Mass transport modeling of natural organic matter (NOM) and salt during Nanofiltration of inorganic colloid-NOM mixtures

Desalination 429 (2018) 60–69

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Mass transport modeling of natural organic matter (NOM) and salt during Nanofiltration of inorganic colloid-NOM mixtures

T

⁎

Yanxiao Yuan, James E. Kilduff

Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, United States

A R T I C L E I N F O

A B S T R A C T

Keywords: Silica colloids Nom Mixture Crossflow nanofiltration Colloidal deposition Enhanced concentration polarization

The behavior of mixtures of inorganic nanoparticles and natural organic matter (NOM) during nanofiltration (NF) was investigated in a lab-scale crossflow filtration system to identify how interactions between these foulants influenced deposition and membrane performance in terms of NOM and salt selectivity. NOM selectivity was reduced substantially when the colloid concentration was sufficient to produce a thick deposited colloidal cake, as a result of enhanced concentration polarization phenomena. This increased the concentration and hence the driving force for NOM. It also increased salt concentration, which screened NOM charge. In addition to reducing the double layer thickness, charge screening has also been shown to reduce NOM effective size, increasing the membrane permeation coefficient. On the other hand, the presence of NOM in the cake layer matrix substantially attenuated the enhancement of salt concentration polarization. A multilayer solute transport model was applied to describe these phenomena and simulate solute selectivity for both NOM and salt in colloid-NOM mixtures. Good agreement of model calculations with experimental data was observed. According to this model, the properties of the first deposited colloidal cake layer is critical in determining the quality of the permeate product in terms of NOM or salt retention.

1. Introduction Nanofiltration (NF) processes are enjoying increased application to desalination of inland brackish waters [1]; softening, including inland brackish water [2] and as part of integrated seaweater desalination processes [3]; and removal of natural organic matter for control of disinfection byproducts [4]. Flux decline during nanofiltration occurs as a result of both natural organic matter (NOM) and inorganic colloidal particles [5–7]. Organic matter includes humic substances (HS), natural biopolymers, and proteins; typical inorganic colloids include alumninosilicates (clays), silica, and iron oxyhydroxide particles [8]. Fine colloidal materials may not be effectively removed by coagulation, granular media filters or microfiltration membranes used for pretreatment; therefore, they have the potential to cause fouling and degrade water quality subsequent to the nanofiltration (NF) process. In this work, colloids refer to inorganic colloids only. Numerous studies have been done regarding NOM fouling, and it has been found that governing physicochemical factors include properties of NOM (chemical composition and functionality, charge, molecular conformation) [9–13], properties of membranes [14–16] (hydrophobicity, surface charge, and roughness), solution chemistry (pH, ionic strength, Ca2 +) [17–19] and operating conditions

⁎

(transmembrane pressure, crossflow velocity) [18,20–22]. These factors are important because they can affect the structure of NOM cake layer including compactness and thickness, which governs the fouling behavior. For colloids with sizes between 1 nm and 1 μm, the contribution of hydrodynamics due to shear-induced diffusion and inertial lift is found to be negligible, and Brownian diffusion and surface interactions are dominant [23–35]. Related factors such as particle size, ionic strength and pH on particle stability, particle back transport, cake structure and subsequent permeate flux have been widely studied [26,30,36–38]. It was found that the specific cake resistant increased with ionic strength when it was lower than the critical coagulation concentration (CCC), while it decreased with ionic strength when it was higher than the CCC. Further investigation with respect to the influence of membrane surface properties on colloidal fouling of RO and NF membranes in crossflow filtration by Zhu et al. [39] and Hoek et al. [40,41] showed that the fouling of these membranes correlated well with membrane surface roughness, regardless of physical and chemical operating conditions. Hoek et al. [42] also investigated the interplay between rejected salt ions and colloidal particles accumulating at the surface of RO and NF, and they concluded that the deposited colloidal layer led to an enhanced salt concentration polarization above the membrane surface

Corresponding author at: Rensselaer Polytechnic Institute, Department of Civil and Environmental Engineering, 4022 JEC Building, 110 8th Street, Troy, NY 12180, United States E-mail address: kilduff@rpi.edu (J.E. Kilduff).

https://doi.org/10.1016/j.desal.2017.12.002 Received 31 August 2017; Received in revised form 1 December 2017; Accepted 1 December 2017 0011-9164/ © 2017 Elsevier B.V. All rights reserved.

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where v is the crossflow velocity, Q is the crossflow rate, Ac is the crosssection area of the channel, and Hc is the channel height. The channel height decreases as the deposited cake layer grows, increasing the shear rate. The deposited cake layer thickness, δC(t), was estimated by [42,49]:

