Next Article in Journal
Risk Analysis of Heavy Metals and Groundwater Quality Indices in Residential Areas: A Case Study in the Rajanpur District, Pakistan
Previous Article in Journal
Hybridized Adaptive Neuro-Fuzzy Inference System with Metaheuristic Algorithms for Modeling Monthly Pan Evaporation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Motion Adsorption Characteristics of Particulate Matter in Water Supply Network

1
College of Civil Engineering, Huaqiao University, 668 Jimei Road, Xiamen 361021, China
2
School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200433, China
*
Author to whom correspondence should be addressed.
Water 2022, 14(21), 3550; https://doi.org/10.3390/w14213550
Submission received: 16 September 2022 / Revised: 28 October 2022 / Accepted: 28 October 2022 / Published: 4 November 2022
(This article belongs to the Section Water Quality and Contamination)

Abstract

:
The corrosion of metal pipes within water distribution systems posed great threats towards the quality and safety of drinking water. In this study, the quantity and distribution of suspended particles alongside the pipes was investigated based on field experiments in a water supply plant located in Zhengzhou City of Henan Province. The changes in water quality alongside the pipes were investigated in lab scale through analyzations about the suspensions and sedimentations using effluents from both conventional and deep treatment (ultra-filtration) under different velocity. The morphology of the suspended particles in the effluents was characterized, and water quality indicators, including the turbidity and metal ions (i.e., Pb, Zn, Cu, and Fe) were measured. The results revealed that the correlation between turbidity and particle quantity increased proportionally with the turbidity, while the quantity of the particles decreased with the increasing of their size. The effluent quality from conventional treatment was significantly higher than the deep treatment concerning all the tested indicators, spontaneously with tiny, suspended particles less than 2 µm. The metal leakage of the pipes was related to the velocity and quality of water, as higher flowing velocity and more suspended particles finally resulted in higher metal resolution.

1. Introduction

The safety of water supply pipe network has always been a concern for people, for different water treatment technology in water works that may cause a series of water source switch problems. There have been many scholars have conducted studies on the water quality of pipe networks on it [1,2,3,4]. Such as the water quality of the ultra-filtration membrane process effluent is different from that of the traditional one, which leads to the water quality problem of switching water into the water distribution network. Water quality with different treatment ways is reflected in many aspects; therein particulate matter has attracted the attention in recent years, many scholars at home and abroad have studied the relationship between particulate matter and secondary pollution in water. Aquatic granular will not only cause sensory discomfort to users, but also reduce the safety of drinking water and also destroy the municipal water supply network system service function, bring complex impacts to the water production and city water use. Bacteria, fungi, protozoa and plant spores commonly found in drinking water are infectious forms of parasites that can cause muscle twitches, diarrhea, vomiting and other illnesses [5]. The high content of heavy metal ions in drinking water will cause damage to the human nervous system, as well as intellectual defects, congenital malformations or cancer [5].
It is significance to analyze the characteristics of water quality from the perspective of particulate matter and study it in the pipe network water combined with the secondary pollution, to master the change law of the secondary pollution in the pipe network and reduce the secondary pollution in the water. Due to the large specific surface area, particulate matter in water will form a water and solid micro-interface state. The transport of pollutants between the aqueous phase and particulate matter results in changes of the soluble pollutants in the water. [6,7,8]. There have great similar between the composition of particulate matter and sediment in water supply network, it is generally believed that the effluent material precipitation in the water works [9], the corrosion and rust of pipes, the formation of biofilms on pipe walls [10] will lead to the increase in particulate matter. J.H.G. Vreeburg et al. [11] found in the actual pipe network that the sediment in the pipe is closely related to water discoloration, and sediment have a real impact on particulate matter. G. Liu [12] through the study of nanofiltration, ion exchange, ultra-filtration treatment technology for water distribution network in sediments and microbial growth, found that the sediment content and particle number exists a good correlation about coefficient is 0.89. Three kinds of the treatment process effluent with the number of particles for microbial growth, promoting effect of different. Studies on particulate matter and sediment in the water supply network show that particulate matter and sediment in the water supply network are highly correlated, and their components are also a certain extent similar. It is feasible to reflect the impact of particulate matter on secondary water pollution by studying sediment [13].
The macroscopic expression of the number of particulate matters usually select turbidity as the index. Through particle counting apparatus can intuitively and quickly reflect the number and size distribution of particulate matter in water; by studying the classification characteristics of particulate matter, can better understand the adsorption and aggregation characteristics of particulate matter. Relevant studies have shown that particulate matter can adsorb microorganisms, heavy metals and other pollution substances in water; different particle sizes will affect the adsorption capacity and adsorption method [14,15,16].
The harm caused by particulate matter in the pipe network cannot be ignored. Most studies just do simple adsorption experiments on particulate matter and related pollutants, without exploring what is the essence of particulate matter and what is the law of adsorption under the dynamic conditions in the actual pipe network [17,18,19,20]. This study will combine adopt experimental study and theoretical analysis to explore particulate matter in the water distribution system characteristics: (1) Through sampling analysis to the water distribution system of northern city, respectively investigate effluent of the conventional processing and deep processing particle size distribution and quantity. (2) According to different water transmission and distribution systems, select a representative flow path and measure the characteristics of particulate matter change and particle size distribution along the path contrasted and analyzed the change curve of particulate matter. (3) Using electron microscopy and other instruments to observe the including particle morphology and aggregation of different characteristics of microscopic particulate matter. Particulate matter in the case of time change and the speed change adsorption rule for what kind of metals, respectively, from the angle of the particulate matter analysis was carried out on the water quality characteristics, the network to study the particles combined with secondary pollution in water body, to grasp the network change law of secondary pollution, it is of great significance of reduce the secondary pollution in water network.

