Study on enhanced sludge dewatering and mechanism by modified corn straw powder in conjunction with tannic acid
You Zhang, Hong Zhang, Hai Xv, Biguo Jia, Yongjian Li, Heping Su, Guorong Diao, Huanlong Song, Chao Wu
TL;DR
This study develops an eco-friendly sludge dewatering agent using modified corn straw and tannic acid, reducing moisture content effectively.
Contribution
A novel natural dewatering agent is developed using modified corn straw and tannic acid, offering an eco-friendly alternative to traditional flocculants.
Findings
Modified corn straw powder reduces sludge moisture content by approximately 20%.
Combining modified corn straw with tannic acid reduces sludge particle size and moisture content by about 30%.
Abstract
In sludge treatment, high moisture content presents a core challenge. Traditional flocculants often release toxic substances that can harm the environment, leading to a growing interest in natural polymer flocculants due to their eco-friendly properties. This study explores the modification of corn straw using sodium hydroxide and 3-chloro-2-hydroxypropyl trimethyl ammonium chloride, aiming to develop a natural and environmentally friendly dewatering agent. The research indicates that the modified corn straw powder can effectively disrupt the structure of sludge flocs, resulting in a significant reduction of approximately 20% in sludge moisture content. Additionally, it was found that the modified corn straw powder, in conjunction with tannic acid, can notably decrease the particle size of sludge, effectively reducing the moisture content by about 30%. The online version contains…
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Figure 9- —Mengsheng Construction Co.,Ltd
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TopicsCoagulation and Flocculation Studies · Phosphorus and nutrient management · Recycling and utilization of industrial and municipal waste in materials production
Introduction
In recent years, the production of urban sludge has shown a steadily increasing trend, and the efficient treatment and disposal of this sludge have become critical challenges that urgently need to be addressed^1,2^. Urban sludge contains a very high proportion of moisture and is primarily composed of bacterial cells, organic materials that are difficult to biodegrade, and various colloidal particles. This unique composition makes it challenging to effectively remove moisture from the sludge^3,4^. Therefore, reducing the moisture content of urban sludge has become a key aspect of the sludge treatment process^5,6^.
In the field of sludge treatment, researchers commonly use chemical dewatering agents such as iron salts, aluminum salts, and cationic polyacrylamide for pre-treatment of sludge^7^. Although these methods improve the dewatering efficiency of sludge, they often generate and release toxic and harmful substances, causing severe damage to the ecological environment and posing threats to human health. In light of this, developing environmentally friendly and efficient sludge dewatering agents has become a pressing issue. Against this backdrop, natural modified polymer flocculants have attracted significant research interest due to their notable advantages of being non-toxic and easily biodegradable^8–12^. Currently, modified starch-based cationic flocculants, cationic lignin-based flocculants, and FeCl3-modified rice husk biochar have been applied in sludge dewatering treatment, achieving preliminary success^13–15^.
However, the sole use of natural organic high molecular weight flocculants still has drawbacks, such as slow reaction rates and limited applicability. Therefore, developing and preparing efficient sludge dewatering flocculants and exploring their combined use with novel conditioning techniques is an important means to address the current sludge dewatering challenges. In 2023, China’s corn straw production is approximately 321 million tons, accounting for 18.50% of the total crop straw production in the country. Discarded corn straw is typically disposed of through incineration. This method not only affects air quality and soil structure but also exacerbates the greenhouse effect^16–18^. Consequently, exploring the use of corn straw as a substrate to prepare a natural modified dewatering agent for sludge treatment can introduce innovative technological approaches to the field of sludge dewatering while significantly enhancing the resource utilization rate of corn straw, contributing to the sustainable development of the ecological environment. Additionally, attempts to combine the natural bio-flocculant tannic acid with modified corn straw powder in the sludge dewatering process will investigate the synergistic effects on sludge dewatering performance, clarify the dewatering reaction mechanism, and provide new technical means for the efficient treatment of sludge.
Materials and methods
Materials
We utilized waste corn stover powder (CSP) with a particle size of 100 mesh (equivalent to 150 microns) as the raw material. Additionally, the following analytical-grade reagents were employed: sodium hydroxide (NaOH), 3-chloro-2-hydroxypropyltrimethylammonium chloride (CHPTAC), chloroacetic acid, and hydrochloric acid.
The sludge samples were collected from a municipal sludge treatment plant located in Yakeshi, China. Upon arrival at the laboratory, the sludge samples were stored at 4 °C and consumed within three days to minimize microbial activity and experimental discrepancies^19^. The fundamental characteristics of the raw sludge are presented in Table 1.
Table 1. Main properties of raw sludge.ParameterValuesMC/%95 ~ 99SRF×10^− 12^/m·kg^− 1^12.92 ~ 13.25Dry sludge/g·L^− 1^6.93 ~ 7.55PH6.49 ~ 6.85
Modification methods of CSP
After drying the CSP sample at 105 °C for 2 h, weigh out 10 g of the sample. The CSP is then modified using NaOH, CHPTAC, and chloroacetic acid. The optimal preparation conditions for modified corn stover powder (MCSP) were determined through orthogonal experiments, encompassing six factors and five levels (Table 2). The sludge moisture content (MC) and sludge resistance to filtration (SRF) are utilized as evaluation indicators.
Table 2MCSP preparation factor level table.NaOH/g(A)Alkalization time/min(B)Temperature/℃(C)CHPTAC/ml(D)Chloroacetic acid/g(E)Grafting time/min(F)15.0040558.6710.0012023.3360605.786.6713532.5080654.335.0015042.00100703.474.0016551.67120752.893.33180
Characterization of MCSP properties
Fourier transform infrared spectroscopy (FT-IR) analysis
In order to confirm the differences in functional groups between MCSP and CSP, Fourier transform infrared spectroscopy was used to characterize MCSP and CSP.
Scanning electron microscope (SEM)
The surface morphology and structure of CSP and MCSP were studied using scanning electron microscopy.
BET analysis
The average pore size and surface area of CSP and MCSP were determined using the Brunauer Emmett Teller (BET) method and an automatic surface area and porosity analyzer.
Evaluation indices for sludge dewatering performance
During the sludge conditioning process, the dewatering performance of sludge is primarily assessed using moisture content (MC), sludge resistance to filtration (SRF), and dissolved solids (DS) content 20^20,21^. The moisture content and dissolved solids content of sludge can be calculated using Eqs. (1) and (2), respectively.
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MC = \left( {1 - \frac{{m_{3} - m_{1} }}{{m_{2} - m_{1} }}} \right) \times 100\%$$\end{document} \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$DS = \frac{{m_{2} - m_{3} }}{{m_{3} - m_{1} }}$$\end{document}Among them, m_1_ is the mass of the evaporating dish (g); m_2_ is the total mass of the evaporating dish and the dehydrated wet filter cake (g); m_3_ is the total mass (g) of the evaporating dish and dry filter cake after drying to a constant weight.
