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Page 1: Laporan Akhir Projek Penyelidikan - core.ac.uk · LaporanAkhirProjek Penyelidikan Jangka Pendek FinalReportO/ShortTerm Research Project 7. Sila sediakan laporan teknikallengkap yang
Page 2: Laporan Akhir Projek Penyelidikan - core.ac.uk · LaporanAkhirProjek Penyelidikan Jangka Pendek FinalReportO/ShortTerm Research Project 7. Sila sediakan laporan teknikallengkap yang

Laporan Akhir Projek PenyelidikanJangka Pendek

Modulated Nanofiltration Process for~

Pesticides Treatment

byProf. Abdul Latif Ahmad.,

Dr. Syamsul Rizal Abd. Shukor

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IlI.11IUNIVERSITI SAINS MALAYSIA

LAPORAN AKHIR PROJEK PENYELIDIKAN JANGKAPENDEKFINAL REPORT OF SHORT TERM RESEARCHPROJECTSila kemukakan laporan akhir ini melalui Jawatankuasa Penyelidikan di PusatPengajian dan Dekan/PengarahlKetua Jabatan kepada Pejabat Pelantar Penyelidikan

4. Tajuk Projek:Title ofProject

Modulated Nanofiltration Process for Pesticides Treatment

i) Pencapaian objektif projek:Achievement ojproject objectives

ii) Kualiti output:Quality ojoutputs

iii) Kualiti impak:Quality ojimpacts

iv) Pemindahan teknologi/potensi pengkomersialan:Technology transjer/commercialization potential

v) Kualiti dan usahasama :Quality and intensity ojcollaboration

vi) Penilaian kepentingan secara keseluruhan:Overall assessment ojbenefits

DD

DD

DD

DD

DD

DD

D

D

DD

0D

DD

EJD

DD

DD

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Laporan Akhir Projek Penyelidikan Jangka PendekFinal Report O/Short Term Research Project

7. Sila sediakan laporan teknikallengkap yang menerangkan keseluruhan projek ini.ISila gunakan kertas berasingan]Applicant are required to prepare a Comprehensive Technical Report explaning the project.(This report must be appended separately)Please refer to Appendix 2

Senaraikan kata kunci yang mencerminkan peny~lidikan anda:List the key words that reflects your research: •

Bahasa Malaysia

Membrane penurasan nanD

Racun perosak

Teknologi membran

Bahasa lnggeris

Nanofiltration membrane

Pesticides

Membrane technology

2

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Laporan Akhir Projek Penyelidikan Jangka PendekFinal Report O/Short Term Research Project

9. Peralatan yang Telah DibeIi:Equipment that has been purchased

I. HPLC column

2. Membrane test cell

;,

Tandatangan PenyelidikSignature ofResearcher

3

~~"/~""1--Tarikh

Date

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Komen Jawatankuasa Penyelidikan Pusat Pengajian/PusatComments by the Research Committees ofSchools/Centres

Lllporan Akhir Projek Penyelidikan Jangka PendekFinal Report OfShort Term Research Project

TANDATANGAN PENGERUSIJAWATANKUASA PENYELIDIKAN

PUSAT PENGAJIAN/PUSATSignature ofChairman

[Research Committee ofSchool/CentreJ

4

I,

TarikhDate

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APPENDIXl

Abstract of Research

,.

I,

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Abstract

In Malaysia, little attention has been given to the presence of pesticides in the

water source and its adverse effects on human health. These huge amount of pesticides

used, especially in agriculture practice, are the emerging contaminants in drinking water

supplies. This is because pesticides applied directly to the soil can be washed off by rain

into nearby bodies of surface water or percolate through the soil to lower soil layers and

groundwater. This project focuses on the removal of pesticide from aqueous solution

using nanofiltration membrane. Two pesticides, atrazine and dimethoate, were selected

for study in this research. Four nanofiltration membranes (NF90, NF200, NF270 and DK)

were subjected to a stirred dead-end filtration of the pesticide solution. It was found that

NF90 showed the best rejection performance, followed by NF200 and DK. Meanwhile,

although NF270 showed the highest permeate flux out of the four membranes tested, it

showed the poorest rejection. In overall, for the four membranes tested, atrazine was

consistently better rejected than dimethoate.

\,

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Abstrak

Di Malaysia, terlalu sedikit perhatian telah diberikan kepada kehadiran racun

serangga dalam sumber air dan kesan buruknya terhadap kesihatan manusia. Amaun

besar racun serangga yang digunakan, terutamanya dalam bidang pertanian, telah menjadi

bahan pencemar yang muncul dalam bekalan air minuman. Ini adalah kerana racun

serangga yang disembur ke tanah boleh dialirkan oleh air hujan sumber air yang

berdekatan atau meresap melalui tanah ke lapisan tanah yang lebih dalam. Projek ini

memfokuskan kepada penyingkiran racun serangga dari larutan akues menggunakan

membran penurasan nano. Dua jenis racun serangga, atrazin dan dimetoat, telah dipilih

untuk diuji. Empat jenis membran penurasan nano (NF90, NF200, NF270 and DK) telah

diuji dengan menjalankan penurasan hujung mati teraduk menggunakan larutan racun

serangga. Melalui kajian ini, ia didapati bahawa NF90 menunjukkan prestasi penolakan

yang terbaik, diikuti dengan NF200 dan DK. Sementara itu, walaupun NF270

menunjukkan prestasi hasil telapan yang tertinggi di antara empat membran yang diuji, ia~

menunjukkan prestasi penolakan yang p~ling lemah. Pada keseluruhannya, keempat-

empat membran yang diuji dapat menolak atrazin dengan lebih baik daripada dimethoate

secara konsisten.

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APPENDIX 2

Comprehensive Technical Report

I,

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Comprehensive Technical Report

In overall, the project has successfully achieved its objectives in application of different

type ofnanofiltration membranes in separation ofpesticides from water. The following sections

report on the results obtained from this research.

Type of pesticides used in Malaysia

Malaysia is actively involved in agriculture practice, planting oil palm, paddy, fruit,

vegetables and others for both local consumption and export purposes. In order to achieve the

objectives such as to maintain the quantity and quality of agriculture productions, pesticides are

used in agriculture sector as a mean ofpest control for sustainability ofthe industry.

In Malaysia, the annual pesticides sales figure exceeds RM 300 million. It is estimated

that annual crop losses in our country could exceed 30% without pesticides (MCPA, 2005).

Approximately 70% ofpesticides sold goes to the plantations. The commonly used pesticides in

the plantations are herbicides. Glyphosate and atrazine are among the most commonly used

herbicides. Meanwhile, insecticides accounts for approximately 16% of pesticides sold in our

country. The rest of the pesticides sold are~fungicides and rodenticides (Chooi, 2005). The

commonly used insecticides are organophosphorus pesticides which are widely used to replace

the organochlorine pesticides due to its short half-life.

Comparison between Membranes

In order to explore the application of different type of nanofiltration membranes in separation of

pesticides from water, four nanofiltration membranes, namely, NF90, NF200, NF270 and DK

were used as subject of study. The study the adsorption process of pesticides on membrane and

its effect on rejection of pestici~es could not be carried out as the analytical equipment available

was not sensitive enough to detect the very minute changes in concentration of pesticides. This

matter has been reported in the 6th month progress report previously.

Plate 1 and Figure 1 show the dead end filtration rig used in this project and its

schematic diagram respectively. The operatihg pressure for the filtration was supplied by

pressurized nitrogen gas. The nitrog~n gas outlet pressure was regulated using a single stage

pressure regulator of Concoa brand whereby the equilibrium pressure was shown on the

pressure gauge.

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Plate I: Dead end filtration rig.

StainlessSteel~edTank

Legend:o :Pressure regulator

[:)i<] : Valve

Figure I: Diagram of experimental set-up.

\,

MembraneStirred Cell

Magnetic Stirrer

Permeate

AnalyticalBalance

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A pressure relieve valve was installed between the nitrogen gas and the reservoir to

relief the pressure build up in the reservoir. The pressurized reservoir forced the water or

solution in the solution chamber to flow into the membrane cell. All pipelines, valves and

reservoir were made of stainless steel material. The reservoir could hold volume up to 1.8 Litre.

Filtration experiments were carried out under stirred dead-end filtration. The cell was

pressurized with compressed high purity nitrogen gas. The solution in the cell was stirred by a

Teflon-coated magnetic bar using Heidolph MR3000D (Germany). The membrane was

immersed for 24 hours in deionized water before being used in any experimental work. In order

to determine the pure water permeability, the membrane was first filtered using deionized water

at 15 x 105 Pa for a minimum of seven hours for compaction. This was done to avoid

compression effect in the later stage of experiment.

Pure water permeability for all four membranes was first determined to obtain the water

flux of the membranes without the presence ofpesticides. After that, the removal of atrazine and

dimethoate from aqueous solution were examined for the four nanofiltration membranes.

For pesticide flitration process, the same compaction process was carried out before the

test cell was emptied and 1.8 Litre of feedsolution was filled into test cell and solution reservoir.

Feed solution for each experiment was prepared by weighing specific amounts of pesticides

before dissolving them in approximately 5 mL of methanol. After that, the solution was added

into deionized water and shaken well. The cell filled with pesticides solution was then

pressurized at operating pressure indicated by a pressure regulator.

.!

The duration of the filtration experiments was approximately 80 minutes for each run.

Permeate from the bottom ctll was collected every 20 min, whereby the cumulative weight was

continuously measured with an ~ectronic balance with an accuracy of ± 0.01 g. The cumulative

weight were converted to cumulative volume and the value of permeate flux were calculated

from there on.

Meanwhile, the permeate concentrations which contained pesticides were measured by

using HPLC (Perkin Elmer Series 200) at wavelength of 200nm. After each run, the cell and the

membrane were washed thoroughly with deionized water. The membrane permeability was

checked and it was observed that the permeability varied within ±2% of the initial measured

value. All experiments were conducted at room temperature (28 ± 2°C).

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Pure Water Permeability

Figure 2 shows the pure water permeability graph for the NF90, NF200, NF270 and DK

membranes. Pure water permeability for the membranes was determined by obtaining the flux

for deionized water for each membrane at different operating pressure. As shown in the figure,

pure water flux for all membranes increased linearly with the increasing applied pressure. All

the curves passed through origin in accordance to the null value of the operating pressure. The

pure water permeability for these membranes was calculated from the slope of the water flux

against the operating pressure.

5.00E-05

4.50E-05

4.00E-05

3.50E-05

Ul 3.00E-05N'

E.... 2.50E-05g><:::J 2.00E-05ii:

1.50E-05

1.00E-05

5.00E-06

O.OOE+OO

0 2 4 6 8 10 12 14

• NF90

• NF200

.. NF270

xDK

16

Figure 2: Pure water permeabilip'.

Pressure x 105 (Pa)

NF270 had the highest water permeability under all pressure conditions among the four

membranes studied, followed by NF90 and NF200 while the DK had the lowest water

permeability compared to other membranes. The pure water permeability value for NF270,

NF90, NF200 and DK were 3.46 x 10-11 m3/(p12.s.Pa), 2.36 x 10-11 m3/(m2.s.Pa), 1.86 x 10-11

,m3/(m2.s.Pa) and 1.12 x 10-11 m3/(m2.s.Pa) respectively.

The finding that NF270 had the highest permeability corresponded to results from Hilal

et at. (2005) that NF270 had the largest average pore size, which was 0.71 nm, followed by

NF90 with 0.55 nm of average pore size while NF200 had average pore size of 0.38 nm

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(Lefebvre et al., 2003). However, DK showed the lowest water permeability although it had

similar average pore size with NF90 (Santos et al., 2006). This suggests that membrane

formulation produced by DowlFilmtec (USA) for NF90, NF200 and NF270 produces high

permeate flux while different membrane formulation by Osmonic (USA) for DK produces low

permeate flux. Formulation of the membrane is very important because water flux through a

membrane is greatly dependent on its ability to form hydrogen bonds with the hydrophilic

groups of the membrane polymer (Williams et al., 1999).

Pesticide Solution Performance

In order to monitor the performance of membranes as a function of time, deionized

water with pesticide of 10 mglL was used as feed. The experiments were conducted at operating

pressure of 6 x 105 Pa and the stirring rate was set at 1000 rpm. This operating pressure was

chosen as to strive for low operating cost by using low operating pressure. High stirring rate was

chosen in order to create high turbulence to the filtration system.

The rejection performance was monitored at every 20 minutes over a period of 120

minutes. This was done to identify the stabl: trend of the rejection as Braeken et al. (2005)

observed that retention would decrease itrongly during the first 15 to 30 minutes and then it

would reach a stable value. The rejection 'performance for NF90, NF200, NF270 and DK is

shown in Figure 3 for atrazine while rejection performance for dimethoate is shown in Figure 4.

I,

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.... -._ ..... _._ ..... _.- ..... -._ ..... _._ ..

..........................................)( )<----.)( ~( )( --)(.... - ....... - ........ _.......... - ......... _.. -.

100

90

80

70

c 600;JUQl 50'iii'0:::~ 40

30

20

10

0

0 20 40 60 80 100 120 140

-·.·-NF90...•... NF200

-'4-' NF270

~DK

Time (min)

Figure 3: Comparison between membranes on atrazine rejection with time at

operating pressure of6 x 105 Pa and stirring rate of 1000 rpm. Feed pesticide.concentration was 10 mg/L,

.... - ....... - ...... - ....... - ....... -........•.....•.....•.....•....

J.: . j( )( - )( --.:...~. )( ~.... - ..- '"-. ., -''- .. - ...... - ',- .. - ..

100

90

80

70c

600;JUQl 50'iii'

0::: 40~

30

20

10

00 20 40 60 80

;

Time (min)'

100 120 140

- +-. NF90..•.. NF200_ .... - NF270~DK

Figure 4: Comparison between membranes on dimethoate rejection with time at

operating pressure of 6 x 105 Pa and stirring rate of 1000 rpm. Feed pesticide

concentration was 10 mg/L.

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-

It could be observed from Figure 3 and Figure 4 that all membranes tested showed a

stable trend of rejection for atrazine and dimethoate with minor fluctuation. Therefore, as to

counter the possibility of the minor fluctuation of rejection, the rejection value obtained from

next section onwards would be an average of the rejection performance over a period of 80

minutes.

NF90 produced the best rejection performance for both pesticides tested, which was

more than 95% rejection for atrazine and approximately 85% for dimethoate. The performance

ofNF200 was the second highest of all four membranes tested while DK showed slightly lower

rejection than NF200. NF270 showed the lowest rejection performance out of the four

membranes tested. This corresponded to the finding that NF270 had the largest average pore

size, which was 0.71 nm (Hilal et al., 2005), and this caused more pesticides to be able to pass

through the membrane.

In overall, all four membranes tested showed better rejection for atrazine than

dimethoate. This observation was obtained despite the fact that dimethoate has slightly higher

molecular weight than atrazine (229.28 g/mol for dimethoate and 215.69 g/mol for atrazine).

Kiso et al. (2001) and Bellona et al. (2004) suggested that although molecular sieving effect

played important role in determining the retention performance by membrane, hydrophobicity.of the solutes must not be neglected. The vl:U!1e of log octanol/water partition coefficient, Ko/w, is

usually used to gauge the hydrophobicity of a particular organic solute. The higher the value of

log Ko/w, the better the rejection would be. This behaviour can be observed in this study since

atrazine has higher hydrophobicity than dimethoate. The value for log Ko/w for atrazine and

dimethoate are 2.34 and 0.70, respectively (Kamrin, 1997). However, it must be noted that the

influence of hydrophobicity of the solutes on rejection would decrease as the molecular size of

the solutes increased (Braeken et al., 2005). This is because molecular sieving effect would beI

very much prominent when ·the molecular size of the solutes was much bigger compared to the

pore size of the membrane. "'f

The dipole moment of the organic solutes also affected the rejection performance of the

membrane. Dimethoate has dipole moment of 5.164 debye while atrazine has dipole moment of

1.763 debye (Kim, 2006). Van der Bruggen et al. (2001) described that molecules with larger

dipole moment approaching the charged membrane were, by electrostatic attraction, properly

oriented towards the pores and entered more easily into the membrane structure. Consequently,

they were less rejected. This situation contributed to the lower rejection of dimethoate as the

large dipole moment of its molecules facilitated its passing through the membrane.