due to hindered back diffusion, and this enhanced concentration polarization then led to an enhanced osmotic pressure across the salt-rejecting membranes. Waite et al. [37] found that the specific cake resistance of aggregated hematite during ultrafiltration depended strongly on the fulvic acid concentration. At a critical concentration, fulvic acid neutralized the hematite surface charge and promoted fast aggregation, resulting in more porous cakes having low resistance. Schafer et al. [43] found that flux decline during microfiltration of hematite and NOM mixtures depended on the method of preparation and aggregation state. Aggregation of henmatite in electrolyte solution followed by NOM adsorption caused greater flux decline than aggregated hematite alone. On the other hand, mixing particles and NOM prior to adding electrolytes resulted in stable particles for which rejection depended fully on primary particle size. Lee et al. [44] investigated this system further and showed that humic acid concentration and the extent of charge neutralization influences both the size and fractal structure of flocs. Li and Elimelech [45] found that combined fouling of a low salt rejection NF membrane by colloidal silica and dissolved NOM exhibited significantly higher flux decline compared to the additive effects of colloidal fouling and organic fouling alone, attributed to hindered back diffusion of foulants and greater foulant deposition. On the other hand, Lee et al. [46] found that flux decline due to combined fouling was less than that inferred from additivity of the individual contributions of colloidal and NOM fouling to flux decline, attributed to an increase in colloidal stability in presence of NOM and the competition between colloids and NOM for calcium ions. However, cake enhanced osmotic pressure played an important role in flux decline of salt-rejecting membranes. They also found that salt rejection by the NF membrane increased noticeably in case of combined fouling, attributed to the accumulation of NOM near the membrane surface. In this work we attempt to quantitatively describe phenomena related to combined fouling of NOM and inorganic colloid mixtures employing a multiple-layer transport model. Such phenomena include the interactions between NOM and colloids on transport, deposition and cake structure; and the effects of deposited colloidal cake on NOM and salt selectivity.

δc (t ) =

1

⎞ ⎛ 6QD∞2 ⎟ k = 0.807 ⎜ 2⎟ ⎜ Mc (t ) ⎜ Am ⎡Hc − ρ (1 − ε ) ⎤ ⎟ p ⎣ ⎦ ⎠ ⎝

Sa =

S∞ exp(Pem ) S∞ + exp(Pem) − 1

(6)

⎟

(7)

where δm is the membrane thickness, and Kc and Kd are the hindrance factors for convective and diffusive transport, respectively. Note that the actual sieving coefficient can be expressed in terms of rejection, Ra = 1 – Sa, and the asymptotic value of the rejection coefficient at large Pem is equal to the osmotic (Staverman) reflection coefficient σ [51]. 2.1.3. Solute mass transport through multiple layers Solute transport through a two-layer membrane was investigated by Jagur-Grodzinski and Kedem [52], and later by Opong and Zydney [50], Boyd and Zydney [53]. Yuan and Kilduff employed a two-layer model to investigate the effects of colloids on salt transport in NF [54]. At steady state, solute flux through each layer is equal; the corresponding expression for an N-layer transport model can be written as:

J

(1)

1 1 = + N Sa exp (∑i = 1 Pei )

2.1.1. Estimation of solute mass transfer coefficient above membrane surface Typical values of the axial Reynolds number are about 100; for laminar flow in a thin rectangular channel, the length-averaged mass transfer coefficient was estimated by the Leveque solution [48]:

N

∑ i=1

exp(Pei ) − 1 i

S∞ i exp (∑k = 1 Pek )

(8)

where i = 1 to N are the transport layers numbered consecutively starting at i = 1 for the upstream layer. In this study, we investigated the fouling and transport of inorganic colloidal nanoparticles and NOM mixtures during nanofiltration. SEM images of clean and fouled membranes, in combination with transport data, revealed that NOM formed a separate layer between a colloidal cake layer and the NF membrane surface (see Supplemental Information). Hence we take deposited colloidal cake and NOM cake as two separate transport layers. In this study we assume constant cake porosity over the course of filtration for both cake layers. A two layer transport model was applied to simulate the retention of NOM as a function of time and a three layer transport model was applied to simulate the retention of salt as a function of time. Model parameters

3

(2)

where D∞ is the bulk diffusion coefficient, Lc is the channel length, and γ is the wall shear rate given by [48]:

6v 6Q = Hc Ac Hc

=

⎜

where Jv is the volumetric flux [m/s] and k is the mass transfer coefficient in the polarization layer.

γ=

Cp Cm

ϕK c δm Jv S Jδ Pem = ⎜⎛ ∞ ⎟⎞ ⎛ m ⎞ = εϕK D ϕK d εD∞ ∞ d ⎠ ⎝ ⎠⎝

Sa

1

(5)

where S∞ is the asymptotic value of the sieving coefficient, attained as flux goes to infinity, and is equal to the product of the hindrance factor for convection (Kc) and the solute equilibrium partition coefficient (ϕ) into the membrane pore. The membrane Peclet number, Pem, is a measure of relative importance of solute convection to diffusion, and is defined as:

The stagnant film model, which relates the solute concentration at the membrane surface (Cw) to that in bulk solution (Cb), was used to account for bulk mass transport and concentration polarization [47], and therefore relate the actual (Sa = Cp/Cm) and observed (So = Cp/Cb) sieving coefficients:

γD 2 k = 0.807 ⎛⎜ ∞ ⎞⎟ ⎝ Lc ⎠

3

2.1.2. Solute mass transport across single membrane layer Solute transport was modeled using a hydrodynamic model, which accounts for hindered convective and diffusive transport in the membrane pore [50]:

2.1. Bulk mass transport

Sa + (1 − Sa) exp ⎡− kv ⎤ ⎣ ⎦

(4)

where Mc(t) is the accumulated colloidal mass per unit area as a function of time, ρp is the solid particle density and ε is the porosity of the cake layer. Combining (2) through (4) yields the mass transfer coefficient as a function of time:

2. Theoretical background

So =

Mc (t ) ρp (1 − ε )

(3) 61

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3.4. Cross-flow membrane filtration system and membranes

were calibrated by minimizing the sum of the squared residuals (SSR) between experimental observed sieving coefficient (So) data and calculated values using Eqs. (8) and (1).