The specific resistance of sludge can be calculated using Eq. (3):
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$SRF = \frac{{2PA^{2} b}}{{\mu \omega }}$$\end{document}Among them, P is the filtration pressure (Pa); A is the filtering area (m^2^), which is the area of the funnel filtering surface; B is the slope (s/m^6^), which is the slope of the straight line of the filtration equation t_i_/V_i_=bV_i_+a, where V_i_ (m^3^) is the volume of the filtrate obtained at the filtration time t_i_ (s); µ is the viscosity of sludge filtrate (Pa·s); ω is the mass of sludge cake produced per unit volume of sludge filtrate (kg/m^3^).
Results and discussion
Preparation conditions of MCSP
The MCSP synthesized under different conditions was added to the raw sludge and stirred at 400 rpm for 15 min^22^. The conditioned sludge was then allowed to stand for approximately 1–2 h until solid-liquid separation was achieved. Finally, the conditioned sludge was vacuum filtered under the same pressure to determine the moisture content (MC) and specific resistance to filtration (SRF) of the sludge. All experiments were conducted at room temperature, and the data presented are averages from repeated experiments.
The R value indicates the significance of influencing factors, with a higher R value signifying greater importance^23^. Using MC as the indicator, the order of importance is (R_A_ > R_D_ > R_E_ > R_C_ > R_B_ > R_F_), which suggests that the amount of NaOH plays the most critical role in the preparation of MCSP. The quantities of CHPTAC and chloroacetic acid also have a certain impact on the preparation of MCSP (Table 3). The effects of alkalization time, temperature, and grafting time are relatively minor. The K_i_ value represents the average moisture content of the conditioned sludge, with a smaller K_i_ corresponding to better dewatering performance.
Table 3. Preparation of MCSP orthogonal experiment results calculation table.ABCDEFK_1_75.2676.4575.8375.4775.6876.61K_2_76.4576.6276.6177.0677.0477.28K_3_76.7477.0976.8976.6276.4277.45K_4_77.1877.2877.2477.6977.2776.84K_5_77.6977.8577.4576.0377.4977.85Range(R)2.431.401.622.221.811.24
For example, regarding influencing factor A, the relationship K_1_ < K_2_ < K_3_ < K_4_ < K_5_ indicates that the optimal level for factor A is 1, meaning the ideal amount of NaOH is 5 g. Similarly, the ideal values for alkalization time, temperature, CHPTAC dosage, chloroacetic acid dosage, and grafting time are 40 min, 55 °C, 8.67 ml, 10 g, and 2 h, respectively. When using SRF as the indicator, the reasonable preparation conditions for MCSP are consistent with those obtained using MC as the indicator (Fig. 1).
Fig. 1. Preparation of MCSP orthogonal experiment sludge specific resistance SRF curve.
Characterization of MCSP
Analysis of functional group changes
To investigate the changes in functional groups between CSP and MCSP, Fourier Transform Infrared Spectroscopy (FTIR) was employed for infrared spectral analysis of both samples.
Fig. 2CSP infrared spectrum.
As shown in Fig. 2, the characteristic peak at 3424 cm^− 1^ in the CSP spectrum and the peak at 3439 cm^− 1^ in the MCSP spectrum both represent hydroxyl groups. The absorption peaks at 2919, 1652, 1516, 1240, and 1039 cm^− 1^ correspond to the stretching vibrations of -C-H, -C = O, epoxy groups, -C-O, and -CO-C, respectively. These peaks primarily originate from the glucose and polysaccharides present in the raw materials, cellulose, and starch^24,25^. The bending vibration absorption peaks of C-H and -CH₂ appear at 1378 and 1419 cm^− 1^, respectively.
Fig. 3MCSP infrared spectrum.
After modification, as illustrated in Fig. 3, the absorption peak at 1516 cm^− 1^ disappears, indicating that the oxygen-containing heterocycles present have been opened during the modification process^26^. The MCSP spectrum shows a new absorption peak at 1751 cm^− 1^, corresponding to the stretching vibration of C = O, which indicates the formation of ester groups after modification. This modification can facilitate the decomposition of organic substances such as fats, proteins, and sugars in the sludge, generating liquid fatty acids and other small hydrocarbon compounds. The peak at 1476 cm^− 1^ is characteristic of the quaternary ammonium group methyl (-N⁺(CH₃)₃), confirming the successful grafting of the cationic groups. Additionally, the absorption peak at 1636 cm^− 1^ corresponds to the stretching vibration of carbonyl groups, while the peak at 1419 cm^− 1^ aligns with the bending vibration of -CH₂ in corn straw powder. The presence of these peaks indicates that CSP and MCSP share a similar carbon chain structure.
In summary, the unique functional groups of MCSP can effectively disrupt the colloidal structure of sludge while achieving electrostatic neutralization, promoting the disintegration of extracellular polymeric substances (EPS) and releasing bound water, organic components, and inorganic components into the liquid phase, thereby significantly enhancing the dewatering performance of the sludge.
Surface area and pore size analysis
To explore the impact of the modification reaction on the average pore size and specific surface area of the raw materials and to clarify the pore size distribution characteristics of MCSP, a surface area and pore size analyzer was used, following the BET (Brunauer-Emmett-Teller) method for detailed analysis of CSP and MCSP.
Fig. 4MCSP aperture distribution map.
The results indicate that, compared to CSP, the modified MCSP exhibits a significant increase in both average pore size and specific surface area. The average pore size of CSP is 2.332 nm, while that of MCSP expands to 6.965 nm. Simultaneously, the specific surface area of CSP is 1.619 m²/g, which increases to 2.534 m²/g for MCSP. As shown in Fig. 4, the pore size of MCSP is primarily concentrated in the range of 2 to 50 nm, indicating that MCSP is a mesoporous material. The presence of a mesoporous structure suggests that MCSP not only provides more neutralization sites for charges in the sludge system, effectively promoting charge balance, but also possesses a high capacity for adsorbing fine particles in the sludge, which is significant for enhancing sludge treatment efficiency.
Micromorphological characterization
To observe the effects of the modification reaction on the morphology of the samples, scanning electron microscopy (SEM) was used to analyze CSP and MCSP. Figures 5a, b display the micro-morphology of CSP, which exhibits an ordered and regular flaky structure, primarily due to the high content of cellulose and lignin components that construct the framework of the raw material.
After modification, the morphology of MCSP presents a unique honeycomb structure, as shown in Figs. 5c, d, with a surface covered in rough protrusions and abundant pore channels. This indicates that the original dense structure of CSP has become loose and porous during the modification process, greatly enhancing its usability. The unique three-dimensional porous structure of MCSP not only facilitates the penetration and diffusion of water molecules, increasing the solubility of MCSP, but also provides numerous adsorption sites, allowing MCSP to effectively adsorb fine particles in the sludge system. Under the influence of electrostatic forces, colloidal particles in the sludge are continuously adsorbed and aggregated, gradually forming larger flocs. As the flocs undergo further sweeping action, more fine particles are continuously adsorbed, effectively promoting the filtration and dewatering efficiency of the sludge.
Fig. 5. Scanning electron microscopy image. (a) 50µmCSP; (b) 20µmCSP; (c) 50µmMCSP; (d) 20µmMCSP.
