Enhanced purification efficacy of the microflocculation–ultrafiltration process for raw water quality from multiple sources during heavy rainfall Open Access

The acceleration of global climate change is increasingly amplifying both the frequency and intensity of meteorological extremes (Newman & Noy 2023; Yun et al. 2023). Among these, intense precipitation events, notably heavy rainfall, have emerged as a pivotal climate concern on a global scale (Dickson & Dzombak 2019). Extreme rainfall events exert profound and complex impacts on water resources and ecosystems (Yan et al. 2023). Heavy rainfall accelerates soil erosion, increasing suspended solids and organic matter (Zhang et al. 2020). This surge in pollutants contaminates water sources, threatening the security of water supplies (Ng et al. 2020).

In response to the multifaceted challenges posed by economic constraints, technological limitations, and governance complexities, our nation has implemented a single-village water supply strategy to enhance the safety of drinking water for rural residents in the eastern region (Zhang et al. 2024). This strategy is particularly effective in sparsely populated, mountainous regions with poor inter-village transportation. Primary water sources include dams, streams, reservoirs, and mountain ponds. The quality of raw water from these natural sources is inherently complex and particularly prone to significant turbidity fluctuations during periods of heavy rainfall (Malerba et al. 2022). This variability poses major challenges to consistently meeting stringent hygiene and water quality standards.

Ultrafiltration (UF) technology, a cornerstone of membrane separation, efficiently removes turbidity, bacteria, viruses, and other impurities at low pressures (Warsinger et al. 2018). UF is widely used in surface water treatment, valued for its high water purity, compact design, and resilience to quality fluctuations. However, membrane fouling continues to challenge the long-term viability of UF systems (Hu et al. 2024). Fouling leads to reduced membrane flux and shortened operational lifespan, thereby compromising the technology's reliability and cost-effectiveness. Microflocculation (MF) reduces pore blockage and filter cake resistance by agglomerating small suspended solids into larger clusters (Lee et al. 2021; Zhao et al. 2023). In the flocculation process, micro-flocs act as nucleation sites catalyzed by larger flocs, promoting the aggregation of suspended solids into loosely structured filter cake layers (Yue et al. 2021). This optimization improves the conditions for subsequent processes, with the characteristics of the flocculent directly impacting the configuration of the filter cake layer and the extent of membrane fouling (Liu et al. 2024). Moreover, compared to conventional flocculation, MF stands out as a cost-effective and efficient pretreatment method that does not require sedimentation apparatus, thus reducing coagulant dosages and offering a more economical pretreatment option (Pivokonsky et al. 2024).

The integration of MF–UF processes not only offers substantial advantages in treatment efficacy and economic viability but also holds great potential for significantly enhancing drinking water quality in rural areas. However, despite these benefits, the application of this technology for rural water supply remains largely theoretical. The primary challenge in real-world implementation lies in addressing the complexity and variability of actual water sources. Rainfall, for instance, introduces significant variability in water quality, as small particulate matter from runoff often infiltrates submerged UF systems, potentially damaging membrane materials (Sutzkover-Gutman et al. 2010; Wang et al. 2010). In this study, we first investigated the effects of rainfall on the water quality of various water sources in mountainous regions. Subsequently, we identified the main components contributing to membrane pollution in the water from four different sources during both rainfall and non-rainfall periods. These components were then simulated in laboratory settings, where UF experiments were conducted to assess their impact. This research provides critical insights into the real-world challenges of applying MF–UF technology in complex environments, particularly under variable conditions like rainfall. The findings will help refine treatment strategies, ensuring more reliable and sustainable drinking water solutions for rural communities facing similar environmental complexities.

Synthetic water resembling natural water sources was prepared, with all chemicals used, unless otherwise specified, being of analytical grade. Humic acid (HA, Aladdin, Shanghai, China) and fulvic acid (FAS, BASF, China) were employed to simulate DOM. To simulate the high turbidity of water during heavy rainfall periods more realistically, kaolin (Al₂O₃·2SiO₂·2H₂O, Tianjin Zhonglian, China) and calcium fluoride (CaF₂, Tianjin Zhonglian, China) were added as suspension models. As the DOM concentration varies in different raw waters, the ratios of chemicals are presented in Table 1. Polyaluminum chloride (PAC, ≥30%) was used as the coagulant, with the optimal dosage determined to be 20 mg/L through testing.

