ELSEVIER Desalination 121 (1999) 183-193

DESALINATION

Sodium chloride stimulus-response experiments in spiral wound reverse osmosis membranes: a new method to detect fouling

E. Roth a, M. Kessler b, B. Fabre a*, A. Accary a aEcole Nationale Sup~rieure de Chimie, Laboratoire Gestion des Risques et Environnement,

25 rue de Chemnitz, F-68200 Mulhouse, France Tel. +33 (3) 89 32 76 73; Fax +33 (3) 89 32 76 61; email: B.Fabre@univ-mulhouse.fr

bDepartamento de Matematica Aplicata, Universitad de Murcia, Campus de Cartagena, Paseo Alfonso XII1, 30203 Cartagena, Spain

Received 7 March 1998; accepted 27 November 1998

Abstract

Fouling is generally described in terms of salt rejection and permeation flow, but these data seem to evolve very slowly, and when they reach a dramatic level, fouling is irreversible. We propose a method to determine the state of the wear of membranes by analyzing sodium chloride stimulus-response experiments. Indeed, it turns out that the shape of the distribution (RTD) of sodium chloride in the permeate flow of the membrane reveals the solute permeation mechanisms for used membranes. For new membranes the distribution of sodium chloride collected in the permeate side as well in the rejection side is unimodal. For fouled membranes we note a singular distribution form with the presence of several modes. The existence of a salt leakage peak, as well as an earlier detection of salt for all the fouled membranes, give evidence of the membrane structure modification. The intensive use of the membranes might have created an enlargement of the pore sizes; salt and solvent permeabilities are improved as well. It turns out that each permeate side sodium chloride distribution can be fitted by a weighted average of Gaussian distributions, the new membrane RTD and the shifted new membrane RTD. The coefficients of this average give us the fraction of the membrane which is enlarged, hampered by the deposited layer and not modified.

Keywords: Reverse osmosis; Fouling; Stimulus-response experiments; Kalman filter; Permeation phenomenon

I. Introduction

Reverse osmosis (RO) is widely applied in very large fields such as desalination, raw water treatment, grape must concentration and ultrapure

*Corresponding author.

water production. Ultrapure water is necessary in hemodialysis to prepare the dialyzing liquid [1]. The wear on membranes causes some danger of bacterial contamination or heavy metal poisoning [2]. Permeate quality has to be seriously monitored. For that purpose germ number and conductivity are usually measured [3].

0011-9164/99/$- See front matter © 1999 Elsevier Science B.V. All rights reserved PII: S0011-9164(99)00019-3

184 E. Roth et al. / Desafination 121 (1999) 183-193

Fouling is generally described in terms of salt rejection and permeation flow [3], but these data seem to evolve very slowly [4,5]; and when they reach a dramatic level, fouling is irreversible. In order to track the physical and chemical changes of the membrane, the permeability of pure water A and the solute transport parameter B should be measured regularly [6]. We propose a method to know the state of fouling of the membrane by analyzing sodium chloride stimulus-response experiments. Indeed it turns out that the shape of the sodium chloride distribution (RTD) in the permeate flow of the membrane reveals the solute permeation mechanisms for used membranes.

The first section of this paper contains the theoretical notions related to the quantities usually used to track fouling: salt rejection and permea- bilities. It also describes the deconvolution algorithm based on the Kalman filter that was used to separate the membrane response to stimulus from the whole system response. In the second section we describe the experimental design and conditions as well as the measurement procedures. The results are presented in the third section together with a discussion.

interpreted as a controlled perturbation of the steady state. The choice of the sample tracer depends on the marked fluid [8]. As we use water, we decided to mark it with sodium chloride and detect it by measuring conductivity.

If the measured signal is noted C(t), the RTD is defined as

E(t) - c ( o

f c(o dt 0

(1)

The magnitude of C(t) does not influence the RTD shape but only the measured precision. E(t) is a normed function whose shape is characteristic of the system.

E(t) relates the normed outlet detected signal y(t) to the normed stimulation z(t) (inlet signal) by a convolution product [9]:

t

y(t) = f E(u).z(t-u).du o

(2)

2. Theory

2.1. Residence time distributions (RTD)

Elements of fluid following different ways through a given system may require different amounts of time to pass. The distribution of these times for the stream of fluid leaving the system determines the exit age distribution E(t), called the RTD of fluid. This concept of the RTD was introduced by Dankverts [7].

