Prediction of reverse osmosis fouling using the feed fouling monitor and salt tracer response technique

Journal of Membrane Science 475 (2015) 433–444

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Prediction of reverse osmosis fouling using the feed fouling monitor and salt tracer response technique A.H. Taheri a,b, L.N. Sim a,b, T.H. Chong a,b,n, W.B. Krantz a,c, A.G. Fane a,b,n a Singapore Membrane Technology Centre, Nanyang Environment & Water Research Institute, Nanyang Technological University, Singapore 639798, Singapore b School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore c Chemical and Biological Engineering, University of Colorado, Boulder, CO 80303, United States

art ic l e i nf o

a b s t r a c t

Article history: Received 27 July 2014 Received in revised form 8 October 2014 Accepted 18 October 2014 Available online 28 October 2014

In this study an on-line feed fouling monitor (FFM) combined with a salt-tracer-response technique (STRT) was used to predict reverse osmosis (RO) fouling under constant flux filtration. The FFM was used to capture foulant loads using a small ‘collection’ ultrafiltration (UF) membrane at the same crossflow hydrodynamics as in the RO experiments. A UF membrane was used in the FFM to decrease the monitoring time and improve the accuracy because it is more responsive to the fouling resistance than an RO membrane. Since the deposits captured by the FFM are potential RO foulants, the resulting information can be used to predict the transmembrane pressure (TMP) rise for the RO membrane. The STRT was used to measure the development of concentration polarization that is important in estimating the cake-enhanced osmotic pressure (CEOP) contribution. A model was developed that includes both the cake resistance and the CEOP effect due to cake formation and was used to predict RO fouling trends. Model foulants were humic acid and colloidal silica. The major focus was on organic fouling by humic acid (20 mg/l) in 2000 mg/l sodium chloride (NaCl) as the ionic background for the RO and FFM fouling experiments. The RO and FFM fouling experiments were conducted at different constant fluxes using the same feed solutions and at the same crossflow velocity (0.1 m/s). The results indicated that higher fluxes cause an increased fouling rate for both RO and the FFM for both types of solute. The CEOP effect, measured by the salt-tracer-response in the RO experiments, was also strongly enhanced by the flux. The model was validated by plotting the predicted RO transmembrane pressure (TMP) as a function of time for different fluxes based on the resistivity from the FFM and the CP obtained from the STRT. For both organic foulants and colloidal silica the results show that the combination of the FFM and salttracer-response STRT is a promising method to provide a good estimate of the RO fouling trends. It also underscores the contribution of CEOP to the increase in TMP during RO fouling of saline feeds. & 2014 Elsevier B.V. All rights reserved.

Keywords: Feed fouling monitor Salt-tracer-response Concentration-enhanced osmotic pressure (CEOP) Reverse osmosis Fouling prediction

1. Introduction Fouling remains the biggest challenge faced by membrane separations. For a salt-rejecting membrane such as used in reverse osmosis (RO) and nanofiltration (NF), the fouling mechanism is often complicated due to the interplay between the salt concentration polarization layer and the growing foulant layer on the membrane surface. Several studies [1–5] that investigated the colloidal fouling of RO and NF membranes have established that a single fouling mechanism such as ‘cake formation’ cannot fully explain the

n Corresponding authors at: School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore. Tel.: þ 65 6790 5272; fax: þ65 6791 0676. E-mail addresses: [email protected] (T.H. Chong), [email protected] (A.G. Fane).

http://dx.doi.org/10.1016/j.memsci.2014.10.043 0376-7388/& 2014 Elsevier B.V. All rights reserved.

observed flux decline or transmembrane pressure (TMP) increase during RO/NF filtration. Consequently a model combining cake filtration theory and the cake-enhanced osmotic pressure (CEOP) effect has been proposed by Hoek et al. [3]. The CEOP effect occurs when the build-up of the cake layer on the membrane surface hinders the back-diffusion of salt ions to the bulk solution that leads to an elevated salt concentration near the membrane surface. As a result, the TMP can be significantly increased. Conventional water quality monitoring or RO fouling predictor indices such as the modified fouling index (MFI) account for the ‘potential’ fouling resistance that would build up on the RO membrane surface but do not take into account the effect of CEOP. Hence, it is important to characterize the build-up of CP during filtration in RO to fully understand the fouling mechanism. Sim et al. [4] extended the concept of their proposed fouling index, the crossflow sampler modified fouling index (CFS-MFIUF), to

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incorporate the CEOP effect in a fouling prediction model. Their preliminary results indicated that a model combining fouling resistance determined via the CFS-MFIUF and CEOP effects provided a good estimate of the overall RO fouling profile. However, in order to quantify the CEOP effect, ex-situ measurement of the foulant cake mass and estimation of the cake porosity were required. Various in situ monitoring techniques for characterizing CP have been developed that include light-deflection techniques [6], radioisotope labelling [7,8], electron-diode array microscopy (EDAM) [7,8] and NMR micro-imaging [9,10]. However, these techniques are not practical or economic due to requirements of special design for the membrane module or expensive monitoring facilities [11]. Therefore, a simple method is required to determine the CP for membrane systems. In a recent paper [12] the authors have demonstrated the capability of combining the fouling resistance and CEOP using two fouling monitors to predict the TMP rise in RO due to colloidal fouling. The two fouling monitors were the feed fouling monitor (FFM) and Ultrasonic Time Domain Reflectometry (UTDR). The FFM provides an estimate of the fouling resistance as well as the porosity of the fouling cake, whereas UTDR measures the growth of the foulant layer thickness for CEOP estimation. The FFM employs a typical crossflow filtration cell equipped with a UF membrane. When operated as the same ‘net flux’ conditions (i.e., actual imposed flux minus the critical flux) as the RO crossflow experiment, the foulant that attaches onto the UF surface simulates the ‘potential’ foulant load on the RO surface. With the aid of dead-end filtration, the specific cake resistance due to the elevated salt concentration in the foulant cake can be corrected. The UTDR technique on the other hand is based on reflection of an acoustic waveform from interfaces such as the membrane and fouling layer in the cell. In this method the UTDR was coupled to a RO membrane cell to monitor the rate of cake thickness increase that is required information to estimate the contribution of CEOP. The results show that the model provides a good estimate of the RO fouling profile over a range of applied fluxes. Thus far, the model has been applied only to colloidal fouling and has not yet been tested on organic fouling in RO filtration. Therefore, the aim of this study was to investigate the applicability of the model to predict organic fouling, as well as colloidal silica fouling during RO filtration. However, due to the small difference between the acoustic properties of the organic cake layer/membrane surface and the organic cake layer/feed solution interface, the detection of an organic cake layer (in this case humic acid) on a membrane surface is a challenge for UTDR [13]. An alternative method for estimating CEOP was developed by Chong et al. [1,14] who used a salt tracer response technique (STRT) to estimate the CEOP instead of employing a mathematical model that required knowledge of the foulant layer thickness. We apply the STRT method in this paper. Tracer tests have been commonly applied to study the residence– time distribution (RTD) of reactors [15] and have also been successfully used to detect fouling in spiral wound RO modules [16]. These techniques provide an analysis of the RTD on the feed and permeate sides of the membrane and characterize fouling and membrane aging. The selected tracer should not react with the foulants or cake layer and should provide a nearly immediate response when injected into the system. In order to determine the salt CP by the STRT method, the instantaneous flux, TMP and salt concentrations on both the feed and permeate sides need to be monitored. When a pulse of salt is injected into a clean RO system, the immediate response of the TMP (for constant flux filtration) or flux (for constant pressure filtration) can provide the required information to estimate the CP of the salt. Furthermore, the CP of a fouled system can be measured with the same procedure as described. Hence, the CEOP