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In addition, dimethoate has aliphatic molecular structure compared to the heterocyclic

aromatic structure of atrazine. Van Gauwbergen and Baeyens (1998) reported that branching of

the molecular structure would improve rejection. Meanwhile, according to Kiso et al. (2000),

non-phenylic structured pesticides were rejected at a relatively lower degree than phenylic

structured pesticides. Hence, although atrazine has slightly lower weight than dimethoate, it was

better rejected compared to dimethoate.

The variation of the permeate flux by the four nanofiltration membranes tested for

filtration ofatrazine and dimethoate is presented in Figure 5 and Figure 6. The filtration process

was started after a minimum of seven hours of membrane compaction using pure deionized

water. A slight decrease of flux with the increase oftime could be observed in both figures. This

could be attributed to slight fouling due to the adsorption of organic pesticide molecules on the

membrane (Williams et al., 1999; Kimura et al., 2003). Therefore, in order to avoid

overestimation of flux due to the adsorption effect, the permeate flux value obtained from next

section onwards would also be an average of flux performance over a period of80 minutes.

Jr- •• _ -Jr- •• _._...... _ .'"-. -- •• - -Jr- • - - -&

+--_.-.-.-.""""'---....--_.-.-.- ...... -_ ....-_ ...•.....•.....•. __ ..•.....•

2.50E-05

2.00E-05

Uf 1.50E-05N

...~E......)( 1.00E-05~

ii:

5.00E-06

O.OOE+OO

0 20

)(

40

)(

60

)(

80

)(

100

)(

120 140

- ...... NF90••••. NF200

- -&- - NF270

~DK

Time (min)

Figure 2: Comparison between membranes on permeate flux during atrazine

rejection with time at operating pressure of6 x 105 Pa and stirring rate of 1000 rpm.

Feed pesticide concentration was 10 mgIL.,

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+- . - ....... - ....... - . --.....~--._ ....... _..........•.....•.....•.....•.....•

.- .. - ..- .. - ..- .. - ..- .. - ..- .. - ..2.50E-05

2.00E-05

-II! 1.50E-05N

C",-

.§.>< 1.00E-05~

u::

5.00E-06

O.OOE+OO

0

)(

20

)(

40

)(

60

)(

80

)(

100

)(

120 140

- +-. NF90••••. NF200

_ •• - NF270

~DK

ft, . ~

Time (min)

Figure 3:Comparison between membranes on permeate flux during dimethoate

rejection with time at operating pressure of6 x 105 Pa and stirring rate of 1000 rpm.

Feed concentration was 10 mglL.

This observation was also in agr~ement with Chang et al. (2002) that retention of

organic molecules in nanofiltration membranes was not only caused by molecular sieving, but

also by electrostatic effects and by adsorption on the membrane surface. Thus, convective

transport through the membrane pores and diffusive transport of adsorbed compounds through

the membrane matrix can be responsible for solute permeation.

In overall, the permeate flux for all membranes is still in agreement with the earlier

study for the pure water pefmeability whereby NF270 had the highest flux followed by NF90

and NF200 while DK had the lpwest permeate flux. This also showed that 0.55nm of average

pore size for NF90 was sufficient to retain dimethoate and atrazine with high percentage of

rejection. Nevertheless, solute-membrane interaction factor was also important (Kosutic at aI.,

2005; Kim et al., 2005) as DK and NF200 could not sustain as much rejection as NF90 although

DK had similar average pore size with NF90 (Santos et al., 2006) while NF200 had smaller

average pore size. It is believed that the intl\raction between pesticides tested and material

formulation for DK and NF200 contributed to the crossing of solutes; just as how interaction

between different membrane formulations and water could contribute to different water flux

performances as mentioned earlier. However, the detailed structural interaction ofthe membrane

and solutes was not studied in this research.

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Effect of Water Quality

The effect of different types of water quality on rejection of pesticides and permeate

flux is investigated in this section. Four types of water were used as feed water in experiment.

They were deionized water, distillated water, tap water and river water which were spiked with

pesticide. The performance of the nanofiltration membranes when filtering river water were

gauged against the performance of the membranes when filtering the three other water matrices.

Fixed parameters including pesticide concentration of 10 mg/L, operating pressure of 6 x 105 Pa

and stirring rate of 1000 rpm were chosen for the experiment. This experiment was conducted in

view of the possibility of water treatment from river water.

Water Composition

The result of water composition analysis is given in Table 1. Deionized water was used

as a reference to the other type of water matrices in this experiment. The deionized water and

distilled water was obtained from the Chemical Laboratory while the tap water was obtained

from Research Laboratory 1 at School of Chemical Engineering, Universiti Sains Malaysia. The

source of river water was from the Kerian River at Nibong Tebal, Pulau Pinang. The river water

had been pre-filtered with a regenerated cenulose (RC)-membrane filters with pore size of.0.45/-lm prior to analysis and preparation as' feed solution.

Table 1: Composition offeed water.

Distilled waterParameter Tap water (mg/L) River water (mgIL)

(mgIL)

COD Not detected Not detected 20.3

Aluminum, (AI) 0.013 0.075 0.011

Barium, (Ba) 12 15 21

Calcium, (Ca).,

0.11 2.94 1.22

Chloride, (Cn 0.4 7.6 4.5

Chromium, (Cr) 0.006 0.015 0.020

Copper, (Cu) 0 4 3

Magnesium, (Mg) 0.01 2.24 3.20;,

Nitrate, (N03-) 0.1 0.2 0.3

Sulfate, (SOl-) 1 18 12

Zinc, (Zn) 0.04 0.05 0.10

Lead, (Pb) 0.001 0.005 0.009

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Effect of Water Quality on Pesticide Rejection

Rejection performance of atrazine and dimethoate by NF90, NF200, NF270 and DK at

different types of water quality is presented in Figure 7 and Figure 8 respectively. It can be seen

from these figures that the rejection trend of the atrazine and dimethoate was generally higher in

the tap water and the river water than the rejection from distilled water and deionized water. As

for the performance of each individual membrane, NF90 showed the highest rejection followed

by NF200, DK and NF270 for both atrazine and dimethoate in all types of water quality

involved.

100

90..

80

70c 600

:;:lu.!!!, 50Gl

D::40

~

30

20

10

0NF90 NF200 NF270 OK

D Deionized water

[J] Distilled water

8 Tap water

mRiver water

Membrane

Figure 4: Effect ofwater quality on rejection of atrazine at operating pressure of 6 x

105 Pa and stirring rate of 1000 rpm. Feed concentration was 10 mgIL.

1

In the case of rejection of atrazine, the rejection from tap water and river water was

slightly higher than rejection f~m distilled water and deionized water for NF90. Similar trend

was observed for NF200, NF270 and DK. However, they experienced a more obvious increase

of rejection i.e. approximately 10% increment from the lowest to the highest atrazine rejection

performance for each individual membrane.

\,

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100

90

80

70c

60..

0:;:l(.)Gl 50'Q)'

0::40';je.

30

20

10

0NF90 NF200 NF270 DK

o Deionized water

IDJ Distilled water

STap water

~ River water

Membrane

Figure 5:Effect ofwater quality on rejection of dimethoate at operating pressure of 6 x

105 Pa and stirring rate of 1000 rpm. Feed concentration was 10 mg/L.

Meanwhile, for the rejection of dimethoate, all four membranes showed apparently

higher rejection in tap water and river water compared to deionized water and distilled water.

The four nanofiltration membranes showed an increase of dimethoate rejection between 7 to..14% for the two groups of water quality (i.e. deionized water with distilled water and tap water

with river water).

The observation of higher rejection occured for river water compared to the deionized

water and distillated water can be explained by the influence of natural organic matter in the

source of water. Naturally, the concentration of natural organic matter was higher in the river

water than in the deionized lYater or distilled water as the latter received further water treatments.

Pesticide could associate with the functional group present on the natural organic matter and..,.form macromolecular complex (Agbekodo et al., 1996). This phenomenon enhanced the effect

of molecular sieving. In addition, there was adsorption of pesticide onto the outer surface or

inside pores of membrane due to the hydrophobicity of that natural organic matter itself (Zhang

et al., 2004). The complex that formed from association of pesticide and natural organic matter

could also compete with the pesticide, result~d in steric congestion whereby more pesticide

being retained during the transportation through the membranes (Agbekodo et al., 1996).

Interestingly, the rejection of pesticide in tap water observed in Figure 7 and Figure 8

was comparable to those in river water, although tap water had undetectable natural organic

matter content. Therefore, it is believed that besides the influence of natural organic matter, the

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effect of ion adsorption also played a significant role in nanofiltration process. The high

concentration of divalent ion such as Ca2+, Mg2+, and SO/- and other monovalent ion in the tap

water and river water, as shown in Table 4.2, also contributed to higher rejection ofthe pesticide.

Ion adsorption could happen due to the interaction between the ion and the membrane (Schaep

et al., 1998; Thanuttamavong et al., 2002). This phenomenon narrowed the membranes pores

and thus, decreased the transportation of pesticide through the membrane. The pore structure of

membranes would be so tight that together with pesticide molecules, the major part of ions

would be removed (Zhang et al., 2004).

Effect of Water Quality on Permeate Flux

Figure 9 and Figure 10 show the flux performance for the rejection of both atrazine and

dimethoate from the different types of water quality tested. Generally, the permeate flux

declined from the deionized water to the river water for all type ofmembranes studied. It can be

observed that while both rejections atrazine and dimethoate in tap water and river water were

higher than rejections in deionized water and distilled water, as shown in Figure 7 and Figure 8,

the flux for both tap water and river water was consistently lower than the flux for deionized

water and distillated water. Based on Figure '9 and Figure 10, it can be observed that the flux

decline was up to 19% for NF90 and NF2aq, 24% for NF270 and 18% for DK for both atrazine

and dimethoate rejection involved.

2.50E-05

2.00E-05

--III 1.50E-05'",§..§.>< 1.00E-05:::Iu:

5.00E-06

O.OOE+OO

NF90 NF200 NF270 DK

(] Deionized water

IIlI Distilled water

EI Tap water

~ River water

Membrane

Figure 6: Effect of water quality on flux performance during rejection ofatrazine at

operating pressure of 6 x 105 Pa and stirring rate of 1000 rpm. Feed concentration

was 10 mglL.

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2.50E-05

2.00E-05

Ul 1.50E-05",'

E;;-§.>< 1.00E-05::Ju:

5.00E-06

O.OOE+OO

NF90 NF200 NF270 DK

o Deionized water

IT] Distilled water

8 Tap water

l.'lI River water

Membrane

Figure 7:Effect ofwater quality on flux performance during rejection ofdimethoate at

operating pressure of 6 x 105 Pa and stirring rate of 1000 rpm. Feed concentration was

10 mg/L.

The addition of pesticides to water was not the cause of flux decline as the relative.water flux in water with the addition of .pesticides only produced minor decline of flux

performance. Therefore, the major influence in the flux decline between the different types of

water quality could be attributed to the concentration of ions and natural organic matter in the

water. Adsorption of ions inside the membrane pores caused a decrease of the effective pore

size and consequently decreased the water flux (Zhang et al., 2004).

Besides, pore blocking happened when molecules with a size that corresponded with thet

size of an important fraction'ofthe pores blocked the membrane pores and caused fouling (Van

der Bruggen et al., 1998). This;rwould cause a decrease in the number of both pesticide and

water molecules passing through the membrane. Consequently, the water flux decreased, but the

rejection was increased. Hence, this fmding is in agreement with the increased rejection of

atrazine and dimethoate described in earlier section.

i,

Parameter Study for Nanofiltration

In order to understand the effect of operating conditions to the rejection and permeate

flux, operating parameters such as operating pressure, pesticide concentration and stirring rate

were varied one at a time to investigate its impact to the performance of the nanofiltration

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membranes. The effect of pH of solution and binary solute mixture were also investigated as to

observe its influence to the rejection and flux performance should such conditions occur.

Effect of Operating Pressure

The effect of operating pressure on pesticide rejection and permeate flux were

investigated at various operating pressure (5 x 105 Pa to IS x 105 Pa), A fixed parameter

including pesticide concentration of 10 mglL and stirring rate of 1000 rpm were chosen for

these experiments.

Effect of Operating Pressure on Pesticide Rejection

Rejection performance of atrazine and dimethoate by NF90, NF200, NF270 and DK at

different operating pressure is presented in Figure 11 and Figure 12 respectively. From these

figures, it can be observed that the rejection ofboth atrazine and dimethoate inclined to be better

when the operating pressure was increased.

............ - ...... -: ..... _- ..... - ...

- +-. NF90- - •. 'NF200- -J. - NF270~DK

1715

••

13119

<Of..

7

_·A_ -J.- •. - -J.-"·r· .

~.-" ­ok' .

5

•.... -.. ,

••••••

100

90

80

c0 70~uQ)

'iii'0::: 60~

50

40

303

Pressure x 105 (Pa)

Figure 8: Effect of operating pressure on rejection ofatrazine at feed concentration

of 10 mglL and stirring rate 1000 rpm.

Transport of solute through nanofiltration membrane can be explained in terms of

diffusion and convection (Hilal et al., 2004). Higher rejection was observed at higher pressure

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due to the increased water flux. The concentration of permeate became diluted with the

increased water flux as the solute molecule was rejected by molecular sieving effect.

-+-.-.-+-._--...... -.-+-.--......... -

..--...•. -....•... --. -.. ... . . -. ....•..•.. _.ok- ..

. -r··-_.ok--.... _..k" ..

100

90

80c0

70:;:;uC1)

'Qj'0::: 60';f.

50

40

303 5 7 9 11 13 15 17

- +- - NF90. -. -. NF200- .. - NF270~DK

Pressure x 105 (Pa)

Figure 9: Effect of operating pressure on rejection of dimethoate at feed

concentration of 10 mgIL and stirring rate 1000 rpm.

In other words, at higher pressures, "the flux of water increased, but the transport of.solute did not increase since the driving force of solute was not pressure but concentration

dependent. This caused the actual solute concentration in the permeate to be lower and therefore

the rejection was higher (Krieg et al., 2004).

However, the rejection of atrazine by NF90 increased for only approximately 2% from

between the lowest and highest operating pressure applied, suggesting that the contribution of

diffusion for atrazine throu&h NF90 was still relevant even at high operating pressure.

<If

Effect of Operating Pressure on Permeate Flux

Figure 13 and Figure 14 show flux performance of the membranes tested during

atrazine and dimethoate rejection respectively. Based on these figures, it was obvious that the

increase in pressure had positive effect on permeate flux for both atrazine and dimethoate;

filtration. 't

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....."

-- .-- NF90

----.---- NF200

---Il--- NF270

--*-DK

171513119

..... .---................

75

5.00E-05

4.50E-05

4.00E-05

3.50E-05

Uf 3.00E-05N

E-.. 2.50E-05.§.><:::l 2.00E-05

u:::

1.50E-05

1.00E-05

5.00E-06

O.OOE+OO

3

Pressure x 105 (Pa)

Figure 1O:Effect ofoperating pressure on permeate flux during rejection ofatrazine at

feed concentration of 10 mglL and stirring rate 1000 rpm.

5.00E-05

4.50E-05• .A...

It'4.00E-05 ",

K3.50E-05

",

..... K .....3.00E-05 .-II! ......- .. - +- - NF90N ...

E ",..- ...... - -. -. NF200E 2.50E-05 'if. ¥ ... .. '

........It' ...... _ •• - NF270

>< •••:::l 2.00E-05 It" ... ---*"-DKu::~ •••

1.50E-05 K... ... ••1.00E-05 ••5.00E-06 I,

O.OOE+OO

3 5 7 9 11 13 15 17

Pressure x 105 (Pa)

Figure 11: Effect ofoperating pressure on permeate flux during rejection of

dimethoate at feed concentration of 10 mg/L and stirring rate 1000 rpm.