To characterize the flow pattern, it is instructive to know how long the individual molecules stay in the studied system, zi. the RTD of the flowing fluid [8]. The RTD curves are given by the stimulus-response experiment, which consist of injecting a tracer in the studied system and detecting it in the outlet. This can also be

The RTD is usually mainly characterized by the mean residence time tofsalt in the system, and its variance o 2, which represents the square of the spread of the distribution. For continuous (resp. discrete measurements) they are defined as [9]

m

t = f t .E ( t ) . d t o

resp. t = E ti.Et. At) (3)

0

(resp. o = Xt-F

(4)

E. Roth et al. / Desalination 121 (1999) 183-193 185

where the (te)~,l are the equispaced measurement times and At is the measurement step.

The RTD is commonly used to diagnose the functioning of any reactor: it contains information to describe the flow. It emphasizes the existence of the studied system's dysfunction such as dead volumes, by-pass and recycling, which can then be tracked by simple observation of its shape [9].

2.2. Deconvolution with the Kalman filter

From the description of the experimental design in Fig. 1, it is clear that, as a result of the stimulus-response experiment, we obtain the distri- bution y(t) of salt in the whole system. However,

to detect fouling or wear, we are actually interested in the distribution x(t) of salt in the membrane. There are interactions between the salt and the membrane: the stimuhs-response experi- ments are not actually a RTD. The sodium chloride distribution in the outlet of the membrane is specific to the couple tracer/membrane. But all the theory of the RTD is applicable to such stimulus-response experiments. Indeed, the way through the pump and the pipes may smoothen the membrane response and consequently hide some particularity of the signal indicative of fouling. From a mathematical point of view, y is related to x by the convolution product:

(A) INJECTION DEVICE ® PERMEATE

by-pass " d i " ~

A , " . . . . . . . '

REJECT

03) INJECTION DEVICE ®

1 b " . . . . . . . :

REJECT

Fig. 1. Flow noises during RTD experiment. A, when membrane being studied. B, for apparatus function measurement (membrane by passing).

186 E. Roth et al. / Desalination 121 (1999) 183-193

l

y(t) =fx(u).g(t-u).du, for all t>0 (5) 0

This equality can be written as Y=G-X with, Y= [V(to),...y(tu)] r, X=[x(to),...(t,)]Tand

where g is the stimulus response of the other elements of the experimental design (i.e., the pump and the pipes). Therefore, in order to obtain x, we had fn'st to determine g(t) (by by-passing the membrane (Fig. lb), and second, to reduce x from the observed y and g in (5).

The observed signalsy and g are in fact discrete (resp. Y(t~)i~o and g(ti)~o). But since the measure- ment frequency is high enough, relation (5) can be approximated by

k

for allk--0,...N y(tk)=j~=x(tj)'g(tk_j)'At (6)

where (N+ 1) is the number of observation times.

G =

g(to) o . . . . . . . . . o g(',) g('o) o . . . . . . o g(,~) g( , , )g(ro) o o

! ! ! i i !

i ! i ! ! i

~('N) g(tN-,) "" g(t0)"'" {3

(7)

To deduce Xfrom (6), it is equivalent to invert the matrix G. Because of the structure of G and the measurement errors, this is a numerically unstable

SOFTENED FEED [ WATER

recycling I NI . t . / . . . . . . . . . . . . . _>>_ . . . . . . . . K o. . . . . . . . . . . . . . . . . ~ , , , ~

f •

' //

L t

. . . . . . . . . . . . . . . . . . . . . . . . - 2 1 ; - . . . . . . . . . . . . . . . ~T !<"'(~rW . . . . . . . . . . . . . . . . . . . . . . . . . . . ~ ~ " I

••• . . . . . . . . . . . . . . . . . . . . . . . . . . ••

REJECT >> '

[~irs t r-ev-ers-e- os-mosis- - "~, Istage RO1

recycling

[~c-o-.-d- r-~-~-~is-~- osmo~i~ ": i l ,stage RO2

ULTRAPURE WATER

F ig . 2. R e v e r s e o s m o s i s a s s e m b l y in " H 6 p i t a l P a s t e u r " o f C o l m a r .