can also be determined. Chong et al. [1,14] used sodium chloride as the pulse tracer to inject into the RO system. Their experiments were conducted under constant flux filtration using mono-sized colloidal silica (20 nm) as the foulant. Their study was able to quantify the CEOP effect that indicated CEOP is more severe at low crossflow velocities and at high fluxes because of the thicker cake layer. Hence, in this study two techniques, FFM coupled with the STRT, were used to provide the information required to predict the TMP rise in RO due to organic fouling and colloidal silica fouling. The online feed fouling monitor (FFM), which is an adaptation of the integrity sensor (IS) concept [17,18], was used to monitor the water quality and fouling resistance while the salt-tracer-response STRT was used to measure the concentration polarization and the CEOP contribution during RO fouling experiments under constant flux. The FFM information was combined with STRT to predict the RO fouling trends.

2. Overview of protocol for model predictions 2.1. TMP performance of crossflow RO filtration in the presence of fouling According to the generally accepted model for RO fouling prediction [12], the TMP rise at constant flux is based on both the hydraulic cake resistance and the CEOP effect TMPr ¼ J r μr Rmr þ J r ðJ r  J crit:r Þμr I r θ t þ CPΔΠ m

ð1Þ

where the subscript r refers to an RO membrane, J r is the permeate flux, J crit:r is the critical flux of the foulant for RO, μr is the fluid viscosity, I r refers to resistivity of the foulant, θ is the fractional deposition factor, t denotes the instantaneous time, CP is the concentration polarization modulus and ΔΠ m is the osmotic pressure difference between the feed and permeate sides of the membrane. Eq. (1) involves three contributions to the TMP during RO filtration. The first term is associated with the pressure drop due to the membrane itself ðΔP membrane Þ. The second term is associated with the pressure drop caused by the fouling resistance ðΔP cake Þ. This term is determined using the FFM and is discussed in Section 2.2. The second term involves the foulant resistivity, which is corrected for the effect of salinity using dead-end filtration experiments that are not affected by crossflow velocity and are discussed in Section 2.2.1. It should be noted that the FFM experiments using UF membranes were conducted at a similar net flux to the RO tests; that is, J Net ¼ J J Crit . Therefore, it was necessary to measure the critical fluxes for both the UF and RO conditions to ensure the experiments were run at comparable net fluxes. The critical flux for these experiments was determined by the step-by-step method [19]. The third term is the CEOP contribution to the pressure drop ðΔP CEOP Þ and is determined by the STRT experiments that are discussed in Section 2.3. As described in our previous paper [12], the resistivity of a fouled RO membrane, I r , can be related to the resistivity obtained from the FFM, I FFM , using the correction for the cake ratio, β I r ¼ βI FFM

ð2Þ

The cake ratio accounts for the difference between the deposited cake on the FFM and the cake formed during RO filtration. In this study β has been assumed to be equal to 1 based on our earlier work [12]. Due to incomplete rejection of humic acid by the UF membrane, the resistivity obtained from the FFM is defined as follows [20,21]: I FFM ¼ αFFM C b RejHA

ð3Þ

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435

where α is the specific cake resistance and C b is the foulant concentration in the bulk. RejHA refers to the rejection of humic acid by the UF membrane. In contrast to dead-end filtration, not all the particles convected to the membrane will be retained in the foulant layer due to shear caused by the crossflow. The deposition factor θ in Eq. (1) can vary from 1.0 for dead-end filtration (complete deposition) to approximately 0.1 for crossflow filtration (partial deposition) [14]. However, it is difficult to estimate the value of the deposition factor a priori. In this study the deposition factor is assumed to be an empirical factor that is determined from the best-fit of the fouling trends.

determine the CP and estimate the contribution of the CEOP effect. Details of the STRT method can be found in the study by Chong et al. [1] and are summarized here. A schematic of the STRT test procedure is shown in Fig. 1. This technique is based on the ability of RO membranes to reject salts such as sodium chloride. As seen in Fig. 1, the conductivity and osmotic pressure of the RO system are increased during the injection of NaCl into the system. As a result, in order to maintain a constant flux filtration, the TMP of the system has to be increased. Before the injection of sodium chloride into the system, the flux can be determined from the following equation:

2.2. FFM experiments to determine the fouling contribution to the TMP

J¼

Since most RO systems are conducted at constant flux, the FFM using a UF membrane was designed to capture the foulants under constant flux and crossflow to simulate the hydrodynamic conditions in the RO tests. The foulants captured by the FFM are potential RO foulants. Hence it is assumed that the specific cake resistance obtained from this simulator can be used to predict the TMP rise for an RO membrane. A UF membrane was used in the FFM since it is more sensitive to particle deposition than an RO membrane and provides rapid assessment of the fouling potential. The information obtained from the FFM can be used to estimate the hydraulic resistance of the cake layer in RO. Note that the CEOP can be neglected in the FFM experiments since the UF membrane does not reject NaCl. Hence, for the FFM, Eq. (1) can be written as follows: TMP ¼ JμRm þ JðJ J crit;UF ÞμI FFM θt

