Desalination 365 (2015) 8–14

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Desalination

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Practical use of standard pore blocking index as an indicator of biofoulingpotential in seawater desalination

Sanghyun Jeong, Saravanamuthu Vigneswaran ⁎Faculty of Engineering, University of Technology, Sydney, P.O. Box 123, Broadway, NSW 2007, Australia

H I G H L I G H T S

• Practical method of biofouling potential for seawater desalination was studied.• Assimilable organic carbon is related to low molecular weight organics in seawater.• Standard blocking index (Ks) using ultrafiltration was used as biofouling index.• Ks was found to have a linear relationship with assimilable organic carbon.• Ks is a representative in-situ indicator of biofouling in desalination plants.

⁎ Corresponding author.E-mail address: Saravanamuth.Vigneswaran@uts.edu.

http://dx.doi.org/10.1016/j.desal.2015.02.0150011-9164/© 2015 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 12 November 2014Received in revised form 4 February 2015Accepted 7 February 2015Available online xxxx

Keywords:Assimilable organic carbonBiofoulingDesalinationModified fouling indicesSeawaterStandard blocking index

A practical approach to evaluate the biofouling potential of feed waters for seawater reverse osmosis (SWRO)was investigated. Assimilable organic carbon (AOC) and modified fouling index through an ultrafiltration10 kDamembrane (MFI-UF10)weremeasured for seawater and pretreated seawater. The pretreatments adoptedwere dual media filtration (DMF) coupled with coagulation and submerged membrane adsorption bioreactor(SMABR). Lowmolecular weight neutrals (LMW-N) responsible for biological growth (or biofouling) constitutedthe major component in seawater and pretreated seawater. A very good linear relationship was observedbetween AOC concentration and LMW-N concentration. A detailed study on various fouling indices revealedthat standard blocking index (Ks) calculated from MFI-UF10 correlated with AOC concentration. This indicatesthat MFI-UF10 test can serve as a preliminary indicator of AOC and LMW-N (which are biofouling precursors).MFI-UF10 can also be used directly in desalination plants.

© 2015 Elsevier B.V. All rights reserved.

1. Introduction

Seawater reverse osmosis (SWRO) has matured as a technology andis employed in large-scale desalination plants in all coastal areas aroundthe world with limited natural hydrological resources [1]. SWROundergoes biofouling (biological fouling) which is difficult to control.Microorganisms such as bacteria, fungus or algae can produce biopoly-mers that aggregate on the surfaces of membranes and develop a bio-film. This leads to a serious operational problem since it acceleratesthe chemical decomposition of RO membranes [2]. The major effect ofbiofouling is direct microbial attack of the membrane, causing decom-position of membrane. Control of biofouling requires more frequentchemical cleaning andmoremicro-biocide. Thiswill result in a rapid de-composition of themembrane due to the high pH of additives used. Thecosts related to biofouling are generally composed of: (i) additional

au (S. Vigneswaran).

energy costs (due to an increase in pressure dropwhich demands an in-crease of feed pressure); (ii) additional chemical cleaning (and wastedisposal) increased down time; and (iii) reduced membrane life.

Early biofouling warning enables preventive measures to be under-taken, either by pre-treatment optimisation or by preventive mem-brane cleaning. Cleaning at an early stage requires less chemicals andless down time and reduces the risk of irreversible fouling and mem-brane damage. Cleaning is more successful at early stage biofouledmembrane systems [3,4]. Vrouwenvelder et al. [5] estimated the poten-tial savings of an early warning of biofouling. It is estimated to be 10% ofthe annual membrane replacement and chemical costs (including laborfor cleaning) and up to 5% of energy costs. The potential annual savingsbased on an average capacity of SWRO plant of 10,000 m3/h can be ashigh as US $2 million.

Early biofouling can be noticed through the measurements of bio-fouling potential, these being the amount of potential biomass andavailability of nutrients. The accumulation of biofilm depends on differ-ent factors, namely: i) nutrient concentration, type and availability; ii)shear forces; and iii) mechanical stability of the biofilm matrix [6].