To test the newly glued and dried membrane, soak it in ultrapure water for 24 h beforehand to remove surface impurities from the membrane. Before each experiment, pre-filter 500 mL of ultrapure water to maintain a constant initial membrane flux. For the first filtration test, add 2 L of water initially, and after filtering 1 L, add water to maintain the volume at 2 L. The initial flux of the membrane after adding water during the filtration cycle indicates the recovery of membrane flux. Repeat this process once. The permeate quality is automatically recorded by a high-precision electronic balance (DJ2002FT, Jinke Hua, China). Finally, conduct MF filtration under the same conditions. Add 20 mg/L of PAC before starting the above test, mix using a six-station magnetic stirrer (HJ-6B), set the test parameters, and stir rapidly at 200 r/min for 30 seconds, followed by slow stirring at 100 r/min for 5 min.

Fifty mL each of pre-prepared raw water and filtered water were taken, and their turbidity was measured using a turbidity meter (WGZ-3B, Shanghai Xinyi, China). The water samples, filtered through a 0.45 μm polyethersulfone membrane (Membrana, Germany), were then placed in quartz cuvettes for measurement of ultraviolet absorbance at 254 nm using a UV/Visible spectrophotometer (L series, Shanghai Youke, China). UV₂₅₄ can represent high molecular weight organic compounds such as humic substances and aromatic compounds.

Microscopic structures on the sample surface were observed using scanning electron microscopy to characterize the morphology of the filter cake layer on the fouled surface. 3D fluorescence spectroscopy, which records fluorescence signals at different excitation and emission wavelengths, enables the rapid and accurate identification and quantification of various organic compounds, providing crucial information on the distribution, content, and spectral characteristics of organic components in water (Kuo & Yuan 2021). Fluorescence excitation–emission matrix (EEM) measurements were performed at room temperature using a fluorescence spectrophotometer (F98, Shanghai Lengguang, China) equipped with a 150-W xenon lamp (Hamamatsu, Japan) as the excitation light source. The emission wavelength scanning range was 280–550 nm, with a scanning interval of 1 nm, while the excitation wavelength scanning range was 200–400 nm, with a sampling interval of 2 nm. The photomultiplier tube gain was set to medium, at 650 V, with a scanning speed of 30,000 nm/min. According to existing classifications, 3D fluorescence spectra can be divided into five typical components: tryptophan-like protein (Ex < 250 nm, Em < 350 nm); tyrosine-like protein (250 nm < Ex < 360 nm, 330 nm < Em < 380 nm); humic substances (250 nm < Ex < 450 nm, 380 nm < Em < 600 nm); and fulvic acid-like substances (220 nm < Ex < 250 nm, 380 nm < Em < 480 nm) (Yu et al. 2019).

In Equation (1), J represents the instantaneous membrane flux, dx denotes the unit water production per unit time, and A signifies the instantaneous membrane area. The membrane area is calculated by measuring the drop in liquid level, which occurs as water is produced in real time.

The dam, characterized by high flow velocities and minimal sediment influx, typically presents relatively clear water quality. In contrast, the reservoir functions as a mixed ecosystem, experiencing periodic algal blooms during dry spells and significant turbidity spikes during heavy rainfall events. Streams, with slower flow velocities, exhibit water quality conditions akin to those observed in reservoirs. Ponds, due to their smaller volume and higher sediment loads, generally demonstrate inferior water quality. As depicted in Figure 2, the single UF membrane process exhibits commendable adaptability in turbidity removal. During dry periods, this process effectively treats water with low turbidity, achieving reductions from 9.80 to 0.20 NTU. For the four types of water sources assessed during non-rainy conditions, as well as for dams and reservoirs subjected to heavy rainfall (where turbidity ranges between 10.00 and 100.50 NTU), the UF process consistently reduces turbidity levels to below 1.00 NTU. However, the effectiveness of the UF membrane diminishes when confronted with highly turbid water; for instance, turbidity levels are reduced to 1.17 NTU in streams during heavy rainfall and to 2.32 NTU in ponds with initial turbidity as high as 495.20 NTU, which do not meet the requisite water quality standards.