ð4Þ

2.2.1. Effect of salt concentration on the specific cake resistance The salt concentration can change the charge on the particles and influence the specific cake resistance and cake porosity. Therefore, due to the different nature of the RO and UF membranes, it is necessary to investigate the effect of salinity on the cake-layer properties such as the specific cake resistance. In order to isolate the effect of the salinity on the double layer, experiments were conducted using a dead-end setup to eliminate the complications introduced by crossflow. The effect of the salt concentration on the specific cake resistance was determined by monitoring the TMP as a function of time during constant flux filtration. The fouling index for the dead-end and constant flux experiments can also be determined using the simplified form of Eq. (4), where θ ¼ 1:0 TMP ¼ J 2 μIt þ JμRm

ð6Þ

where Rm is the membrane resistance and Rf is the fouling resistance, μ is the viscosity of the permeate, ΔΠ b is the difference in the osmotic pressure between the permeate and feed solutions and CP is the concentration polarization. When no fouling is present the CP is linked to the flux and boundary layer mass transfer in the membrane system. However, due to particle deposition and the development of a cake layer, the salt concentration near the membrane wall C w is increased due to the hindered backtransport; therefore   C w C p J CP ¼ ð7Þ ¼ exp kef f Cb  Cp where kef f is the effective mass-transfer coefficient. The osmotic pressure of the RO system is increased when a pulse of NaCl is introduced into the system. Hence, the TMP of the system increases in order to maintain constant flux filtration. Therefore J¼

Eq. (4) indicates that the fouling index I FFM can be determined from the slope of the TMP versus time plot for constant flux filtration using the FFM.

ðTMP  CPΔΠ b Þ
 μ Rm þ Rf

ðTMPs  CPΔΠ bs Þ
 μ Rm þ Rf

ð8Þ

where ΔΠ bs is the difference between the osmotic pressure of the feed and the permeate stream. By combining Eqs. (6) and (8), CP can be related to the TMP of the system and the ionic conductivities of the feed and permeate before and during the NaCl pulse. Hence, CP can be determined from the following equation: CP ¼

TMPs  TMP ΔΠ bs  ΔΠ b

ð9Þ

where ΔΠ b is the difference between the osmotic pressure of the feed and the permeate stream before the NaCl pulse. As can be seen from Eq. (9), by monitoring the TMP and conductivity of the system before and during salt injection, CP can be estimated [1].

ð5Þ

The specific cake resistance then can be calculated by combining Eqs. (5) and (3) and plotting the TMP as a function of time for the dead-end experiments under constant flux filtration. 2.3. STRT for Determining the CEOP A series of RO fouling experiments was conducted to assess the ability of the FFM to predict RO fouling and compare the predicted profiles with actual RO performance. The RO experiments were run using the same feed as in the FFM experiments over a range of different constant fluxes to determine the increase in TMP as a function of time, whereas the STRT tests were conducted to

Fig. 1. Schematic of the STRT to determine the concentration polarization and CEOP in an RO membrane system operated at constant flux: (a) Feed concentration showing increase to Conds during salt injection; (b) Permeate concentration showing increase to Conds during salt injection; (c) TMP versus time showing increase to TMPs owing to concentration polarization during salt injection.

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The salt concentration in the feed solution and the permeate stream can be determined from the conductivity (k) as follows [22]: log ðkÞ ¼ 0:9856 log ðCÞ þ 0:3444

ð10Þ

where C is the NaCl concentration in mg/l. The osmotic pressure of the NaCl can be determined from the following: ð11Þ

Π ¼ 2CRg Tϕ J (8:314K mol )

where Rg is the universal gas constant and ϕ is the molar osmotic coefficient determined from the following equation [23]: log ð1  ϕÞ ¼  1:09373  0:08101C  0:17492 log C 2 0:01785C 2 ð12Þ Eq. (12) is valid for NaCl concentrations ranging from 5.85 mg/l to 17,880 mg/l. 2.4. RO fouling predictions Information obtained from the FFM, STRT experiments and the dead-end tests was used to predict the RO performance using the fouling model adapted for CEOP [see Eq. (1)]. The predicted TMP profiles were compared with those for the actual RO performance.

3. Materials and methods 3.1. Membranes and chemicals UF regenerated cellulose (RC, 30 kDa) membranes (Millipore— PLTK15005) with a nominal water permeability of 300 l/m2 h/bar were used for the FFM experiments to capture the model foulants. RO membranes (DOW FilmTec BW30) with a nominal water permeability of 2.5 l/m2 h/bar were used in flat sheet form. The UF membrane provides a more sensitive and rapid response to the fouling than does an RO membrane. Hence, the UF membrane was used in the FFM at a net fouling rate (i.e., actual flux minus the critical flux) equal to that of the RO system. In order to run the FFM and RO at the same net flux, it is important to determine the critical fluxes for both UF and RO for the same feed and hydrodynamic conditions. All filtration experiments were initiated with Milli-Q water to determine the membrane resistance Rm and to stabilize the membrane. Humic acid (Sigma-Aldrich) was used as the model organic foulant. A number of experiments were also performed with colloidal silica (Sigma-Aldrich, Ludox TMA) as an inorganic foulant. The desired concentration of NaCl (Sigma-Aldrich) was used in the experiments to prepare the background ionic solution and for the salt tracer tests. All feed solutions were prepared with Milli-Q water. The humic acid concentration was measured by a TOC analyzer (Shimadzu TOC-V CSH) to determine the rejection of the organic foulant by the UF membrane.