9S. Jeong, S. Vigneswaran / Desalination 365 (2015) 8–14

Adenosine triphosphate (ATP) method is a good indicator for thepresence of microbial number in biomass content (thus the biofoul-ing potential). When subjected to the light and luciferin–luciferase isadded, ATP produces luminescence, which can be detected andmeasured in relative luminescence units (RLU) [7]. However, to ef-fectively control the biofouling, biodegradable organic matter(BOM) has to be removed with the microbial inactivation. This is be-cause a few surviving cells will enter the system, adhere to surfaces,and multiply at the expense of biodegradable organic substancesdissolved in the bulk aqueous phase, even 99.99% of all bacteria areeliminated by pre-treatment (e.g., microfiltration or biocideapplication) [6].

According to a previous study BOM is the limiting nutrient forbacterial growth [8]. BOM concentration is quantified as two things—assimilable organic carbon (AOC) and biodegradable dissolved or-ganic carbon (BDOC). Both are bacterial regrowth potential indica-tors. Dissolved organic carbon (DOC) and BDOC are typically morerelated to higher molecular weight compounds (e.g., humic acids),while lower molecular weight compounds are quantified as AOC(e.g., acetic acids and amino acids). AOC refers to a fraction of “labile”or “bio-available” DOC that is readily assimilated and utilized by mi-croorganisms resulting in an increase of biomass. AOC has actuallybeen correlated with bacterial counts in water samples [9]. Thus,AOC is the main component which influences biological fouling (bio-fouling). Recently, Jeong et al. [10] developed a direct biolumines-cence measurement method using Vibrio fischeri MJ-1 (V. fischeri)to measure AOC concentration in seawater samples since to datethere no representative method has been developed. This methodcan estimate the AOC concentration within a short time of 1 h.However, it is still difficult to implement this method on-site in thedesalination plant.

Currently, most operating SWRO plants use the silt density index(SDI) to test and evaluate the produced pretreated seawater. However,SDI can only be used as amethod tomeasure and predict the particulatefouling potential of feed water [13], not the organic and biofouling po-tential. Therefore, the overall aims of this paper are to: firstly, under-stand AOC compounds in seawater and pretreated seawater samplesfor developing a suitable and an accurate detection and assessmentmethod of biofouling; and secondly, develop a suitable biofoulingindex to represent the AOC.

2. Experimental

2.1. Seawater and pretreated seawater

The seawater was drawn from Chowder Bay, Sydney, Australia,pumped from 1 m below the sea surface level and filtered througha centrifuge filtration system to remove large particles. The averagevalues of pH, total suspended solids and turbidity of seawater usedin this study were 8.2, 3.6 mg/L and 0.4 NTU, respectively. Twelveseawater samples were collected during this study. The seawaterwas then fed into two different types of pretreatment systems,namely dual media filter (DMF) and submerged membrane adsorp-tion bioreactor (SMABR). They were operated with continuous feed-ing of seawater. DMF was packed with sand and anthracite (20 cmand 70 cm from the bottom, respectively) and operated with andwithout in-line coagulation of 0.68 mg/L of ferric sulphate. It wasoperated for 14 days and 45 samples were collected for analysis dur-ing this period. A semi pilot-scale SAMBR with powder activated car-bon (PAC) addition was also operated for 56 days. Sixteen sampleswere analyzed during this period. In SMABR, PACwas used for organ-ic adsorption and microbial development to degrade the organicsalready adsorbed onto PAC. The detailed experimental designs ofeach pretreatment system have been described in previous studies[14,15].

2.2. Organic fractionation by liquid chromatography-organic carbondetector

Different organic fractions in DOC present in raw seawater and per-meate (or effluent) fromDMFand SMABRwere examined using a liquidchromatography with organic carbon detection (LC-OCD). Biopolymers(BP), humic substances (humics, HS), building blocks (BB), and lowmo-lecular weight neutrals (LMW-N) were fractionated from DOC using asize exclusion chromatography column according to their molecularsize. The detailed specification and information concerning LC-OCDhas been published recently in another study [16]. A dual column wasused for the saline sample in LC-OCD analysis. Injection volume and re-tention time were 2000 μL and 180min, respectively. LC-OCDmeasure-ment for each sample was done in duplicate and themean value of DOCis reported in this paper (variation was less than 5%).