Particle size fractal dimension (Df)
To characterize the complexity of the surface structure of corn stalk powder (CSP) and modified corn stalk powder (MCSP), Image Pro Plus 6.0 software was used to perform pixel analysis on Fig. 5 in Sect. 3.2.3. The equivalent area (A) and equivalent perimeter (P) of the particles were extracted, and the fractal dimension (Df) was calculated based on the fractal geometry Eq. (4). A smaller Df value indicates a more loosely packed and branched surface structure, which enhances the potential for interfacial interactions with sludge particles.
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{logP}\mathrm{(}\mathrm{ε}\mathrm{)=}\frac{{\mathrm{D}}_{\mathrm{f}}}{\mathrm{2}}\mathrm{⋅}\mathrm{logA}\mathrm{(}\mathrm{ε}\mathrm{)+}\mathrm{C}$$\end{document}Where: ε is the unit size, A is the equivalent area, P is the equivalent perimeter, and C is the constant.
Table 4. Fractal dimension (Df) of corn stalk powder before and after modification.SampleC2/DfStatistical AnalysisDfValueStandard ErrorValueStandard ErrorResidual Sum of SquaresAdjusted R-squaredValueStandard ErrorCSP0.1158.20E-0425.0001.5201.820E + 050.9250.0801.520MCSP0.0602.55E-0433.3333.2102.550E + 060.9950.0603.210
The fractal dimension calculations for corn stalk powder (CSP) and modified corn stalk powder (MCSP) are shown in Table 4. The fractal dimension of CSP is 0.080, and after modification, the fractal dimension of MCSP decreased to 0.060. This result indicates that the surface structure of the modified MCSP is more loosely packed, exhibiting a highly branched, cluster-like morphology, which is consistent with the morphological analysis in Sect. 3.2.3. The lower fractal dimension of MCSP after modification suggests that its surface structure is more conducive to effective collision with sludge floc particles, thereby providing a structural foundation for interfacial interactions during the subsequent sludge dewatering conditioning process.
Comparison of modification processes
Lekniute‑Kyzike et al.^27^ used CHPTAC to etherify potato starch under alkaline conditions, followed by cross-linking and mechanical shearing to produce cationic starch (CS) or cross-linked cationic starch (CCS). Starch, however, has a relatively high production cost, and the single-etherification process results in a final product with only cationic functionality. This limits the process to charge neutralization and adsorption bridging, which facilitates flocculation by reducing the electrostatic repulsion between sludge particles. Moreover, due to the lack of other functional groups, this process can only improve floc formation and dewatering efficiency but is unable to achieve more efficient sludge dewatering, especially in terms of enhancing organic matter fixation or promoting bound water release.
In contrast, the application of single-esterification processes in sludge dewatering is further limited, mainly due to the low efficiency of ester group grafting and incomplete esterification, which leads to a lower density of functional groups. Ester groups can only improve the material’s interaction with water, but they are unable to significantly reduce the sludge viscosity or promote the release of bound water, resulting in suboptimal dewatering effects.
Compared to the single-etherification and single-esterification processes, the CSP “NaOH, CHPTAC, and chloroacetic acid” ternary modification process exhibits significant innovations in the following aspects:
(1)Raw Material Utilization: This process uses corn stalk (CSP), a widely available and low-cost agricultural waste, as the raw material, aligning with the principles of resource utilization and circular economy. The process does not require complex component purification or separation; mechanical grinding alone is sufficient to prepare it as a reactant. The natural network of cellulose, hemicellulose, and lignin polymers in CSP provides abundant active sites, facilitating the grafting of multiple functional groups, significantly reducing raw material costs and preprocessing energy consumption.
(2)Modification System Design: The ternary modification process involves alkaline activation (NaOH), cationic etherification (CHPTAC), and esterification (chloroacetic acid), forming a multifunctional reaction system. NaOH not only disrupts the hydrogen bonds between corn stalk polymers and activates hydroxyl groups, but it also provides a stable alkaline environment for subsequent reactions. CHPTAC introduces quaternary ammonium cations, granting the product charge neutralization ability, while chloroacetic acid introduces ester functional groups simultaneously. This dual-functional system enhances interactions with sludge particles and overcomes the limitations of traditional single-step, single-functional group processes.
(3)Advantages of the Mechanistic Process: The traditional etherification process relies solely on charge neutralization to promote flocculation and dewatering. In contrast, the cationic groups in MCSP rapidly destabilize the sludge colloid by charge neutralization, promoting particle aggregation. The ester group further catalyzes the decomposition of extracellular polymeric substances (EPS) in the sludge, releasing bound water and reducing viscosity, thus fundamentally enhancing dewatering efficiency. This “physical flocculation and chemical catalysis of EPS disruption” mechanism represents a more complex dewatering process, which is more efficient and stable than traditional single-mechanism methods.
MCSP in combination with Tannic Acid (TA) for sludge conditioning
Tannic acid (TA) is a natural secondary metabolite of plants, known for its numerous phenolic hydroxyl groups, which endow TA with unique physicochemical properties such as the ability to complex and precipitate proteins and adsorb metal ions. These properties make it useful in sludge dewatering treatment^28^. However, excessive addition of MCSP can lead to electrostatic repulsion among particles in the sludge system, making aggregation difficult. Therefore, this study aims to investigate the dewatering effects of combining TA with MCSP to eliminate or reduce the negative impact of excessive MCSP on sludge dewatering.
The factors influencing the combined conditioning of sludge with TA and MCSP include four variables at four different levels (Table 5), with moisture content (MC) and specific resistance to filtration (SRF) set as target indicators. All experiments were conducted at room temperature, and the data presented are averages from repeated experiments (Table 6).
Table 5TA collaborative MCSP sludge regulation factor level table.MCSP/(%DS)(A)TA/(mmol/gDS)(B)Stirring speed/rpm(C)Stirring time/min(D)200.12005250.230010300.340015350.450020
Table 6. Orthogonal experimental results of TA collaborative MCSP sludge conditioning.ABCDK166.470.068.371.0K269.868.569.669.5K365.265.667.868.2K468.567.270.869.8Range(R)4.64.432.8
Using MC as the indicator, the order of importance is R_A_ > R_B_ > R_C_ > R_D_, indicating that the amount of MCSP plays the most significant role in the sludge conditioning process, while the dosage of TA also has a considerable impact (Table 6). For influencing factor A, the relationship K_3_ < K_1_ < K_4_ < K_2_ suggests that the ideal level for factor A is 3, meaning the optimal dosage of MCSP is 30% DS. Similarly, the ideal values for TA dosage, stirring speed, and stirring time are 0.3 mmol/g DS, 400 rpm, and 15 min, respectively. When using SRF as the indicator, the optimal conditions for conditioning sludge with TA in combination with MCSP are consistent with those obtained using MC as the indicator (Fig. 6).
Fig. 6TA collaborates with MCSP to regulate the SRF curve of sludge.