mix the solution in the feed tank during filtration. A back-pressure regulator (Swagelok, Model KBP) was employed to control the system pressure and flow during filtration. The feed and permeate pressures were monitored using high precision pressure transducers (Ashcroft digital industrial gauge—30 2174 SD 02L). Two flow-meters (Cole Palmer-PMR1-010640 and PMR1-010810) were used to monitor the feed flow rate. The conductivity and temperature of the feed and permeate were monitored using conductivity meters (Eutech Alpha Cond500). The permeate stream and concentrate were recycled back to the feed tank during the filtration. In the case of the STRT experiments, a metering pump (Pulsafeeder, model Pulsatron) was used to inject NaCl solution into the high pressure feed line of the RO cell. In order to keep the NaCl concentration constant in the feed tank, the permeate stream and concentrate were drained from the system during the tracer tests while the feed tank was topped up with a fresh feed solution to maintain a constant volume. It should be noted that highly concentrated NaCl (200 g/L) solution was used as a tracer during STRT experiments. Flux, pressures, crossflow rate and the conductivities of the feed and permeate were monitored using a data-acquisition system (National Instruments, Model PCI 6014). The RO fouling experiments were initiated by filtering Milli-Q water for approximately 24 h at a pressure of approximately 20 bar to compact the membrane and stabilize the system. The system was then equilibrated at the desired ionic background (2000 mg/l NaCl), crossflow velocity (0.1 m/s) and flux for approximately 3 h. Before introducing the model foulant into the system, salt-tracer tests were conducted on the clean membrane; the value obtained for the latter was used as the reference point for the fouling tests. During the salttracer tests, a highly concentrated NaCl (200 g/L) solution was introduced into the feed solution (before entering the RO cell) using the injection pump at a rate of 1 mL/min to increase the concentration of salt to 500–1000 mg/l. The concentration of injected salt and duration of the pulse were chosen to obtain stable detection [1]. When the salt pulse was stopped, the TMP and conductivity of both the feed and permeate returned to their initial values while the system was operated for an additional 2 h to stabilize. Afterwards the model foulant was introduced into the feed tank and the fouling experiments were started. The same procedure was used for the salt-tracer tests for estimating the CP during the fouling experiments. Based on Eq. (9), the TMP and feed/permeate conductivity values were used to estimate the CP during filtration. 3.2.2. Feed fouling monitor (FFM) to characterize the fouling The low pressure crossflow filtration setup was used in this study to conduct the critical flux measurements for the UF membranes and FFM experiments. The custom-made acrylic crossflow membrane cell

3.2. Experimental apparatus 3.2.1. RO setup and STRT implementation The schematic of the RO setup is shown in Fig. 2. The custommade stainless steel RO cell that was used for this study had a flow channel that was 320 mm long, 60 mm wide, and 0.8 mm high with an effective membrane area of 0.0186 m2. A high pressure pump (Hydra-Cell Pump) was used to transfer the feed solution from a 20 l tank to the RO unit. The permeate flow was controlled by a mass flow controller (Brooks Instrument, Model 5882). The feed water temperature was kept constant at 2571 1C using a chiller (Polyscience, Model 9112). An overhead stirrer (Panasonics, Model MX8G5B) was used to

Fig. 2. Schematic of the reverse osmosis setup for fouling studies.

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had an effective membrane area of 0.0012 m2. The channel of the cell was 60 mm long, 20 mm wide and 7 mm high. More details of the low pressure crossflow filtration setup are described in our previous study [12].

4.1. RO experiments RO fouling experiments were conducted at different fluxes using humic acid (20 mg/l) as the organic model foulant. In all the experiments 2000 mg/l NaCl was added as an ionic background. The TMP of the system as well as the feed and permeate conductivity was measured during filtration. This information was used to estimate the concentration polarization, which is discussed in Section 4.1.1. The TMP as a function of time for the fouling tests using humic acid for a range of constant fluxes is plotted in Fig. 4. The TMP and fouling rates (dTMP/dt) increased with increasing flux for humic acid. As discussed earlier the TMP rise for RO can be due to both the hydraulic cake resistance and CEOP. However, the CEOP is often the major factor for salt-rejecting RO membranes [5,14,24,25]. For RO prediction purposes the critical flux was also measured using the step-by-step method and was found to be J cr U RO ¼ 16 7 2 LMH (liters per square meter per hour) for humic acid. 4.1.1. Determination of the concentration polarization The STRT was used to monitor the development of concentration polarization during RO filtration to estimate the CEOP. 4.1.1.1. CP in the absence of fouling. Fig. 5 shows the TMP, feed/ permeate conductivity and calculated CP during one of the STRT

Dead-end tests Effect of salinity Section 4.2.1

Determination of α(t) Section 4.2.1.2

STRT Section 4.1.1

Estimation of CP(t)

Estimation of CEOP(t)

3.3. Experiment procedure

4. Results and discussion

FFM Experiments Measure α Section 4.2

RO Experiments Section 4.1

3.2.3. Dead-end setup to determine the specific cake resistance Since a UF membrane does not reject salt, the effect of salinity on the cake layer in the UF and RO systems will differ. The dead-end UF setup was used to investigate the effect of the ionic environment on the specific cake resistance of the foulant. A stainless steel feed reservoir (2 l capacity) was connected to a custom-made dead-end filtration cell (maximum capacity of 120 ml) with an active membrane area of 0.0012 m2. A nitrogen gas cylinder was used to supply the required pressure filtration. A schematic of the dead-end filtration setup is described in our previous study [12]. Measured TMP vs. Predicted TMP

Estimation of cake resistance Rf(t)

RO TMP prediction

Fig. 3. Experimental procedure to predict RO performance from FFM measurements, dead-end tests, and the STRT.

25 42.1 LMH

20 36.1 LMH

TMP (kPa)

The RO experiments were conducted for a range of constant fluxes using humic acid as a model foulant. The STRT was used periodically to assess the development of concentration polarization in the RO experiments. The specific cake resistance was determined by the FFM using the model adapted for RO [Eq. (4)] under the same hydraulic conditions and comparable net fluxes. These results were used to predict the RO fouling performance. The effect of salinity on the specific cake resistance of humic acid was also investigated. The dead-end apparatus was used under constant flux for this to avoid the complications of a crossflow velocity on the particle deposition and to isolate the effect of the salt on the cake properties. The results from the dead-end filtration tests were used to study how the salt would affect the specific cake resistance in the FFM and RO. The TMP profiles were predicted using the FFM and salt-pulse data and compared with actual RO performance. A similar procedure was followed for experiments with colloidal silica, using specific cake resistance data from our earlier study [12]. Fig. 3 shows a block flow diagram that summarizes the method for estimating the RO TMP profile from the information obtained from the FFM and the STRT.