2.3. Assimilable organic carbon measurement

In this study, a newly developed bioluminescence method was usedto measure AOC concentration of seawater and pretreated seawatersamples. This method uses V. fischeri MJ-1 to very accurately measurethe AOC within 1 h. A detailed procedure of AOC measurement can befound elsewhere [10]. Glucose was used as an AOC standard carboncompound in this test. Thus, AOC concentration is represented as μg-Cglucose equivalents/L.

2.4. Fouling indices

Fouling indices weremeasured at constant pressure dead-endmodeusing a lab-scale membrane filtration unit (Fig. 1). In dead-end filtra-tion, the blocking laws are used as a resistance model as derived byHermia [11]. It describes the total resistance as a function of the filtratedvolume or the filtration time.

Cake filtration mechanism is commonly used to model particle re-tention and flux decline. However, blocking laws do not model particleretention, as the blocking models do not add insight about, if foulingchanges the retention characteristics, they onlymodel how the deposit-ed fouling particles are placed onto/into themembrane surface and howthese influence the resulting fluxes. The fouling mechanism is inferredfrom the shape of the filtration curve. The assumption which leads tothe best fit is an indication of the fouling mechanism [12]. The slope ofthe filtration curve is an indication of the amount of foulants in thewater. Hence, thismay be regarded as ameans tomonitorwater quality.Ideal cake filtration is based on the assumption that all particles are ac-cumulated in a cake layer. Furthermore, it is assumed that the cake re-sistance is proportional to the thickness of the cake. The standardblocking law is based on the assumption that all particles settle insidethe pores. Hence, the occupied pore volume is proportional to thefiltrated volume. The Hagen–Poiseuille equation is used to relate thepore volume (diameter) to the resistance.

2.4.1. Silt density index (SDI)In SDI test, the time required to filter afixed volume (500mL) of feed

water through a standard 0.45 μm pore size microfiltration (MF) mem-branewith a diameter of 47mmunder constant-pressure (207±3 kPa)wasmeasured. The difference between the initial time and the time of asecond measurement (after silt built-up) represents the SDI value. Thecalculation of SDI is as follows:

SDI ¼1−ti=t f

� �

T� 100 ð1Þ

where, ti and tf are the initial andfinal time in seconds required to collectthe 500 mL permeate respectively, and T is the total elapsed flow time(in this study, 5 min, thus is called SDI5). Referring to the seawater

Fig. 1. Schematic diagram of a lab-scale membrane filtration for fouling indices.

10 S. Jeong, S. Vigneswaran / Desalination 365 (2015) 8–14

and pretreated sample (low turbidity sample), the plugging ratepercentage exceeds 75% [17]. Thus SDI5 is used in this investigation.

2.4.2. Modified fouling index with microfiltration 0.45 μm (MFI-MF0.45)Both SDI and MFI-MF0.45 measurements were conducted under the

same constant-pressure dead-end filtration process but differed onlyin terms of the data recording and processing. For SDI calculation, onlyti, tf and T are recorded and transferred into Eq. (1) while continuous re-cording of cumulative permeate volume and filtration time is requiredfor MFI-MF0.45 calculation:

tV=A

¼ 1J0

þ Kc

2V=Að Þ: ð2Þ

In Eq. (2), t is the filtration time, V is the cumulative permeate vol-ume, A is the effective filtration area, and J0 is the initial flux. Kc (s/m2)is the coefficient of cake filtration model. From the Eq. (2), the linearplot made between t / (V/A) and V/A shows that the filtration in MFI-MF0.45 follows the cake filtration model [18]. The MFI is based only onthe cake filtration mechanism and is dependent on particle size. Thisis based on the Carman–Kozeny equation for specific cake resistance[19,20]. Here, the MFI can only be used as a basis for modeling flux de-cline in membrane systems, if cake filtration is dominant mechanism[20]. Cake filtration only occurs if: a) particles are larger than pore size(which leads to total rejection) or b) particles tend to form aggregatesonto the membrane surface, leading to a dynamic cake (not accompa-nied by retention).