Evaluation of dewatering effect
To investigate the functionality of MCSP and the differences in sludge conditioning with TA, the filtration rates, moisture content (MC), and specific resistance to filtration (SRF) of three types of sludge samples were analyzed. The MCSP-TA-sludge exhibited a faster filtration rate and produced a greater volume of filtrate (Fig. 7). The MC and SRF values for MCSP-TA-sludge were lower, indicating better dewatering performance (Fig. 8).
Fig. 7. Filtration rate curves of different types of sludge.
Three representative time points covering the entire filtration process were selected (initial stage at 1s, rapid growth phase at 10s, and steady state at 60s). The filtrate volume data for each sludge group, along with parallel sample results, mean ± standard deviation (Mean ± SD), and relative standard deviation (RSD), were statistically analyzed. The RSD for all groups was less than 3%, indicating good reproducibility of the parallel experiments and that the data variation is within a reasonable range.The data for the three representative time points (covering the entire filtration process) are summarized in Table 7:
Table 7. Statistical analysis of parallel experimental data for sludge filtrate volumes at different time points (unit: mL).TimeSample GroupSample 1(ml)Sample 2(ml)Sample 3(ml)Mean ± SD(ml)RSD(%)1sRaw sludge11.030.981.00 ± 0.0252.501sMCSP-sludge44.083.944.01 ± 0.0701.751sMCSP-TA-sludge88.127.888.00 ± 0.1201.5010sRaw sludge11.812.1511.4711.81 ± 0.3402.8810sMCSP-sludge20.420.8120.0220.41 ± 0.3951.9410sMCSP-TA-sludge34.435.2333.5934.41 ± 0.8202.3860sRaw sludge12.412.7512.0712.41 ± 0.3402.7460sMCSP-sludge22.0522.1621.9722.06 ± 0.0950.4360sMCSP-TA-sludge3838.2337.8138.01 ± 0.2100.55
One-way analysis of variance (ANOVA) was performed to verify the significance of the differences in filtrate volumes among the three sludge groups at each key time point. The results are presented in Table 8. The F values for all time points were greater than 3000, and the P values were all less than 0.001, indicating highly significant differences in filtration performance between the original sludge, MCSP-conditioned sludge, and MCSP-TA synergistically conditioned sludge. The improvement in filtration rate achieved by MCSP alone and in combination with TA is not due to random error and holds clear statistical significance. Additionally, this analysis confirmed the reliability of the filtration performance ranking “MCSP-TA > MCSP > Sludge,” further supporting the conclusion that “MCSP and TA synergistically reduce filtration resistance.”
Table 8. Results of one-way analysis of variance (ANOVA).TimeDegrees of Freedom(df₁/df₂)F P 1s2/65521.04< 0.00110s2/63299.24< 0.00160s2/617850.29< 0.001
Fig. 8. Different types of sludge moisture content and sludge specific resistance.
MCSP is an organic flocculant that contains both cationic and anionic groups. Its unique chemical structure effectively reduces the electrostatic repulsion between colloidal particles in the sludge and weakens the interactions between sludge flocs and bound water molecules. This disruption of the extracellular polymeric substances (EPS) structure in the sludge not only accelerates the filtration process but also increases the volume of the filtrate. When an appropriate amount of TA is introduced into the MCSP-conditioned sludge, the small colloidal particles in the sludge aggregate into larger particles, enhancing dewatering performance^29^. Additionally, TA can complex and co-precipitate with extracellular protein-based macromolecules in the sludge, which are significant factors affecting sludge dewatering^30,31^, thereby further improving the dewatering performance.
Sludge moisture content (MC) and specific resistance to filtration (SRF) are key indicators for evaluating dewatering performance. The raw data, parallel sample results, mean ± SD, and RSD for MC and SRF of the original sludge, MCSP-conditioned sludge, and MCSP-TA synergistically conditioned sludge were statistically analyzed, and the results are presented in Table 9. The RSD for all indicators was less than 2.1%, indicating excellent data reproducibility and that experimental operation errors are well-controlled.
Table 9. Sludge moisture content and specific resistance to filtration data.Evaluation indicatorSludge typeSample 1Sample 2Sample 3Mean ± SDRSD(%)MC(%)Raw sludge9596.293.995.03 ± 1.151.21MCSP-sludge7475.372.874.03 ± 1.251.69MCSP-TA-sludge6566.263.965.03 ± 1.151.77SRF×10^−^¹² (m/kg)Raw sludge13.2513.4213.0813.25 ± 0.171.28MCSP-sludge6.256.366.146.25 ± 0.111.76MCSP-TA-sludge3.53.573.433.50 ± 0.072.00
One-way analysis of variance (ANOVA) was performed to verify the significance of differences in MC and SRF indicators among the three sludge groups. The results are presented in Table 10. The F value for the MC indicator was 2647.94, and the F value for the SRF indicator was 5055.00, with both P values being < 0.001. This indicates highly significant differences in the improvement of sludge MC and SRF under different conditioning methods. These results further confirm that MCSP conditioning alone can significantly reduce the sludge moisture content (from 95.03% to 74.03%) and specific resistance to filtration (SRF, from 13.25 × 10⁻¹² m/kg to 6.25 × 10⁻¹² m/kg), while the combination of MCSP and TA further enhances these effects (MC decreases to 65.03%, and SRF decreases to 3.50 × 10⁻¹² m/kg).
Table 10. Results of one-way analysis of variance (ANOVA).Evaluation indicatorDegrees of freedom(df₁/df₂)F P MC2/62647.94< 0.001SRF2/65055.00< 0.001
Analysis of organic matter content changes in extracellular polymeric substances (EPS)
To further elucidate the mechanisms by which modified corn stalk powder (MCSP) conditioning alone and MCSP combined with tannic acid (TA) conditioning affect sludge EPS, three-dimensional fluorescence spectroscopy (EEM) combined with quantitative analysis methods were employed to investigate the changes in the total amount of proteins (PN), polysaccharides (PS), and humic acids (HA) in EPS before and after conditioning. Special attention was given to the spatial distribution differences of these components in soluble EPS (S-EPS), loosely bound EPS (LB-EPS), and tightly bound EPS (TB-EPS). Additionally, the PN/PS ratio was used to establish a correlation between component changes and dewatering performance, providing a quantitative basis for optimizing conditioning agents to improve sludge dewatering.
Changes in the total content of EPS components
The total content of PN, PS, and HA in sludge EPS under different conditioning methods and the results of inter-group significance analysis are presented in Table 11.
Table 11. Total content and significance analysis of each component in EPS (n = 3, unit: mg/g VSS).ComponentUntreatedMCSPMCSP-TASignificance analysisPN16.45 ± 0.825.08 ± 0.303.39 ± 0.20U vs. M: P < 0.01;M vs. MT: P < 0.05༛U vs. MT: P < 0.01PS2.21 ± 0.151.05 ± 0.080.80 ± 0.06U vs. M: P < 0.01;M vs. MT: P < 0.05༛U vs. MT: P < 0.01HA0.89 ± 0.070.52 ± 0.040.46 ± 0.03U vs. M: P < 0.01;M vs. MT: P > 0.05༛U vs. MT: P < 0.01Note: U represents the unconditioned group, M represents the MCSP-conditioned group, and MT represents the MCSP + TA synergistic conditioning group.