E. Roth et al. / Desalination 121 (1999) 183-193 187

operation, and the result is quite unsatisfactory. In order to improve the deconvolution model, we include a random measurement error term [ 10] and obtain Y=GrX+W with W = [w(to),...w(tN)] r. The w(t~)~o~ v are uncorrelated, zero mean random variables. To reconstruct X is, then, a classical filtering problem. The discrete Kalman filter is well adapted to solve this problem and has the advantage of being easily implemented. It provides the solution , ~ o f X in the sense that (Y-G.~) r . (Y-G" ~) is small [10].

The results obtained through this procedure for the RTD of salt in the membranes are presented in Figs. 3 and 4.

2.3. Rejection

The conductivity ~:, which can easily be measured in the outgoing flow, is proportional to the concentration. We can also define R', the conductivity rejection, by

R' K r - K p - - - ( 8 )

K r

~:r is the rejection solution conductivity and Kp the conductivity at the membrane wall. R' might be

Cm-G representative of R R - in low con-

cm centration situation where we can estimate K~ ~- r,~ (Cm and Cp denote, respectively, the solute con- centration near membrane surface and in the permeate).

The rejection is a function of temperature [11]. We therefore were careful that temperature ranged between 18.0-~0.3 °C during the stimulus-response experiments.

2.4. Pure water and solute permeabilities

Steady-state permeation of water and solute molecules through a RO membrane can be

0.10 ~ ,

, 0 . . . . 0 Fl-[

o.o6 a,~ "~. ' , l , = t ,

#" ,%. 0-, I I I m 0 2O 4O

t (s) 60

Fig. 3. Sodium chloride distribution in the rejection side.

t ' ' I

0.10

O.OS I ', t J , •

T

G f [ ~ = = I o 20

V vFT5 0 oFT7

O---- e F"nB

t ( ~

Fig. 4. Sodium chloride distribution in the permeation side.

expressed as [ 12]

Qp = A "S" (AP - o" A~) (9)

188 E Roth et al. / Desalination 121 (1999) 183-193

4 = B . ( c : c )+(l-o). S

3. Experimental (10)

3.1. Membranes

where A is the pure water permeability, ~ P is the transmembrane pressure drop and An is the osmotic transmembrane pressure drop, o is the reflection coefficient, ~ is the solute molar flux, B is the solute transport parameter, C w is the concentration on the membrane surface and cis an arithmetical average between the solute concen- tration near the membrane surface and the concentration in the permeate.

For a perfect membrane, o = 1. Then equations (9) and (10) give:

= A.S.(AP-A ) ( l l )

We used polyamide spiral-wound membrane elements FILMTEC TW 30-4040. The spiral- wound geometry has been described many times [13]. Five membranes were tested: a new one (FTN) and four used ones (FT3, FT5, FT6, FT7) coming from the ultrapure water production plant of H6pital Pasteur (Colmar, France) and which had been producing ultrapure water for hemo- dialysis for 4 years before being changed because of fouling problems.

Fig. 2 describes the ultrapure water production unit of H6pital Pasteur and, in particular, the position of the seven membranes. The membranes FT3, FT5, FT6 and FT7 were tested.

a, (12)

2.5. Solvent and solute permeabilities joint evolution with fouling

The solvent and solute permeabilities coefficients A and B appearing in Eqs. (11) and (12) are characteristic of the membrane state, and their evolution indicates the membrane wear mechanism [6]:

• a decrease of A, B remaining constant, indi- cates that the fouling layer is compacting.

• a simultaneous decrease ofbothA and B means the fouling layer as well as the membrane are compacting.

• an increase of B or bothA and B indicates that the membrane structure chemical decompo- sition is occurring.

• a decrease of A and an increase of B indicate that the fouling layer compaction and the chemical changes of the active layer are occurring at the same time.

3.2. Pilot

The experiments were carried out with the RO pilot described in Fig. 1. Fig. 1 a shows in bold the flow way during rejection experiments with the membrane or during rejection measurements. Fig. lb shows in bold the flow way which by- passes the membrane during the measurement of the apparatus function during stimulus-response experiments.

The initial configuration of this pilot was modified to be able to make stimulus experi- mentation with the addition of an injection system among the pump, on-line conductivity detectors on permeate and reject and a possibility of by-passing the membrane to measure the RTD in pipes and pump (Fig. lb).

The feed water of the pilot used during the stimulus experiments was ultrapure water stocked in a tank.