The cross-flow membrane filtration system is shown in Fig. 1. The test cell was made by in-house, with a channel length of 56 mm, width of 38 mm, and height of 1 mm. These channel dimensions provide an effective membrane area of 2.12 × 10− 3 m2 and a cross-sectional flow area of 3.78 × 10− 5 m2. Nitrogen gas was used to pressurize a 20 L stainless steel feed reservoir (Pope Scientific, Saukville, WI). A recycle loop (having 60 mL volume) was used to provide independent control of crossflow velocity, and a needle valve in the retentate line was used to adjust recovery. In this crossflow configuration, feed rate, recovery, and cross-flow velocities were controllable. Unless otherwise noted, the system was operated at room temperature (21–23 °C) with an initial permeate flux of 1.25 × 10− 5 m/s (45LMH), a cross-flow velocity 0.1 m/s (shear rate = 600, Reynolds number = 200), and a recovery of 50%. Unless otherwise noted, solution pH was maintained at pH 7, and the background electrolyte was 0.01 M NaCl. Filtration experiments were done using an aromatic polyamide thin-film composite nanofiltration membrane (NF 90, Dow-Film Tec Inc., Minneapolis, MN). Characteristics of this membrane include a MWCO of 200 Da, average resistance of 4.01 × 1013m− 1, zeta potential of –25 mV (0.01 M NaCl, pH 7), and salt rejection of 70 to 80% (0.01 M NaCl, pH 7, applied pressure 60–100 psi).

3. Materials and methods 3.1. Model colloidal particles and characterization We used colloidal SiO2 as a model inorganic colloid (MP 1040, Nissan Chemical, Houston, TX). Particles were obtained as a 40.7 wt% aqueous suspension containing less than 0.08% wt NaO2. The suspension had a specific gravity of 1.30, yielding a calculated particle density of about 2.31 g/cm3. SEM images showed that the particles were spherical and monodisperse with an average hydrodynamic diameter of 125.2 ± 4.9 nm determined using a particle analyzer (90Plus, Brookhaven Instruments) and zeta potential of −57.0 ± 2.24mV (ZetaPlus, Brookhaven Instruments) at pH 7, and an ionic strength of 0.01 M NaCl. 3.2. Aquatic NOM Two aquatic NOM samples were chosen for this research, both isolated by reverse osmosis. One sample was isolated from the Tomhannock (TMK) reservoir, NY; total organic carbon recovery was higher than 95% [55]. The second sample was Suwannee River NOM (SR), obtained from the International Humic Substances Society (IHSS). Properties of the two NOM samples are shown in Table 1. Dissolved organic concentration (DOC) was quantified using a total organic carbon analyzer (Shimadzu TOC-VCPH/CPN). Molecular weight (MW) distribution of the NOM samples was determined by high-pressure size exclusion chromatography (HPSEC). Organic acidity was measured by potentiometric titration using an auto titrator (DL55, Mettler Toledo, OH).

3.5. Fouling experiments 3.5.1. Experimental protocol Prior to each filtration experiment, a new membrane coupon was compacted for 2 h at 120 psi using reagent-grade water. Then, the membrane hydraulic resistance, Rm, was determined by measuring pure water flux, Jv over a range of applied transmembrane pressure, ΔP, from 30 to 100 psi; Rm = ΔP/μJv. After the membrane hydraulic resistance was determined, reagent grade water was replaced by a solution having the same pH and ionic strength as the test suspension but having no colloidal particles. The membrane was compacted for another 10–12 h at a pressure of 120 psi, then the permeability was measured again using the same method mentioned above to determine the pressure needed to obtain the desired initial flux Jo = 45 LMH (1.25 × 10− 5 m/ s). The compaction solution was then replaced by the test feed suspension, and filtration proceeded under constant pressure. The needle valve was adjusted to keep the recovery constant at 50%. Experiments were conducted over an 8 h period with samples collected every 10 min for the first hour, every 20 min for the next 4 h and every 30 min for the last 3 h. Unless otherwise noted, experimental conditions were as follows: 200 mg/L colloid concentration, 10 mg DOC/L NOM, I.S. 0.01 M NaCl, and pH = 7.0.

3.3. Determination of colloid concentration and NOM concentration in colloid-NOM mixtures UV absorption (Cary 100, Varian) was used to determine inorganic colloid concentration in colloid-NOM mixtures based on the following observations: 1) the colloidal particle size in NOM-colloid mixtures was monitored throughout the 8 h filtration, and no detectable change was observed for all mixtures (results were not shown); 2) no detectable adsorption of NOM onto the particle surface was observed either by DOC or UV254 measurement (results were not shown), which is consistent with the results of Li and Elimelech [45]. For samples containing colloid only, the concentration was obtained directly from a calibration curve prepared at 254 nm. To determine the colloid concentration in a NOM-colloid mixture, first the UV absorbance of the mixture was measured, then the sample was centrifuged at 10,000 rpm for 60 min (Eppendorf Model 5403) to remove inorganic colloids. The UV absorbance of the supernatant containing NOM was measured, and subtracted from the total to yield the absorbance of the colloids. In addition to UV absorbance data, DOC measurements for all feed and collected samples were made.