As shown in Table 11, the PN content in unconditioned sludge is the highest at 16.45 ± 0.82 mg/g VSS, dominating the organic matter in EPS, followed by PS and HA with contents of 2.21 ± 0.15 mg/g VSS and 0.89 ± 0.07 mg/g VSS, respectively. After MCSP conditioning alone, the content of each component in EPS significantly decreased (P < 0.01), with PN, PS, and HA decreasing by 69.1%, 52.5%, and 41.6%, respectively. This reduction is primarily due to the electro-neutralization effect of the quaternary ammonium groups on the MCSP surface, which compresses the double electrical layer of the sludge colloids, disrupting the binding stability between EPS and sludge particles. Additionally, the porous structure of MCSP adsorbs and captures free and loosely bound EPS components through the adsorption bridging effect, embedding them within the flocs, thus reducing the detectable component content in EPS. When MCSP is used in combination with TA, the content of each EPS component further decreases, with the reduction rates of PN, PS, and HA increasing to 79.4%, 63.8%, and 48.3%, respectively. Furthermore, significant differences in PN and PS content between the MCSP and MCSP-TA conditioning groups were observed (P < 0.05), fully demonstrating the synergistic effect between the two. This is because the polyphenolic structure of TA not only interacts with PN to form hydrophobic precipitates and stacks π-π bonds with HA, but also assists in breaking the cross-linked structure of LB-EPS and TB-EPS, promoting the release and accelerating the degradation of polysaccharides, ultimately leading to further reduction in the total organic matter content of EPS.
Spatial distribution characteristics of EPS components
The stratified structure of EPS directly affects its ability to bind water in the sludge. By extracting the layers and combining them with EEM quantification, the distribution changes of PN, PS, and HA in S-EPS, LB-EPS, and TB-EPS were analyzed, and the results are shown in Figs. 9, 10 and 11.
Distribution and changes of PN
The distribution and changes of PN in the EPS layers and under different conditioning groups are shown in Fig. 9. In unconditioned sludge, PN is primarily distributed in LB-EPS (11.50 ± 0.58 mg/g VSS), accounting for 69.9% of the total PN. The contents in S-EPS and TB-EPS are 1.45 ± 0.07 mg/g VSS and 3.50 ± 0.18 mg/g VSS, respectively. As a loosely structured transitional layer with high reactivity, LB-EPS becomes the primary target for the conditioning agents.
Fig. 9. Distribution of PN content in EPS layers.
After MCSP conditioning, the PN content in LB-EPS decreased to 3.08 ± 0.18 mg/g VSS, while the contents in S-EPS and TB-EPS reduced to 0.80 ± 0.05 mg/g VSS and 1.20 ± 0.07 mg/g VSS, respectively. This is related to the action mechanism of MCSP, where the cationic groups of MCSP preferentially undergo electro-neutralization and adsorption reactions with PN in the loosely structured LB-EPS. In contrast, the dense structure of TB-EPS and the lower total amount of S-EPS result in smaller reductions.
After the combined MCSP-TA conditioning, the PN content in LB-EPS further decreased to 2.19 ± 0.13 mg/g VSS, in TB-EPS to 0.70 ± 0.04 mg/g VSS, and in S-EPS to 0.50 ± 0.03 mg/g VSS. TA, through hydrophobic interactions and hydrogen bonding, selectively binds to the hydrophilic groups exposed on PN molecules to form complexes, deactivating the hydrophilicity of PN. Additionally, the small molecular characteristics of TA allow it to penetrate into the denser structure of TB-EPS, promoting the release of some bound PN, which is then adsorbed by MCSP. This results in a comprehensive reduction in PN content across all layers. As a key component for maintaining the stability of the sludge colloids, the reduction in PN content directly weakens the colloidal repulsion and hydrophilicity between sludge particles, facilitating the densification of the floc structure and creating favorable conditions for the release of bound water.
Distribution and changes of PS
In unconditioned sludge, PS is primarily distributed in LB-EPS (1.55 ± 0.10 mg/g VSS), accounting for 70.1% of the total PS. The contents in S-EPS and TB-EPS are 0.35 ± 0.03 mg/g VSS and 0.31 ± 0.02 mg/g VSS, respectively (Fig. 10). This distribution pattern results from the polysaccharide molecules being loosely bound within the floc gaps through hydrogen bonds and ionic bonds, significantly increasing the sludge’s hydrophilicity and bound water content. This hydrophilicity is a key factor in the water retention during the dewatering process and is one of the main reasons for the poor dewatering performance of unconditioned sludge.
Fig. 10. Distribution of PS Content in EPS Layers.
After MCSP conditioning, the PS content in LB-EPS decreased to 0.55 ± 0.04 mg/g VSS, while in S-EPS and TB-EPS, it decreased to 0.25 ± 0.02 mg/g VSS. This is because MCSP, through charge neutralization, disrupts the floc structure, causing the polysaccharides, which have weaker stability, to be released from the floc gaps first. After the MCSP-TA combination conditioning, the PS content in LB-EPS further decreased to 0.40 ± 0.03 mg/g VSS, while in S-EPS and TB-EPS, it decreased to 0.21 ± 0.01 mg/g VSS and 0.19 ± 0.01 mg/g VSS, respectively. This is due to the polyphenolic structure of TA, which can form hydrogen bonds with the hydroxyl groups in polysaccharide molecules. On one hand, this enhances the disruption effect of LB-EPS flocs, promoting the release of bound polysaccharides. On the other hand, it aids in the partial degradation of polysaccharides, reducing the total amount of soluble and bound PS, thereby effectively weakening the polysaccharides’ ability to retain water in the sludge.
Distribution and changes of HA
In unconditioned sludge, HA is primarily distributed in LB-EPS (0.45 ± 0.03 mg/g VSS) and TB-EPS (0.34 ± 0.02 mg/g VSS), accounting for 50.6% and 38.2% of the total HA, respectively, with only 0.10 ± 0.01 mg/g VSS in S-EPS (Fig. 11). HA molecules are rich in negatively charged functional groups such as carboxyl and hydroxyl groups, which can maintain the dispersion and stability of sludge colloids through electrostatic repulsion and hydrogen bonding. These interactions also enhance the hydrophilicity of the sludge, making it more difficult to remove water.
Fig. 11. Distribution of HA content in EPS layers.
After MCSP conditioning, the HA content in LB-EPS, TB-EPS, and S-EPS decreased to 0.26 ± 0.02 mg/g VSS, 0.17 ± 0.01 mg/g VSS, and 0.09 ± 0.01 mg/g VSS, respectively. The cationic groups of MCSP reduce the water solubility of HA through electro-neutralization, causing it to transition from a dissolved state to a precipitated state. Additionally, the porous structure of MCSP adsorbs and encapsulates the released HA particles, thereby reducing the detectable HA content in EPS.