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All membranes tested experienced a steady increment of permeate flux with the

increase of pressure applied to the system. While the increase of permeate flux against pressure

formed a perfectly straight correlation in pure water permeability in Figure 1, the deviation of

permeate flux from the direct correlation could be attributed to the adsorption of pesticide

molecules on the membrane (Kimura et al., 2003).

In an osmotic pressure controlled nanofiltration system, the flux can simply be related

to the pressure as follows,

(4.1)

where Vw is permeate flux (m3/m2.s), Lp is the membrane permeability (m3/(m2.s.Pa), Mis

the pressure differential (Pa), a is the reflection coefficient (dimensionless) and !:J.1C is the

osmotic pressure differential (Pa) (Spiegler and Kedem, 1966). For a fixed solute concentration,

the effective driving force for the solvent transport would be higher with an increment in

operating pressure (Syamal et al., 1997). Furthermore, the increase in driving force would

overcome the membrane hydraulic resistance. Therefore, increasing the pressure would force

more water to pass through the membrane and resulted in a higher permeate flux.

.Effect of Feed Pesticide Concentratio~

The effect of feed pesticide concentration on pesticide rejection and permeate flux were

investigated at various feed pesticide concentration (2 to 22 mgIL). A fixed parameter including

operating pressure of 6 x lOS Pa and stirring rate of 1000 rpm were chosen for these experiments.

Effect of Feed Pesticide Concentration on Pesticide RejectionI .

Rejection performance of atrazine and dimethoate by NF90, NF200, NF270 and DK at

different pesticide concentratio1;' is presented in Figure 15 and Figure 16. It can be seen from the

figures that there is a small decrement on pesticide rejection for all membranes tested with an

increase in feed pesticide concentration. This is because the effect ofpesticides concentration on

pesticides rejection is less pronounced with dilute feed concentration. This finding is in

agreement with work by Zhang et al. (2004) and Causserand et al. (2005). This shows that in;

practical terms, the membranes have almost tIle same efficiency level for pesticide rejection in

water even though the feed concentration varies from time to time.

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100

90

80

c0 70:;:;uCIl'0)0::: 60~

50

+-._.- ..... _.- .... . -.- ............ ..... _.- ..

•.......•.......•.......•* .......•.......•)( ------)(.. )( )(.. -....... -....... - ~

" ..... - ....." -...

- +-. NF90

" •• ,NF200

_ ... - NF270

--*-DK

40

8 10 12 14 16 18 20 22 24

Concentration (mg/L)

642

30 +-----,,---,----,---,-----,---,----,--r---r--.--,---,

o

Figure 12: Effect ofpesticide concentration on rejection ofatrazine at operating

pressure of6 x 105 Pa and stirring r.ate 1000 rpm,

100

90

80

c0 70:;:;uCIl'0)0::: 60?f!.

50

40

.... -.- ..... _.- ..... -._ ..... -._ ..... -._ ..

•.......•.......•.......•.......•>E ••••••••

)(---.--)*(----))oE-(---7<)«(----4lX

..... - •• ...L--- .. -...... ..-........ _........ _....;,

- +-. NF90••••. NF200

_ •• - NF270

--7E-DK

8 10 12 14 16 18 20 22 24

Concentration (mg/L)

642

30 -f---.---,---r----,----r---,----,--,--,----,----...------,

o

Figure 13: Effect ofpesticide concentration on rejection of dimethoate at operating

pressure of6 x 105 Pa and stirring rate 1000 rpm.

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However, concentration gradient had been acknowledged in various nanofiltration

models such as solution-diffusion model and Spiegler-Kedem model as the driving force to

solute transport (Bhattacharya and Ghosh, 2004). Decrease of pesticides rejection was observed

with the increase of feed concentration. This was due to the increased competitive sorption on

membrane sites between feed solute and water (Williams et al., 1999). The solute activity at the

influent side became higher, which resulted in higher diffusion of the solute through the

membrane. Another possible explanation for this trend of result was a reduction of the net

driving force due to the increase of osmotic difference between the retentate and permeate when

the feed concentration increased (Freger et al., 2000). This resulted in lower water flux, which

translated into more concentrated permeate.

Effect of Feed Pesticide Concentration on Permeate Flux

Figure 17 and Figure 18 show flux performance of the membranes tested during

atrazine and dimethoate rejection respectively. The same pattern of permeate flux was observed

in this experiment as there was also small decrement on permeate flux with an increase in feed

pesticide concentration.

2.50E-05 ..... - ......... _ ..... -.--- ...... _ ....... _.-..6.

2.00E-05

......III~ 1.50E-05",-E......~ 1.00E-05ii:

..... -• . . -+- . - - -+- . - . -+- . - . -+- - - . -+

- ....•..... - •.... _-.- .....•.... _-.

- ....... NF90_•• - ·NF200

- -. - NF270

--*-DK

5.00E-06)( )( )( )( )( )(

6 8 10 12 14 16 18 20 22 24

Concentration (mg/L)

O.OOE+OO +----,.--,---,-------,--...,--r---.---,----,.--,---,----,

024

Figure 14: Effect ofpesticide concentration on permeate flux during rejection of

atrazine at operating pressure of6 x 10\Pa and stirring rate 1000 rpm.

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.... - •• -jr .. -'. -jr .. -., -jr .. - .. -jr •. -"-4

~'-.-.~._.-.~._.-.~.-._.~._._.~

..............................................

2.50E-05

2.00E-05

'iii 1.50E-05N

E......§.>< 1.00E-05:::li!

5.00E-06)( )( )( )( )( )(

- .•. - NF90

...•... NF200

-'4-' NF270

~DK

O.OOE+OO +--,---,---,--.,.----,,.------,--.---,---,---,-----.---.

o 2 4 6 8 10 12 14 16 18 20 22 24

Concentration (mg/L)

Figure 15: Effect ofpesticide concentration on permeate flux during rejection of

dimethoate at operating pressure of 6 x 105 Pa and stirring rate 1000 rpm.

The slight decrease ofpermeate flux was due to the increase of concentration difference

between the two sides of the membrane and tl1.e subsequent increase in the osmotic pressure that

opposed the permeate flow (Ahn et al., 1999). Moreover, the increased competitive sorption on

membrane sites between feed solute and water also caused the permeation of water through

membrane to decrease, thus resulting in flux decline (Williams et al., 1999). There was also

reduction of the net driving force due to the increase of osmotic difference between the retentate

and permeate when the feed concentration increased, causing lower water flux (Freger et al.,

2000).

Effect of Stirring Rate .,.The effect of stirring rate on pesticide rejection and permeate flux were investigated at

various stirring rate (300 to 1000 rpm). This range of stirring rate was chosen because the

motion of stirrer beyond it was no longer smooth. A fixed parameter including operating

pressure of 6 x 105 Pa and pesticide concentration of 10 mg/L were chosen for these

experiments. \,

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Effect of Stirring Rate on Pesticide Rejection

Figure 19 and Figure 20 show the rejection performance of atrazine and dimethoate by

NF90, NF200, NF270 and DK at different stirring rate. An increase of pesticide rejection was

observed for both atrazine and dimethoate with the increase ofstirring rate.

This observation was obtained because increasing the water turbulence on the

membrane surface disturbed the onset of the mass transfer boundary layer near the membrane

wall and reduced the accumulation of solutes on the membrane surface, thus, reducing the effect

of concentration polarization (AI-Bastaki and Abbas, 2001; Bhattacharjee and Datta, 2003).

Usually, in the case of cross-flow filtration, the most direct technique to promote mixing is to

increase the fluid velocity past the membrane surface or integrating membrane spacers (Baker,

~._._._.~._._._.~._._._._._.-+

•...........•...........•.................;)( )( )(

2000).

100

90

80

r::.2 70...(J

.S!,Gl0:: 60~

50

40

30100 300

..

500

..

700 900 1100

_ .•. - NF90

. ..•... NF200

-...-NF270

---*-DK

Stirring rate (rpm)

Figure 16: Effect ofstirring rate on rejection ofatrazine at operating pressure of6 x

lOs Pa and feed concentration of 10 mg/L.

,,

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"'--.'_'._'.-'.A",-- .. - .. -.-.- ..- .. -.- '

.........................•• • • • • • • ' )()( X

~

_.~._._.~._.-.-.- ..+-. -'

100

90

80

c0 70;lCJQ)

'Qi'n:: 60';/!.

50

40

30100 300 500 700 900 1100

- ..... NF90..•. ·NF200- .• - NF270~DK

Stirring rate (rpm)

Figure 17: Effect of stirring rate on rejection of dimethoate at operating pressure of6 x

105 Pa and feed concentration of 10 mgIL.,.

In the case of dead-end filtration, increasing the stirring rate would reduce the boundary

layer thickness by increasing turbulent mixing at the membrane surface. The reduced membrane

wall concentration occurring on the membrane surface with the increased stirring rate resulted in

lower concentration gradient. Therefore, as shown in Figure 19 and Figure 20, better rejection

was obtained.

IEffect of Stirring Rate o'n Permeate Flux

.;Flux performance ofNF90, NF200, NF270 and DK tested during atrazine and

dimethoate rejection at different stirring rate is presented in Figure 21 and Figure 22

respectively, Only slight increase was observed in the flux performance for all membrane tested,

This is because the main driving force of the flux was pressure gradient and in this experiment,

constant pressure was applied to the membra~e. The slight improvement of flux was obtained,

due to the reduced boundary layer caused by the increasing turbulent mixing at the membrane

surface.

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2.50E-05Jr •. _ ......... _ ......... _ •• _ .......

2.00E-05

.......III

",' 1.50E-05E,;;-E.....~ 1.00E-05ii:

... .-.,-,+-.-.-. '-'_.+-'-'-........•.......•........... .. - +-. NF90

•••• ·NF200_ •., - NF270

---*-DK

5.00E-06 )( )( )( )(

1100900700500300

O.OOE+OO +----,--------r-----,------.---------,

100

Stirring rate (rpm)

Figure 18: Effect of stirring rate on permeate flux during rejection ofatrazine at

operating pressure of6 x 105 Pa and feed concentration of 10 mglL.

2.50E-05

Jr •• _ .......... _ ......... _ •• _ .......

2.00E-05

'iii",' 1.50E-05E

",-.§.

~ 1.00E-05ii:

.-._.-+.... _._ .... _._ .... -•.......•.......•...... - .

- +-. NF90

•••• ·NF200_ .., - NF270

---*-DK

)( )( )( )(

I

of

300 500 700 900 1100

Stirring rate (rpm)

O.OOE+OO +----,-------,------,-----,-----,

100

5.00E-06

Figure 19: Effect ofstirring rate on permeate flux during rejection of dimethoate at

operating pressure of6 x 105 Pa and f~ed concentration of 10 mgIL.,

Having similar phenomenon as the earlier section, membrane wall concentration

occurring on the membrane surface decreased with the increased stirring rate. This caused the

subsequent decrease in the osmotic pressure that less opposed to the permeate flow (Ahn et al.,

1999) while at the same time, competitive sorption on membrane sites between feed solute and

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water decreased (Williams et al., 1999). Consequently, the increased permeate flux was

observed.

Effect of Initial pH of Solution

The effect of initial pH of solution on pesticide rejection and permeate flux were

investigated at several pH of solution (4 to 9). A fixed parameter including operating pressure of

6 x 105 Pa, pesticide concentration of 10 mgIL and stirring rate of 1000 rpm were chosen for

these experiments.

Effect of Initial pH of Solution on Pesticide Rejection

The effect of initial pH of solution on the atrazine and dimethoate rejection at fixed

operating pressure, pesticide concentration and stirring rate are presented in Figure 23 and

Figure 24. From the figures, it can be seen that the rejection performance for atrazine and

dimethoate by NF200, NF270 and DK increased as the pH was increased while the rejection

trend for NF90 was almost constant regardless ofthe pH condition.

~._-_.-.-._.-.-._._~._._.-.-.-.~

..........•",.-"..•..... '

~.. -" .. -·.·-NF90

...•.•• NF200

--,&-' NF270

--*-DK

10987;,

pH

6

.'.. '.. ,.'

54

~.,

k" •

100

90

80

70c0

60:o:lUCII'Cjj'a:: 50~

40

30

20

10

3

Figure 20: Effect of initial pH of solution on rejection of atrazine at operating pressure

of6 x 105 Pa, feed concentration of 10 mg/L and stirring rate 1000 rpm.

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Polyamide thin-film composite membranes have charge characteristics that influence

the separation capabilities. This can be altered by pH of solution. The isoelectric point of

polyamide membrane is generally between 4 to 5 (Puasa, 2006). The occurrence of an

isoelectric point means that at lower pH than the isoelectric point, the membrane is positively

charged and vice-versa. Hence, in the case of polymeric membranes, surface membrane charge

is typically negative at high pH values, it increases as the pH decreases and switches to positive

values at low pH (Bandini and Mazzoni, 2005).

~'-'-'---'-'---'-'-~'-'---'-'-'-'

••.'

--.·-NF90...•... NF200

_.JL_. NF270

~DK

10987654

-'_.,k'"' •

.'.'

_.,_.,

.. '.•..~ ........ ,.. '.......

......

-..:.:':'~'.:..'-'-------~~'lJ •• -_ .. ...c.'

100

90

80

70c0

60+:llJQ).....Q)

c::: 50'#.

40

30

20

103

pH

1000 rpm.

Figure 21: Effect of initial pH ofsolution on rejection ofdimethoate at operating

pressure of6 x 105 Pa, feed concentration of 10 mgIL and stirring rateI

"f

However, in contrary to the usual phenomenon which occurs for ionic species whereby

at isoelectric point, the flux is usually at the highest while the rejection is at the lowest (Ooi,

2005), the trend observed for the uncharged pesticides molecules is somewhat different. In the

case of uncharged molecules, instead of being influenced by the changes in membrane surface

charge, it is believed that it was the changes of\the membrane structures and/or formation of

high molar mass complexes which significantly affected the performance of solute rejection and

permeate flux.

According to Nystrom et ai. (1995), the retention of vanillin was very low at low pH but

the retention was high at pH 10. It was deduced that vanillin formed high molar mass complexes

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at this pH. Nevertheless, the possibility of formation of high molar mass complexes at high pH

was sidelined in this research since the rejection of atrazine and dimethoate only increased at

high pH for NF200, NF270 and DK while NF90 showed a slight decrease of rejection at high

pH.

Hence, it is deduced that the trend of atrazine and dimethoate rejection obtained for

NF200, NF270 and DK in this experiment was due to the changes of the membrane structures

caused by the pH of solution. The results obtained were in agreement with observation done by

Freger et al. (2000) whereby the rejection of lactate decreased with the decrease of pH. It was

concluded that acidic hydrolysis disrupted the chemical links, which reduced the degree of

crosslinking (Le., rigidity) of the polymer matrix and caused the polyamide polymer to become

more hydrophilic (Freger et al., 2005).

On the other hand, the increase ofatrazine and dimethoate rejection at high pH observed

for NF200, NF270 and DK could be caused by the hydration swelling of the membrane skin

layer. This could result in shrinking of membrane pore size, and thus, reduced the permeation of

solute through the pores of the membrane (Freger et al., 2000). However, it is believed that

NF90 was rather chemical-resistant as it showed somewhat consistent performance regardless of

the pH of solution. There was only a &op of about 3% of rejection performance for NF90

compared to the obvious increase or reduction of rejection performance shown by the rest of the

nanofiltration membranes tested.

Effect of Initial pH of Solution on Permeate Flux

The effect of initial pH of solution on the permeate flux during rejection of atrazine and

dimethoate at fixed operaAng pressure, feed pesticide concentration and stirring rate are

presented in Figure 25 and FiglJfe 26, respectively. Since the acid hydrolysis (Freger et al., 2005)

and swelling of membrane skin layer (Freger et al., 2000) is believed to be responsible for the

increase or decrease in pesticide rejection for NF200, NF270 and DK, it is expected that the

permeate flux would be as much affected by pH of solution as the pesticide rejection

performance.;,

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2.50E-05

2.00E-05

...._.. _.. _.. - .. _....... -........... - ..-..