2. Materials and Methods

2.1. Experimental Contents

Two water plants in Zhengzhou City of Henan Province supply water, which are conventional treatment and advanced treatment respectively. The study started from 14 November 2019, to 30 November 2021, according to different water transmission and distribution systems. Select the representative water flow path, several sampling points were selected on it. Measure and analyze the characteristics of particulate matter number and particle size distribution change along the water flow path. In addition, study the adsorption and release of pollutants by particulate matter in ductile iron pipes through a small test device in the laboratory, the raw water was obtained from the user end. Add 0.1 g of sediment from the ductile iron pipe to 1 L ultra-filtration water, and then stirred to make the particles just in suspension state. In this experiment, the sediment in the ultra-filtration water pipeline is re-suspended when the hydraulic condition changes sharply, the adsorption and release of dissolved pollutants by the re-suspended particles in the water phase are simulated. After that, clean the pipe network and change the ultra-filtration water into the conventional water before the experiment. Icp-Ms (Agilent 7500cx, Santa Clara, CA, USA) was used for detecting lead, copper, zinc, total iron, etc. [21,22]. SEM (ZEISS Sigma 500 SEM, Cambridge, UK) Characterization: select different concentrations aqueous as the test objects. By bench top laser particle analyzer (IBR bench top particle counter, USA) detect the number of particles in eight particle size channels in water. The particle detection set values were 2~3 µm, 3~5 µm, 5~7 µm, 7~10 µm, 10~15 µm, 15~20 µm, 20~25 µm and greater than 25 µm. Use portable turbidity meter detect turbidity, and by scanning electron microscopy detect the particles of pretreat water samples.

2.2. Laboratory Velocity and Particles Adsorb Metal Ions Experiment

In this experiment, experimental water uses ultra-filtration water and tap water were. Experimental process: water tank−pump−flow meter−experimental pipe section−outlet. The schematic diagram of the experimental setup is shown in Figure 1. By controlling the opening degree of the valve, control the flow rate.
During the test, in addition to the valve on the outlet pipe, the rest of the valves are in the open state, the raw water through the pump pressure, out of the pipe and into the return tank, so back and forth. The experimental device changes the hydraulic conditions in each experimental pipe section in different states (control of flow rate) by adjusting the valve opening degree. It runs 24 h a day, two days a cycle, and change 180 L water in each cycle. During the flow rate test, increase the flow rate from 0.3 m/s to 1.3 m/s, run each flow rate section for 2 h, and take water samples regularly.
Cut off waste ductile iron pipe, take the sediment from it and put the sediment into the Petri dish to dry, weigh 0.2 g for later use, 1 L of ultra-filtration water and conventional treatment water were added to two plastic beakers, using a magnetic stirrer to keep the particles in suspension state. 0.1 g sediment was added to 1 L ultrafiltration water and conventional treatment water, respectively. At 0 (water sample without adding sediment), 30 s, 1 min, 2 min, 5 min, 10 min, 20 min, 40 min, 1 h, 2 h, 3 h, 4 h, 5 h, 19 h, 28 h, 42 h, takes 15 mL water samples, and filtered by 0.22 µm pore size membrane filter. The filtered water sample was acidified by adding 100 µL of high-grade pure nitric acid, and then stored in the refrigerator at 4℃ to be tested.