After the MCSP-TA combination conditioning, the HA content in LB-EPS, TB-EPS, and S-EPS further decreased to 0.22 ± 0.01 mg/g VSS, 0.16 ± 0.01 mg/g VSS, and 0.08 ± 0.01 mg/g VSS, respectively. TA, through π-π stacking interactions with the aromatic structure of HA, works synergistically with the adsorption effect of MCSP to further reduce the HA content in LB-EPS, although its removal effect on HA in the densely structured TB-EPS is limited.
PN/PS ratio
The PN/PS ratio is a key indicator of sludge dewatering performance, with a lower ratio indicating better dewatering performance. The PN/PS ratios for different conditioning groups are shown in Fig. 12: the unconditioned group had the highest ratio at 7.44 ± 0.35, indicating high sludge viscosity and difficulty in water removal. After MCSP conditioning, the ratio decreased to 4.84 ± 0.22, significantly improving dewatering performance. Following MCSP-TA combined conditioning, the ratio further decreased to 4.24 ± 0.18, achieving the best dewatering effect.
Fig. 12PN/PS ratio of different types of sludge.
MCSP primarily reduces the PN content through electro-neutralization, which is the main reason for the decrease in the PN/PS ratio. The introduction of TA further optimizes the PN/PS ratio by selectively removing hydrophilic PN from LB-EPS. The reduction in the PN/PS ratio not only diminishes the colloidal repulsion caused by PN but also weakens the water retention ability of PS, leading to the densification of the sludge flocs, an increase in hydrophobicity, and enhanced release efficiency of bound water, thereby reducing the moisture content of the cake. This result, confirmed at the molecular level, demonstrates that the combined use of MCSP and TA can effectively optimize sludge dewatering performance by regulating the PN/PS ratio.
Sludge filtrate COD
Chemical oxygen demand (COD) typically represents the amount of reducible substances in a sample. In this study, the reducible substances are primarily the organic compounds in the sludge filtrate. A higher COD value indicates a greater organic content. The COD of the filtrates from untreated sludge (Untreated), MCSP-conditioned sludge (MCSP-sludge), and MCSP combined with TA-conditioned sludge (MCSP-TA-sludge) was quantitatively analyzed. The results are shown in Fig. 13.
Fig. 13. Sludge filtrate COD.
As shown in Fig. 13, the COD of the original sludge filtrate is the highest at 953.33 ± 8.50 mg/L. After MCSP conditioning, the COD decreases to 570.00 ± 8.08 mg/L, as the quaternary ammonium groups and porous structure of MCSP capture dissolved organic matter and encapsulate it within the flocs. After combining MCSP with TA, the COD further decreases to 395.00 ± 8.50 mg/L, as the polyphenolic hydroxyl groups of TA interact with the organic matter through hydrophobic precipitation and hydrogen bonding, synergistically enhancing the organic matter fixation effect of MCSP. The results indicate that the conditioning process not only does not exacerbate organic pollution but also significantly reduces the organic load in the filtrate, with no risk of secondary organic contamination. One-way analysis of variance (ANOVA) shows highly significant differences in COD values among the filtrates from different sludge types (P < 0.001), indicating that both MCSP conditioning alone and its synergistic effect with TA have a stable and significant effect in reducing the filtrate COD.
Median particle size and zeta potential of sludge
To validate the feasibility of fine sludge particle aggregation into larger flocculent structures, the median particle size (d₅₀) and Zeta potential of sludge samples were systematically analyzed, with the results presented in Fig. 14. The median particle size of sludge flocs increased from 30.10 μm (untreated) to 65.40 μm for MCSP-conditioned sludge(MCSP), and was further elevated to 86.23 μm for MCSP-TA co-conditioned sludge(MCSP-TA). Meanwhile, the Zeta potential of sludge underwent a transition from negative to positive values, with the MCSP-TA co-conditioned sludge exhibiting a Zeta potential closest to electroneutrality.
Fig. 14. Variation diagram of median particle size and zeta potential of different types of sludge.
The Zeta potential of untreated sludge exhibits a relatively high absolute value, which hinders the aggregation of fine sludge particles and results in small, dispersed particle distributions. Following the addition of MCSP, the cationic quaternary ammonium groups carried by MCSP electrostatically interact with the negatively charged functional groups on the sludge surface, thereby reducing the absolute value of the Zeta potential. Furthermore, the long-chain molecular structure of MCSP enables the adsorption of fine sludge particles, which are subsequently bridged into larger flocs, leading to a significant increase in sludge floc size. When TA is co-applied with MCSP for sludge conditioning, the phenolic hydroxyl groups in TA form hydrogen bonds with the quaternary ammonium groups of MCSP. Moreover, the weakly anionic groups of TA further neutralize the residual negative charges on the sludge surface via charge transfer interactions, markedly reducing the electrostatic repulsion among sludge particles. Consequently, the absolute value of the sludge Zeta potential approaches zero, and the sludge floc size is further enhanced.
One-way analysis of variance (ANOVA) was used in this study to verify the significance of differences in median particle size and Zeta potential among different types of sludge, as shown in Tables 12 and 13.
Table 12. Median Particle Size and Zeta Potential Data.MeasurementMethodSample 1Sample 2Sample 3Mean ± SDRSD(%)Median Particle Size(µm)Untreated30.130.529.730.10 ± 0.401.33MCSP65.466.164.865.43 ± 0.650.99MCSP-TA86.2387.185.486.24 ± 0.850.98Zeta Potential(mV)Untreated-15.19-15.42-14.98-15.19 ± 0.221.45MCSP7.457.587.337.45 ± 0.131.68MCSP-TA4.134.204.064.13 ± 0.071.69
Table 13. One-way ANOVA overall difference test results.MeasurementDegrees of Freedom(df₁/df₂)F P Median particle size2/61528.76< 0.001Zeta potential2/61386.42< 0.001
There are highly significant differences (P < 0.001) in the median particle size and Zeta potential of the sludge after treatment with different methods, proving that both MCSP conditioning alone and MCSP combined with TA consistently and reliably improve the floc size and colloidal stability of the sludge.
Rheological properties analysis of sludge
The rheological properties of sludge directly reflect its internal structural stability and flow resistance, which are related to energy consumption in engineering processes such as pumping and dewatering after conditioning. Based on the Herschel-Bulkley (H-B) model, steady-state rheological tests were performed using a rotational rheometer (TA Instruments AR2000ex) on original sludge, MCSP-conditioned sludge (MCSP-sludge), and MCSP combined with tannic acid-conditioned sludge (MCSP-TA-sludge). The analysis focused on the yield stress (τ₀), consistency coefficient (K), flow behavior index (n), and apparent viscosity of the conditioned sludge, quantifying the stability of the internal structure and the effectiveness of bound water release.
Fig. 15. Sludge rheological curves.
As shown in Fig. 15, the curves of shear stress and apparent viscosity as a function of shear rate for the sludge conditioned by different methods exhibit a consistent trend: In the low shear rate range (0.1 to 100 s⁻¹), the apparent viscosity decreases sharply; in the high shear rate range (100 to 1000 s⁻¹), the viscosity levels off. Compared to the original sludge, the shear stress curves for both MCSP-sludge and MCSP-TA-sludge shift downward, indicating that the overall viscosity of the conditioned sludge is reduced.