J! 1.50E-05E.,-g~ 1.00E-05

u:::

~._.-._._._._._.~._.-._.-.-.

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

-·.·-NF90

...•... NF200

-':A-' NF270

-x--DK

5.00E-06)( )(

10987654

O.OOE+OO +---,----r------,-----,---....,----,------,

3

pH

Figure 22: Effect of initial pH of solution on permeate flux during rejection of atrazine at

operating pressure of 6 x 105 Pa, feed concentration of 10 mglL and stirring rate

1000 rpm.

2.50E-05

2.00E-05

..... - ........ -. "'_ ... - ........ - .. - .. - ....

J! 1.50E-05.§g~ 1.00E-05

~._._.-.-._._._.~._._._._.-....~ ..,

-·.·-NF90

...•... NF200

-':A-' NF270

~DK

5.00E-06)( )( )(

1098; 7,654

O.OOE+OO -j----,----,.-----,-----,-----,---,--------,

3

pH

Figure 23: Effect of initial pH of solution on permeate flux during rejection of dimethoate at

operating pressure of 6 x 105 Pa, feed concentration of 10 mg/L and stirring rate

1000 rpm.

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However, based on Figure 25 and Figure 26, it seemed that except for NF270, the effect

of pH of solution seemed not be to as much on permeate flux if compared to the degree of

changes seen in the rejection performance. Thus, it is deduced that the difference in permeate

flux was not that obvious because the changes at the polymer was little, but it was sufficient to

efficiently retain or allow more solutes through the membrane. Again, NF90 showed that it was

somewhat resistant to the changes of pH of solution as it showed almost constant flux

performance regardless ofthe pH condition.

Effect of Binary Solnte Mixture

The effect of binary solute mixture on pesticide rejection were investigated at several

ratio of atrazine:dimethoate. The ratio of atrazine:dimethoate was set at 0:100, 20:80, 50:50,

80:20 and 100:0 for a total of 10 mgIL pesticides (i.e. 0:100 means 0% of atrazine and 100%

dimethoate in the solution, 20:80 means 20% of atrazine and 80% of dimethoate in the solution

and so on). Fixed parameters of operating pressure at 6 x 105 Pa and stirring rate at 1000 rpm

were chosen for these experiments.

Effect of Binary Solute Mixture on Pesticide Rejection.Rejection of binary atrazine-dimethoate mixture was tested at a fixed applied pressure,

total pesticides concentration and stirring rate to examine if the membrane would have the same

good performance when the two pesticides co-exist. Figure 27 (a) to (d) shows that all four

nanofiltration membranes tested had slightly lower retention for both atrazine and dimethoate in

the presence of binary solute mixture compared to the single solute condition.

This observationV(as in line with observation made by Plakas et al. (2006) which

suggested that simultaneous filtration of more than one pesticide resulted in a kind of"f

competitive adsorption on the membrane surface and, thus, created a greater passage to the

permeate side. These results were also in agreement with the report by Kiso et al. (2000) which

found that herbicides displaying higher rejection in single ,solute solutions may permeate more

in mixed solute systems.

;,

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100 100

• ......•90 90

80 80c c0 0

70:;:; 70 :;:;u u .----.CIl CIl'Gj' 'Gj' • •a::: 60 a::: 60C>l! C>l!

50 50

40 40

30 30

0 20 40 60 80 100 0 20 40 60 80 100

%Atrazine %Atrazine

(a) (b)

100 100

90 90

80 80

c c,2 70

,2 70... tlu CIlCIl'Gj'

60~ 'l 60II::

~ ~

50 .--.. 50

•40 • 40

30 300 20 40 60 80 100 0 20 40 60 80 100

% Atrazine % Atrazine(c) (d)

I-+--Atrazine --Dimethoate II

Figure 24: Effect ofbinary solute mixture on rejection ofatrazine and dimetboate on (a) NF90,

(b) NF200, (c) NFflo and (d) DK at operating pressure of6 x 105 Pa, total

pesticides concentration of 10 mgIL and stirring rate 1000 rpm.

Effect of Binary Solute Mixture on Permeate Flux

The effect of binary solute mixture on"permeate flux is presented in Figure 28. The

effect of binary solute mixture on permeate flux was minor since the pressure, total

concentration and stirring rate in this experiment were set constant and the only changes of

parameter was the ratio ofpesticides. Therefore, this posed little influence to the performance of

permeate flux. This observation provides some insight that in the real case of water treatment,

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binary or multiple solute mixture would have little significance in the permeate flux

performance.

2.50E-05

2.00E-05.. - .. -... .. - .. - .. - .... . - .. - .. - ... .. - ........

Iii'N' 1.50E-05

...~§.><~ 1.00E-05iL

. _. _. +-. _. _. _. -+-. -' _. _. -+-. _. - .•........•............•............•........•

- +-. NF90••••. NF200

_ •• - NF270

~DK

5.00E-06

10080604020

O.OOE+OO +----,...-----,-----.-----,-----,o

% Atrazine

Figure 25: Effect of binary solute mixture o~ permeate flux during rejection of mixture of.atrazine and dimethoate at operating pressure of 6 x 105 Pa, total pesticides

concentration of 10 mg/L and stirring rate 1000 rpm.

Statistical Analysis using Design.of Experiment method

Since operating pressure, feed pesticide concentration and stirring rate were the main

operating conditions for napofiltration system tested, a statistical approach using general

factorial design was employed to compare the significance of their contribution in affecting the

rejection and flux performance:The factor of membrane selection was also included in the

analysis to compare its significance in affecting the final results compared to the contributions

by the operating conditions.

General Factorial Designi,

Experiments based on the general factorial experimental design in Table 2 were carried

out and relevant results, which lists the rejection and flux performance for both atrazine and

dimethoate, is presented accordingly. The results were further analyzed using the Design Expert

6.0.6. software. Since membrane (NF90, NF200, NF270 and DK) was categorical factor while

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operating pressure, feed pesticide concentration and stirring rate were numerical factors, the

relationship between those numerical factors and the two dependent variables (% rejection and

flux) was analyzed for each membrane.

Table 2: Experimental design for atrazine and dimethoate.

Run no. A: Membrane B: Pressure c: Pesticide D: Stirring rate

x lOs concentration

(Pa) (mg/L) (rpm)

I NF90 6 2 3002 6 2 10003 6 20 3004 6 20 10005 12 2 3006 12 2 10007 12 20 3008 12 20 10009 NF200 6 2 30010 6 2 1000II 6 20 30012 6 20 100013 12 2 30014 12· 2 1000IS 12 20 30016 12 20 100017 NF270 6 2 30018 6 2 100019 6 20 30020 6 20 100021 12 2 30022 12 2 100023 12 20 30024 12 20 100025 DK -I 6 2 30026 6 2 100027 6 20 30028 6 20 100029 12 2 30030 12 2 100031 12 i 20 300,32 12 20 1000

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ANOVA Analysis

Table 3 shows the experimental results based on the general factorial experimental

design. The results in Table 3 allowed the development of mathematical equations where each

response (% rejection and flux) is assessed as a function of pressure (B), pesticide concentration

(C) and stirring rate (D) and the 2-factors interaction among the independent variables (AB, AC,

AD, BD, BC, and CD) for each membrane (A).

Table 1: Experimental results based on the general factorial experimental design.

Atrazine DimethoateRUl.,lno.

12345678910111213141516171819202122232425262728293031

32

% Rejection

98.2998.7397.2397.7598.5298.9398.5897.9366,4367.5463.0168.9878,4274.8377.8175.0048.3555.5540.9748!9664.38

"I"6l.65 .

56,4259.7354.6765.4352.6859.3970.0472.9567.14

63.89

1.28E-051.2lE-051.17E-051,45E-052.56E-052.79E-052.50E-052.55E-05l.OlE-05

"l.20E-05'9.67E-061.08E-051.93E-052.23E-052.l2E-052.07E-051.96E-052.03E-051.99E-052.00E-053.76E-053.97E-053.6lE-053.8lE-054.32E-065.79E-064. 11E-065,400-068.93E-061.l0E-058.34E-06

1.2lE-05

% Rejection

85.2287.7783.0285.9391.299l.7889,7388.1151.4951.9254.6262.1465.7462.7359.0655.0448.6135.8336.3334.8353.4158,4847.7961.6644.5850.0143.1646.2864.8574.0162.51

65.31

1.13E-051.37E-051.3lE-051.37E-052,43E-052.83E-052.25E-053.02E-05l.OlE-051.00E-059.55E-069.89E-061.98E-052.08E-051.90E-051.97E-051.89E-051.93E-051.86E-051.94E-053.62E-054.13E-053.74E-053.83E-054.8lE-065.10E-064.84E-064.99E-069.66E-069.33E-069.84E-06

9.53E-06

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The statistical significance of the factors were evaluated by F-test and "Prob>F" using

analysis of variance (ANOVA) and is presented in Table 4 and Table 5 for atrazine and

dimethoate, respectively. As shown in the tables, there are certain model terms with

"Prob>F>O.5" which indicated that those terms were insignificant to the rejection or flux

performance. Those insignificant terms can be reduced by reselecting only the significant terms

to be included in the model in order to improve the accuracy ofthe model equation.

Table 2: ANOVA for the significance ofmodel and model terms for atrazine.

Source Model Sum of Mean F Value Prob> F Remarks

terms Squares Square

% Rejection

Model 9543.82 530.21 129.53 < 0.0001 significant

A 8570.81 2856.94 697.96 < 0.0001 significant

B 546.51 546.51 133.51 < 0.0001 significant

C 75.82 75.82 18.52 0.0009 significant

D 36.77 36.77 8.98 0.0103 significant

AB 166.05 55.35 13.52 0.0003 significant

AC 47.14 "15.71 3.84 0.0361 significant

AD 31.09 10.36 2.53 0.1024

BC 0.24 0.24 0.06 0.8114

BD 69.34 69.34 16.94 0.0012 significant

CD 0.05 0.05 0.01 0.9135

Flux

Model 3.17E-09 1.76E-1O 182.71 < 0.0001 significant

A 1.89E-09 6.30E-1O 653.67 < 0.0001 significant

B 1'!08E-09 1.08E-09 1125.63 < 0.0001 significant

C 1.16E-12 1.16E-12 1.20 0.2926

D 1.80E-II 1.80E-II 18.67 0.0008 significant

AB I.72E-IO 5.73E-II 59.47 < 0.0001 significant

AC 5.85E-13 1.95E-13 0.20 0.8929

AD 1.21E-12 4.d2E-13 0.42 0.7437

BC 6.13E-13 6.13E-13 0.64 0.4393

BD 1.28E-12 1.28E-12 1.33 0.2691

CD 9.79E-14 9.79E-14 0.10 0.7550

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Table 3: ANOVA for the significance ofmodel and model terms for dimethoate.

Source Model Sum of Mean F Value Prob> F Remarks

terms Squares Square

% Rejection

Model 9178.98 509.94 19.98 < 0.0001 significant

A 7512.23 2504.08 98.11 < 0.0001 significant

B 1125.21 1125.21 44.08 < 0.0001 significant

C 55.62 55.62 2.18 0.1637

D 28.96 28.96 1.13 0.3062

AB 376.44 125.48 4.92 0.0169 significant

AC 18.88 6.29 0.25 0.8623

AD 28.84 9.61 0.38 0.7714

BC 17.95 17.95 0.70 0.4168

BD 7.07 7.07 0.28 0.6074

CD 7.76 7.76 0.30 0.5907

Flux

Model 3.31E-09 1.84E-10 149.43 < 0.0001 significant

A 1.93E-09 6.4'3E-10 522.84 < 0.0001 significant

B l.llE-09 '1.11E-09 903.94 < 0.0001 significant

C l.77E-13 1.77E-13 0.14 0.7106

D l.77E-ll 1.77E-ll 14.40 0.0022 significant

AB 2.25E-10 7.49E-1l 60.91 < 0.0001 significant

AC 1.67E-12 5.55E-13 0.45 0.7206

AD 1.63E-11 5.42E-12 4.41 0.024 significant

BC 5.16E-13 5.16E-13 0.42 0.5285I

BD . 6.1lE-12 6.11E-12 4.96 0.0442 significant

CD l.!2E-13 1.22E-13 0.10 0.7576

The statistical parameters obtained from the ANOVA for the reduced model of the

responses are given in Table 6. ANOVA results of the reduced models showed Prob>F<O.OOOl

for all the responses, indicating that the model equation adequately described the rejection and,

flux performance in the interval of investigation. The effect of each variable on the response

was the combination of coefficients and variable values as well as contribution of interaction of

variables that cannot be observed by conventional experimental methods. A high R2 value of

close to 1, is desirable to indicate that 1ack-of-fit is insignificant (Noordin et al., 2004). In this

statistical analysis, the values of R2 for % rejection and flux for atrazine and dimethoate were

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in Table 7.

0.9912,0.9945,0.9478 and 0.9944, respectively. This indicates that only 0.56-5.22% ofthe total

variation was not explained by the model.

Table 4: Statistical parameters obtained from the ANOVA for the reduced models.

Variable Atrazine Dimethoate

% Rejection Flux % Rejection Flux

Significant terms A,B,C,D, A,B,D,AB A,B,AB A,B,D,AB,

AB,AC,BD AD,BD

Prob>F <0.0001 <0.0001 <0.0001 <0.0001

R2 0.9912 0.9945 0.9478 0.9944

Adequate precision 40.44 74.56 22.56 55.95

Standard deviation, SD 2.17 8.72E-07 4.5502 9.86E-07

Coefficient ofvariance, CV 3.02 4.87 7.31 5.60

The coefficient of variance, CV, is the ratio of the standard error to the mean value of

the observed response (as a percentage). It is a measure of reproducibility of the model. As a

general rule of thumb, a model can be considered reasonably reproducible if its CV is not

greater than 10% (Wong, 2006). None of the tv values obtained for the responses studied in.this experiment exceeded 10%, as shown in Table 6, indicating the good reproducibility of the

model.

Meanwhile, adequate precision shown in Table 6 compares the range of the predicted

values at the design points to the average prediction error. Ratio greater than 4 is considered to

be adequate model discrimination (Noordin et al., 2004). All the adequate precision values

obtained in this analysis (40.44, 74.56, 22.56, 55.95) were well above 4, indicating the modelsI

were significant. Empirical models in terms of coded values for the two responses are tabulatedwi!

,,

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Table 5: Empirical models in terms ofcoded values.

Membrane Empirical models

NF90 Atrazine:Rejection = 87.78 + 0.99*B - 0.04*C + 0.02*D -0.014*B*D

Flux = -1.86E-06 + 2.2IE-06*B + 2.14E-09*D

Dimethoate:Rejection = 80.74 + 0.79*B

Flux = -1.33E-06 + 1.95E-06*B + 1.49E-09*D + 4.l6E-IO*B*D

NF200

NF270

Atrazine:Rejection = 46.65 + 2.58*B - 0.03*C + 0.02*D -0.014*B*D

Flux = -9.82E-07 + 1.7lE-06*B + 2.14E-09*D

Dimethoate:Rejection = 49.44 + 0.93*B

Flux = 1.9lE-06 + 1.38E-06*B - 3.00E-09*D + 4.16E-IO*B*D

Atrazine:Rejection = 29.82 + 2.93*B -·0.33*C + 0.02*D -0.014*B*D

Flux = 6.25E-07 +2.99E-06*B +2.14E-09*D

Dimethoate:Rejection = 22.46 + 2.74*B

Flux = 5.54E-07 + 2.94E-06*B - 1.15E-09*D + 4.l6E-IO*B*D

DK Atrazine:Rejection = 40.41f. + 2.65*B - 0.28*C + 0.02*D -0.014*B*D

Flux = -1.64E-06 + 8.62E-07*B + 2.l4E-09*D

Dimethoate:Rejection = 25.35 + 3.44*B

;,Flux = 2.76E-06 + 5.05E-07*B - 3.8lE-09*D + 4.l6E-IO*B*D

Usually, it is necessary to check the fitted model in order to ensure that it provides an

adequate approximation to the real system. Unless the model shows an adequate fit, proceeding

with investigation of the fitted model is likely to give poor or misleading results. By applying

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the diagnostic plots such as the predicted against actual values plot, normal probability plot and

studentized residuals against predicted plots, the model adequacy can be judged. The predicted

against actual value plot of % rejection and flux for atrazine and dimethoate is presented in

Figure 29. The model for % rejection and flux for both pesticides were satisfactory as the actual

values were distributed relatively near to the straight line as shown in the figures.