3.3. RTD experimental conditions

We worked at Qp = 4.91×10 -5 m 3 s -1 and Q 7 1.41×10 -4 m 3 s -I (the rejection flow rate) in order to have the same velocities of the reject and the

E. Roth et al. / Desalination 121 (1999) 183-193 189

permeate for each tested membrane. That made us able to compare the RTD. Depending on the membrane, feed pressures ranged between 13.5 x 105 Pa and 15.5 x 105 Pa. We checked that the pressure did not influence the RTD unlike flow. Temperature ranged between 18.0~ 0.3 °C.

Qp(20oc)__ n(z)"QS) (13) rl(20°C)

where rl(T ) is the solution viscosity at the temperature. The pure water permeability of each membrane is deduced from Eq. (11) and presented in Table 1.

3.4. Detection and acquisition

Sodium chloride concentrations in the rejection side and in the permeation side were determined using a CDM230 conductivity meter and a calibration curve. To collect data a TURBO PASCAL acquisition program was connected to the conductivity meter and worked with a 5Hz frequency.

3.6. Rejection measurement

Membrane rejection performances were established by making reverse osmosis on tap water. The feed, permeate and reject flow conductivity were measured at steady state. Experiences were carried out at T=16.5+/- 0.3 °C. R ' values are presented in Table 1.

3.5. Pure water permeability measurement

For each membrane the permeate flow Qp produced by ultrapure water RO was measured for applied feed pressures included between 12.5 × 105 and 15.5x 105 Pa. Permeate flows strongly depend on temperature: they are expressed for 20 ° with the relation [6]:

Table 1 Membrane characteristics

4. Results and discussion

4.1. Sodium chloride stimulus-response experi- ment results

4.1.1. Rejection side

For all tested membranes, the distribution of salt in the rejection side is roughly symmetrical (Fig. 3). A previous work dealing with tracing of the rejection side of reverse osmosis hollow fiber modules with calcium chloride shows that a

FTN FT3 FT5 FT6 FT7

A (20°C) (xl0 -li m.s -1 .Pa -l)

R' (%) T = 16.5±0.5°C Qp (m3.s -1) Qr (m3.s-1)

Reject flow, RTD, t-(s) Characteristic, 0 2 (s 2)

Permeate flow, RTD, 7 (s) Characteristic, 0 2 (s 2)

5.4 5.7 4.7 5.2 4.7

99.2 92.3 91.5 81.3 96.5 4.9×10 -5 5.4x10 -5 4.3x10 -5 4.9x10 -5 4.0×10 -5 1.44×10 -4 1.39x10 -4 1.50x10 -4 1.44x10 -4 1.53x10 -4

18.9 24.2 21.7 20.8 20 26.5 47.4 38.1 38.9 28

20.9 15.4 17.0 11.1 17.3 44.2 133.3 76.4 62.8 70.7

190 E. Roth et al. / Desalination 121 (1999) 183-193

complete mix time variable fit better experimental data than a plug flow model [14]. Stimulus- response tests on spiral-wound elements with sodium or calcium chloride reveal that a plug flow with dispersion model seems to describe the flow pattern [15]. Our aim was to differentiate the stimulus response of a used membrane from that of the new one. We can note that the mean residence time Y and the variance o 2 allow distinguishing them from each other (Table 1). For fouled membranes (FT3, FT5, FT6 and FT7), the mean residence times of salt in membrane range between 20.0 s and 24.2 s and are greater than in the new membrane (FTN), for which t= l 8.9 s. Moreover, the variance, which represents the distribution's spreading, increases for the fouled membranes (Table 1). First, the deposited layer might be an obstacle to the salt crossing, and second, the rejection of the membrane seems to decrease with use. Nevertheless, the lack of a trail on distribu- tions indicates that salt is not trapped in the biofilm matrix.

4.1.2. Permeate side

For the new membrane (FTN), the distribution of sodium chloride collected in the permeate side, is unimodal (Fig. 4), with a mean residence time of 20.9 s and a variance of 44.2 (Table 1). It is not as symmetrical as the distribution obtained in the rejection side, which is due to smaller flow velocities and other effects.

The distribution of salt in the fouled mem- branes is shifted forward (Fig. 4) so that the mean residence times of salt are smaller than in the new membrane (Table 1).