The rheological curves were fitted using the H-B model, as shown in Eq. (5):
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tau = \tau _{0} + K\dot{\gamma }^{n}$$\end{document}Where: τ is the shear stress (Pa), τ₀ is the yield stress (Pa), K is the consistency coefficient (Pa·sⁿ), γ is the shear rate (s⁻¹), and n is the flow behavior index. The fitting results are shown in Table 14. The correlation coefficients (R²) for all fittings are greater than 0.98, indicating that the model accurately characterizes the rheological properties of the sludge.
Table 14. Herschel-Bulkley Model Fitting Results for Sludges.Sludge typeτ_0_(Pa)K(Pa·sⁿ) n
R ^2^ Apparent Viscosity(Pa・s)Sludge2.91360.00451.19280.98350.0248MCSP-sludge1.38720.08150.77690.99020.0207MCSP-TA-sludge0.92150.12980.87140.99410.0167
From the analysis of Table 14, the yield stress (τ₀) reflects the strength of the sludge floc structure. The yield stress for the sludge is the highest at 2.9136 Pa. After MCSP conditioning, τ₀ decreases to 1.3872 Pa, which is attributed to charge neutralization disrupting the EPS colloidal structure, loosening the floc, and initiating the release of bound water. After MCSP is combined with TA, τ₀ further decreases to 0.9215 Pa. The complexation and precipitation of EPS proteins by TA, along with the synergistic breakdown of the EPS network, result in the release of more bound water, directly confirming the action cycle of flocculation reconstruction and bound water release.
The consistency coefficient (K) reflects the overall viscosity. The K value for the sludge is the lowest at 0.0045 Pa·sⁿ, corresponding to a dispersed colloidal structure. After MCSP conditioning, K increases to 0.0815 Pa·sⁿ due to the formation of large flocs through adsorption bridging. In the combined group, K further increases to 0.1298 Pa·sⁿ, where TA promotes floc densification, although the K value remains within an acceptable range for engineering applications and does not affect flow performance.
The flow behavior index (n) of 1 represents a Newtonian fluid, while n < 1 indicates a pseudoplastic fluid. The n value for the sludge is 1.1928, indicating poor shear resistance. For the MCSP group, n decreases to 0.7769, meaning shear forces can break down the flocs and reduce viscosity. In the MCSP-TA combined group, n further decreases to 0.8714, indicating a more uniform floc structure and improved shear stability, which is beneficial for pipeline transport and dewatering equipment operation.
The apparent viscosity decreases from 0.0248 Pa·s (sludge) to 0.0167 Pa·s (MCSP-TA combined group), indicating that the flow resistance of the conditioned sludge has been reduced, optimizing pumpability and lowering operational energy consumption, further supporting the practical application value of this technology.
Evaluation of sludge morphological characteristics
To observe the changes in surface morphology of different types of sludge particles, the surface characteristics of raw sludge, MCSP-sludge, and MCSP-TA-sludge were analyzed.
Fig. 16. Scanning electron microscopy images of different types of sludge. (a) 50 μm original sludge; (b) 20 μm original sludge; (c) 50µmMCSP-sludge; (d) 20µmMCSP-sludge; (e) 50µmMCSP-TA-sludge; (f) 20µmMCSP-TA-sludge.
As shown in Figs. 16a, b, the surface of the original sludge exhibits a dense and smooth texture, with some small particles scattered around. After conditioning with MCSP, the surface of the sludge particles transforms from a tight and smooth state to a loose, rough, and uneven condition, indicating that the addition of MCSP disrupts the originally stable floc structure in the sludge, leading to the formation of numerous pores and grooves on the particle surfaces. These pores and grooves provide effective channels for the release of bound water from within the sludge, as seen in Figs. 16c, d. When TA is used in conjunction with MCSP to condition the sludge, the colloidal structure of the sludge particles is further broken down and decomposed, subsequently forming a loosely distributed floc structure during the re-polymerization process. This mechanism of fragmentation and re-polymerization positively impacts the disruption of the EPS structure in the sludge, facilitating the release of bound water and the subsequent sedimentation of sludge flocs, as illustrated in Figs. 16e, f.
Heavy metal content
The “heavy metal residue in sludge cake” and “heavy metal leaching in filtrate” concentrations were determined for the original sludge, MCSP-conditioned sludge (MCSP-sludge), and MCSP combined with TA-conditioned sludge (MCSP-TA-sludge) from the Yakeshi sludge treatment plant. The results were compared with the standards outlined in the “Sludge Disposal and Mixed Landfilling of Municipal Sewage Treatment Plants” (CJ/T 249–2007) and the “Water Quality Standards for Sewage Discharge into Urban Sewers” (CJ343-2010). The results are presented in Table 15.
Table 15. Comparison of sludge heavy metal content with national standard limits.“Sludge Disposal and Mixed Landfilling of Municipal Sewage Treatment Plants”(CJ/T 249–2007) (mg/kg)PbCrAsCd≤ 100≤ 300≤ 30≤ 10Sludge cake (mg/kg)23 ± 0.3618 ± 0.4512 ± 0.350.55 ± 0.02MCSP sludge cake (mg/kg)20.7 ± 0.4016.1 ± 0.3510.8 ± 0.300.50 ± 0.020MCSP-TA sludge cake (mg/kg)19.1 ± 0.4014.8 ± 0.3510.0 ± 0.300.46 ± 0.020“Water Quality Standards for Sewage Discharge into Urban Sewers”(CJ343-2010)(mg/L)≤ 1≤ 1.5≤ 0.5≤ 0.1Sludge filtrate (mg/L)0.029 ± 0.00150.024 ± 0.00150.040 ± 0.00200.059 ± 0.0025MCSP sludge filtrate (mg/L)0.034 ± 0.00150.028 ± 0.00150.048 ± 0.00200.071 ± 0.0030MCSP-TA sludge filtrate (mg/L)0.041 ± 0.00200.033 ± 0.00150.057 ± 0.00250.084 ± 0.0035
Heavy metals in the sludge cake are primarily bound to the active sites of EPS through complexation and adsorption, forming a solid-phase enriched state. As shown in Table 15, the original sludge cake contains the highest concentrations of heavy metals, with Pb, Cr, As, and Cd at 23 ± 0.36, 18 ± 0.45, 12 ± 0.35, and 0.55 ± 0.02 mg/kg (DS), respectively. After MCSP conditioning, the heavy metal content in the cake significantly decreases, with Pb reduced to 20.7 ± 0.40 mg/kg, Cr to 16.1 ± 0.35 mg/kg, As to 10.8 ± 0.30 mg/kg, and Cd to 0.50 ± 0.02 mg/kg. This is attributed to the cationic electro-neutralization effect of MCSP, which disrupts the EPS colloidal structure, causing some of the heavy metals bound to EPS to lose their complexation sites and be released from the solid phase into the liquid phase. After MCSP combined with TA conditioning, the heavy metal content in the cake further decreases, with Pb at 19.1 ± 0.40 mg/kg, Cr at 14.8 ± 0.35 mg/kg, As at 10.0 ± 0.30 mg/kg, and Cd at 0.46 ± 0.02 mg/kg. This is because the polyphenolic hydroxyl groups of TA interact with the proteins in EPS, promoting hydrophobic precipitation and enhancing the breakdown of the EPS network, leading to the migration of more bound heavy metals into the filtrate. As a result, the heavy metal content in the sludge cake decreases. Compared to the standard limits outlined in the “Sludge Disposal and Mixed Landfilling of Municipal Sewage Treatment Plants” (CJ/T 249–2007), the heavy metal concentrations in the sludge cakes from all experimental groups are well below the standard limits, meeting the requirements for sludge mixed landfilling and ensuring environmental safety.