3. Results

3.1. Correlation between Particulate Matter and Turbidity

For the main pipes of the water distribution system of urban water works in northern China, the number of particulate matters in water and the variation of turbidity value in the actual pipe network water quality monitoring are shown in Figure 2.
In Figure 2, the correlation between the number of particles and turbidity is 0.845. Along the flow direction, with the increase in the number of particles, the corresponding turbidity value also gradually increases, and there is a good linear relationship between the number of particles and turbidity of water samples. The percentage of particle size distribution between 2~10 µm in water is more than 90%, above 20 µm is <10 pcs/mL. In the process of conventional water treatment, most of the large particulate matter is removed, the number of microparticles in the factory water accounts for a large percentage and plays a major role in the water distribution network.
According to different water transmission and distribution systems, the urban pipe network layout selects two water flow paths and measure the characteristics of particulate matter number and particle size distribution change along it. Through laboratory tests comparative analysis, the water samples, respectively detect and compare total number of particles and turbidity of effluent from the pipe network under the two treatment processes, as shown in Figure 3. Test each monitoring point water sample for 8 times, at the summary of field experimental data, the average value of the last six groups was taken as the number of particulate matters at the monitoring point when the data of remove the first test. Use two portable turbidity testers of the same model to obtain the turbidity value of the water and take the average value of the two times as the turbidity value of the monitoring point when the difference was less than the allowable deviation.
It can be seen from Figure 3 that along the direction of water flow, in addition to local mutation phenomenon due to the properties of the pipe properties, the number of particles in the conventional treatment process gradually increases, and in the advanced treatment process slightly increases compared with that in the factory water. The increase in turbidity value in water is caused by the turbulent flow of pipe, collision in the process of water flow scouring the pipe wall, the loose material of pipe wall falling off into the water environment due to the hydraulic erosion. The decrease in turbidity value is due to the pore structure of the growth ring, which makes the impurity particles in the water adhere to the growth ring on the pipe wall and reduces the impurity particles in the water [23]. Along the direction of water flow, the turbidity of conventional treatment process has an upward trend, while the turbidity of advanced treatment process fluctuates within a certain range.

3.2. Analysis of Microscopic Characteristics of Particulate Matter in Water Supply Network

SEM was used to observe the characteristics of filtered and dried particles, the particle size range: 1~3 µm, 3~5 µm, 5~10 µm, 10~25 µm, >25 µm. Measurement of particle morphology and composition in all size range and determine each element molar proportion. The morphological characteristics of single particles in the pipe network water (SEM images) are shown in Figure 4 below.
It can be seen from the SEM images in Figure 4, that the particle size > 3 µm, the particles began to become irregular. In the range of 3~5 µm, many particles show flocculent shape, there were very few flocculent particles when its size >5 µm. The reason is that there are few substances with flocculant properties in the pipe network water (such as aluminum salt and iron salt), which can only adsorb particles with smaller particle size in the water to form particles with a particle size of 3~5 µm through the “adsorption, bridging and net capture” action, but cannot adsorb particles with a larger particle size > 5 µm. And the hydraulic conditions in the pipe network change rapidly, resulting in the formation of flocculent particles with a particle size > 5 µm broken by the impact of water flow, form flocculating particles with a small size range. It can be seen that there are many particles with smaller sizes adsorbed on the particles size who >5 µm. Among the particles of 10~25 µm is too. Thus, it is intuitively explained that particles of small and medium size in the pipe network can adsorb and aggregate with each other to form particles of larger size, which is easier to produce precipitation.
Since the number of 2~3 µm particles in tap water accounts for the highest proportion, accounting for more than 45% of the total number of >2 µm particles, so we selected 2~3 µm particles as the object to study the chemical composition. Use SEM-EDS to determine the composition, and the molar proportion of each element in each particle (except oxygen element) as shown in Table 1. Detect numbered T-1 to T-8 particles of 2–3 µm.
In Table 1, the main component of particulate matter that accounts for about 75% of the total number of 2~3 µm particles is Ca element, and the molar proportion of Ca element in a single particle is about 40%. Si and Al elements accounts for about 20% of the total number of 2~3 µm particles, and the molar proportions of the two elements are about 25%. Element C was detected in all particles, and its molar proportion was about 4%. Mg element was detected in about 50% of the total particles, and the molar proportion in a single particle was about 3%. In the particulate matter No.2, the molar proportion of F element in the particle was 63%, speculated that the main chemical composition of the particle might be CaF2. Detect Fe, Ti, V, Mo, K, Na, Cl, La, Pd and other elements in individual particles with particle size range of 2~3 µm.