2.4.3. Modified fouling index with ultrafiltration (MFI-UF) and standardblocking index (Ks)

SDI andMFI-MF often fail to predict organic fouling due to their lim-itation of capability to measure fouling potential by organic adsorption.In this study, UF membrane with smaller molecular weight cut-off(MWCO) was used for better prediction of organic fouling potential.Since organics present in seawater are smaller than the UF membrane'spore size (MWCO), organics are adsorbed either onto the pores of themembrane or on its surface. Modified fouling index (MFI) was mea-sured using hydrophilic UF membrane (material: Polyethersulfone,PES, made from NADIR®RM). In each MFI test, new UF membranes(with MWCO of 10 kDa and diameter of 47 mm) were used toavoid the residual fouling. Pure water flux of 10 kDa UF is higher than150 L/m2h at 3 bar. The retention of PVP K17 by UF 10 kDa is 63–85%(the information was provided from manufacturer). Zeta potential andcontact angle of UF 10 kDa are−13 ± 1 mV (at pH 7) and 44 ± 5°, re-spectively (The values weremeasured in our laboratory). From the pre-liminary tests with UF membranes of different MWCOs of 5, 10 and20 kDa, 10 kDamembranes was chosen as the fouling pattern which re-sulted in a linear plotwithfiltration time. Subsequently, in this study, UF

10 kDa membrane was employed. Here, MFI using 10 kDa UF mem-brane is represented as MFI-UF10. The raw water and treated seawaterwere pressurized at 2.0 bar (207 ± 3 kPa) using N2 gas at the roomtemperature.

Standard (pore) blocking coefficient (Ks) was calculation using thefollowing equation (Eq. (3)):

tVð .

AÞ

¼ 1J0

þ Ks

2t ð3Þ

where t is the filtration time, V is the cumulative permeate volume, Ais the effective filtration area (0.001735 m2), J0 is the initial flux, andKs (1/m) the coefficient standard blocking model. From Eq. (3), a linearplot of t/(V/A) vs t indicated a proof of the standard blocking [21].Models were postulated for the following three mechanisms, assumingthat the filter media is comprised of a mass of fine capillaries throughwhich liquid flow. (1) Complete blocking occurs when particles plugthe capillaries; (2) Cake filtration involves the formation of a porouslayer on the surface of the medium, thereby imposing additional resis-tance; (3) Standard blocking occurs when the solids adhere to thewalls of the capillaries, thus progressively reduces their internal diame-ter. The thirdmechanism is termed “standard blocking” because it is ob-served to be the most common in the absence of cake filtration.

3. Results and discussion

3.1. DOC and organic fraction in seawater

In this study theDOC concentrations of seawater and pretreated sea-waterwere analyzed using LC-OCD. The proportion of each organic frac-tion in DOC was calculated using software (ChromCALC, DOC-LABOR,Karlsruhe, Germany) based on chromatogram obtained from LC-OCD.Fig. 2 presents the average concentration of DOC, HS and LMW-N in sea-water (SW) and pretreated seawater samples (DMF effluent andSMABR effluent). DMF removed 20% of DOC from seawater containingthe reduced amount of 24% of HS and 19% of LMW-N. Compared toDMF, the reduction of LMW-N by SMABR was higher (around 50%from seawater) since biological degradation had occurred in SMABR.The removal of HS by SMABR (28% from seawater) was similar to thatdone using DMF.

In SW and pretreated SW samples (DMF effluent and SMABR efflu-ent), the sum of BP, BB and LMW acid concentration is less than 5% oftotal DOC. Consequently these three organic compounds were notdiscussed in this study. HS and LMW-Nwere found to be the dominantorganic compounds (higher than 95%) in DOC of seawater samples.Thus, the main organic foulants on the subsequent RO membrane areHS and LMW-N even though BP (or extracellular polymeric substances;

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

DO

C

HS

LM

W-N

DO

C

HS

LM

W-N

DO

C

HS

LM

W-N

SW DMF effluent SMABR effluent

Con

cent

ratio

n (m

g/L

)

Fig. 2. Concentration of DOC, HS and LMW-N of seawater (SW) and pretreated seawatersamples (DMF effluent and SMABR effluent).