For the fouled membranes FT6 and FT3, we note a singular distribution form with the presence of two modes. The existence of a salt leakage peak, as well as earlier detection of salt for all the fouled membranes, give evidence of the membrane structure modification. The intensive use of the membranes might have enlarged the pinholes initially present in the membrane structure [16]:

salt and solvent permeabilities increase. The values of salt rejection and pure water permea- bilities (Table 1) confirm this interpretation. According to their higher water permeabilities and worse solute rejections, membranes FT6 and FT3 (whose distribution shows a leakage peak) are the membranes with the most modified structure. This demonstrates that solute permeation in a used membrane might no more be only due to diffusion but also to pore flow.

Moreover, we note that the distribution of salt in a fouled membrane never spread out over the new membrane's one. The deposited layer seems to obstruct a large part of the membrane. The flow shall then be allocated on a smaller surface and have higher permeation velocities.

4.2. Explanation of the different permeation ways

Pore enlargement and surface occlusion by the deposited layer are two phenomena that occur in the used membranes. It turns out that each permeate distribution, Ep(O, can be fired by a weighted average of Gaussian distribution, G(t), the new membrane distribution, E~p~(t), and the z seconds shifted new membrane distribution,

a s

Ep(t) = a.G(t) + b.EpeW(t) + c.ETW(t+x) (14)

with

exp[-(t-~t) 2 ] anda+b+c=l (15) c t)-o. [2.o2J

where ~t and o 2 are, respectively, the mean and the variance characterizing the Gaussian distribution.

The coefficients a, b and c represent the fraction of salt permeation for, respectively, the Gaussian, new membrane and shifted new membrane distributions:

E. Roth et al. / Desalination 121 (1999) 183-193 191

• a represents the membrane structure modifica- tion in the sense of a pore enlargement.

• b represents the fraction of membrane surface in which the salt permeation seems to occur as in the new membrane.

• c represents the fraction of membrane surface where salt permeation is disturbed by the deposited layer. It plays the role of a second membrane.

Table 2 shows that the FT3 membrane is the only one for which c~O. For all the other membranes, the distribution is a fit by a weighted average of a Gaussian distribution, which takes only into account the pore enlargement and the distribution of the new membrane. In fact, FT3 has belonged to the first stage of RO in H6pital Pasteur. It was fed by pre-treated water unlike the other three (FT5, FT6 and FT7) belonging to the second stage, which were fed by the first stage of RO. A less laden feed water could explain the lack of a shitted term in the average. Some binocular photographs of the membrane FT3 surface (Fig. 5) and the membrane FT6 surface (Fig. 6) confirm the first RO stage is covered by a fouling layer instead of the second-stage membranes. Moreover, we note that for the membrane whose distribution is bimodal (FT3 resp. FT6), the coefficient a is about the same (0.27 resp. 0.3). The Gaussian characterizing the structure modification has quite the same mean residence time and variance (Table 2). The membrane worn

Fig. 5. Binocular photography of membrane FT3 surface area (× 15).

Fig. 6. Binocular photography of membrane FT6 surface area (× 15).

Table 2 Average characteristics for each membrane

FT3 FT5 FT6 FT7

~t(s) 6.1 10.8 7 II 02 (s 2) 10.2 20.2 8.4 16 a 0.27 0.6 0.3 0.55 b 0.57 0.4 0.7 0.45 c 0.16 0 0 0

out seems in this case to have been independent of the feed water nature (we remember that FT3 and resp. FT6 belong to the first and resp. the second RO stage). Their pure permeabilities are both higher than those of the new membrane. Their solute rejection are as much worse than those of the new membrane by several percent (Table 1).

The two other membranes (FT5 and FT7) distribution present the same kind of average (Table 2). The Gaussian term is characterized by a

1 9 2 E. Roth et al. / Desalination 121 (1999) 183-193

mean residence time about 4 s higher than those for a bimodal distribution. Structure modification is occurring.

Rejections and pure water permeabilities of fouled membranes are usually lower than the new membrane rejection and permeability. Only membrane FT3 permeability is higher. We can note that the membrane with bimodal distribution has low rejections and high permeabilities. This is to be connected to Kimura's observation of A and B tendencies with membrane wear and is due to the chemical changes of these membranes [6]. The global measured permeability of the membrane takes into account two opposite phenomena: on one hand the structure modification by enlarge- ment tends to improve A, and on the other hand, the membrane or the deposited layer compaction tends to diminish A. The pure water permeability of membrane FT3 is greater than those of the new membrane in spite of the proven presence of a consequent fouling layer (c~0, Table 2). The phenomenon of pore enlargement dominates. For membranes FT5 and FT7, the compaction of the membrane tends to diminish A. But on the other hand, the low rejections (Table 1) of these mem- branes indicate the membrane structure has worn out and become less selective for solutes.