In contrast, the MF–UF combined process demonstrates superior efficacy in turbidity removal, exhibiting robust resistance to fluctuations in water quality. Post-filtration turbidity remains consistently below 1.00 NTU. Unlike the UF membrane process, which primarily relies on physical sieving mechanisms for turbidity reduction, the MF–UF combined approach aggregates particles through interactions with coagulants. This pretreatment process significantly enhances turbidity removal efficiency, resulting in more effective treatment outcomes.

In the MF reaction, the neutralization of charges weakens the repulsion between suspended solids and colloidal particles in water, causing them to gradually collapse and form micro-flocs, thereby achieving the removal of organic matter. According to Figure 3, for dams and streams throughout the entire period, the MF–UF process achieves UV₂₅₄ removal rates exceeding 90%. During non-rainy and heavy rainfall periods, the UV₂₅₄ removal rates for reservoirs and ponds are 87.40, 86.42, 82.14, and 77.17%, respectively, maintaining at approximately 80%. Notably, during heavy rainfall, ponds exhibit the lowest UV₂₅₄ removal rate due to increased surface runoff and soil erosion, which washes organic matter, nutrients, and other pollutants into the water, leading to significant increases in organic matter concentration and turbidity.

For highly turbid and organic-rich waters, the capability of the MF–UF combined process is limited, but it demonstrates significant overall removal effectiveness. It can be concluded that compared to the single UF process, the MF–UF combined process significantly enhances the removal of dissolved organic substances. Pre-flocculation before UF aggregates pollutants into larger particles, which are easier to be retained by the UF membrane, thus avoiding direct membrane contact and reducing membrane fouling caused by pore adsorption and blockage. Additionally, the removal effects of UV₂₅₄ by both processes are relatively stable across different water sources.

The fluorescence peak in Region V of the raw water spectra is notably strong, peaking during both non-rainy and heavy rainfall periods. This indicates that the organic matter in raw water is predominantly humic substances, with lower levels of protein-like compounds. Humic substances are chemically stable due to their complex structures with aromatic rings and carboxyl groups, allowing them to remain in water bodies longer. In contrast, protein-like compounds have simpler structures and are more prone to rapid degradation by microbial and biological processes. Figures 4(b) and 4(e) depict the removal efficiency of organic matter in dam water during non-rainy and heavy rainfall periods by direct UF. It is evident that the fluorescence intensity in the water after UF is slightly reduced, but not significantly overall. In contrast, Figures 4(c) and 4(f) show the UF effluent after MF, where no distinct fluorescence peaks are observed. This indicates that MF enhances the removal of humic substances and similar compounds significantly.

In Figures 5(c) and 5(f), the fluorescence intensity is similar but significantly reduced compared to Figures 5(a) and 5(d), indicating that MF exhibits good adaptability to water quality. It can effectively remove organic matter during both heavy rainfall and non-rainy periods.

Due to the inefficiency of UF in removing organic matter, water bodies often contain high levels of organics. In reservoirs, excessive algae proliferation can lead to eutrophication, promoting the production and release of organic matter, especially organic waste and algal metabolites. Consequently, the organic matter content in UF effluent from reservoirs is higher compared to that from hillside ponds. In contrast, water treated with MF removes organic matter, and the algae growth process itself absorbs nutrients for growth, thereby reducing the concentration of DOM in the water. Therefore, water from reservoirs treated with MF–UF combined processes exhibits lower organic matter concentrations compared to water from hillside ponds.

Due to membrane fouling reducing membrane flux and increasing operating costs (Laîné et al. 2003), this study compares the changes in UF membrane flux for four different water sources during non-rainy periods and heavy rainfall periods under UF and MF–UF processes.

Clearly, compared to non-rainy periods, filtration times are longer during heavy rainfall periods for the same volume of water. However, the MF–UF process can shorten filtration time. Additionally, during the filtration process, the initial membrane flux enters a rapid decline phase, followed by minor fluctuations in flux. From Figure 8, it is evident that during the rapid flux decline phase, dam water from non-rainy periods under UF processes experiences a flux decline to approximately 70 L/m²·h, whereas under MF–UF processes, the flux stabilizes at around 100 L/m²·h. For dam water during heavy rainfall periods under UF processes, the flux declines to approximately 50 L/m²·h, whereas under MF–UF processes, the flux stabilizes at around 90 L/m²·h.