3.5.2. Estimation of deposited colloidal mass Deposited colloidal mass as a function of time was calculated from a mass balance made on the recycle loop:

Mc (t ) = CF

SUVA254 (L m− 1 mg− 1)

Mw/Mn (Da)

-COOH (meq/g OC)

-OH (meq/g OC)

TMK NOM SR NOM

2.5 4.5

1294/515 2360/1760a

8.8 9.9b

11.1 3.9b

a b

t

(Vb (t ) + Vp (t )) dt −

− VLoop (Cb (t ) − CF )

∫0

t

Vb (t ) Cb (t ) dt (9)

where Mc is the deposited mass, CF is the feed concentration, Vb is the cumulative volume of the retentate samples, Vp is the cumulative volume of the permeate samples, Vloop is the volume of the recycle loop, and Cb is the concentration in the retentate samples.

Table 1 NOM Characteristics. NOM

∫0

3.5.3. Measurements of NOM/salt retention DOC or conductivity measurements in retentate and permeate lines allow the calculation of the observed NOM or salt retention Ro, defined as:

Data from [56]. Data from IHSS.

62

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Y. Yuan, J.E. Kilduff

Gas release valve Thermometer

Fig. 1. Schematic diagram of cross-flow membrane filtration system.

Flowmeter

Gear pump Membrane cell

N2 gas cylinder

Ro = 1 −

Bubble

2.7µm filter

removal

Back pressure

line

valve Retentate

Feed reservoir

Permeate

Scale

Scale

Cp Cb

electron microscope (FESEM). The fouled membrane samples were airdried in refrigerator. For cross section imaging, the fouled membrane samples were frozen at liquid nitrogen temperature and then fractured. The membranes samples were then sputter coated with Au before being analyzed. Images are provided in Supplemental Information.

(10)

where Cp and Cb are the DOC or conductivity in permeate and retentate, respectively. 3.6. Prediction of selectivity applying multiple layer transport model

4. Results and discussion In this work, a two-layer transport model was applied to simulate NOM selectivity while a three-layer transport model was selected to simulate salt selectivity. The Peclet number in the colloidal/NOM cake layer is described as [26]:

Pe =

Jδc (t ) Jδ (t ) Jδ (t ) = c = c D∗ εc D∞ εc D∞

4.1. Permeate flux Fig. 2 (a)–(c) presents the flux decline behavior of colloid suspensions and NOM solutions alone, and the mixture of MP 1040 colloid and NOM as function of feed colloidal concentration and NOM type. Flux decline was more rapid for colloid-NOM mixtures than either colloid or NOM alone, but less than the sum, indicating that fouling mechanism is not additive, as previously reported [46]. NOM source played a role in determining the fouling behavior; for both NOM alone and NOM colloid mixtures, flux decline was more rapid for the TMK as compared to the SR NOM. However, at a fixed DOC concentration of 10 mg/L, the flux decline of the SR NOM-colloid suspension was more sensitive to changes in the feed colloidal concentration. When the feed colloid concentration was increased from 200 to 1000 mg/L, the normalized flux at t = 8 h dropped from 61% to 43% for the SR NOM-colloid suspensions while it dropped from 53% to 41% for the TMK NOMcolloid suspensions. Fig. 3(a) shows the evolution of the deposited colloidal cake mass as function of time, feed colloidal concentration and NOM type for NOMcolloid mixtures. Corresponding data for individual colloid suspensions were plotted for comparison. It is clear that the rate of colloid deposit on the membrane surface is lower in the presence of either TMK or SR NOM regardless the feed colloid concentration, as shown in Fig. 3(a), although the effect of NOM is lower as the colloid concentration increases. This observation is consistent with the results of Lee et al. [46] using a similar crossflow filtration system and the same NF 90 membrane, but larger colloids (MP 3040, 300 nm). This reduction in colloid deposition in the presence of NOM is part of the reason why the flux decline of the NOM-colloid mixtures is less than the sum of the flux decline for individual components. The effect of NOM depends on NOM type; TMK NOM caused a greater reduction than SR NOM. The TMK NOM has a higher molar charge density, which may play a role in this process. It is also possible that NOM further stabilized the particles via an amount of adsorption too small to be detected by the methods used here. The relationship between the deposited mass of colloidal cake and corresponding cumulative permeate volume is plotted in Fig. 3(b). When the effects of flux decline are removed, it is evident that the effects of NOM in reducing colloid deposit are not seen until after about

(11)

∗

where D is the hindered diffusion coefficient of NOM/salt in the colloidal/NOM cake layer, which is a function of the corresponding cake porosity, εc. For the colloidal cake, a porosity of 0.266 was used, and for NOM cake, a random packing porosity of 0.4 was chosen. The diffusion coefficient for SR NOM was estimated as 5.20× 10− 10 m/s using the Stokes-Einstein equation based on molecular weight estimates, which is consistent with other reports in the literature [57]. Similarly, the diffusion coefficient of TMK NOM was estimated as 7.50 ×10− 10 m/s. The diffusion coefficient of salt was taken as 1.48× 10− 9 m/s [16]. In this study, for each transport layer a “structural parameter” was defined as δϕKc/εϕKd, and treated as a fitting parameter; the asymptotic sieving coefficient was also treated as a phenomenological parameter. These parameters combine the effects of conformation (in the case of NOM) and electrostatic effects (in the case of both salt and NOM). The overall objective of this work was to demonstrate the efficacy of hydrodynamic modeling as a phenomenological approach to describe transport in complex multi-species systems. First, membrane properties were estimated by performing filtration experiment with a colloid free 0.01 M NaCl solution, measuring the observed sieving coefficient. The actual sieving coefficient was determined from Eq. (1), and the structural parameter and asymptotic sieving coefficient were calibrated using Eq. (6), minimizing the sum of the squared residuals (SSR) between experimental data and calculated values. NOM and salt retention are then modeled using the multiple-layer transport model Eq. (8) to obtain the predicted Sa, using asymptotic sieving coefficients in each transport layer as calibration parameters, and Eq. (1) to obtain the predicted observed sieving coefficient So. 3.7. SEM analysis of cake structure The structure of surface and cross-section of the fouled membranes were characterized using a JEOL JSM-6335 field-emission scanning 63