3.3. Adsorption of Particulate Matter and Metal Elements

3.3.1. Adsorption of Ultra-Filtration Effluent Particles and Metal Elements in Advanced Treatment Process

The adsorption and release of Fe, Mg, Cr and Co by the suspended particulate matter formed after adding ultra-filtration water to the sediment in the ductile iron pipe are shown in Figure 5.
As shown in Figure 5, the concentration of dissolved Fe, Mg and Cr in the aqueous phase reaches the peak within 0–2 min after the sediment is added to the ultra-filtration water. At 3 h, the concentration values reached the peak again. The reason is that the sediment joined within 2 min, suspended sediment formation of suspended particles on the adsorption of Fe, Mg, Cr ions is much higher. Suspended particulate matter in the surface adsorption of Fe, Mg, Cr ion release quickly, resulting in within 2 min, the concentration of Fe, Mg and Cr ions in aqueous phase reached the peak. At the time of 3 h, the sediment contains about 30% organic matter, which can be combined with a large number of heavy metal ions. With the extension of hydraulic stirring time, the four ions of Fe, Mg, Cr and Co bound by organic matter are released into the aqueous phase, resulting in these elements in the aqueous phase at the peak concentration. In water, the adsorption rate of suspended particles for metal ions is much higher than its release rate. Due to the adsorption effect of suspended particles on metal ions in the aqueous phase, the concentration peak in the aqueous phase will be rapidly reduced. After 19 h, the concentration values of Fe, Cr and Co in the aqueous phase are basically stable. For Mg element, its concentration value is still in dynamic change after 28 h, but the range of change is below the initial concentration value.
The adsorption and release of Ca, Mn and Al elements by the formed suspended particles are shown in Figure 6. As the Figure 6, after the sediment is added to the ultra-filtration water, the suspended particles formed gradually release the three elements of Ca, Mn and Al adsorbed on the surface, leading to the gradual increase in the concentration of Ca, Mn and Al in the aqueous phase. The reason may be that there are a lot of Ca, Mn and Al adsorbed on the surface of suspended particulate matter, and many of the main components of suspended particulate matter are Ca, Mn and Al. Many suspended particulate matters gradually dissolve and release those ions under hydraulic agitation, leading to they gradual increase.
The adsorption and release of Cu, Cd and Zn ions by the formed suspended particles are shown in Figure 7. Suspended particulate matter quickly releases Cu and Cd ions and adsorbed on the surface, cause the concentration of them in the aqueous phase rises to the peak value in a short time. After that, is slowly adsorbed by suspended particulate matter, and in the water basically reaches the dynamic equilibrium state after 2 h. For Zn ion, the suspended particles slowly adsorb it in the water, which makes it gradually decrease and approaches dynamic equilibrium after 3 h.
The adsorption and release of Pb, Ti, As and V by the formed suspended particulate matter are shown in Figure 8.
From the Figure 8 that the concentration of lead reaches peak at 1 min and reaches peaks again at 28 h. Between 5 min and 19 h, the concentration is relatively stable and dynamically changes in a small range below the initial concentration value. The adsorption and release of Pb by suspended particulate matter is similar to the above adsorption and release of Fe, Mg, Cr. For Pb ion concentration peak occurs again at 28 h, which is longer than that of Fe, Mg, Cr. Ti element in water was rapidly adsorbed by suspended particles. After 5 min, the concentration of Ti ion in water was close to the dynamic equilibrium. After the sediment was added to the ultra-filtration water, As and V showed a change law of rapid adsorption and then slow release, finally the concentration value was restored to close to the initial concentration value.

