colloid Mn) was calculated as the manganese content in water filtered through a 1 µm filter, subtracting the corresponding dissolved Mn. The first two panels represent systems without stirring at DO levels of 0 mg L\(^{-1}\) and 7 mg L\(^{-1}\). The subsequent four panels show systems with stirring at DO levels of 0, 2, 5, and 7 mg L\(^{-1}\).
Fig. S11
Fig. S12
Table S1
The sediment from Reservoir F exhibits several key physical and chemical properties. The moisture content, as per the standard HJ 613-2011, is 78.46%. The granularity distribution shows that the sediment particles have a Dx(10) of 3.87 µm, a Dx(50) of 122.33 µm, and a Dx(90) of 271.33 µm, indicating a mixture of fine and coarse particles. In terms of sequential extraction of phosphorus, the following values were observed: Ex-IP (0.62145 mg L\(^{-1}\)), Fe-IP (2.01584 mg L\(^{-1}\)), Al-IP (0.62654 mg L\(^{-1}\)), Ca-IP (0.26148 mg L\(^{-1}\)), and Re-IP (0.10972 mg L\(^{-1}\)). The sediment also has a specific surface area of 23.3095 m\(^2\) g\(^{-1}\) as determined by BET analysis, with a pore volume of 0.08428 cm\(^3\) g\(^{-1}\), measured using BJH adsorption. The average pore diameter is 17.0244 nm, indicating the presence of relatively fine pores in the sediment. These properties highlight the physical and chemical characteristics of the sediment, which are essential for understanding its behavior in environmental simulations.
Parameters | Values |
---|---|
Moisture content | |
Granularity | |
Sequential extraction of P | |
Surface Area | |
Pore Volume | |
Pore diameter | |
Table S2
The extraction of various phosphorus (P) fractions was accomplished through a combination of the methodology proposed by ref.9, as subsequently refined by ref.10, and the phosphorus extraction protocol detailed by ref.11. The determination of phosphorus refers to the ammonium molybdate spectrophotometric method12.
Fraction | Extraction method |
---|---|
Table S3
Reservoir | Month | Depth (m) | Water temperature (°C) | pH |
---|---|---|---|---|
Table S4
In systems with different dissolved oxygen levels, manganese concentrations in the water peaked within 15–30 minutes of stirring and then declined rapidly. The decline process was well described by a second-order kinetic equation: \(1/c_t = 1/c_0 + k \cdot t\), where \(c_0\) represents the modeled maximum Mn concentration, and \(k\) is the second-order rate constant. Table S4 presents the parameters of the second-order kinetic model and the results of statistical tests for each system.
Operation | DO (mg L⁻¹) | c₀ (µg L⁻¹) | k (min⁻¹) | p-value |
---|---|---|---|---|
Table S5
For manganese (Mn) fractionation, the sequential extraction procedure outlined in the Chinese national standard13 was used. Extracted solutions were stabilized with 1% nitric acid and analyzed for manganese concentrations using inductively coupled plasma mass spectrometry (ThermoFisher iCAP Q).
This study primarily focused on the transformation relationships among three manganese fractions due to the relative stability of the residual fraction, which is less reactive chemically:
- Mild acid-soluble fraction: Elements electrostatically adsorbed on particle surfaces, released via ion exchange, or bound within carbonates.
- Reducible fraction: Elements associated with iron and manganese oxides.
- Oxidizable fraction: Elements bound to active organic matter groups or sulfur compounds that oxidize to soluble sulfate forms.
Fraction | Extraction method |
---|---|
Table S6
Characteristic | Mild Acid-Soluble Manganese | Reducible Manganese | Oxidizable Manganese |
---|---|---|---|
Form of Existence | Adsorbed manganese, carbonates, and soluble salts | Manganese oxides (e.g., MnO₂, Mn₂O₃) | Organically bound manganese, sulfide-bound manganese |
Stability | Easily released and highly mobile | Relatively stable, released primarily under anoxic conditions | Stable, but released under oxidative conditions |
Extraction Conditions | Extracted using weak acids (e.g., acetic acid, HCl) | Extracted with reducing agents (e.g., hydroxylamine hydrochloride) | Extracted using oxidizing agents (e.g., H₂O₂) |
Environmental Significance | Indicates short-term release potential and bioavailability | Suggests potential for release under reducing (anoxic) conditions | Indicates potential for release under oxidative conditions |