Desalination 429 (2018) 60–69

Y. Yuan, J.E. Kilduff 1.2

0.20

(a)

(a)

2

Deposited cake mass, kg/m

Normalized flux, J/J 0

1.0 TMK(10) SR(10)

0.8

MP(200)

0.6

TMK(10)+MP(200) SR(10)+MP(200)

0.4

Sum of TMK and MP(200) Sum of SR and MP(200)

0.2

MP(200)

0.15

TMK(10)+MP(200) SR(10)+MP(200) MP(500)

0.10

TMK(10)+MP(500) SR(10)+MP(500) MP(1000) TMK(10)+MP(1000)

0.05

SR(10)+MP(1000)

0.0 0

60

120

180

240

300

360

420

480

0.00

Time, min

0

1.2

120

180

240

300

360

420

480

Time, min

(b)

1.0

TMK(10)

0.20

SR(10)

0.8

TMK(10)+MP(500)

0.6

SR(10)+MP(500)

0.4

Sum of TMK and MP(500) Sum of SR and MP(500)

0.2 0.0 0

60

120

180

240

300

360

420

(b)

2

MP(500)

Deposited cake mass, kg/m

Normalized flux, J/J 0

60

480

Time, min

MP(200)

0.15

TMK(10)+MP(200) SR(10)+MP(200) MP(500)

0.10

TMK(10)+MP(500) SR(10)+MP(500) MP(1000)

0.05

TMK(10)+MP(1000) SR(10)+MP(1000)

1.2

0.00

(c) Normalized flux, J/J 0

1.0

0

TMK(10)

100

SR(10)

0.8

300

400

500

600

700

Permeate volume, mL

MP(1000)

Fig. 3. Deposited colloidal cake mass as function of (a) time (b) cumulative permeate volume, colloidal feed concentration and NOM type.

TMK(10)+MP(1000)

0.6

200

SR(10)+MP(1000) Sum of TMK and MP(1000)

0.4

5.0E-06

Sum of SR and MP(1000)

MP only

0.2

TMK+MP

4.0E-06

0.0 0

60

120

180

240

300

360

420

SR+MP

480

J*, m/s

Time, min

Fig. 2. Normalized flux as function of time, feed colloidal concentration and NOM type (a) feed colloidal concentration of 200 mg/L; (b) feed colloidal concentration of 500 mg/ L; (c) feed colloidal concentration of 1000 mg/L. For all experiments, DOC = 10 mg/L, I.S. = 0.01 M NaCl, pH = 7.0, Jo = 1.25 × 10− 5 m/s, shear rate 600 s− 1, recovery = 50%.

3.0E-06

2.0E-06

1.0E-06

200 mL of permeate volume. 0.0E+00 200

4.2. Colloid and NOM deposition

500

1000

Colloid feed concentration, mg/L NF

Back transport of the 125 nm colloids used here is dominated by Brownian diffusion and electrostatic double layer repulsion. To evaluate the effects of back transport empirically, we express the mass deposition in terms of an effective flux, Jv – J⁎ where J⁎ incorporates all back transport mechanisms, and is analogous to a critical flux [26,58]. Therefore,

Mc (t ) =

∫0

t

(J (t ) − J ∗) CF Am dt

Fig. 4. Influence of NOM on back transport of colloidal particles in NOM-colloid mixtures.

the TMK NOM was significant, approximately doubling when the feed colloidal concentration was lower than 500 mg/L. DOC mass deposited from NOM solutions and combined NOM-colloid suspensions are plotted in Fig. 5, assuming negligible NOM deposit in the concentration polarization layer. Less DOC deposition was observed in the presence of colloidal particles compared to NOM alone, regardless of feed colloid concentration. In contrast to inorganic colloids, which cannot permeate the membrane, a reduction in NOM deposit corresponded to a greater mass of NOM collected in the permeate, as shown in Fig. 6. Therefore, NOM transport through the membrane was increased by the presence of colloids. Under the same experimental conditions, the SR NOM deposition was greater than the TMK NOM. This is largely because the back transport of TMK NOM was larger than

(12)

The best fit J⁎ values were obtained by minimizing the sum of the squared residuals (SSR) between the experimental data and model predictions using Eq. (12), and are presented in Fig. 4. The J⁎ values decrease with increasing colloid concentration, as expected based on the concentration dependence of the diffusion coefficient. The presence of NOM increased the back transport of colloidal particles regardless of feed colloid concentration or NOM type, with a larger increase observed for TMK NOM mixtures. The increase of particle back transport J⁎ by 64

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Y. Yuan, J.E. Kilduff

1.2

0.8

Observed DOC rejection

Deposited DOC mass, mg

1.0

TMK(10) SR(10)

0.6

TMK(10)+MP(200) TMK(10)+MP(500) TMK(10)+MP(1000)

0.4

SR(10)+MP(200) SR(10)+MP(500)

0.2

SR(10)+MP(1000)

0.0 0

60

120

180

240

300

360

420

1.0 0.8 0.6 0.4

TMK(10)+MP(200)

0.2

480

0.0 0

Fig. 5. Deposited DOC mass as function of time, feed colloidal concentration and NOM type.