3.3.2. Adsorption of Effluent Particles and Metal Elements by Conventional Treatment Process

The adsorption and release of Fe, Co, Cr and Ti by the suspended particulate matter formed after the sediment in ductile iron pipe is added to tap water are shown in Figure 9. The adsorption and release of Fe, Co, Cr, Ti and other ions by suspended particulate matter is similar to the adsorption and release of them by adding the sediment to ultra-filtration water. However, for the case of adding to tap water, the concentration peak can be produced again at 4 h, which is 1 h slower than that of adding to ultra-filtration water. The concentration of Fe in the aqueous phase again peaked at 19 h because of the relatively complex composition of tap water.
The adsorption and release of Al, Ca, Mn and V by the formed suspended particulate matter are shown in Figure 10. As the Figure 11, the suspended particles gradually release elements Al, Ca, Mn and V, leading to the gradual increase in the concentration of Al, Ca, Mn and V in the aqueous phase. The adsorption and release of Al, Ca and Mn are similar to the situation when sediments are added to ultra-filtration water.
The adsorption and release of Mg ion by the formed suspended particulate matter are shown in Figure 11. It can be seen that suspended particulate matter can quickly release the adsorbed Mg ion, the concentration of Mg ion in the aqueous phase increases rapidly, and approaches the dynamic equilibrium state after 30 s.
The adsorption and release of As and Pb ions by the formed suspended particulate matter are shown in Figure 12. Suspended particles quickly adsorbed As ion in the aqueous phase, and then gradually released it. The suspended particles adsorbed Pb ion in the aqueous phase at first, and then the adsorption and release alternately. After 2 h, the concentration of Pb ion in the aqueous phase increased dynamically.
The adsorption and release of Zn, Cu and Cd ions by the formed suspended particles are shown in Figure 13. As can be seen from the figure, suspended particles first quickly release the adsorbed on the surface Zn, Cu and Cd ions, which rapidly increases the concentration in the aqueous phase. After that, the suspended particles gradually adsorbed Zn, Cu and Cd ions in the aqueous phase, then gradually decreased. This situation is similar to the adsorption and release of Zn, Cu and Cd ions after sediments are added to ultra-filtration water.

3.4. Effect of Flow Rate on Metal Adsorption of Water Particles in Conventional Treatment

According to the water supply standard, when the pipe diameter is 25~40 mm, the flow rate in the pipe ≤ 1.2 m/s. Since the diameter of the water supply pipe in this study is 25 mm, and considering the stagnant water flow, the study flow rate is 0.3~1.3 m/s. Firstly, the flow rate test was conducted on the conventionally treated water, each flow rate section was run for 2 h and regularly water sampling. The variation law of particulate matter in the pipeline water of DN25 was shown in Figure 14. After changing the flow rate, the content of metal ions in water generally has a rising trend, but the rising rule of each metal ion is different. The rising rule is as follows: For DN25 pipeline, Fe ion content exceeds the standard when the flow rate reaches 0.60 m/s, Pb exceeds the standard when the flow rate is 0.40 m/s, As exceeds the standard when the flow rate is 0.60 m/s. Although several other metal ions do not exceed the standard in the process of the experiment, but the content has an increasing trend.
Iron ion is one of the main components of the growth rings in water in ductile iron pipes. During the experiment, the metal ions adsorbed in the growth rings in the pipe wall and during the flushing process released, the increase in metal ion content is not only related to hydraulic flushing, collision and friction, but also related to the pipe properties. With the increase in test time, the pump running for a long time cause the temperature rises slightly, other parameters change law: pH and alkalinity have a slow upward trend. The variation of turbidity during the experiment is basically consistent with the variation of particulate matter, and the turbidity value or the number of particulate matters can be used to represent the variation trend of various metal ions in water. This indicates that particulate matter in water is closely related to the phenomenon of secondary pollution, and its value can represent the degree of secondary pollution in water to a certain extent.