11S. Jeong, S. Vigneswaran / Desalination 365 (2015) 8–14

EPS) can also be present in the membrane foulant since they have highmolecularweight and are sticky in nature.With regard to biofouling, HSis relatively less utilized by microbes compared to LMW-N. This is be-cause HS has stable and complex structures and their molecular weightis high at approximately 1000 Da. On the other hand the molecularweight of LMW-N is less than350Da and they comprise acetate, carbox-ylic acids, and aminoacids that can be easily utilized bymicroorganisms.Therefore, LMW-N is one of the major biofouling forming organic com-pounds (or biofouling precursors). As substrates for heterotrophic bac-teria LMW components are quantitatively more important thancomponents of high molecular weight (HMW). Organic acids, carbohy-drates, and amino acids constitute major classes of dissolved LMW or-ganic compounds, which are known as important potential sources ofcarbon and energy for marine microorganisms [22,23].

3.2. Relationship between LMW-N and AOC

In this study, AOC concentration was measured using a rapidbioluminescence test with V. fischeri MJ-1. Fig. 3 presents a goodcorrelation between AOC concentration and LMW-N concentra-tion (obtained from LC-OCD) both in seawater and pretreatedseawater with a high correlation factor (R2) of more than 0.98.

y = 21.97x

R² = 0.98

0

200

400

600

800

1000

1200

0 10 20 30 40 50

LMW

-N (µ

g/L)

AOC (µg-C glucose equivalents/L)

Fig. 3.Correlation between AOC concentration and LMW-N concentration of seawater andpretreated seawater samples.

Quantitatively speaking, LMW-N concentration is roughly 22times the value of AOC concentration as can be seen in Fig. 3(LMW-N concentration ≈ 22 × AOC concentration).

A previous study reported that both low molecular weight(LMW b 1 kDa) and high molecular weight (HMW N1 kDa) dissolvedorganic compounds and can be utilized by bacteria [24]. However, itemerged that the LMW fraction of DOC was utilized to a greater extentthan HMWDOC. As mentioned earlier, BOM can be classified into BDOCand the AOC. The role of BDOC as ameasure of biological stability is con-troversial since no correlation between AOC and BDOC in rawwater anddrinkingwater was found. Also, Van der Kooij [25] suggested that BDOCcould not be used to predict the regrowth level because no significantcorrelation was found between BDOC and heterotrophic bacteriacounts. Conversely, AOC concentration is one of themost important fac-tors in controlling the attached biomass and heterotrophic bacteria ac-tivity in water because AOC is the part of DOC that can be easilyassimilated by bacteria and converted into cell mass. The AOC wasquantitatively related to the microbial growth and biofouling in spiralwound RO membranes [26]. The results obtained from analysis ofseawater and pretreated seawater samples (n = 73) showed thatLMW-N is closely associated with AOC compounds. However, to mea-sure LMW-N specific equipment is required and measuring AOC mustbe carried out in very clean laboratory conditions. Thus it cannot beused for routine monitoring in the field. For this reason AOC test hasbeen applied to diagnose the microbial growth potential of the feedwater in laboratory-based process design and optimization studies [27].

Biofouling compromises the quality of RO product and this makesRO an expensive technology. To minimize the problems caused by bio-fouling in regard to the ROmembrane's performance, the challenge is tochoose the right monitoring and controlling techniques before it is es-sential. This is because applying these techniques is system-specific.Rapidmonitoring approaches are highly recommended to impose a sat-isfactory level of control over the biofouling problem in the industrial-scale ROmembrane system. Therefore, this study attempted to observethe relationship between the AOC value andMFI (the one which can bemeasured in the plant) to estimate AOC in a practical way.

3.3. Why not SDI or MFI-MF0.45μm?

At present, SDI (and sometimes MFI-MF0.45) is widely used in desa-lination plants. In this investigation, both SDI and MFI-MF0.45 values ofseawater and pretreated seawater were measured and compared withthe AOC concentration of corresponding samples (Fig. 4). As expected,AOC concentration had a good correlation neither with SDI 5 min(SDI5) nor with MFI-MF0.45. Currently there is no representative toolandmore specifically, there is no standard indicator to estimate the bio-fouling potential of waters loaded with biomass. SDI measurement isbased on the reduction of permeability with time of a water samplethrough aMFmembrane and, as such, it cannot give precise informationabout biomass. One study showed that there was no significant varia-tion of SDI in the filtered water, thus indicating that SDI is not sufficientto assess the pretreated water samples [28]. To overcome the deficien-cies of SDI, a MFI-MF0.45 has been developed. Likewise SDI, MFI-MF0.45test is based on the occurrence of cake filtration during a substantialpart of the test and this provides a more linear relationship with partic-ulate matter content, not dissolved organics [29].