1011.9/

nIl

31.33

.-__Predlctedvs. Actual -.

Actual

(a)

Predicted vs, Actualr----- ------,

III

.1 m

/UActual

3.07£-01

l::Ii11;.1J5

WE·O'

3MOI

;,

".--_............:Predictedvs. Actual. -.

/

Actual

(b)

r--............ PredictedVs. Actual -.

..

Actual

(c) (d)

Figure 26: DESIGN-EXPERT plots for atrazine and dimethoate. Predicted versus actual values

plot for (a) % rejection; (b) flux for atrazine and (c) %rejection; (d) flux for dimethoate.

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Figure 30 shows the normal probability plots for atrazine and dimethoate which

indicates whether the residuals follow a normal distribution. If the model is adequate, the points

on the normal probability plots of the residuals should form a straight line (Idris et al., 2006). A

check on points on normal probability plots of the residuals reveal that the residuals fall on a

straight line implying that the errors are distributed normally for all the responses.

III

-1,01

Normal.PlotofResiduals....--- ----I

II-l

~95.::t

3

:1

;1f01r~

};f]

I

r-__Normal.PlotofResiduals._.-..-..........,

91

i 90

.D !II,ro.De

Q.III

'f.i 311

E 200Z 10

Sludentized Residuals(a)

,.--__Normal Plot of Residuals__...,

Stude~dRe~duaJs

(b)

•..--.-- ........NormaFPlotofResiduals. -,

99

95

~90

1l 80III.D 10eQ.

~o

~

1 30

20

Z 10

III

III

\,

StudenliZedResiduals Sludentized Residuals

(c) (d)

Figure 27: DESIGN-EXPERT plots. Normal probability of residual for (a) % rejection; (b) flux

for atrazine and (c)% rejection; (b) flux for dimethoate.

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Figure 31 shows the plots of studentized residual versus predicted values for atrazine

and dimethoate. The plots of the residuals against the predicted response should be structureless,

that is, they should contain no obvious patterns and unusual structure (Idris et al., 2006). The

figures show a random spread of the studentized residuals across almost all levels of the

predicted values. This implies that the models proposed are adequate.

.--__Residuals vs. Predicted__---..,300-1--------------_--1

...Residuals V$. Predicted

r-----~---..--,

HIl-III

IIIII III • " III II IIIiI. ... • iIII ::l .11 III::l III :!Z III'l1'iii II l1li " II IIIII II .111 41 l1lia: a: III ...

III 'tJ ,-'tJ 0,00 II .. II.Ill. 1lI

~: III. 18~ III III IIIIII i IIc •III 18 'tJ II'l1 II III. II

~III ~ •

811 •

1/III

III

·3.00 .-I I I 1 I

1.11,,06 1:~ me·os 3.06 3m,

.PredictadPradieted

(a) (b)

Residuals.vs.••Predicted Residualsvs. Predicted300f 300

MIl.

llII II II•II!I II

•!!. II !!.II II::l • ::l

III II~ III ~. II II..

II..

I IIIa: a: III

" 0.00. • ~0,(11)..

~ I III III .:!t II IIIII "f" ..c III III c IIIII • III III 111 II IB" " II IIIJl III III JlCIl ·1.10 III CIl -1.50

• IIIII

-3.00 ·300

3tHIII 5l.1J 64.$ mo 1Il.13 I mE·1II! fJ3&O; 131&0; l.OIE·o; 31l6E-$,

Predicted Predictad

(c) (d)

Figure 28: DESIGN-EXPERT plots. Studentized residuals versus predicted values plot for (a)

% rejection; (b) flux for atrazine and (c) %rejection; (d) flux for dimethoate.

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The interaction graph between membrane and pressure as well as membrane and

pesticide concentration for each membrane in the case of rejection of atrazine are presented in

Figure 32. It can be seen from Figure 32 (a) and (b) that while the rejection by NF90 was not

much affected by the increase of pressure or pesticide concentration, rejection was generally

higher with higher pressure and rejection was lower when the pesticide concentration was high.

-_.-_..--~

• 6 X 105 Pa

".

'.

B: Pressure

z.,'<:<>,

.. ~".. .. '"

""'" ,'" I",

""'~.,70.53

55.75

100..10

NFSO NF200 NF270

A: Membrane

(a)C: Cone

85A1

70.60

56,]8

.2 mg/L

.&20 mg/L

NF90 NF200 NF270

A: Membrane(b)

Figure 29: DESIGN-EXPERT plots. Interaction graph between (a) membranes and pressure; (b)I,

membranes and pesticide concentration.

Meanwhile, the interaction plot between operating pressure and stirring rate is presented

in Figure 33. The interaction trend for all membranes had a common point whereby they

showed the lowest rejection at low pressure and low stirring rate.

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8'PresSUfeWOOO 6.00

D'stirringfate

(a) (b)

(c) (d)

Figure 30: DESIGN-EXPERT plots. Interaction\graph between pressure and stirring rate for (a)

NF90; (b) NF200; (c) NF270; (d) DK for rejection ofatrazine.

Figure 34 shows the interaction graph between membrane and pressure for flux during

rejection of atrazine. The flux was generally higher when the pressure was higher. This trend

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corresponded to the finding in the earlier section that pressure highly influenced flux

performance.

3.97E·05

2.9-BE·05

1.9BE'05

B: Pressure

.6 X 105 Pa

.... 12 X 105 Pa

.•.:III:•.....................

9.93E-OG

OOOE+OO

::IE: _._ - ;]IE' •• '

"

A: Membrane

NF270 DK

Figure 31: DESIGN-EXPERT plots. Interaction graph between membrane and

pressure for flux during rejection ofatrazine.

.Figure 35 shows the interaction graph between membrane and pressure for rejection of

dimethoate. The results observed from the interaction graph are in good agreement with the

model for rejection ofdimethoate obtained earlier. A positive sign for the factor B in the model

indicates that the ability ofthe system to achieve higher rejection with the increase in value of

pressure (B).

93.55 -

-

B: Pressure

.6x105 Pa

.&12 X 105 Pa

64 .. 19 -

49.51 -

34.33 -

NF90

I., ". ....~, 1 ······ I

INF270

A: Membrane

Figure 32: DESIGN-EXPERT plots. Interaction graph between membrane and pressure for

rejection ofdimethoate.

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Figure 36 shows the interaction graph between membrane and pressure as well as

membrane and stirring rate for flux performance during rejection of dimethoate. The effect of

pressure obviously had high influence on the flux performance as a double increment of

pressure seemed to have much more positive effect on the flux compared to the more than triple

increment ofstirring rate.

4.13E·05

3.20E-OS

~ 22SE-05

4.21E·06

B: Pressure

x----------------.--I

.6 X 105 Pa

... 12 X 105 Pa

4.13E-05 -

3.20E-05 -

2.2BE-05 -

1.35E-05 -

4.21E-Q(s -

I

INF90

NF200

" A: Membrane(a)

D: Stirring rate

INF2QQ\,

NF270

INF270

OK

.300 rpm

... 1000 rpm

IDK

I

A; .••Membranelb)

Figure 33: DESIGN-EXPERT plots. Interaction between (a) membranes and pressure; (b)

membranes and stirring rate for flux during rejection ofdimethoate.

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Meanwhile, interaction graph between pressure and stirring rate for each membrane is

presented in Figure 37. All membranes showed the highest flux performance at high pressure

and stirring rate as shown in Figure 37 (a) - (d).

3.11tJ.00 600

(a) (b)

\, 10000 600

~ ~

Figure 34: DESIGN-EXPERT plots. Interaction between pressure and stirring rate for (a) NF90;

(b) NF200; (c) NF270; (d) DK for flux during rejection ofdimethoate.

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Confirmation Test

In order to validate the adequacy of the model, four confirmation runs were performed

for each pesticide. The conditions are listed in Table 6 and Table 7 for atrazine and dimethoate,

respectively. The test conditions for the confirmation experiments were obtained from Design

Expert 6.0.6. software. The predicted values were also obtained from the software based on the

models developed previously. The predicted values and the actual experimental values were

compared and the percentage error was calculated. All these values are listed in Table 6 and

Table 7 as well. The percentage error between the actual and predicted value for rejection and

flux rate are within 10% range. Thus, the empirical models developed were reasonably accurate,

for both the rejection and permeate flux.

Modeling of Spiegler-Kedem

Although the Design Expert 6.0.6. software was able to produce regression model for

the performance of the nanofiltration membranes tested, it is important to validate performance

of the membrane using mathematical model. Since NF90 prevailed as the best-performed

nanofiltration membrane in this study, it was subjected to validation using Spiegler-Kedem (SK)

model. Spiegler-Kedem model is a mathema~cal model for reverse osmosis and nanofiltration

process based on irreversible thermodynamics (Ahmad et al., 2005). The rejection and permeate

flux data used for this section was obtained from earlier section on effect ofoperating pressure.

\,

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Table 6: Conftrmation experiments for atrazine.

Membrane Pressure Pesticide Stirring % Rejection Flux (m3/m2.s)

x 105 concentration rate Actual Predicted Error Actual Predicted Error

(Pa) (mg/L) (rpm) (%) (%)

NF90 12 15.78 1000 95.02 97.89 3.02 2.49E-05 2.67E-05 7.37

NF200 12 5.07 -- 1000 72.32 76.31 5.52 2.34E-05 2.16E-05 7.61

NF270 12 6.39"; 1000 58.03 61.67 6.27 3.94E-05 3.86E-05 2.02

OK 12 13.99 1000 65.98 67.27 1.96 9.86E-06 1.08E-05 9.50

...-Table 7: Conftrmation experiments for dimethoate.

Membrane Pressure Pesticide Stirring % Rejection Flux (m3/m2.s)

x 105 concentration rate Actual Predicted Error Actual Predicted Error

(Pa) (mg/L) (rpm) (%) (%)

NF90 12 4.42 1000 88.34 90.23 2.14 2.53E-05 2.75E-05 8.77

NF200 12 8.98 1000 61.68 60.64 1.69 2.35E-05 2.12E-05 9.96

NF270 12 6.03 1000 50.41 55.33 9.76 3.99E-05 3.96E-05 0.79

OK 12 10.05 955 59.72 64.67 8.28 9.88E-06 9.95E-06 0.75

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Parameter Estimation

The Spiegler-Kedem model was characterized by the hydraulic permeability of the

membrane, Pw ' reflection coefficient, (j', solute permeability, Ps and mass transfer coefficient,

ks ' Results of parameter estimation for NF90 using Levenberg-Marquardt method is shown in

Table 10.

Table 8: Parameters estimated using Lavenberg Marquardt Method on the

experimental results.

Parameter Value

Atrazine Dimethoate

Hydraulic permeability, Pw

Reflection coefficient, (j'

Solute permeability, Ps

Mass transfer coefficient, ks

2.361lE-ll

0.9835

3,4317E-07

1.2894E-05

2.3611E-ll

0.9560

2,4142E-06

1.2524E-05

The reflection coefficient, a, was in good agreement with the results obtained in the

experimental work as it showed that NF90 had the value of an almost ideal membrane. This is

because the value close to 1 meant that it had high ability to pass solvent in preference to solute

(Spiegler and Kedem, 1966), resulting in high rejection of solute by NF90. Meanwhile, atrazine

had slightly higher mass transfer coefficient than dimethoate due to its slightly lower molecular

weight (Schwarzenbach et al., 1993). However, atrazine had obviously lower solute permeability,I

Ps ' compared to dimethoate. This lower solute permeability value possessed by atrazine explains.,.its higher rejection compared to dimethoate.

Comparison between Experimental and Modeling Data

The rejection of pesticide against permeat<v flux curve is presented in Figure 35. It can be,seen from the comparison between the experimental data and predicted data that the Spiegler-

Kedem model provided a good prediction in representing the experimental value. In fact, the

coefficient of determination (R2) obtained for the fitted data was 0.9871 and 0.9692 for atrazine

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and dimethoate, respectively. This shows that as confirmed by the irreversible thermodynamics

model, the rejection of solute increased with the increasing permeate flux.

The solute rejection and permeate flux are plotted against applied pressure in Figure 36

and Figure 37, respectively. It is observed that while the solute rejection against pressure curve

for predicted value by Spiegler-Kedem model fitted well with the experimental data, the model

was unable to match the slope of the experimental flux against pressure curve as good as it did in

the case for rejection. However, the trend as experimental data was still in agreement with the

predicted data by the model and did not deviate far from each other.

1.00

0.90

0.80

0.70

c 0.600

+:30.50CJ

CIl'ara::: 0.40

0.30

0.20

0.10

.. . - --. - - - -.............................

0.00 ----,------,----..,----,----,-------,------,

O.OOE+OO 5.00E-06 1.00E-05 1.50E-05 2.00E-05 2.50E-05 3.00E-05 3.50E-05

Flux (m3/m2.s)

• Experim~t atrazine•••• - . SK model atrazine

• Experiment dimethoate

---SK model dimethoate

Figure 35: Solute rejection against permeate flux curve from experimental data and the predicted

results from Spiegler-Kedem model.

\,

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.........................................1.00

0.90

0.80

0.70

c 0.600:t:lu 0.50ell'(j)'a::: 0.40

0.30

0.20

0.10

0.000 2

.................

4 6 8 10 12 14 16

Pressure x 105 (Pa)

• Experiment atrazine•••••. SK model atrazine

• Experiment dimethoate

---SK model dimethoate

Figure 36: Solute rejection plotted against preSSlffe using the experimental data and predicted

results from Spiegler-Kedem mod;!:

4.00E-05

3.50E-05

3.00E-05

U! 2.50E-05...E

",-

2.00E-05.§.><:::J 1.50E-05ii:

1.00E-05

5.00E-06

O.OOE+OO0 2 4 6 8 10

I

Pressure x 105 (Pa)

12 14 16

I • Experiment atrazine • Experiment dimethoate --SK model atrazine&dimethoate I

Figure 37: Permeate flux plotted against pressure using the experimental data and

predicted results from Spiegler-Kedem model.

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Concentration Polarization Profile

Figure 38 provides the concentration polarization profiles for atrazine and dimethoate at

different operating pressure. The profiles were gauged based on the ratio of membrane wall

concentration to bulk concentration (Cm/Cb) (Ahmad et at., 2007). Based on the membrane wall

concentration calculated from the Spiegler-Kedem model, the concentration polarization profile

was depicted to increase with the increasing pressure. Both solutes demonstrated similar trends on

concentration polarization where the solute concentrations increased from the initial bulk

concentration to the maximum concentration (wall concentration) at the maximum pressure

applied. Although previous results showed that the rejection increased with the increasing

pressure, these profiles show that the effect of concentration polarization would be magnified

with the increasing pressure. The same trend was also observed by Bhattacharjee and Datta

(2003). Thus, due consideration should be given when choosing the suitable applied pressure for

nanofiltration system.

18

16

14

12

'" 100-E0 8

6

4

2

00 2 4 <if. 6 8 10 12 14 16

Pressure x 105 (Pa)

I- .+ - .Atrazine • Dimethoate I

Figure 38: Concentration polarization profile plotted against pressure.

;,

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,,

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APPENDIX 3

Journal Publications

,..