4. Conclusions

This study through the pipeline network of water particles and the turbidity measurement combined with laboratory experimental device of test set (tap water, ultra-filtration water two kinds of water), the determination of metal elements, particulate matter and sediment in pipe network for composition analysis, according to the static and dynamic two kinds of different situations particulate matter on the study of adsorption and release of pollutants, explore the relationship between particulate matter and sediment in pipeline water, and then analyze the relationship between particulate matter and secondary pollution. With the increase in turbidity value, the correlation between turbidity value and the number of particles also increased. The number of particles gradually decreased from small particles (2 µm) to large particles (25 µm).
Changing the flow rate, the number of particles, turbidity and the concentration of metal ions in water all showed an upward trend. In conventional treatment water, the corrosion degree of pipe wall and metal ion concentration in water are higher which indicates that the number of particles has a great influence on the deposition and corrosion of the pipe inner wall. With the passage of time, under the condition of hydraulic erosion, it will cause secondary pollution to the pipe network. According to the actual situation, it is considered to adopt various flushing methods to clean the pipe wall, or partially replace the pipe to effectively control the phenomenon of secondary water pollution.
Due to the complex composition of sediment in the pipeline, there are mineral components, organic components, microbial components, etc. The formed suspended particulate matter can combine with metal ions in various ways, such as complexation, direct adsorption of metal ions and simple physical adsorption [24]. Suspended particulate matter in water is greatly affected by hydraulic conditions and water quality changes. Result the adsorption and release of metal elements by suspended particles do not appear similar to the traditional zero-order, first-order and second-order reaction kinetics. Further study the adsorption and release of particulate matter for pollutants in water supply network, explore the kinetic law and have a deeper understanding of the action mechanism of particulate matter for secondary pollutants. In order to control the content of particulate matter in the pipe network and improve the water quality of pipe network, the sources of particulate matter in the pipe network and the factors affecting the content of particulate matter are further studied.

Author Contributions

Data curation, L.W., W.S. and G.W.; Formal analysis, L.W.; Methodology, Z.Z. and C.L.; Writing—original draft preparation, Z.Z., L.W.; writing—review and editing, L.W.; funding acquisition, Z.Z. All authors have read and agreed to the published version of the manuscript.