437

15 30.0 LMH

10

5

0 0

5

10

15

20

25

30

35

40

45

Time (hour) Fig. 4. RO experiment: TMP as a function of time for different fluxes at a crossflow velocity of 0.1 m/s and a feed: 20 mg/l HA and 2000 mg/l NaCl.

pulses for the clean system (without foulants). The measured CP before injection of foulants can be used as a reference point. As can be seen, before the injection of NaCl into the system, the TMP was 13.2 bar at a flux of 36.1 l/m2 h (Fig. 5a). When NaCl was injected into the system, the conductivity of the feed increased from 3.65 to 5.28 ms/cm (Fig. 5b). Since the osmotic pressure of the system increased, the TMP also increased to 14.8 bar in order to maintain constant flux filtration. At the same time the conductivity of the permeate stream increased from 0.24 to 0.33 ms/cm due to higher salt permeation (Fig. 5b). Eq. (9) was then used to estimate the CP value from the TMP and feed and permeate conductivities (Fig. 5c). It should be noted that the CP values reached a steady value during the salt injection and did not continue to increase since there was no foulant in the system.

4.1.1.2. CP during fouling. Fig. 6 shows the TMP (panel a), feed/ permeate conductivity (panel b) and measured CP (panel c) as a function of time during the STRT pulses after introducing the humic foulant into the system. The salt-tracer tests were conducted approximately 16 h after the foulant was added. The TMP was approximately 14.2 bar at a flux of 36.1 l/m2 h before the salt pulse (Fig. 6a). When NaCl was injected into the system, the TMP increased to 15.3 bar in order to maintain constant flux filtration due to an increase in the osmotic pressure of the system (Fig. 6b). As shown in Fig. 6a, the TMP profile slowly

438

a

A.H. Taheri et al. / Journal of Membrane Science 475 (2015) 433–444

20

20

16

TMP (bar)

TMP (bar)

16 12 8

12 8 4

4

0 16.65

0 136

140

144

148

152

16.70

16.75

16.80

6

0.6

5

0.5

4

0.4

3

0.3

2

0.2

1

0.1

0

Feed conductivity (ms/cm)

0.7

140

144

17.00

148

0.7

6

0.6

5

0.5

4

0.4

3

0.3

2

0.2

1

0.1

152

16.70

16.75

16.80

16.85

16.90

16.95

0 17.00

Time (hour)

Time (min)

c

16.95

7

0 16.65

0 136

16.90

Permeate conductivity (ms/cm)

7

Permeate conductivity (ms/cm)

Feed conductivity (ms/cm)

b

16.85

Time (hour)

Time (min)

4

5

4

3

CP

CP

3 2

2 1 1 0 136

138

140

142

144

146

148

150

0 16.65

16.70

Time (min) Fig. 5. TMP (panel a), feed (panel b), and permeate conductivity CP (panel c) versus time during one of the STRT pulses in the absence of a foulant for an NaCl concentration of 2000 mg/l at a flux of 36.1 l/m2 h and a crossflow velocity of 0.1 m/s.

continued to increase to 15.8 bar during the STRT pulse instead of reaching a steady value as was observed in Fig. 5a. Eq. (9) was used to estimate the CP value from the TMP and feed/permeate conductivity (Fig. 6c). The measured CP value also slowly increased as a function of time during the pulse from almost 2.8 to approximately 3.2. A possible explanation for this is the suppression of the electrostatic double layer repulsion and creation of a more compact fouling layer under the higher ionic strength.

4.1.2. Effect of fluxes on CP The STRT was applied several times during runs at a fixed flux. The variation of the CP values as a function of time determined by the salt-tracer test for different fluxes in the presence of humic acid in the feed is shown in Fig. 7. During the filtration at constant flux, the cake layer slowly built up and consequently the TMP increased (Fig. 4). The trends in the CP values in Fig. 7 confirmed the existence of CEOP in humic acid

16.75

16.80

16.85

16.90

16.95

Time (hour) Fig. 6. TMP (panel a), feed and permeate conductivity (panel b), and CP (panel c) as a function of time during one of the STRT pulses for a feed containing 20 mg of humic acid and an NaCl concentration of 2000 mg/l at a flux of 36.1 l/m2 h and a crossflow velocity of 0.1 m/s.

RO fouling. That is, the back-transport of NaCl is hindered by the presence of the cake layer, causing the concentration of NaCl to increase near the membrane surface [1,25,26].

4.2. FFM experiments RO membrane processes are usually operated under constant flux filtration that causes an increasing TMP due to fouling. Since both the pressure and flux can cause cake compression, conducting the FFM experiments under the constant flux mode and crossflow can simulate RO fouling behavior. In order to find a suitable flux for predicting RO fouling behavior from the FFM simulator, the effect of flux in the range of 95–155 l/m2 h on the fouling was investigated using 20 mg/l of humic acid as the model foulant and 2000 mg/l NaCl as the ionic buffer. The crossflow velocity was kept constant at 0.1 m/s for all the experiments. The TMP as a function of time for a range of fluxes for crossflow filtration of 20 mg/l humic acid is shown in Fig. 8.

A.H. Taheri et al. / Journal of Membrane Science 475 (2015) 433–444

Specific cake resistance (m/kg) ×10-14

4 R² = 0.98

3

CP

R² = 0.99

2

R² = 0.97

42.1 LMH

1

36.1 LMH 30.0 LMH

0 0

2

4

6

8

10

12

14

16

439

100 80

R² = 0.93

60 40 20 0 70

90

18

110

130

150

170

Flux (LMH)

Time (hour) Fig. 7. Concentration polarization CP as a function of time for a feed containing 20 mg/l humic acid and 2000 mg/l of NaCl at a crossflow velocity of 0.1 m/s.

70

Fig. 9. Experimentally determined specific cake resistance as a function of flux for the humic acid cake layer. Crossflow velocity: 0.1 m/s, 20 mg/l HA, 2000 mg/l NaCl.

Table 1 Surface zeta potential of the model foulanta

60 150 LMH

TMP (kPa)

50 40

140 LMH

30

125 LMH 110 LMH

20

95 LMH

Sample

Zeta potential (mV)

RO membrane UF membrane Humic acid

 87 1.2  217 1.9  59.9 7 2.2

a Reported values are the average of three measurements and the standard deviation about this average.