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ELSEVIER

Available online atwww.$ciencedirect.com..~",-.;- ScienceDirect

Journal of Hazardous Materials xxx (2007) xxx-xxx

Journal ofHazardousMaterials

www.elsevier.com/locate/jhazmat

Abstract

Dimethoate and atrazine retention from aqueoussolution by nanofiltration membranes

A.L. Ahmad *, L.S. Tan, S.R. Abd. ShukorSchool a/Chemical Engineering, Engineering Campus, Universiti Sains Malaysia,

14300 Nibong Tebal, Seberang Prai Selatan, Pulau Pinang, Malaysia

Received 14 December 2006; received in revised form 15 May 2007; accepted 16 May 2007

In order to produce sufficient food supply for the ever-increasing human population, pesticides usage is indispensable in the agriculture sectorto control crop losses. However, the effect of pesticides on the environment is very complex as undesirable transfers occur continually amongdifferent environmental sections. This eventually leads to contamination ofdrinking water source especially for rivers located near active agriculturepractices. This paper studied the application ofnanofiltration membrane in the removal of dimethoate and atrazine in aqueous solution. Dimethoatewas selected as the subject of study since it is being listed as one of the pesticides in guidelines for drinking water by World Health Organization.Nevertheless, data on effectiveness of dimethoate rejection using membranes has not been found so far. Meanwhile, atrazine is classified as one ofthe most commonly used pesticides in Malaysia. Separation was done usin&, a small batch-type membrane separation cell with integrated magneticstirrer while concentration of dimethoate and atrazine in aqueous solution was analyzed using high performance liquid chromatography (HPLC).Four nanofiltration membranes NF90, NF200, NF270 and DK were Tested for their respective performance to separate dimethoate and atrazine.Of all four membranes, NF90 showed the best performance in retention of dimethoate and atrazine in water.©2007 Elsevier B.V. All rights reserved.

rfeywords: Nanofiltration; Membrane technology; Pesticides; Dimethoate; Atrazine

1. Introduction

Malaysia is an active player in agriculture practice, plant­ng oil palm, paddy, fruit, vegetables and many other products'or local consumption and some for export purpl>ses. PesticidesIre also part and parcel of agriculture sector as' a mean of pest:ontrol for sustainability of the industry. Annuall~ sales fig­Ire of approximately RM 300 million is recorded by Malaysian;ropLife and Public Health Association [1]. The huge amount oflesticides used is emerging as contaminants in water. This is noturprising because pesticides sprayed on crops can be drifted by~ind into nearby water source while pesticides applied directly) the soil can be washed off by rain into nearby surface waterodies or percolate through the soil to lower soil layers androundwater [2].

• Corresponding author. Tel.: +6045937788; fax: +6045941013.E-mail addresses:[email protected] (A.L. Ahmad),

[email protected](L.S. Tan),[email protected] (S.R.Abd. Shukor).

104-3894/$ - see front matter © 2007 Elsevier B.V. All rights reserved.li:1O.l0l6/j.jhazmat.2007.05.047

In this study, the pollutants selected were dimethoate andatrazine. Dimethoate is a type of organophosphorus insecticidethat has been identified as one of the chemicals from agricul­ture activities for which guideline value has been established byWorld Health Organization in the guidelines for drinking water[3]. In fact, its presence in water is not a surprise since it is highlysoluble in water and adsorbs very weakly to soil particles, thus,subjecting it to considerable leaching [2]. Although this woul~

normally cause minute concentration of pesticides presence inwater, its chronic effect to the livings has been of more concern.Doull [4] reported that dimethoate could cause oncogenicity,mutagenicity, fetotoxicity and reproductive effects. Meanwhile,the other pollutant studied is atrazine as it is among the mostc,ommonly used pesticides in Malaysia especially for its usagea~ herbicide in plantations. Although atrazine is considered to bea low toxic herbicide, extensive amount of its usage has rankedit among the most common pesticides found in surface waterand groundwater [5]. This situation has warranted urgent globalattention to abate theirpresence in drinking water. Recent reportshave revealed that high doses of atrazine induce abnormalitiesand deformities in non-target organisms. Furthermore, the syn-

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2 A.L. Ahmad et at. / Journal ofHazardous Materials xxx (2007) xxx-xxx

,.­

Nomenclature

A membrane areaCf concentration of feedCp concentration of permeatebt time differenceb V cumulative volume differenceKow octanollwater partition coefficientLv membrane permeabilityR percentage of pesticide rejectionVw permeate flux

ergy effect of dimethoate-atrazine is more lethal than the effectof the individual pesticide since the toxicity of dimethoate wasenhanced significantly when they are in binary combination [6].

Traditionally, removal of pesticides for the production ofdrinking water was done by activated carbon filtration. It waseffective, but expensive and required frequent regeneration [7].Over the past few years, nanofiltration membranes have beenstudied as potentially useful means of pesticide removal con­sidering the fact that the molecular weights (MWt) of mostpesticides are more than 200 Da [2,5].

Nanofiltration has been successfully applied in drinkingwater treatment plant in Mery-sur-Oise, France [8], Leiduin [9].and Heemskerk [10] in Holland as well as Saffron Walden inEngland [11]. However, there is still a long list of pesticidesin guidelines for drinking water by World Health Organization[3] but lack of data for their effective separation using mem­brane, including dimethoate. Therefore, there are still room forthe investigation ofthe feasibility ofusing membrane technologyto remove dimethoate from water, with addition to observationfor binary mixture of dimethoate-atrazine.

Thus, the objective of this study is to examine the perfor­mance of nanofiltration membranes to retaindimethoate andatrazine in aqueous solution. Four nanofiltrati&n membraneswere subjected to stirred dead-end filtration. The effect of feedconcentration and operating pressure on the permeafe flux andfeed-based rejection of dimethoate and atrazine were investi­gated.

Table 1Properties of dimethoate and atrazine [2]

2. Materials and methods

2.1. Pesticides

Dimethoate with 99.8% purity and atrazine with 97.4% puritywere purchased from Riedel-de Haen (Germany). The molecularstructures of both pesticides are presented in Table 1.

2.2. Membranes

Three types of nanofiltration membranes provided byDowlFilmtec (USA) and another type of nanofiltrationmembrane purchased from Osmonics (USA) were used inthis experiment. The thin film polyamide membranes fromDowlFilmtech used were NF90, NF200 and NF270, while thethin film polyamide membrane from Osmonics used was DK.Polyamide membranes were used in this study because they wereable to achieve good pesticides retention [12,13]. Table 2 pro­vides the specification of the membranes used as given by themanufacturers.

2.3. Membrane stirred cell

A 300-mL stirred cell (Sterlitech), model Sterlitech™HP4750, USA, was used to conduct the dead-end filtrationexperiments. The membrane diameter was chosen to be 0.049 mwith effective membrane area ofl,46 x 10-3 m2. The maximumoperating pressure for this cell was 69 x 10+5 Pa.

2.4. Experimental setup and procedure

Dead-end filtration experiments were carried out with thestirred cell (Sterlitech™ HP4750). The pesticide solution inthe cell was stirred by a Teflon-coated magnetic bar. The cellwas pressurized using compressed high purity nitrogen gas. Thepressure in the permeate side was approximately atmosphericunder all condition. The transmembrane pressures used duringexperiments were 6 and 12 x 10+5 Pa. The concentration of pes­ticide was set to be at 2 and 20 mglL. This concentration washigher than the usual concentration found in the case of run-offdue to consideration of the membrane in case of accidental spillofpesticides in water source. The stirring speed was set constantat 1000 rpm.

AtrazinePesticide

Chemical structure

Molecular weight (Da)Solubility in waterLog octanol/water partition coefficient, Kow

" [16].

Dimethoate

s \II _/'/~

/0-P1-:S- II CH.3CH 0

3 0/

CH:J229.2825 gIL at 21°C0.70

TN, N--l~~~N~

H3C H N H CH3

215.6920 mglL at 20°C2.61"

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AL. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx 3

Table2Specification of membrane used

Membrane NF90 NF200 NF270 DK

ManufacturerMaterialContact angle (0)"pure water permeabilityb (m3{(m2 sPa))Maximum operating pressure (Pa)Maximum operating temperature (OC)

pH range

DowlFilmtecPolyamide

1.90 X 10-11

41 x 10+5

453-10

DowlFilmtecPolyamide26±21.17 x 10-11

41 x 10+5

453-10

DowlFilmtecPolyamide28±23.20 x 10-11

41 x 10+5

453-10

OsmonicsPolyamide

7.84 X 10-12

40 X 10+5

383-10

" [5].b Our measurements.

Fig. 1. Schematic diagram of experimental setup.

where ~V is the cumulative volume difference (m3), ~t is thetime difference (s) andA is the membrane area (m2), respectively.

All experiments were conducted at room temperature(25 ± 2 QC). A schematic diagram of the expertnental setup isshown in Fig. I. .

(2)

2.5. Analytical method

Concentration of dimethoate and atrazine in feed and perme­ate was analysed using high performance liquid chromatography(HPLC) by Perkin Elmer (USA). The HPLC column usedwas Zorbax SB-CN (5fJo, 4.6mm Ld. xl50mm long, AgilentTechnologies). The mobile phase was a mixture of 35% ace­tonitrile and 65% deionized water while the flow rate was set at1.0 mL/min. The UV detector was operated at a wavelength of200 nm. The peak for dimethoate was detected at around 3.5 minwhile the peak for atrazine was detected at around 5.3 min. Per­centage of rejection was obtained with the following equation:

where R is the percentage of pesticide rejection, Cp is the con­centration of permeate (mglL) and Cf is the concentration offeed (mglL)

3.1. Retention ofdimethoate and atrazine

3. Results and discussion

The retention performance of dimethoate and atrazine byNF90, NF200, NF270 and DK at different pressure and con­centration is presented in Figs. 2 and 3, respectively. From thesefigures, it is obvious that the retention of both dimethoate andatrazine tend to be better when the pressure was increased from6 to 12 x 10+5 Pa. It could be seen that NF90 produced the bestretention performance for the operating pressure and feed con­centration tested, at approximately 85% for dimethoate and morethan 95% retention for atrazine. The performance of DK wasthe second highest of all four membranes tested while NF200showed slightly lower retention than DK when both were oper­~ted at the same pressure and feed concentration. NF270 showedthe lowest rejection performance out of the four membranestested, especially for dimethoate retention. Higher retention wasobserved at higher pressure due to the increased water flux. Theconcentration of permeate became diluted with the increasedwater flux as the solute molecule was rejected by molecularsieving effect.

Meanwhile, the concentration effect was less significant onrejection of dimethoate and atrazine as compared to the effectof pressure as there was only slight increment of rejection per-

R = (1 - Cp) x 100%

" Cf

(1)

Pel'lllc.tc

MombrlUloStirred Coil

SmilllessSteolFecd.Tollk

~@ :Pressuroregu!a1or

~ :V.t"e

The cell contained a nanofiltration membrane with an effec­tive area of 1.46 x 10-3 m2. The membrane was immersed for24 h in deionized water before being used in any experimentalwork. Membrane permeability was determined by initially filter­ing it using deionized water at 12 x 10+5 Pa for approximately8 h for compaction to avoid compression effect in the later stageof experiment. Then, stabilized water flux at different operat­ing pressures was obtained and membrane permeability values(Lp) could be determined from the slope of flux against pressuregraph.

For separation process, the same compaction process wascarried out before the test cell was emptied and 1.8 L of feedsolution was filled into the test cell and solution reservoir. Thecell was then pressurized at the operating pressure indicated bya pressure regulator. Permeate from the bottom of the cell wascollected and its weight was measured with an electronic balance·of ±0.01 g accuracy. The cumulative weight were converted tocumulative volume and the permeate flux could be obtained.Permeate flux, Vw (m3/m2 s), was obtained using Eq. (1):

~VVw=--

~t· A

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A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx

100 100(b)

80 80c c0

~ 60 0 60(I) ~'iii' (I)

0:: 'iii'40

?fl-40 0::

?fl-

20 20

0 06 12 6 12

Pressure x 10+5 (Pa) Pressure x 10+5 (Pa)

100 100(c) (d)

80 80

c c0 0 60:;:l 60 :;:lu u(I) (I)'iii' 'l0:: 40 40?fl- ?fl-

20 20

0 06 12 6 12

Pressure x 10+5 (Pa) Pressure x 10.5 (Pa)

1m2 mg/L lEI 20 mg/L IFig. 2. Rejection of dimethoate by Nf'iJQ (a), NF200 (b), NF270 (c), and DK (d).

100 100(b)

80 80

c c0 60 0 60~

:;:lu

(I) (I)

'iii'40

'iii'0:: 0:: 40?fl- ::!!0

20 20

0 06 12 6 12

Pressure x 10·f (pa) Pressure x 10+5 (Pa)

100 100(c) (d)

80 80

c c0 60 0 60:;:l :;:lu u(I) (I)

'l..,..

40(I)'0::' 40

::!! ?fl-o

20 20

0 06 12 6 12

Pressure x 10+5 (Pa) Pressure x 10+5 (Pa)

1m2 mg/L 1SlI20 mg/L IFig. 3. Rejection of atrazine by NF90 (a), NF200 (b), NF270 (c), and DK (d).

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A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx 5

formance although the concentration was increased 10 times ascompared to two times increment of pressure. This finding is inagreement with work done by Causserand et a1. [13] and Zhanget a1. [14]. This shows that in practical terms, the membraneshave almost the same efficiency level for dimethoate rejectioneven though the feed concentration varies as much as 10 timesfrom time to time. However, atrazine retention performance ofNF200 and NF270 of around 80% was obtained by Plakas eta1. [5] when the concentration of atrazine was between 0.150and 0.300 mg/L. This suggests that while effect of concentra­tion did not pose much impact if compared to effect of pressure,it was still a valid gradient for transport of solute through mem­brane. NF90 was found to be a more robust membrane in viewof atrazine retention since its retention was almost equal even atsuch high concentration of 2-20 mg/L.

Overall, all four membranes tested showed better retentionfor atrazine than dimethoate although dimethoate has slightlyhigher molecular weight than atrazine. Several rcports [15-18]suggested that although molecular sieving effect must not beneglected, hydrophobicity of the solutes played a very importantrole in determining the retention performance by membrane.The higher the value of log Kow , the better the rejection wouldbe. This behaviour was shown in this study since atrazine has

higher hydrophobicity than dimethoate. Moreover, dimethoatehas aliphatic molecular structure compared to the heterocyclicaromatic structure of atrazine. Kiso et aI. [16] reported that non­phenylic pesticides were rejected at a relatively lower degreethan phenylic pesticides.

3.2. Permeate flux performance

Figs. 4 and 5 show the flux performance of the membranes fordimethoate and atrazine retention, respectively. Based on thesefigures, it was obvious that the increase in pressure had signifi­cant effect on permeate flux for both dimethoate and atrazineretention tests. All membranes tested experienced approxi­mately double increment of permeate flux when the operatingpressure was doubled from 6 to 12 x 10+5 Pa. This shows thatpermeate flux increment corresponded linearly to the pressureapplied to the solution. Meanwhile, concentration of feed hadvery little effect on the permeate flux as compared to operat­ing pressure. It showed no significant trend although it causedslightly lower permeate flux when it was increased for certainmembrane especially at P= 12 x 10+5 Pa run. Thus, effect ofconcentration can be excluded from consideration when it comesto flux performance.

4.00 4.00(a) (b)

3.50 3.50

ur 3.00 ur 3.00N N

E E 2.50;0- 2.50 ;0-

.§. .§."I 2.00 "I 2.000 0.... ....

1.50>< 1.50 ><>< ><:::I :::I 1.00u: 1.00 u:

0.50 0.50

0.00 0.00

6 12 6 12

Pressur~ x 10+5 (Pa) Pressure x 10+5 (Pa)

4.00 4.00(d)

3.50 3.50

ur 3.00 ur 3.00N N

E E;0- 2.50

;0- 2.50.§. .§."I 2.00 "I 2.000 0.... ....>< 1.50 >< 1.50>< ~ )(:::I ':::I

u: 1.00 u: 1.00

0.50 0.50

0.00 0.006 12 6 12

Pressure x 10+5 (Pa) Pressure x 10+5 (Pa)

1m2 mg/L 12120 mg/L IFig. 4. Flux performance on dimethoate by NF90 (a), NF200 (b), NF270 (c), and DK (d).