60

120

180

240

300

360

420

480

Time, min Fig. 7. Influence of deposited colloidal cake on the observed DOC rejection of TMK NOM. Solid lines are mass transport model fits to the data.

25 DOC of the retentate, mg/L

TMK(10)+MP(500) TMK(10)+MP(1000)

Time, min

(a) TMK(10)

20

TMK(10)+MP(200)

larger hindrance effect (lower retentate concentrations) consistent with its larger molecular size. The permeate DOC concentration increased dramatically in the presence of inorganic colloids, as shown in Fig. 6(b), with a pronounced increase in NOM passage when the feed colloid concentration was increased from 500 to 1000 mg/L. An interesting feature of the permeate concentration plot is the maximum observed regardless the colloidal feed concentration and NOM type, as shown in Fig. 6(b). This illustrates the dynamic nature of the NOM transport, and may indicate changes in the cake structure with time. The dramatic change of the NOM concentration in both the retentate and the permeate led to a significant reduction in the NOM selectivity across the membrane, as shown in Figs. 7 and 8. Without colloids, the DOC rejection by the NF 90 membrane is about 99% for the TMK NOM and 94% for the SR NOM, likely reflecting a combination of size and charge density. However, rejection decreases dramatically with increasing inorganic colloid concentration, for both TMK and SR NOM. Based on these data, it is apparent that water quality in terms of NOM concentration (and subsequent disinfection by-product formation) can deteriorate dramatically if a thick colloidal cake layer is allowed to form. The mass transport model (solid lines) captures the trends in data quite well. The Peclet number of NOM in the porous colloidal cake layer calculated from the model is 0.1–3.9, about an order of magnitude

TMK(10)+MP(500)

15

TMK(10)+MP(1000) SR(10)

10

SR(10)+MP(200) SR(10)+MP(500)

5

SR(10)+MP(1000)

0 0

60

120

180

240

300

360

420

480

Time, min

10 DOC of the permeate, mg/L

TMK(10)

(b) 8

TMK(10) TMK(10)+MP(200) TMK(10)+MP(500)

6

TMK(10)+MP(1000) SR(10)

4

SR(10)+MP(200) SR(10)+MP(500)

2

SR(10)+MP(1000)

0 0

60

120

180

240

300

360

420

480

Time, min

Fig. 6. DOC concentrations in (a) the retentate (b) the permeate as function of time, feed colloidal concentration and NOM type.

Observed DOC rejection

1.2

that of SR NOM, due to its smaller molecular size, which resulted in higher concentration of TMK NOM in the retentate as shown in Fig. 6(a). However, the effect of increasing feed colloidal concentration on DOC deposition is different for these two NOM samples. For TMK NOM, higher feed colloidal concentrations reduced DOC deposition, while the opposite was true for SR NOM, as shown in Fig.5. This difference appears due to the combined result of hindered back transport above the membrane and enhanced transport across the membrane. A more detailed examination of NOM selectivity will be discussed next.

1.0 0.8 0.6 0.4

SR(10) SR(10)+MP(200)

0.2

SR(10)+MP(500) SR(10)+MP(1000)

0.0

4.3. NOM selectivity

0

Inorganic colloid deposits hindered NOM back transport and reduced selectivity, resulting in lower DOC in the retentate, and higher DOC in the permeate, as shown in Fig. 6. A reduced effective diffusion coefficient can explain the reduced back transport; SR NOM showed a

60

120

180

240

300

360

420

480

Time, min Fig. 8. Influence of deposited MP colloidal cake on the observed DOC rejection of SR NOM. Solid lines are mass transport model fits to the data.

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Desalination 429 (2018) 60–69

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1.2

R eff = rs +

4rs3 σs2 λ (1 − λ ) εε0 kB Tκ

Observed initial DOC rejection

larger than that in the membrane layer (0.1–0.3). The Peclet number in the cake layer increased with time due to the growth of the cake, while it decreased with time inside the membrane due to the declined flux. The large difference between these two Peclet numbers indicates the occurrence of considerable concentration polarization between the cake and the membrane layers, and it became more severe with time. This enhanced concentration polarization is one of the reasons leading to the substantial reduction in the NOM retention. According to the two-layer model, the overall actual sieving coefficient will always approach the asymptotic sieving coefficient of the upstream transport layer, in the limit of very high filtrate flux, irrespective of the properties of downstream layers. Therefore, the properties of the deposited colloidal cake layer may be critical in determining the quality of the permeate product. There are two explanations for this marked reduction in NOM retention. The first is the enhanced NOM concentration polarization due to the hindrance of NOM back transport by the deposited colloidal cake layer, and subsequent higher driving force for transport across the membrane. Second, enhanced concentration polarization of the salt content can screen NOM charge. This can cause a reduction in effective NOM molecular size, due to a combination of a reduced electrostatic double layer thickness and a more compact molecular configuration. Both phenomena can result in greater partitioning into the pore space. The effect of ionic strength on NOM retention has been observed by Cornel and Summers [59,60], and Kilduff and Weber [61] among others. The effects of the electrostatic double layer on effective solute size has been addressed theoretically; based on the electrostatic potential energy of interaction for a spherical solute in a cylindrical pore [62], Pujar and Zydney [63] developed the following approximation for the effective pore radius, Reff:

⎜

0.8

0.6 TMK NOM-colloid mixture SR NOM-colloid mixture

0.4 0

200

400

600

800

1000

Feed colloidal concentration, mg/L Fig. 9. Dependence of observed initial DOC rejection on feed colloidal concentration.

membrane charge and pore size; the NOM charge and molecular size; and the extent of charge screening by salts, as influenced by the extent of colloid deposit and corresponding enhancement in concertation polarization. For example, in a similar study using the same NF 90 membrane by Lee et al. [46], no significant change in NOM retention was observed at a feed colloidal concentration of 200 mg/L, possibly due to 1) less significant enhanced concentration polarization effect for both NOM and salt considering the larger colloids (300 nm) used; or, 2) the lower colloidal concentration used in their study, as the most substantial reduction in the retention of NOM in this study was observed at a feed colloidal concentration of 1000 mg/L. In another study of the influence of colloidal fouling on rejection of trace organics by RO [49], in the presence of colloidal cake layer, rejection of inert organics declined to a minimum, then increased and eventually stabilized at a fixed value.