Funding

Approval No. 51278206 Interaction analysis and dynamic simulation study of particulate matter and secondary pollution in water supply pipe network National Natural Science Foundation of China.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mi, Z.L.; Zhang, X.J.; Wu, H.T.; Chen, C.; Wang, J. Control of release of corrosion products caused by water source switch in drinking water distribution systems. China Water Wastewater 2013, 29, 44–48. [Google Scholar]
  2. Liu, G.; Zhang, Y.; Knibbe, W.-J.; Feng, C.; Liu, W.; Medema, G.; van der Meer, W. Potential impacts of changing supply-water quality on drinking water distribution: A review. Water Res. 2017, 116, 135–148. [Google Scholar] [CrossRef] [PubMed]
  3. Lin, X.; Xu, Q.; Li, Y.; Zhao, B.; Li, L.; Qiang, Z. Modeling iron release from cast iron pipes in an urban water distribution system caused by source water switch. J. Environ. Sci. 2021, 110, 73–83. [Google Scholar] [CrossRef] [PubMed]
  4. Jing, Z.; Lu, Z.; Mao, T.; Cao, W.; Wang, W.; Ke, Y.; Zhao, Z.; Wang, X.; Sun, W. Microbial composition and diversity of drinking water: A full scale spatial-temporal investigation of a city in northern China. Sci. Total Environ. 2021, 776, 145986. [Google Scholar] [CrossRef] [PubMed]
  5. Boxall, J.; Skipworth, P.; Saul, A. Aggressive flushing for discolouration event mitigation in water distribution networks. Water Sci. Technol. Water Supply. 2003, 21, 179–186. [Google Scholar] [CrossRef]
  6. Qu, J.H.; He, H.; Liu, H.J. Typical environmental micro-interfaces and its effect on environmental behaviors of pollutants. Acta Sci. Circumstantiae 2009, 29, 2–10. [Google Scholar]
  7. Tang, H.X. Enviromental Nano-Pollutants(ENP) and their micro-interfacial process on aquatic particles. Acta Sci. Circumstantiae 2003, 23, 146–155. [Google Scholar]
  8. Bright, C.E.; Mager, S.M. A national-scale study of spatial variability in the relationship between turbidity and suspended sediment concentration and sediment properties. River Res. Appl. 2020, 36, 1449–1459. [Google Scholar] [CrossRef]
  9. Zacheus, O.M.; Lehtola, M.J.; Korhonen, L.K.; Martikainen, P.J. Soft deposits, the key site for microbial growth in drinking water distribution networks. Water Res. 2001, 35, 1757–1765. [Google Scholar] [CrossRef]
  10. Prévost, M.; Laurent, P.; Servais, P. Biodegradable Organic Matter in Drinking Water Treatment and Distribution; American Water Works Association: Denver, CO, USA, 2005. [Google Scholar]
  11. Vreeburg, J. Discolouration in Drinking Water Systems: A Particular Approach. Ph.D. Thesis, Civil Engineering and Geosciences, Delft University of Technology, Delft, The Netherlands, 2007. [Google Scholar]
  12. Liu, G.; Lut, M.C.; Verberk, J.Q.J.C.; Van Dijk, J.C. A comparison of additional treatment processes to limit particle accumulation and microbial growth during drinking water distribution. Water Res. 2013, 47, 2719–2728. [Google Scholar] [CrossRef] [PubMed]
  13. Mussared, A.; Fabris, R.; Vreeburg, J.; Jelbart, J.; Drikas, M. The origin and risks associated with loose deposits in a drinking water distribution system. Water Supply 2019, 19, 291–302. [Google Scholar] [CrossRef]
  14. Li, D.P. Research and technological development trends on drinking water safety assurance: I. Pollution sources and control targets. Chin. J. Environ. Eng. 2010, 4, 1921–1925. [Google Scholar]
  15. Vreeburg, J.H.G.; Schippers, D.; Verberk, J.Q.J.C.; van Dijk, J.C. Impact of particles on sediment accumulation in a drinking water distribution system. Water Res. 2008, 42, 4233–4242. [Google Scholar] [CrossRef] [PubMed]
  16. Chen, L.; Li, X.; van der Meer, W.; Medema, G.; Liu, G. Capturing and tracing the spatiotemporal variations of planktonic and particle-associated bacteria in an unchlorinated drinking water distribution system. Water Res. 2022, 219, 118589. [Google Scholar] [CrossRef] [PubMed]
  17. Neilands, K.; Bernats, M.; Rubulis, J. Accumulation and modeling of particles in drinking water pipe fittings. Drink. Water Eng. 2012, 5, 47–57. [Google Scholar] [CrossRef] [Green Version]
  18. Prest, E.I.; Schaap, P.G.; Besmer, M.D.; Hammes, F. Dynamic Hydraulics in a Drinking Water Distribution System Influence Supended Particles and Turbidity, But Not Microbiology. Water 2021, 13, 109. [Google Scholar] [CrossRef]
  19. Braga, A.S.; Filion, Y. The interplay of suspended sediment concentration, particle size and fluid velocity on the rapid deposition of suspended iron oxide particles in PVC drinking water pipes. Water Res. 2022, 15, 100143. [Google Scholar] [CrossRef] [PubMed]
  20. Zurauskiene, R.; Valentukeviciene, M.; Satkunas, J. The main microelements and phosphorus content of sediments formed in a drinking water supply system. Est. J. Earth Sci. 2016, 65, 248–257. [Google Scholar]
  21. Hao, T. Study on the Release of Iron Ion in Water Supply Pipe Network. Ph.D. Thesis, Department of Environmental Engineering, Tianjin University, Tianjin, China, 2007. [Google Scholar]
  22. Water and Wastewater Monitoring and Analysis Methods, 4th ed.; China Environmental Science Press: Beijing, China, 2002.
  23. Chen, J.F. Study of Water Quality Prediction Model in Urban Water Distribution Systems. Ph.D. Thesis, Tianjin University, Tianjin, China, 2009. [Google Scholar]