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A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx

4.00 4.00(a) (b)

3.50 3.50

U! 3.00 U! 3.00N N

E E... 2.50 ... 2.50.§. .§.'7 2.00 '7 2.00Cl Cl.... ....>C 1.50 >C 1.50>C >C:::l :::l

u::: 1.00 u::: 1.00

0.50 0.50

0.00 0.006 12 6 12

Pressure x 10+5 (Pa) Pressure x 10+5 (Pa)

4.00 4.00(d)

3.50 3.50

U! 3.00 U! 3.00N N

E E... 2.50 ... 2.50.§. .§.'7 2.00 '7 2.00Cl Cl.... ....>C 1.50 >C 1.50>C >C:::l :::l

u::: 1.00 u::: 1.00

0.50 0.50

0.00 0.006 12 6 12

Pressure x 10+5 (Pa) Pressure x 10+5 (Pa)

11m2 mg/L liS 20 mg/L IFig. 5. Flux perfonnance on atrazine by NF90 (a), NF200 (b), NF270 (c), and DK (d).

NF270 produced the highest permeate flux for all conditionstested. This was especially obvious at operating pressure of12 x 10+5 Pa. NF90 showed the second highestpermeate flux outof the four membranes with approximately 40% IO'fer comparedto permeate flux by NF270. Meanwhile, NF200 snowed consid­erably low flux rate compared to NF270 while DK,.producedthe lowest permeate flux performance as it has approximately300% lower flux compared to NF270. Based on the publisheddata, NF270 had average pore size of 0.71 nm, NF90 had aver­age pore size 0.55 nm while NF200 had average pore sizeof 0.38 nm [19,20]. Hence, the results obtained in this studycorresponded to the average pore size reported in the litera­ture.

However, this also showed that while 0.55 nm average poresize for NF90 was sufficient to retain dimethoate and atrazinewith high percentage of rejection, solute-membrane interactionfactor was also important [15,18,21] as DK and NF200 couldnot sustain as much rejection as NF90 although DK had similaraverage pore size with NF90 [22] while NF200 had smalleraverage pore size. The interaction between membrane materialfor DK and pesticides tested was believed to contribute to thecrossing of solutes through the membrane because it had lowerpercentage of retention of pesticides compared to NF90. This

validated the claim by the manufacturer that NF90 is suitablefor pesticides and herbicides removal [23].

3.3. Retention performance ofNF90 foratrazine-dimethoate

Since NF90 showed good rejection for both atrazine anddimethoate individually, rejection of atrazine-dimethoate wastested at pressure of 6 x 10+5 Pa and stirring rate of 1000 rpmto examine if the membrane would have the same goodperformance when the two pesticides co-exist. The ratio ofatrazine:dimethoate was set at 20:80,50:50 and 80:20 for a totalof 10 mg/L pesticides. Fig. 6 shows that NF90 still maintained itsgolild performance of retention for both atrazine and dimethoatein the presence of binary mixture of pesticides, although therewas slightly lower retention observed compared to the singlesolute condition. This observation was in line with observa­tion by Plakas et al. [5] which suggested that simultaneousfiltration of more than one pesticide resulted in a kind of com­petitive adsorption on the membrane surface and, thus, created agreater passage to the permeate side. These results were also inagreement with the report by Kiso et al. [16] which found thatherbicides displaying higher rejection in single solute solutions

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Fig. 6. Rejection performance of atrazine-dimethoate for NF90.

References

7

[2] M.A. Kamrin, Pesticide Profiles: Toxicity, Environmental Impact and Fate,CRC Press, Boca Raton, 1997.

[3] World Health Organization. Guidelines for drinking-water qualit:'2004, third ed. http://www.who.int/water_sanitation..health/dwq/gdwq3/enlindex.html. Accessed on 16 June 2005.

[4] J. Doull, Pesticide Carcinogenicity, in: N.N. Ragsdale, R.E. Menzer (Eds.),Carcinogenicity and Pesticides: Principles, Issues and Relationship, Amer­ican Chemical Society, Washington DC, 1989, pp. 1-5.

[5] K.V. Plakas, A.J. Karabelas, T. Wintgens, T. Melin, A study of selected her­bicides retention by nanofiltration membranes-the role of organic fouling,J. Membr. Sci. 284 (2006) 291-300.

[6] T.D. Anderson, KY. Zhu, Synergistic and antagonistic effects of atrazineon the toxicity of organophosphorodithioate and organophosphoroth­ioate insecticides to Chironomustentans (Diptera: Chironomidae), Pestic.Biochem. Physiol. 80 (2004) 54-64.

[7] B. van der Bruggen, J. Schaep, W. Maes, D. Wilms, C. Vandecasteele,Nanofiltration as treatment method for the removal of pesticides fromground waters, Desalination 117 (1998) 139-147.

[8] B. Cyna, G. Chagneaub, G. Bablon, N. Tanghe, Two years ofnanofiltrationat the Mery-sur-Oise plant, France, Desalination 147 (2002) 69-75.

[9] P.A.C. Bonne, E.F. Beerendonk, J.P. van der Hoek, J.A.M.H. Hofman,Retention of herbicides and pesticides in relation to aging RO membranes,Desalination 132 (2000) 189-193.

[10] J.A.M.H. Hofman, E.F. Beerendonk, H.C. Folmer, J.C. Kruithof, Removalof pesticides and other micropollutants with cellulose acetate, polyamideand ultra-low pressure reverse osmosis membranes, Desalination 113(1997) 209-214.

[11] E. Wittmann, P. Cote, C. Medici, J. Leech, A.G. Turner, Treatment of ahard borehole water containing low levels of pesticide by nanofiltration,Desalination 119 (1998) 347-352.

[1'2] S.S. Chen, S.T. James, L.A. Mulford, C.D. Norris, Influences of molec­ular weight, molecular size, flux, and recovery for aromatic pesticideremoval by nanofiltration membranes, Desalination 160 (2004) 103­111.

[13] C. Causserand, P. Aimar, J.P. Cravedi, E. Singlande, Dichloroanilineretention by nanofiltration membranes, Water Res. 39 (2005) 1594­1600.

[14] Y. Zhang, B. van der Bruggen, G'x. Chen, L. Braeken, C. Vandecasteele,Removal of pesticides by nanofiltration: effect of the water matrix, Sep.Purlf. Techno!. 38 (2004) 163-172.

[15] C. Bellona, J.E. Drewes, P. Xu, G. Amy, Factors affecting the rejection oforganic solutes during NF/RO treatment - a literature review, Water Res.38 (2004) 2795-2809.

[16] Y. Kiso, Y. Nishimura, T. Kitao, K Nishimura, Rejection properties ofnon-phenylic pesticides with nanofiltration membranes, J. Membr. Sci. 171(2000) 229-237.

[17] Y. Kiso, Y. Sugiura, T. Kitao, K. Nishimura, Effects of hydrophobicityand molecular size on rejection of aromatic pesticides with nanofiltrationmembranes, J. Membr. Sci. 192 (2001) 1-10.

[18] K Kosutic, L. Furac, L. Sipos, B. Kunst, Removal of arsenic and pesticidesfrom drinking water by nanofiltration membranes, Sep. Purif. Techno!. 42(2005) 137-144.

[19] N. Hilal, H. AI-Zoubi, N.A. Darwish, A.W. Mohammed, Characterisationof nanofiltration membranes using atomic force microscopy, Desalination177 (2005) 187-199.

[2P] X. Lefebvre, J. Palmeri, J. Sandeaux, R. Sandeaux, P. David, B. Maleyre,, C. Guizard, P. Amblard, J.-F. Diaz, B. Lamaze, Nanofiltration modeling: a

comparative study of the salt filtration performance of a charged ceramicmembrane and an organic nanofilter using the computer simulation programNANOFLVX, Sep. Purif. Techno!. 32 (2003) 117-126.

[21] T.-V. Kim, G. Amy, J.E. Drewes, Rejection of trace organic compounds byhigh-pressure membranes, Water Sci. Techno!. 51 (2005) 335-344.

[22] J.L.C. Santos, P. Beukelaar, I.F.J. Vankelecom, S. Velizarov, J.G. Crespo,Effect of solute geometry and orientation on the rejection of unchargedcompounds by nanofiltration, Sep. Purif. Techno!. 50 (2006) 122-131.

[23] The Dow Chemical Company, nanofiltration products, Filmtec1M mem­branes, http://www.dow.com/liquidseps/prod/app..nano.htm. Accessed on20 November 2006.

10080

-A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx

40 60% Atrazlne

20

100

80

i 60

~ 40

~ 20

00

Authors would like to thank Universiti Sains Malaysia forfunding this research with short-term grant (Account 6035167).Appreciation also goes to DowlFilmtec for providing the mem­branes.

4. Conclusion

Acknowledgements

[I] Malaysian CropLife and Public Health Association. http://www.mcpa.org.my/index.php. Accessed on 2 June 2006.

The performance of nanofiltration membrane to retaindimethoate and atrazine in aqueous solution was examinedin this study. Four nanofiltration membranes, NF90, NF200,NF270 and DK, which have molecular weight cut-off of around200 were subjected to stirred dead-end filtration and the effect offeed concentration and operating pressure on the permeate fluxand feed-based rejection of dimethoate was investigated. It was· •found that increasing the transmembrane pressure posed positiveeffect on dimethoate and atrazine rejection and permeate flux.However, effect of feed concentration had little significance onthe performance of the membranes tested.

NF90 showed the best retention performance while NF270showed the highest permeate flux out of the four membranestested. However, good retention quality should be the primaryproperty in choosing the appropriate nanofiltration membranefor application in pesticides treatment from water. Therefore,despite its high permeate flux, NF270 is not suitable especiallyfor dimethoate retention as it showed the poorest Jetention quaI­ity. NF90 is deemed the more suitable nanofiltration membranefor dimethoate and atrazine retention from aqueo~ solutionsince, it showed the highest retention of dimethoate and atrazinecoupled with considerably good permeate flux. Furthermore,although there was slight reduction of retention performance forNF90 in binary atrazine-dimethoate solution, it stilI managed tomaintain its robust retention performance.

may permeate more in mixed solute systems. However, resultsobtained in this study showed that while there was slight reduc­tion of pesticides retention, the performance of NF90 was stilIcommendable even though it was in mixed solute system.

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ELSEVIER

Available online at www.sciencedirect.com...-""'@;' ScienceDirect

Journal of Hazardous Materials xxx (2007) xxx-xxx

Journal ofHazardousMaterials

www.elsevier.com/locate/jhazmat

ysia, 14300 Nibong Tebal,

pted 23 October 2007

atmosphere and water. The presence of pesticides in water hasbeen reported by previous researchers [5-9]. Low-level residue.;of pesticides in water generally may not present acute toxicityproblems, but chronic effects will likely be ofconcern [10]. Thisis because pesticides could have chronic effects such as cancer[11-13], reproductive effects, fetal damage, delayed neurologicmanifestations and possible immunologic disorders [12].

In view ofthis scenario, many studies on separation of pesti­cides using nanofiltration membranes have been done in recentyears. Size exclusion by a nanofiltration membrane is recog­nized to be the main retention mechanism for pesticides. Otherparameters such as hydrophobicity, dipole moment, polarity andcharge of a molecule have also been found to influence the rejec­tion performance [14-18]. On the other hand, according to Chenet al. [19], rejection of pesticides was dependent on operationalflux and recovery as well. For a particular pesticide in the tw...oPerational fluxes and recoveries, the highest percent rejectionoccurred at high flux and low recovery, and the lowest percentrejection occurred at low flux and high recovery. Meanwhile, astudy done by Zhang et al. [20] found that pore narrowing byion adsorption and water matrix influenced rejections.

So far, not much attention has been given to the changesin nanofiltration performance during nanofiltration of pesti-

plext envi­

air mayan effec­

away fromay locations

to til; soil mayce water or per­

groundwater [2].tended to urban­

that the movementy a function of water

sorption capacities of

esticides is, it will even­reat to human's health via

37788; fax: +6045941013..my (A.L. Ahmad),[email protected]

The role of pH in nanofiltration of atrazine anddimethoate from aqueous solution

A.L. Ahmad*, L.S. Tan, S.R. ASchool ofChemical Engineering, Engineering Campus, Universiti

Seberang Prai Selatan, Pulau Pinan

Received 9 July 2007; received in revised form 23 Octo

Keywords: Nanofiltration; Membrane teclmology; Pesticides; Dime

The effect of pesticides on the environment ias undesirable transfers occur continually amoronmental sections. Pesticides that are spraeventually end up in soils or water. The attive medium which can move airbornetheir application sites and redeposit the[1]. On the other hand, pesticides appliebe washed ofI by rain into nearby bodiGolate through the soil to lower soil IPesticides uses and transfers haveized catchments [3]. However, itofpesticide in and through the soisolubility of the pesticides anthe soil type [4].

No matter where the app .tually end up becoming a p

Abstract

This study examined the performance of nanofiltration membranes to ine and dimethoate in aqueous solution under different pHconditions. Four nanofiltration membranes, NF90, NF200, NF270 and D ted to be examined. The operating pressure, feed pesticide andstirring rate were kept constant at 6 x 105 Pa, 10mglL and 1000 rpm. It t increasing the solution's pH increased atrazine and dimethoaterejection but reduced the permeate flux perfOlmance for NF200, NF K. However, NF90 showed somewhat consistent performance inboth rejection and permeate flux regardless of the solution's pH. N :1i!;tained above 90% of atrazine rejection and approximately 80% ofdimethoate rejection regardless of the changes in solution's pH. Thus NF90 is deemed the more suitable nanofiltration membrane for atrazine anddimethoate retention from aqueous solution compared to NF200, d DK.© 2007 Published by Elsevier B.V.

1. Introduction

-• COlTesponding author. TelE-mail addresses: chla .

[email protected](L.S.(S,R.Abd. Shukor).

Q1

I 0304-3894/$ _ see front matter © 2007 Published by Elsevier B.V.I doi:l0.l0l6/j.jhazmat.2007.l0.073

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z A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx

215.6920mgIL @ 20 Ge1.7b

2.61c

5. Experimental set-up and procedure

2.2. pH adjustment

Atrazine

2.3. Membranes

The chemicals used to adjust the pH of the pesticide solu­tions for filtration experiments were hydrochloric acid, HC137%(w/w) and sodium hydroxide, NaOH (l M). These chemicalswere obtained from Merck.

Three types of nanofiltration membranes provided byDowlFilmtec (IJSA) and one type of nanofiltration membranepurchased frQ1h Water Technologies (USA) with molecu­lar weight cttf¥· (MWCO) of around 200 Da were used inthis expe . e thin film polyamide membranes fromDowlFil were NF90, NF200 and NF270 while thethin fil e membrane from GE Water Technologiesused Table 2 provides the specification of the mem-bran given by the manufacturers.

hnL stirred cell (Sterlitech), model Sterlitech™50, USA, was used to conduct the dead-end filtration·ments. The effective membrane area is 1.46 x 10-3 m2.

The maximum operating pressure for this cell was 69 x 105 Pa.

Dead-end filtration experiments were carried out with thestirred cell (Sterlitech™ HP4750). The pesticide solution in thecell was stirred by a Teflon-coated magnetic bar. The cell waspressurized using compressed high purity nitrogen gas. Thepres­sure in the permeate side was approximately atmospheric underall condition. The pesticides solution, prepared using deionizedwater, was adjusted to different initial pH by adding 1M NaOHor 37% (w/w) HCI. The pH measurement was conducted usingpH meter (Mettler Toledo Delta 320 pH Meter). The operating

H

S ~~o-~-s I'"'-CH3

~ I 'H3C 0 0

/H3C

229.2825 gIL @ 21 °e2.0'0.70

Nomenclature

A membrane areaCf concentration of feedCp concentration of permeateKow octanollwater partition coefficientLp membrane permeabilitypKa acid disassociation constantR percentage of pesticide rejection6.t time differenceVw permeate fluxb.V cumulative volume difference

Pesticide

Dimethoate with 99.8% purity and atrazine wiwere purchased from Riedel-de Haen (Germanstructures of both pesticides are presented in

2. Materials and methods

cides in aqueous solution when there are changes in its pH.However, this factor must not be neglected as the role of pHis also important in determining the stability of membrane[21,22]. Therefore, the objective of this study is to investigatethe performance of nanofiltration membranes to retain atrazineand dimethoate in aqueous solution under different pH condi­tions. The effect of initial solution's pH for pesticide rejectionand permeate flux were obtained and examined. This study isa continuation from a previous study which focused on theeffect feed concentration and operating pressure on the permate flux and rejection of dimethoate and atrazine from aquesolution [23].