5. Conclusions

Stimulus-response experiments can point out the state of wear for a membrane by comparing the sodium chloride distribution in the outlets of the new membrane. This method is the first to reveal the transport phenomena that occur in the membrane: the presence of membrane leakage when a Gaussian in the average, deep fouling covering the membrane surface when presence of the shifted distribution in fouling. Coefficients give the intensity of each of these two phenomena as well as the fraction of membrane not covered by fouling and whose structure is not modified.

This method indicates when the wear process takes place. There is nothing to do against it in

contrast with the presence of a deposited layer which could be minimized by regular cleaning. This work should be completed with further membrane structure investigation to qualify this structure wearing out.

6. Symbols

A a , b , c - -

B

C

c ( o - -

e ( 0 - -

e (0 -

_ _

G ( O - -

g ( t ) - -

O - - R R' S T t

x ( t ) - -

y ( O - -

z ( O - -

Pure water permeability, m.s- ~.Pa- Coefficients in Eq. 18 Solute transport parameter, m.s-I Concentration, mol.m -3 Measured signal Arithmetical average of concentra- tion in Eq. 14, mol.m -3 Exit age distribution (RTD) Membrane RTD New membrane RTD Shifted new membrane RTD Gaussian distribution Stimulus response of the apparatus Solute molar flux, m.s -~ Flow rate, m3.s -1 Rejection Conductivity rejection Membrane surface, m 2 Temperature, °C Time, s Mean residence time, s Membrane RTD Normed outlet detected signal Normed inlet detected signal

G r e e k le t ters

m

A P - -

AT~ m

O 2 B

O

Conductivity, S.m -1 Transmembrane pressure, Pa Transmembrane osmotic pressure, Pa Variance, s 2 Reflection coefficient in Eqs. 13 and 14

E. Roth et al. / Desalination 121 (1999) 183-193 193

At Ix m

Viscosity, cp Measurement step, s Mean residence time of the Gaus- sian distribution, s

Subscripts

b - - Bulk m - - Membrane p - - Permeation r - - Rejection w - - Membrane wall

References

[1] R.A Laurence and S.T. Lapierre, Amer. J. Kidney Dis., 25(5) (1995) 738.

[2] G. Riondet, E. Lua and B.M. Certain, S.T.P. Pharma- pratiques, 1(2)(1991) 187.

[3] M.L. Durham, Ultra Pure Water, 9 (1989) 30. [4] H.C. Flemming, Biofouling in water treatment in

biofouling and biocorrosion in industrial water systems. Proc., International Workshop on Industrial

Biofouling and Biocorrosion, Stuttgart, 1990; Springer-Verlag, Berlin, Heidelberg, 1991.

[5] E. Roth, B. Fabre, A. Accary and B. Failer, Rev. Sci. Eau, 3 (1998) 409.

[6] S. Kimura, Desalination, 100 (1995) 77. [7] P.V. Danckwerts, Chem. Engineering Sci., 2(1)

(1953) 1. [8] J.P. Leclerc, C. Detrez, A. Bernard and D. Schweich,

Revue de l'Institut Franrvais du P~role, 50(5) (1995) 641.

[9] O. Levenspiel, Chemical Reaction Engineering, 2nd ed., Wiley, New York, 1972.

[10] R.E. Kalman, SIAM, J. Control, 1 (1961) 152. [11] N.M. AI-Bastaki and H.I. AI-Qahtani, Desalination,

99 (1994) 159. [12] O. Kedem and A. Katchalsky, Biochimica and

Biophysica Acta, 27 (1958) 229. [13] J.M. Dickson, J. Spencer and M.L. Costa, Desali-

nation, 89 (1992) 63. [14] W.N. Gill, M.R. Matsumoto, A.L. Gill and Y.-T. Lee,

Desalination, 68 (1988) 11. [15] D. Van Gauwbergen and J. Baeyens, Desalination,

110 (1997) 287. [16] R.I. Uruma and B.J. Marinas, J. Membr. Sci., 123

(1997) 267.