  24. Tang, H.X.; Qian, Y.; Wen, X.H. Characteristics and Control Techniques of Particulate Matter and Refractory Organic Matter in Water Bodies: Particulate Matter in Water Bodies. China Environmental Science Press: Beijing, China, 2000. [Google Scholar]
Figure 1. Diagram of test device about dynamic simulation of particle adsorption at different flow rates.
Figure 1. Diagram of test device about dynamic simulation of particle adsorption at different flow rates.
Water 14 03550 g001
Figure 2. Changes in the number of particulate matter and turbidity for along the pipeline: particle size 2~10 µm (a); Particle size >10 µm (b).
Figure 2. Changes in the number of particulate matter and turbidity for along the pipeline: particle size 2~10 µm (a); Particle size >10 µm (b).
Water 14 03550 g002
Figure 3. Variation of particulate matter and turbidity in conventional and deep treatment water.
Figure 3. Variation of particulate matter and turbidity in conventional and deep treatment water.
Water 14 03550 g003
Figure 4. SEM images of single particulate matter in different particle size ranges: 1~3 µm SEM image (ac); 4~5 µm SEM image (df); 10~25 µm SEM image (gh); >25 µm SEM image (i).
Figure 4. SEM images of single particulate matter in different particle size ranges: 1~3 µm SEM image (ac); 4~5 µm SEM image (df); 10~25 µm SEM image (gh); >25 µm SEM image (i).
Water 14 03550 g004
Figure 5. In UF water the effects of suspended particulate matter in different time adsorption and release of Fe and Mg (a); Cr and Co (b).
Figure 5. In UF water the effects of suspended particulate matter in different time adsorption and release of Fe and Mg (a); Cr and Co (b).
Water 14 03550 g005
Figure 6. In UF water the effects of suspended particulate matter at different time adsorption and release of Ca, Mn and Al.
Figure 6. In UF water the effects of suspended particulate matter at different time adsorption and release of Ca, Mn and Al.
Water 14 03550 g006
Figure 7. In UF water the effects of suspended particulate matter at different time adsorption and release of Cu and Cd (a); Zn (b).
Figure 7. In UF water the effects of suspended particulate matter at different time adsorption and release of Cu and Cd (a); Zn (b).
Water 14 03550 g007
Figure 8. In UF water the effects of suspended particulate matter at different time adsorption and release of Pd (a); Ti (b) and V (c).
Figure 8. In UF water the effects of suspended particulate matter at different time adsorption and release of Pd (a); Ti (b) and V (c).
Water 14 03550 g008
Figure 9. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Fe and Cr (a); Ti and Co (b).
Figure 9. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Fe and Cr (a); Ti and Co (b).
Water 14 03550 g009
Figure 10. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Al, Mn and Ca (a); V (b).
Figure 10. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Al, Mn and Ca (a); V (b).
Water 14 03550 g010
Figure 11. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Mg.
Figure 11. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Mg.
Water 14 03550 g011
Figure 12. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of As and Pb.
Figure 12. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of As and Pb.
Water 14 03550 g012
Figure 13. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Cu and Zn (a); Cd (b).
Figure 13. In conventional treatment water the effects of suspended particulate matter at different time adsorption and release of Cu and Zn (a); Cd (b).
Water 14 03550 g013
Figure 14. Effects of suspended particulate matter at different velocity adsorption and release in DN25 tube of Pb and Fe (a); Al and As (b); Mn and Ca (c), Mg and Cr (d).
Figure 14. Effects of suspended particulate matter at different velocity adsorption and release in DN25 tube of Pb and Fe (a); Al and As (b); Mn and Ca (c), Mg and Cr (d).
Water 14 03550 g014
Table 1. The molar proportions of each element in each particle size range of 2~3 µm measured.
Table 1. The molar proportions of each element in each particle size range of 2~3 µm measured.
The Molar Proportion of Each Element in a 2-3 Micron Particle (%)
Element
Sample
T-1T-2T-3T-4T-5T-6T-7T-8
Ca39.1224.3529.8331.02 8.7422.5733.24
Si4.36 6.3113.633.3122.8617.225.28
Al 28.2919.0513.37
Mg 3.053.56 2.261.964.46
Fe 2.27
K 1.636 1.17
Na 17.44
C5.312.223.382.864.694.265.656.96
Cl 1.852.6914.68 1.494.13
F 63.85
Mo 15.99
La 0.68
Pd 0.24 0.4
Ti 2
V 0.54
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Zhao, Z.; Wang, L.; Shi, W.; Li, C.; Wei, G. Motion Adsorption Characteristics of Particulate Matter in Water Supply Network. Water 2022, 14, 3550. https://doi.org/10.3390/w14213550

AMA Style

Zhao Z, Wang L, Shi W, Li C, Wei G. Motion Adsorption Characteristics of Particulate Matter in Water Supply Network. Water. 2022; 14(21):3550. https://doi.org/10.3390/w14213550

Chicago/Turabian Style

Zhao, Zhiling, Lu Wang, Wenhang Shi, Cong Li, and Guozijian Wei. 2022. "Motion Adsorption Characteristics of Particulate Matter in Water Supply Network" Water 14, no. 21: 3550. https://doi.org/10.3390/w14213550

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

Article Metrics

Back to TopTop