10 0 0

0.3

0.6

0.9

1.2

1.5

1.8

2.1

2.4

Time (hour) Fig. 8. TMP as a function of permeate volume for different fluxes under a crossvelocity of 0.1 m/s for a feed containing 20 mg/l HA and 2000 mg/l NaCl.

The results of the fouling experiments for humic acid demonstrated that the slope of the TMP versus time curves increased as the flux increased. Eq. (4) was used to calculate specific cake resistance of humic acid from the initial slope of the TMP as a function of time. For application of Eq. (3) the total permeate volume was used to measure the rejection of humic acid by the UF membrane (typically rejection¼55710%). This partial rejection of humic acid on the FFM using UF membrane could lead to underestimation of the αHA on the RO membrane. For example Sioutopoulos et al. [27] measure αHA on a range of UF membrane with different rejection and observed marginally higher α for the tightest UF. This suggests that our FFM prediction could slightly underestimate TMP rise on the RO for HA solution. Fig. 9 shows the calculated specific cake resistance for humic acid as a function of the flux. These results show a direct relation between the specific cake resistance of humic acid and the filtration flux. According to Boerlage et al. [28], the increase in specific cake resistance with increasing flux is probably related to a reduction in the porosity due to convective drag. It should be noted that the critical flux of the humic acid for the FFM experiments was measured using the step-by-step method and found to be higher than the critical flux measured for the RO membrane under the same conditions (J cr:FFM:HA ¼ 80 7 5 LMH). The difference between the ionic environment and membrane properties could explain the difference in Jcrit UF and Jcrit r. As shown in Table 1, the RO membrane had a lower zeta potential than the UF membrane that would imply reduced particle–membrane repulsion. Note that the zeta potential was measured at pH of 6 using an electrolyte solution of 10 mM potassium chloride (KCl). Hence, the higher critical flux for UF could be due to a higher electrostatic barrier to deposition [24,29]. We have observed similar differences between the RO and UF critical fluxes for colloidal silica [12]. An additional factor introduced

in that paper is the ‘diffusiophoresis’ phenomenon that transports colloids up a salt gradient [30,31]. This mechanism could have a role in RO, but not in UF. Both diffusiophoretic and electrokinetic effects would tend to give a lower critical flux for RO conditions. The results obtained from the FFM are used in combination with those from the dead-end filtration to modify the specific cake resistance in Section 4.3.2. The RO performance with humic fouling is then predicted in Section 4.4.1. 4.3. Dead-end filtration 4.3.1. Effect of salt concentration As discussed earlier, the effect of the salt concentration on the specific cake resistance of humic acid (20 mg/l) was studied using the dead-end setup under constant flux filtration in order to isolate the effect of the ionic environment on the double layer. It is generally observed that fouling of a humic substance in a higher ionic strength environment is more severe [32]. At a higher salt concentration, humic acid molecules change configuration and create a more dense cake layer. As a result the specific cake resistance increases with increase in the salt concentration as observed in Fig. 10. The correlation for the measured specific cake resistance as a function of salt concentration for constant flux filtration between 0 and 15,000 mg/l of NaCl is as follows: α ¼ ð0:029C 2NaCl þ 0:234C NaCl þ 4:358Þ  1014

ð13Þ

Eq. (13) is used to estimate the change in specific cake resistance with salt concentration for RO fouling prediction purposes in Section 4.3.2. 4.3.2. Correction for the specific cake resistance Since RO membranes reject salt, the effect of different salinities in RO and UF systems should be taken into account for prediction purposes. Hence, the specific cake resistance at different salt concentrations was compared with the specific cake resistance at the reference salinity (α0 at 2000 mg/l NaCl) for humic acid. For high

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retention membranes, Eq. (7) can be simplified as follows: Cw CP ¼ for C p ⪡C w Cb

ð14Þ

The ratio of the specific cake resistance for humic acid normalized with respect to the reference value (α/α0) as a function of concentration polarization is shown in Fig. 11. The specific cake resistance of humic acid in RO (αr ) can be estimated at any concentration polarization by the specific cake resistance obtained from the FFM measurements using αr ¼ αFFM  ð0:0236CP2 þ 0:0927CP þ 0:8613Þ

ð15Þ

Since CP 41, Eq. (15) indicates that the specific cake resistance increases as CP increases. 4.4. RO fouling prediction 4.4.1. Humic acid The principal goal of this paper is to combine information obtained from the FFM, salt-tracer tests and dead-end experiments to predict RO fouling. Hence, the fouling trend of the RO for humic acid is predicted using Eq. (1) that includes contributions from the cake resistance and the CEOP effect. The contribution of the hydraulic cake resistance to RO fouling was determined from the specific cake resistance at an equivalent net flux for the same flow conditions in the FFM (Section 4.2). The resulting specific cake resistance was then modified for the effect of salt concentration (Section 4.3.2). The initial trends of the CP (10–20 h) were used to estimate the contribution of

CEOP over the duration of the tests. As noted in Section 2.1 the application of Eq. (1) requires knowledge of the fractional deposition factor (θ). This is an empirical factor for which a value of θ¼0.04 was found to provide the best agreement between the model predictions and experiment as shown in Appendix 1. A sensitivity analysis in Appendix 1 indicates that the model predictions are not particularly sensitive to small inaccuracies in the value of θ. The RO fouling prediction approach was conducted using 20 mg/l humic acid as the organic foulant and 2000 mg/l NaCl as an ionic background. As mentioned earlier, the TMP profile for RO can be determined from the resistance obtained via the FFM and the CEOP determined from the salt-tracer test. Fig. 12 shows the predicted TMP as a function of time for the filtration of humic acid with and without considering the CEOP effects compared with the experimental TMP measured for RO fouling. It can be seen from Fig. 12 that the prediction by FFM–STRT without the CEOP effect underestimated the RO fouling. However, the prediction based on FFM–STRT coupled with CEOP improved the predicted TMP profile, which underscores the importance of CEOP in contributing to the increase in TMP due to organic fouling in RO of saline feeds. Fig. 13 compares the TMP as a function of time during RO fouling at different fluxes with those predicted by the model using the FFM and STRT. As can be seen the predicted trends are in very good agreement with actual RO performance. The results confirm that the model in combination with the FFM and STRT measurements provides a good estimate of the TMP profile for RO fouling over a range of fluxes

25

TMP (kPa)

20

15

10 Experimental

5 Prediction with CEOP effect Prediction without CEOP effect

0 0

5

10

15

20

25

30

35

40

45

Time (hour) Fig. 10. Effect of NaCl concentration on the specific cake resistance for a feed containing 20 mg/l of humic acid using a UF membrane (30 kDa) at a constant flux of 95 l/m2 h.