(13)

where rs is the solute radius, σs is the surface charge density of the solute, εo is the permittivity of free space and ε is the dielectric constant of the bulk solution, kB is the Boltzmann constant, κ is the inverse Debye length, and λ is the ratio of solute radius to membrane pore radius. Assuming a constant centerline value of the electrostatic energy of interaction in the membrane pores, the effect on the partition coefficient is given by [64]:

ψ ϕ = (1 − λ )2exp ⎛− E ⎞ k ⎝ BT ⎠

1.0

4.4. Salt selectivity Deposited inorganic colloids had a strong influence on the transport behavior of salt. The colloidal cake hindered the salt back transport by reducing its effective diffusion coefficient, leading to enhanced concentration polarization above the membrane surface [42]. This reduced the salt selectivity dramatically, as shown in Figs. 10 to 14. The hindrance effect increases with increasing Peclet number, which is proportional to cake layer thickness. However, the presence of NOM in the cake layer matrix substantially attenuated this enhancement in salt concentration polarization. As shown in Figs. 10 and 11, the salt concentration in the permeate increased with time and feed colloidal concentration, while the salt concentration in the retentate declined with increasing feed colloidal concentration for both NOM mixtures, consistent with trends for individual colloid suspensions. However, the extent of this increase or decrease is much smaller, leading to a less reduction in the salt selectivity in colloid-NOM mixtures. The apparent reason for the effect of NOM in colloid-NOM mixtures is that less colloid deposited in the presence of NOM, as depicted in Fig. 3. Another important reason contributing to this reduction is the initial NOM cake layer formed between the colloid cake and the membrane, which could serve as an active second membrane to screen out salt. The structure of this deposited NOM layer should be much tighter than those formed in the case of NOM alone due to the reduction in the effective size of NOM molecules. Moreover, the colloidal cake structure of mixtures might be different from those of colloid alone. As shown in Fig. 14(a), at the same amount of colloidal deposit, less salt passed through the membrane in the presence of NOM. This could be either due to the condensed NOM cake layer or duo to the less significant salt concentration polarization at the presence of NOM discussed next. More interestingly is the salt behavior above the membrane, and the data was shown in Fig. 14(b). At

⎟

(14)

where ψE is the electrostatic energy of interaction. Using a mass transport model, Yuan and Kilduff [65] described the effects of flux and ionic strength on NOM sieving in UF; they found that effect of ionic strength on the electrical double layer thickness could account for the observed changes in effective solute radius. Ionic strength may also affect the molecular configuration, i.e., rs. Ghosh and Schnizer found that humic substances are flexible linear molecules at low ionic strength (and high pH), but they coil into a compact configuration and behave like rigid spherical colloids at high ionic strength (and low pH) [66]. In addition to ionic strength effects, the presence of colloids may be another factor contributing to the effective size reduction of NOM. As shown in Fig. 9, the initial observed DOC rejection declined about 12 to 14% when the feed inorganic colloidal concentration was increased from 0 to 1000 mg/L in NOM mixtures. The initial dependence of NOM rejection on the feed colloidal concentration indicates that the effective NOM radius was reduced to some extent because the colloidal cake did not have time to develop. In contrast, no colloid dependence on the initial salt rejection was observed (discussed in the next section). (See Figs. 12 and 13.) The observed large reduction in the NOM selectivity across NF membranes in the presence of colloids has not been reported in the literature to our knowledge. Three factors appear significant: the 66

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(a) 800

Observed salt rejection

Conductivity in the permeate, µs/cm

1000

TMK(10) MP(200) TMK(10)+MP(200)

600

MP(500) TMK(10)+MP(500)

400

MP(1000) TMK(10)+MP(1000) 0.01M NaCl

200

0.9 TMK(10)

0.8

TMK(10)+MP(200) TMK(10)+MP(500)

0.7

TMK(10)+MP(1000) MP(200)

0.6

MP(500) MP(1000)

0.5

0

0.01M NaCl

0.4 0

60

120

180

240

300

360

420

480

0

60

120

180

300

360

420

480

Fig. 12. Influence of the deposited colloidal and TMK NOM cakes on the selectivity of salt.

2500

(b) 2200

1.0

TMK(10) MP(200)

Observed salt rejection

Conductivity in the retentate, µs/cm

240

Time, min

Time, min

TMK(10)+MP(200)

1900

MP(500) TMK(10)+MP(500)

1600

MP(1000) TMK(10)+MP(1000) 0.01M NaCl

1300

1000 0

60

120

180

240

300

360

420

0.9 SR(10)

0.8

SR(10)+MP(200) SR(10)+MP(500)

0.7

SR(10)+MP(1000) MP(200)

0.6

MP(500) MP(1000) 0.01M NaCl

0.5

480

0.4

Time, min

0

Fig. 10. Influence of the deposited colloidal and TMK NOM cakes on the conductivity of salt in (a) the permeate (b) the retentate (conductivity at 25 °C).