The heavy metals in the sludge filtrate mainly originate from the dissolved components released from the solid phase of the sludge, and their concentration changes are inversely correlated with those in the cake. As shown in Table 15, the heavy metal content in the filtrate of the original sludge is the lowest among all experimental groups, with Pb, Cr, As, and Cd concentrations of 0.029 ± 0.0015, 0.024 ± 0.0015, 0.040 ± 0.0020, and 0.059 ± 0.0025 mg/L, respectively. After MCSP conditioning, the heavy metal concentrations in the filtrate increase slightly, with Pb at 0.034 ± 0.0015 mg/L, Cr at 0.028 ± 0.0015 mg/L, As at 0.048 ± 0.0020 mg/L, and Cd at 0.071 ± 0.0030 mg/L. This increase is directly related to the dissolution of solid-phase heavy metals after the disruption of EPS by MCSP, although the increase is limited, indicating that most of the heavy metals remain in the solid phase. After MCSP combined with TA conditioning, the heavy metal content in the filtrate further increases, with Pb at 0.041 ± 0.0020 mg/L, Cr at 0.033 ± 0.0015 mg/L, As at 0.057 ± 0.0025 mg/L, and Cd at 0.084 ± 0.0035 mg/L. This increase is due to the enhanced dissolution efficiency of heavy metals facilitated by TA’s effect on the EPS network, although the overall concentrations remain within a low range. Compared to the standard limits in the “Water Quality Standards for Sewage Discharge into Urban Sewers” (CJ343-2010), the heavy metal concentrations in the filtrates from all experimental groups are below the standard limits, ensuring environmental safety.
Evaluation of environmental and economic benefits
The Benefit-Cost Ratio (BCR) serves as a core indicator for quantifying the sustainability of sludge pretreatment technologies. This study defines the BCR as the ratio of equivalent benefits to total costs, based on the “Technical Specifications for Sludge Treatment and Disposal in Urban Sewage Treatment Plants” (DB61/T 1571–2022) and localized cost data from Yakeshi City. The formula for BCR is provided in Eq. (6):
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{BCR}\mathrm{=}\frac{\mathrm{Equivalent\:benefits}}{\mathrm{Total\:cost}}$$\end{document}The equivalent benefits are quantified through a two-dimensional approach: first, the cost savings from auxiliary fuel due to the reduction in moisture content after sludge pretreatment. This is calculated based on the benchmark parameter from the guidelines, which states that “for every 1% reduction in moisture content, 1 m³ of natural gas consumption is reduced,” combined with the 2024 industrial natural gas price in Yakeshi City (0.49 USD/m³). Second, the savings in transportation costs resulting from the weight reduction due to the release of bound water. This is calculated based on the weight of the released bound water and the local short-distance transportation cost (1.67 USD/t). All data are sourced from the Yakeshi City government procurement website, the Urban Management and Law Enforcement Bureau, and other public platforms, with 2024 measured values. The specific data sources are presented in Table 16.
Table 16. Localized cost survey results for the urban sludge treatment industry in Yakeshi city, 2024.Cost categoryParametersValueData SourceChemical pricesMCSP Unit Price0.35 USD/kg https://www.yks.gov.cn/OpennessContent/show/492687.html CPAM Unit Price0.42 USD/kg https://www.ccgp-neimenggu.gov.cn TA Unit Price0.92 USD/kg https://www.ccgp-neimenggu.gov.cn Energy costsIndustrial Electricity Unit Price(1-10 kV)0.066 USD/kWh http://fgw.nmg.gov.cn Industrial Natural Gas Unit Price0.47 USD/m³ http://www.als.gov.cn Labor costsSludge Conditioning Operation & Maintenance Daily Wage42.8 USD/day https://www.jobui.com Transportation costsSludge Short-Distance (within 20 km) Transport Comprehensive Cost1.67 USD/t https://neimonggol.zhaobiao.cn Equipment depreciationSludge Conditioning Equipment Annual Depreciation Rate8.3% https://www.mohurd.gov.cn
Based on the above definition of equivalent benefits and authoritative cost data, the BCR value for 1 ton of sludge was recalculated. The results are presented in Table 17, where a BCR greater than 1 indicates that the overall benefits exceed the economic investment costs.
Table 17BCR for 1 ton of sludge.ProjectMCSPMCSP-TACPAMTotal Cost (USD)11.5216.159.87Equivalent Benefit - Auxiliary Fuel Savings (USD)9.8714.107.99Equivalent Benefit - Transportation Cost Savings (USD)2.844.572.02Total Equivalent Benefit (USD)12.7118.6710.01BCR1.101.161.01
As shown in Table 17, the BCR value for the MCSP and TA synergistic conditioning sludge scheme is 1.16, indicating that the overall benefits of this scheme have surpassed the economic investment, resulting in a positive return. In contrast, the economic benefits of MCSP alone and CPAM conditioning are relatively limited. This result strongly supports the economic feasibility and practical value of the MCSP-TA conditioning technology. The two-dimensional calculation logic for equivalent benefits aligns more closely with the practical scenarios of sludge treatment projects, significantly enhancing its persuasiveness.
Conclusion
This study focused on the preparation of MCSP and the analysis of its physicochemical properties, exploring the mechanisms and optimal conditions for sludge conditioning with MCSP in combination with TA, and evaluating the dewatering effects on different types of conditioned sludge. The main conclusions are as follows:
- The concentration of NaOH has the most significant impact on the preparation of MCSP, with the ideal conditions being 5 g of NaOH, 40 min of alkalization time, a temperature of 55 °C, 8.67 ml of CHPTAC, 10 g of chloroacetic acid, and a grafting reaction time of 2 h.
- The combination of MCSP and TA for sludge conditioning can disrupt the EPS structure of the sludge, facilitating the release of bound water and the subsequent sedimentation of sludge flocs. The optimal conditioning conditions are 30% DS for MCSP, 0.3 mmol/g DS for TA, a stirring speed of 400 rpm, and a stirring time of 15 min.
- The moisture content of sludge conditioned solely with MCSP and that conditioned with MCSP in combination with TA decreased by 20% and 30%, respectively. The analysis indicates that the dewatering effect of sludge conditioned with MCSP and TA is superior, providing higher environmental and economic benefits.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary Material 1