Fig. 12. Predicted TMP with and without CEOP effect and the experimentally determined RO fouling behavior. Crossflow velocity of 0.1 m/s for a feed containing 20 mg/l of humic acid and 2000 mg/l of NaCl.

25 42.1 LMH

4 20

36.1 LMH

TMP (kPa)

α /α0

3

2

15 30.0 LMH

10

5

1

0 0

0 0

1

2

3

4

5

6

7

8

9

Concentration Polarization(CP) Fig. 11. Ratio of the specific cake resistance for humic acid normalized with respect to the reference value as a function of concentration polarization at a constant flux of 95 l/m2 h for a feed containing 20 mg/l of humic acid.

5

10

15

20

25

30

35

40

Time (hour) Fig. 13. TMP versus time for a range of RO fluxes, measured trends (solid lines) and predicted values (dashed lines) based on the FFM running at the same net flux as the RO at a crossflow velocity of 0.1 m/s for a feed containing 20 mg/l of humic acid and 2000 mg/l of NaCl.

A.H. Taheri et al. / Journal of Membrane Science 475 (2015) 433–444

4.4.2. Colloidal silica A similar procedure was followed for RO fouling by colloidal silica (200 mg/l SiO2 and 2000 mg/l NaCl) for which representative data are provided for comparison. Details of the FFM data can be found elsewhere [12]. Fig. 15 shows that the FFM–STRT method was able to predict the TMP trends well. As already mentioned, the predicted trends are determined based on the hydraulic cake resistance and the CEOP effect. Fig. 16 compares the contributions of CEOP and hydraulic resistance (RF) for two experiments with colloidal silica. It is evident that for these conditions the CEOP effect was more important than the resistance effect. This is probably due to the

25

20 36.1 LMH

TMP (bar)

using humic acid as an organic foulant. Similar trends were observed for colloidal silica fouling (see Section 4.4.2). The pressure drops due to the hydraulic cake resistance and CEOP are compared with the predicted TMP in Fig. 14. For the range of conditions tested the CEOP was equal to or greater than the pressure drop due to the fouling resistance.

15

10 30.0 LMH

5

0 0

5

10

15

20

30

35

40

45

50

55

60

Fig. 15. TMP as a function of time for a range of RO fluxes showing the measured (solid lines) and predicted values (dashed lines) based on FFM running a same net flux with RO, cross-flow velocity of 0.1 m/s and feed containing 200 mg/l of colloidal silica and 2000 mg/l NaCl.

90 Predicted pressure rise

Predicted pressure rise

140

80 CEOP

CEOP

120

70 Hydraulic resistance

Hydraulic resistance

60

∆Pc (kPa)

100 80 60

50 40 30

40

20

20

10

0

0 0

5

10

15

20

25

30

35

40

0

10

20

Time (hour)

30

40

50

60

Time (hour)

400

120 Predicted pressure rise

350

CEOP

300

Hydraulic resistance

Predicted pressure rise

100

CEOP Hydraulic resistance

80

250

∆Pc (kPa)

∆Pc (kPa)

25

Time (hour)

160

∆Pc (kPa)

441

200 150

60 40

100 20

50 0 0

5

10

15

20

25

30

35

40

45

0

0

Time (hour)

∆Pc (kPa)

CEOP Hydraulic resistance

30

40

50

60

Fig. 16. ΔTMP versus time for RO fouling owing to a feed containing 200 mg/l of colloidal silica and 2000 mg/l of NaCl at a cross-flow velocity of 0.1 m/s at fluxes of a: 30 l/m2 h and b: 36.1 l/m2 h.

Predicted pressure rise

600

20

Time (hour)

800 700

10

500

thicker cake developed with colloidal silica. The relative contributions of CEOP and RF depend on the effective ‘particle’ size, the porosity and the cake height as well as the flux and salinity. This explains the difference between the non-deformable silica of 20 nm diameter and the macromolecular humic acid. We have analyzed the interactions between these parameters elsewhere [33].

400 300 200 100 0 0

5

10

15

20

25

30

35

Time (hour) Fig. 14. ΔTMP as a function of time for a feed containing 20 mg/l of humic acid and 2000 mg/l of NaCl at a crossflow velocity of 0.1 m/s at fluxes of (a) 30 l/m2 h, (b) 36.1 l/m2 h, and (c) 42.1 l/m2 h.

5. Conclusions By using a feed fouling monitor (FFM) employing a UF membrane the RO performance in the presence of humic acid and colloidal

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A.H. Taheri et al. / Journal of Membrane Science 475 (2015) 433–444

APPENDIX A. Deposition factor

silica can be characterized in a much shorter time. However, it is necessary to estimate the individual contributions of cake resistance and CEOP to the RO fouling. In this study RO fouling was predicted using the on-line feed fouling monitor (FFM) combined with a monitor based on the salt tracer response technique (STRT) under constant flux filtration. The online FFM, employing a UF membrane, was applied to predict RO fouling under the same net flux (imposed flux minus the critical flux) and flow conditions. The STRT was used to determine the CEOP component of the TMP. Fouling was studied using humic acid and colloidal silica as the model foulants in aqueous solutions of sodium chloride as an ionic buffer for both the FFM and RO experiments. The effect of flux on the fouling rate and cake properties was investigated for both RO and the FFM. The results showed that higher fluxes caused an increased fouling rate for both RO and the FFM. In contrast with the FFM experiments for which the CEOP effect does not exist, in RO systems CEOP plays a more significant role than cake resistance in determining the TMP rise during filtration. However, the contribution of cake resistance to RO fouling increased as flux increased, which was more evident for the RO experiments using humic acid. The effect of salt concentration on the specific cake resistance was investigated using dead-end filtration. The specific cake resistance of the cake layer was observed to increase over a broad range of NaCl concentrations (2000–16,000 mg/l) for humic acid and this can be explained by a decrease in the particle–particle repulsion and a change in the foulant layer packing as the salt concentration increased. The results indicate that RO performance data in the absence of fouling, in combination with the FFM and the STRT, can provide a reasonable estimate of the TMP rise during RO fouling over a broad range of effective fluxes for both colloidal silica and humic acid. The predicted TMP profiles also underscore the significant contribution of CEOP to RO fouling.