Wei et al. [12] measured the volume filtered (V) with time (t) in aSDI approach for seawater in the SWRO under a constant-pressure(207 kPa) and dead-end filtrationmode. They found that t/(V/A) vs t re-vealed a very good linearity (correlation coefficient R2 N 0.99) from theearly stage of SDI test, indicating that standard blocking was the domi-nant fouling mechanism during the filtration process rather than cakefiltration. Very low concentration of suspended solids rejected by MFof 0.45 μm in seawater was the main reason why a cake layer did notform. High turbidity removal during the SDI test/MFI-MF0.45 was dueto the retention of organic colloids on and/or adsorbed in membrane

(a)

(b) (c)

y = 156.96x - 1537.4

R² = 0.5208

0

100

200

300

400

500

600

9.0 10.0 11.0 12.0 13.0

MFI

-MF 0

.45

(s/m

2 )

SDI5

y = 5.7256x - 36.971

R² = 0.09920

10

20

30

40

50

10.0 11.0 12.0 13.0

AO

C (µ

g-C

glu

cose

eq

uiva

lent

s/L

)

SDI5

y = 0.0309x + 20.096

R² = 0.13650

10

20

30

40

50

0.0 200.0 400.0 600.0

AO

C (µ

g-C

glu

cose

eq

uiva

lent

s/L

)

MFI-MF0.45 (s/m2)

Fig. 4. Relationships (a) between SDI5 and MFI-MF0.45, (b) between SDI5 and AOC and (c) between MFI-MF0.45 and AOC.

12 S. Jeong, S. Vigneswaran / Desalination 365 (2015) 8–14

pores. It can therefore be stated that standard blocking is the predomi-nant mechanism leading to the removal of colloidal organic substancesfrom the seawater. The standard blocking coefficient Ks (i.e., the slope oft/(V/A) ∼ t) could be used as a representative fouling indicator for sea-water because it showed good linearity with feed seawater containinglow turbidity. Both SDI and MFI-MF0.45 do not provide any informationregarding the nature of the foulants passing through a 0.45 μm mem-brane and the risks of biofouling [30].

3.4. MFI-UF and Ks vs AOC

Measuring AOC cannot often be done in desalination plants becausethere are practical difficulties. In this study an attempt was made to es-tablish a relationship between AOC (or LMWorganics) and Ks value ob-tained from MFI-UF10 (both for SW and pretreated SW samples). Thisstudy investigated the appropriateness of standard blocking index(Ks) calculated from MFI-UF. It should be noted that Ks is not an abso-lute value of biofouling potential.

As mentioned earlier, the reason why UF (of 10 kDa of MWCO) wasused is to adsorb more organics to represent biofouling (or biofoulingpotential) in desalination plants. Yu et al. [31] developed a multiplemembrane array system (MMAS) in which microfiltration (MF), ultra-filtration (UF), and nanofiltration (NF) membranes were connected ina series to evaluate the fouling potential of feedwaters for RO. They test-ed the MMAS using real seawater spiked with different target foulantsto check the responsiveness of the system to feed waters with differenttarget foulants after optimizing the series configuration of the MF, UF,and NF membranes in the system. The results showed that in the MFIto detect organic fouling a 10 kDa membrane exhibited the highestvalues.

In this study, MFI-UF10 was carried out using PES 10 kDa UF mem-branewith 1 L of RSWand pretreated seawater samples. UFmembranes