60

120

180

240

300

360

420

480

Time, min

Fig. 13. Influence of deposited colloidal and SR NOM cakes on the selectivity of salt. Conductivity in the permeate, μs/cm

1000

(a)

800

the same amount of colloidal deposit, at early stage the salt concentration in the bulk has not much difference between the colloid alone and mixtures, the deviation occurred at later times. The salt concentration started decreasing with time after it reached to a maximal value for colloid alone, while it stayed constant after reaching to a maximal value and did not decrease with time for NOM-colloid mixtures. This difference indicates the less serious salt concentration polarization effect for the cakes of mixtures, a possible evidence of a looser colloidal structure at the presence of NOM compared to colloid alone. Smaller observed salt sieving coefficients were found for NOM mixtures compared to colloid alone at the same amount of colloidal deposit, as shown in Fig. 14(c). The three-layer modeling results are plotted as solid lines in Figs. 12 and 13; model fits are in very good agreement with the experimental data, indicating this three-layer transport model reasonably captures the salt transport behavior during filtration of mixtures. The Peclet number inside the colloidal cake varied from 0.1–1.3, inside NOM cake from 0.001–0.1, and inside the membrane from 0.04–0.1.

SW(10) MP(200) SW(10)+MP(200)

600

MP(500) SW(10)+MP(500)

400

MP(1000) SW(10)+MP(1000) 0.01M NaCl

200

0 0

60

120

180

240

300

360

420

480

Time, min

Conductivity in the retentate, μs/cm

2500

(b) 2200

SW(10) MP(200)

1900

SW(10)+MP(200) MP(500)

5. Conclusions

SW(10)+MP(500)

1600

MP(1000)

The flux decline of colloid-NOM mixtures is more than that of either colloid alone or NOM alone, but less than the sum of those two. A lower mass of colloidal deposit in the presence of NOM is one of the reasons, although the mechanism requires further investigation. A dramatic reduction in NOM selectivity was observed in the presence of high colloid concentrations that produced a thick colloidal cake. The deposited colloidal cake hindered back transport of both salt and NOM, increasing concentration polarization and reducing the effective size of NOM. Charge screening likely resulted in a reduction in the NOM double layer and a more compact molecular configuration. A large reduction in salt selectivity was observed in the presence of colloids due to the enhanced

SW(10)+MP(1000) 0.01M NaCl

1300

1000 0

60

120

180

240

300

360

420

480

Time, min

Fig. 11. Influence of the deposited colloidal and SR NOM cakes on the conductivity of salt in (a) the permeate (b) the retentate (conductivity at 25 °C).

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Conductivity in the permeate, µs/cm

1000

Acknowledgements

(a) MP(200)

800

The authors acknowledge the U.S. Environmental Protection Agency (EPA grant RD83090901-0), and the U.S. National Science Foundation (BES-9984709) for financial support.

MP(500) MP(1000)

600

TMK(10)+MP(200) SR(10)+MP(200)

Appendix A. Supplementary data

TMK(10)+MP(500)

400

SR(10)+MP(500) TMK(10)+MP(1000)

200

Supplementary data to this article can be found online at https:// doi.org/10.1016/j.desal.2017.12.002.

SR(10)+MP(1000)

0 0.00

0.05

0.10

0.15

References

0.20

2

Deposited colloidal mass, kg/m

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Conductivity in the retentate, µs/cm

2200

(b) 2000

MP(200) MP(500)

1800

MP(1000) TMK(10)+MP(200)

1600

SR(10)+MP(200) TMK(10)+MP(500)

1400

SR(10)+MP(500) TMK(10)+MP(1000) SR(10)+MP(1000)

1200 1000 0.00

0.05

0.10

0.15

0.20

Deposited colloidal mass, kg/m2

0.6

(c) 0.5

MP(200)

So of salt

MP(500)

0.4

MP(1000) TMK(10)+MP(200)

0.3

SR(10)+MP(200) TMK(10)+MP(500)

0.2

SR(10)+MP(500) TMK(10)+MP(1000) SR(10)+MP(1000)

0.1 0 0.00

0.05

0.10

0.15

0.20

Deposited colloidal mass, kg/m2

Fig. 14. Influence of NOM on (a) the permeate conductivity; (b) the retentate conductivity; (c) the observed sieving coefficient of salt in NOM-colloid mixtures.

salt concentration polarization, as expected and shown by others. However, the presence of NOM in the cake layer matrix substantially attenuated this enhancement and mitigated the reduction in salt selectivity. This could be explained by a complex cake structure consisting of a colloid cake over a separate dense NOM cake capable of screening out salt. It is likely that the presence of a thick colloidal deposit promoted the formation of this real NOM cake. A phenomenological multilayer solute transport model was applied to simulate solute selectivity for both NOM and salt. Good agreement of model calculations with experimental data was observed, indicating the effectiveness of this model in capturing the transport behavior of both NOM and salt across the cake layers and the membrane layer. According to the multiple layer transport model, the property of the first deposited colloidal cake layer is critical in determining the quality of the permeate product in terms of NOM or salt retention. A practical implication of this work is to clearly demonstrate that water quality can be dramatically reduced if a thick colloidal cake layer is allowed to form on NF membranes during surface water treatment, which could have serious implications for subsequent treatment processes. 68

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