These results indicate that MF can delay membrane fouling and effectively improve membrane flux. This is because the MF process forms loose, porous flocs that do not easily enter and clog membrane pores; instead, they uniformly cover the membrane surface to form a filter cake layer, thereby reducing cake layer compaction (Shao et al. 2017; Ao et al. 2018). The porous filter cake layer increases the number of channels for water flow through the filter cake, thereby reducing resistance to water passing through and enhancing membrane flux.

Additionally, the data suggest that stream water sources, characterized by higher pollutant concentrations, experience more rapid membrane flux declines compared to dam water sources. This indicates that as the concentration of contaminants increases, membrane fouling intensifies, resulting in a more pronounced decrease in flux over time. Between both water sources, it is evident that the MF–UF–UF process mitigates flux fluctuations more effectively than direct UF, especially as pollutant concentrations rise. The ability of MF–UF to maintain a higher, more stable flux suggests that MF pretreatment significantly reduces fouling, allowing the UF membrane to perform more consistently across varying levels of contamination.

The organic matter concentrations in pond and reservoir water sources are roughly similar, but reservoir water contains a higher concentration of algae compared to pond water. Additionally, pond water contains non-viscous sediments that are absent in reservoir water. Based on these results, it can be concluded that direct UF is relatively more effective in removing sediment-laden water compared to algae, with shorter processing times. Moreover, MF demonstrates faster removal of algae compared to direct UF, resulting in shorter overall filtration times for reservoir water compared to pond water.

Long-term operation of membranes leads to notable morphological alterations on their surfaces, primarily influenced by the infiltration of various pollutants, which directly impacts filtration efficiency. This study utilizes SEM to elucidate the microstructural changes of the membrane surface and pore architecture, particularly focusing on the fouling of UF membranes after treating dam and stream waters during heavy rainfall events.

The particle sizes within the direct UF cake layer tend to be uniform, resulting in minimal interstitial gaps and high packing density, which contributes to increased compaction. This compaction is a consequence of the physical sieving and consolidation mechanisms inherent in direct UF, leading to elevated transmembrane pressure and a rapid decrease in membrane flux. In contrast, the MF–UF cake layer comprises a heterogeneous mix of particle sizes, including larger flocculated aggregates and smaller primary particles, as shown in Figure 12(c). This size variation introduces additional channels and voids, promoting fluid movement and minimizing resistance within the cake layer.

Furthermore, the particles in the direct UF cake layer exhibit a rigidity that enhances the layer's stability and pressure resistance during filtration. Conversely, the particles in the MF–UF cake layer are softer and more elastic due to the MF process, allowing for improved adaptability to pressure variations and greater stability throughout filtration. This flexibility ultimately aids in reducing fouling and maintaining filtration efficiency by accommodating changes in operating conditions.

The direct UF process demonstrated effective performance for water sources with low to moderate turbidity but exhibited limitations under high turbidity conditions. In contrast, the MF–UF combination process displayed superior turbidity removal capacity and greater resilience to water quality fluctuations. Specifically, the inclusion of MF pretreatment significantly enhanced the removal of DOM, achieving an approximate UV₂₅₄ removal rate of 80% across diverse water sources. The MF–UF process thus showed relatively consistent treatment efficacy across varying water qualities.

Humic-like substances, which are chemically stable and complex, are challenging to remove via direct UF alone. However, MF pretreatment markedly improves their removal efficiency. Moreover, the synergistic effect of MF and algae further augments the removal of DOM. While MF treatment has limited effectiveness under high organic matter concentrations, it significantly boosts the overall efficiency of the water treatment process.

MF pretreatment results in a looser and more permeable cake layer on the UF membrane surface, which enhances the removal of suspended solids and DOM, mitigates membrane fouling, and slows the decline in membrane flux, thereby reducing filtration time. Conversely, the cake layer in direct UF tends to be smooth and tightly packed, whereas the MF–UF cake layer is porous, facilitating better liquid diffusion and permeation. Therefore, integrating MF as a pretreatment step in UF processes is recommended, especially for water sources with variable turbidity and organic matter concentrations. This hybrid MF membrane system should be prioritized in decentralized water supply engineering due to its cost-effectiveness and protective benefits for the UF membranes, the most expensive component of the supply system.

This work was financially supported by Zhejiang Province Single-Village Water Supply Technology Research Project (RA + 202308).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.