of different sizes (5, 10 and 20 kDa)were tested and 10 kDawas chosensince it exhibited a linear relationship between Ks value and AOC con-centration (or LMW organics) at a reasonable permeate flux that per-mitted the test to be completed within 90–120 min. Then optimalfiltration time to achieve organic fouling with LMW organics in MFI-UF10 was estimated based on DOC and LMW organics measurement(using LC-OCD) (Fig. 5). As can be seen fromFig. 5, BP, BBwere removedwithin the first 20 min of the test and their values were very low(0.032–0.042mg/L). Asmentioned in Section 2.2, LC-OCDuses a size ex-clusion chromatography (SEC) column according to their molecularsize. BP containing polysaccharides and proteins has higher molecularweight than 10 kDa. Thus, BP can be removed due to the size exclusionfrom the initial filtration time. BB is the hydrolysated compounds orweathering products of HS. The LMW-N concentration was high – inthe order of 0.6 mg/L – and they kept on being removed by UF10 evenfiltration lasting 90 min. HS was also high (in the order of 0.6 mg/L)and they were not removed by the UF10 filter used. Thus, LMW-N com-pounds were one of the dominant organic fractions in seawater whichwere rejected by UF 10 kDa membrane (UF10) with filtration time(Table S1 and Fig. 5). This test showing the fouling trend can be support-ed in determining LMW-N (or AOC compounds as observed inSection 3.2). Adsorption of LMW organic molecules (which are muchsmaller than theUFmembrane pore size orMWCO) could lead to signif-icant membrane fouling. Adsorption phenomena are driven by the na-ture of the interactions between the organic compounds and UFmembrane. Previous studies revealed that a hydrophilic membranewas more suited for adsorption of solutions containing LMW organiccompounds, as is the case for natural waters into membrane pores[32,33]. HS is hydrophobic-DOC fraction of seawater. These compoundsare mainly removed due to the potential electrostatic interaction [34].Thus, it could not be removed by hydrophilic UF membrane. Kennedyet al. [35] supported this rejection mechanism. Their study also showed

Fig. 5. Trend of organic fractions in MFI-UF10 filtration test.

13S. Jeong, S. Vigneswaran / Desalination 365 (2015) 8–14

that LMW-organics (like LMW-N) are mainly composed of hydrophilic-DOC. This led to more LMW-N rejection by hydrophilic UF membrane.These compounds could penetrate membrane pores and/or channelsof the cake layer resulting in standard blocking as also shown in a previ-ous study [12].

AOC concentrations were then measured and related to Ks values ofSW and pretreated SW samples (Fig. 6). Detailed values can be found insupplementarymaterial (Table S2). The results demonstrated that stan-dard blocking index (Ks) calculated fromMFI-UF10 correlated with AOCconcentration in seawater and pretreated seawater samples. Thismeansthat MFI-UF10 test can be used as an indicator of AOC as well as LMW-N

y = 29.476x + 0.5319

R² = 0.9746

0

5

10

15

20

25

30

35

40

45

50

0.000 0.500 1.000 1.500 2.000

AO

C (µ

g-C

glu

cose

equ

ival

ents

/L)

Ks from MFI-UF10 (1/m)

Fig. 6. Correlation of Ks value obtained from MFI-UF10 value with AOC concentration inseawater and pretreated seawater samples.

(which are biofouling precursors). MFI-UF10 test can be easily imple-mented in desalination plants since it can use a similar test unit suchas SDI (which is currently used in desalination plants). It is only requiredto replace different types of membrane (UF 10 kDa). However, to usethe Ks value in estimating the indicative biofouling potential in feedwa-ters to SWRO, further studies must be carried out.

4. Conclusions

LMW-N as a dominant DOC fraction in DOC of seawater andpretreated seawater showed a good correlation with AOC. This is dueto the fact that LMW-N is one of the major biofouling precursors.LMW-N concentration is closely associated with AOC concentrationboth in seawater and pretreated seawater samples. AOC can be estimat-ed using LMW-N concentration measurement (using the LMW-N andAOC calibration curve). A linear relationship between Ks values andLMW organics and AOC in the seawater and pretreated seawater usedand the operating conditions employed was observed. A good linearcorrelation between AOC and standard (pore) blocking coefficient (Ks)(obtained fromMFI-UF10 test) shows that Ks can be utilized as a prelim-inary indicator of AOC. This means that MFI-UF10 is a practical and in-situ method for early indication of biofouling in seawater desalinationplants. In this study, we chose one type of UF membrane mainly toshow the concept of Ks and its relationship with AOC and LMW or-ganics. However, further study is needed with different types of UFmembrane and different water sources to verify the relationship in aconcrete manner. The emphasis of the paper is (i) to show that thereis a linear relationship between Ks and AOC (or LMW organics) and(ii) the suitability of Ks as initial estimate of biofouling indicator on-site (instead of a laborious AOC and LMW analyses in advancedlaboratories).

14 S. Jeong, S. Vigneswaran / Desalination 365 (2015) 8–14

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.desal.2015.02.015.

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