In contrast to dead-end filtration, only a fraction of the feed water passes through the membrane during crossflow filtration. That is, not all the particles entering the module will be retained by membrane filtration in the crossflow process, whereas during dead-end filtration all the particles larger than the membrane pore diameter will be trapped on the membrane surface. The deposition factor θ for RO systems is defined as the fraction of the particles in the feed water deposited or accumulated on the membrane. The value of θ varies from 1.0 (complete deposition) to approximately 0.1 (partial deposition). The value of θ can be affected by several parameters such as the nature of the foulant, imposed flux and the hydrodynamics. Hence, in most applications it is difficult to estimate the exact value of θ. In this study the value of θ¼ 0.04 has been determined empirically. Tables A 1a and A 1b present the experimental and predicted TMP values based on different deposition factor values in the range of 0.01–0.1 under different fluxes for humic acid and colloidal silica, respectively. To select the deposition factor, the root-mean-square error (RMSE) between the experimental TMP and the TMP predicted by the model for three different fluxes was calculated using deposition factors in the range of 0.01–0.1. The RMSE of the error is defined by Eq. (A 1a) as follows: " σ ¼




TMPExperimental  TMPPredicted ∑ 3 i¼1 3

2 #1=2 ðA1aÞ

Figs. A 1a and A 2a present the RMSE as a function of the deposition factor for humic acid and colloidal silica, respectively. As can be seen from Figs. A 1a and A 2a, the minimum RMSE was at a deposition factor of approximately 0.04. Hence θ¼0.04 was selected as deposition factor for both the humic acid and colloidal silica experiments in this study to give the lowest model error. The model was also examined for its sensitivity to the selected deposition factor (θ ¼ 0:04). For this purpose, θ was changed by 710% and 750% and the resulting predicted TMP was compared to the predicted TMP at θ ¼ 0:04. The absolute relative error of the predicted TMP was calculated using Eq. (A 2a) as follows:

Acknowledgments AbsoluterelativeerrorofpredictedTMPð%Þ ¼

This project was supported by the Environment and Water Industry Programme Office (EWI) of Singapore (Project Ref. EWI RFP 09/01). The authors also acknowledge the Singapore Economic Development Board for their support of the Singapore Membrane Technology Centre (SMTC).

  TMPPredictedð0:04Þ  TMPPredictedðθÞ   100 TMPPredictedð0:04Þ

ðA2aÞ Fig. A 3a shows the relative error or percentage change in the predicted TMP for different deposition factors under different fluxes using colloidal silica and humic acid as the foulant.

Table A 1a Experimental TMP and predicted TMP values for different deposition factors (HA). Flux (LMH)

30.00 36.10 42.10

Experimental TMP (bar)

12.67 17.11 22.32

Predicted TMP (bar, rows 2–4) for a range of values of the deposition factor (row 1) 0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

12.49 15.71 19.28

12.61 16.19 20.18

12.72 16.68 21.08

12.84 17.17 21.98

12.95 17.66 22.88

13.07 18.14 23.78

13.18 18.63 24.67

13.30 19.12 25.57

13.41 19.61 26.47

13.53 20.10 27.37

Table A 1b Experimental TMP and predicted TMP values under different deposition factors (SiO2). Flux (LMH)

30.00 36.10

Experimental TMP (bar)

11.54 14.66

Predicted TMP (bar, rows 2–3) for a range of values of the deposition factor (row 1) 0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

11.50 14.49

11.52 14.53

11.54 14.57

11.56 14.61

11.58 14.66

11.60 14.70

11.62 14.74

11.63 14.78

11.65 14.82

11.67 14.86

A.H. Taheri et al. / Journal of Membrane Science 475 (2015) 433–444

443

factor at higher fluxes. This also confirmed that the higher contribution of the cake resistance to RO fouling increases as the flux increases, which can be observed in Figs. 14 and 16.

4 3.5 3

RMSE

2.5

References

2 1.5 1 0.5 0 0

0.02

0.04

0.06

0.08

0.1

0.12

Deposition Factor Fig. A 1a. Root mean square error (RMSE) between the experimental TMP and its predicted value as a function of the deposition factor (20 mg/l HA). 0.3 0.25

RMSE

0.2 0.15 0.1 0.05 0 0

0.02

0.04

0.06

0.08

0.1

0.12

Deposition Factor

Absolute Relative error of predicted TMP (%)

Fig. A 2a. Root mean square error (RMSE) between the experimental TMP and its predicted value as a function of the deposition factor (200 mg/l SiO2). 9

30 LMH

8.2

8 36.1 LMH

7 42.1 LMH

5.7

6 5 4 3 2

1.8

1.6 1.1

1

0.6

0.4

0.3

±10% Change (HA)

±50% Change (SiO2)

0.08 0.14

0 ± 50% Change (HA)

±10% Change (SiO2)

Relative change in Deposition Factor Fig. A 3a. Percentage change in the predicted TMP as a function of the change in deposition factor under different fluxes for humic acid and colloidal silica.

As shown in Fig. A 3a, the absolute relative error in the predicted TMP incurred as a result of 10% and 50% uncertainty in the value of the deposition factor was smaller for colloidal silica than humic acid for the three fluxes. This indicates that colloidal silica was less sensitive than humic acid to the deposition factor. In view of the fact that the deposition factor was used in this study to modify the contribution of the cake resistance in RO fouling (Eq. (1)), these results suggest that the sensitivity of the predicted TMP for colloidal silica to the deposition factor is less than for humic acid. That is, the contribution of the cake resistance to RO fouling for colloidal silica was found to be less than humic acid. These results are in good agreement with Figs. 14 and 16 that show the relative contributions of CEOP and cake resistance to RO fouling. From Fig. A 3a, it also can be seen that the absolute error in the predicted TMP incurred as a result of 10% and 50% uncertainty in the value of the deposition factor is more sensitive to the deposition

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