2.1. Pesticides

Table IProperties of dimethoate and atrazine [2]

Chemical structureMolecular weight (Da)SolUbility in waterAcid disassociation constant, pLogKow-a [30].

b [31].c [32].-

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A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx 3

Table 2.Specification of membrane used

Membrane

ManufacturerMaterialContact angle" CO)Surface charge (pH 7)pure water permeabilitye (m3{(m2 sPa»Maximum operating pressure (Pa)Maximum operating temperature (DC)

pH range

NF90 NF200 NF270 DK

DowlFilmtec DowlFilmtec DowlFilmtec OsmonicsPolyamide Polyamide Polyamide Polyamide

26±2 28±2Negativeb Negativeb NegativeC Negatived1.90 x 10-11 1.17 x 10-11 3.20 X 10-11 7.84 X 10-12

41 X 105 41 X 105 41 X 105 40 x lOS45 45 45 383-10 3-10 3-10 3-10

Concentration of atr dimethoate in feed and perme-ate was analysed usin ormance liquid chromatography(HPLC) by Perkin-Elmer SA). The HPLC column usedwas Zorbax SB-CN (5/-L, 4.6 mm i.d. x 150 mm long, AgilentTechnologies). The mobile phase was a mixture of 35% ace­tonitrile and 65% deionized water while the flow rate was set at

II

(2)

AnalyticalBalance

Pornlcate

MembraneStirred Cell

Magnetic Stirrer

StainlessSteelFeed Tank

Fig. 1. Diagram of experimental set-up.

~® :Pressureregullltor

~ :VllIve

where R is the percentage of pesticide rejection, Cp is the con­centration of permeate (mg/L) and Cf is the concentration offeed (mg/L)

1.0 mLimin. The UV detector was operated at a wavelength of200 nm. The peak for dimethoate was detected at around 3.5 minwhile the peak for atrazine was detected at around 5.3 min. Per­centage of rejection was obtained with the following equation:

R = (1 - ~:) x 100%

3. Results and discussion;,

The effect of initial solution's pH on the atrazine anddimethoate rejection at fixed operating pressure, pesticide con­centration and stirring rate are presented in Figs. 2 and 3. Fromthe figures, it can be seen that the rejection performance foratrazine and dimethoate by NF200, NF270 and DK increasedas the pH was increased while the rejection trend for NF90 wasalmost constant regardless of the pH condition. The percent-

3.1. Rejection ofatrazine and dimethoate

(1)

ce (m3), ~t is the(m2), respectively.for four times and

les were used as thee conducted at room

diagram of the experi-

" [331.b [341.C [351.d [361e Our measurements.

~Vv --­

w - ~tA

where ~V is the cumulative volumetime difference (s) andA is the mem

Samples were collected at evthe average values obtained fromresults in this work. All expe 'etemperature (25 ± 2 QC). A smental set up is shown in Fi

2.6. Analytical method

pressure, feed pesticide and stirring rate were kept constant at6 x 105 pa, lOmg/L and 1000rpm while the initial solution'spH were varied at 4, 7 and 9.

The cell contained a nanofiltration membrane with an effec­tive area of 1.46 x 10-3 m2. The membrane was immersed for24 h in deionized water before being used in any experimentalwork. Membrane permeability was determined by initially fil­tering it using deionized water at 12 x 105 Pa for approximatel8h for compaction to avoid compression effect in the later stageof experiment. Then, stabilized water flux at different oping pressures was obtained and membrane permeability(Lp) could be determined from the slope of flux against pgraph.

For separation process, the same compaction prcarried out before the test cell was emptied and 1.solution was filled into the test cell and solution rcell was then pressurized at the operating pressura pressure regulator. Permeate from the bottomcollected and its weight was measured with an eof ±0.01 g accuracy. The cumulative weightcumulative volume and the permeate fluxPermeate flux, Vw (m3/m2 s), was obtain

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two membranes are slightly different although with the samepolyamide thin-film composite. NF270 has a very thin semi­aromatic piperazine-based polyamide active layer while NF90consists of a fully aromatic polyamide active layer [24]. Thisslight difference of membrane structures can be one of reasonsthat NF90 showed superior rejection characteristics comparedto other nanofiltration membranes tested at the experimentalconditions.

Puasa [25] reported that polyamide thin-film composite mem­branes have charge characteristics that influence the separationcapabilities, wbich can be altered by the solution's pH and itwas reported~n e isoelectric point of polyamide membraneis generally o~t n 4 and 5. The occurrence of an isoelectricpoint me er pH than the isoelectric point, the mem-brane is charged and vice-versa. Hence, in the caseof polym ranes, surface membrane charge is typicallynegati pH values, it increases as the pH decreases andswit itive values at low pH's [26].

Ho contrary to the usual phenomenon which occursfo ecies whereby at isoelectric point, the flux is usu-

ighest while the rejection is at the lowest [27], theserved for the uncharged pesticides molecules is some­

t different. In the case of uncharged molecules, instead ofinfluenced by the changes in membrane surface charge,

it is elieved that it was the changes of the membrane struc-es and/or formation of high molar mass complexes which

ificantly affected the performance of solute rejection andrmeate flux [28]. Nevertheless, the possibility of formation

of high molar mass complexes at high pH is sidelined in thisresearch since the rejection of atrazine and dimethoate onlyincreased at high pH for NF200, NF270 and DK while NF90showed a slight decrease of rejection at high pH.

Hence, it is deduced that the trend of atrazine and dimethoaterejection obtained for NF200, NF270 and DK in this experimentwas due to the changes of the membrane structures caused bythe solution's pH. The results obtained were in agreement withobservation done by Freger et al. [29] whereby the rejectionof lactate decreased with the decrease of pH. In another workby Freger et al. [22], it was concluded that at low pH, acidichydrolysis disrupted the chemical bonds in the membrane poly­mer matrix. This condition reduced the degree of crosslinking(i.e., rigidity) of the polymer matrix which eventually caused thedecrease of rejection. At the same time, acidic hydrolysis alsocaused the increase of the hydrophilic sites at the membrane[22]. The increase of hydrophilic sites would cause the increaseof permeate flux. On the other hand, the increase of atrazine anddimethoate rejection at high pH observed for NF200, NF270 and

\ DK could be caused by the hydration swelling of the membrane, skin layer [29]. This could result in shrinking of membrane pore

size, and thus, reduced the permeation of solute through thepores of the membrane. Meanwhile, it is believed that NF90was rather chemical-resistant as it showed somewhat consis­tent performance regardless of the solution's pH. There wasonly a drop of about 3% of rejection perfOlmance for NF90compared to the obvious increase or reduction of rejection per­formance shown by the rest of the nanofiltration membranestested.

ionor clearer

er.Jtjectedefmolec­

iscussed inhydropho­of atrazine

10

- .... ·NF

-·.··N-w- NF270__ OK

10

- ..... NF90··.··NF200-w- NF270__ OK

9

9

to the alteration of initial

8

AL. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx

7

pH

pH

6

85

5

...,.!.',.'! .....

.................... ,.. ,.........

4

4

i- ._.. _._- -' _.-. - .... -. -'- -.. - 'i

.-----_..-._._'-.'-'-'-'--§

100

90

80

70c:0g 60

'ii'a: 50'IJl

40

30

20

103

4

100

90

80

c: 700

! 60'aYa: 50.,.

40

30

20

103

Dimethoate

pH4 pH9

NF90 2.71 3.43 4.33NF200 24.55 22.35 24.11NF270 25.12 41.59 26.04DK 8.67 7.65 17.73

Membrane

Table 3Percentage of changes in rejection perfsolution's pH

Fig. 3. Effect of initial solution's pH on rejection of dimet

Fig. 2. Effect of initial solution's pH on rejection of atrazine.

age of changes in rejection performance due to tof initial solution's pH is also presented is Tascrutiny. It is noted that atrazine was consistenthan dimethoate although dimethoate has sligular weight than atrazine. This behaviour hour previous work whereby it was due to tbicity (log Kow) and heterocyclic aroma .[23].

Meanwhile, Nghiemetal. [24]repoNF90 is smaller than that of NF270

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A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx 5

2.50E'05

2.00E·05

•.. ' 1.50E-05.§"ei 1.00E·05

ii:

P .... _ .... _ .... _ ... _ ........ - ..

.. -....-..- ..... NF90··.··NF200...... - NF270

... ·_·_·_·_·_·_·.. ·_· ,·_·-·~OK..,. , .

2;50E·05 i-..-..............-.. ..~ .... .... .._.._..-.

•· ... ··-·-·_·_·-.. ·_·... ·_·-ll.................................... - .... ·NF90··.··NF200... '" -NF270~DK

5.00E.06Ie II 5.00E·OS )(

3.2. Permeate flux peiformance

Fig. 4. Effect of initial solution's pH on permeate flux during rejection ofatrazine.

10986 7pH

5

itial solution's pH on pemleate flux of pure water.

4O;OOE+OO+--......---._-..-_-...._-.-_-,,..---.

3

Authors would like to thank Universiti Sains Malaysia forfunding this research with ShortTerm Grant (Account 6035 167).Appreciation also goes to DowlFilmtec for providing the mem­branes.

solution's pH as it showed almost constant fluxregardless of the pH condition.

Acknowledgements

t IS study, the feasibility of nanofiltration membranes for¥ction ofpesticides in aqueous solution was evaluated with

perspective of understanding the performance of nanofiltra­membranes in different pH conditions. Four nanofiltration

m mbranes, NF90, NF200, NF270 and DK, with molecularwe!ght cut-off of around 200 were subjected to stirred dead-endfiltration and the effect of initial pH's solution on the perme­ate flux and feed-based rejection of atrazine and dimethoatewas investigated. It was found that increasing the solution's pHincreased atrazine and dimethoate rejection but at the same time,reduced the permeate flux performance for NF200, NF270 andDK. However, effect of solution's pH had rather small signifi­cance on the performance of NF90.

From the results, it can be concluded that the NF90 had thehighest rejection of all the membranes tested. It managed tomaintain above 90% of atrazine rejection and approximately80% of dimethoate rejection regardless of the changes in solu­tion's pH. Besides, it was rather chemical-resistant as it showedsomewhat consistent performance in both rejection and perme­ate flux regardless of the solution's pH. This finding strengthensthe conclusion from our study [23] that NF90 is deemed the moresuitable nanofiltration membrane for atrazine and dimethoateretention from aqueous solution compared to NF200, NF270andDK.

10

- NF90

•• NF200

-"'- NF270~OK

solu­mpared

ceo Thus,s not that

e, but it wases thr~gh thewhat resistant

987pH

s4

Ie

.... _._._. - .-'''' -t- ..... _._ ....

•..................•............•

..._..-..-..-.. ....._..- .....2:50E005

2:001:;·05

5.00E·08

cr'Iii i.50e·os

gS Moe·osii:

The effect of initial solution's pH on the permeate flux duringrejection of atrazine and dimethoate at fixed operating pressure,feed pesticide concentration and stirring rate are presented inFigs. 4 and 5, respectively. As the acid hydrolysis at low pH orswelling of membrane skin layer at high pH, as explained in thprevious section, is believed to be responsible for the increaseor decrease in pesticide r~jection for NF200, NF270 andit is expected that the permeate flux would be as much affby solution's pH as the pesticide rejection performancethe acid hydrolysis and hydration swelling. The effectsolution's pH on permeate flux ofpure water is showSimilar trend ofpermeate flux was observed with thpesticide at different pH which further supportedthat the variation of trend observed was due tothe membrane structures.

However, it seemed that except for NF270,tion's pH seemed not to be as much on permeato the degree ofchanges seen in the rejectionit is believed that the difference in permobvious because the changes at the polysufficient to efficiently retain or allowmembrane. Again, NF90 showed that'

References

[1] M.S. Majewski, Sources, movement, and fate of airborne pesticides, in:H. Frehse (Ed.), Pesticide Chemistry: Advances in International Research,Development, and Legislation, VCH Verlagsgesellschaft mbH, German)'1991.

986 7pH

54O;OOE+OO +--..,--.....,.--.---...---,..-.....---,

3

Fig. 5. Effect of initial solution's pH on permeate flux during rejection ofdimethoate.

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A.L. Ahmad et al. / Journal ofHazardous Materials xxx (2007) xxx-xxx

I,

[19] S.S. Chen, S.T. James, L.A Mulford, C.D. Norris, Influences of molecularweight, molecular size, flux, and recovery for aromatic pesticide removalby nanofiltration membranes, Desalination 160 (2004) 103-111.

[20] Y. Zhang, B. Van del' Bruggen, G.X. Chen, L. Braeken, C. Vandecasteele,Removal of pesticides by nanofiltration: effect of the water matrix, Sep.Purif. Techno\. 38 (2004) 163-172.

[21] S. Bandini, J. Drei, D. Vezzani, The role of pH and concentration on theion rejection in polyamide nanofiltration membranes, J. Membr. Sci. 264(2005) 65-74.

[22] V. Freger, A Bottino, G. Capannelli, M. Perry, V. Gitis, S. Belfer, Charac­terization of novel acid-stable NF membranes before and after exposure toacid using ATR-FrIR, TEM and AFM, J. Membr. Sci. 256 (2005) 134-142.

[23] AL. Ahmad, .S. Tan, S.R. Abd. Shukor, Dimethoate and Atrazine Reten-tion from Solution by Nanofi)tration Membranes, J. Hazard.Mater., in Q:

[24] L.D. Ngh' hafer, M. Elimelech, Nanofilration ofhorrnone mim-icking c contaminants, Sep. Sci. Techno\. 40 (2005) 2633-2649.

[25] S.w. lar-enhanced ultrailftration for removal ofreactive dyesfrom lution, M.Sc. thesis, Universiti Sains Malaysia, Penang,20

[26] S. Mazzoni, Modelling the amphoteric behaviour ofpolyamidemembranes, Desalination 184 (2005) 327-336.

evelopment of polymeric composite nanofiltration membrane:characterization and its evaluation on copper sulfate rejection.

thesis, Universiti Sains Malaysia, Penang, 2005.strom, L. Kaipia, S. Luque, Fouling and retention of nanofiltratioll

embranes, J. Membr. Sci. 98 (1995) 249-262.. Freger, T.C. Arnot, J.A. Howell, Separation of concentrated,~ganic/inorganic salt mixtures by nanofiltration, J. Membr. Sci. 178 (2000)185-193.

] HC Agrochemicals Co., Ltd. http://www.hcchemica\.com/techlinsecticideslDimethoate.htm. Accessed on 10 September 2007.

1] B. Yaron, R Calvet, R Prost, Soil Pollution: Processes and Dynamics,Springer-Verlag, Heidelberg, 1996.

[32] Y. Kiso, Y. Nishimura, T. Kitao, K, Nishimura, Rejection properties ofnon-phenylic pesticides with nanofiltration membranes, J. Membr. Sci. 171(2000) 229-237.

[33] K,V. Plakas, AJ. Karabelas, T. Wintgens, T. Melin, A study ofselected her­bicides retention by nanofiltration membranes-the role oforganic fouling,J. Membr. Sci. 284 (2006) 291-300.

[34] C. Bellona, J.E. Drewes, The role of membrane surface charge and solutephysico-chemical properties in the rejection of organic acids by NF mem­branes, J. Membr. Sci. 249 (2005) 227-234.

[35] L.D. Nghiem, A.1. Schafer, M. Elimelech, Phamlaceutical retention mech­anisms by nanofiltration membranes, Environ. Sci. Techno\. 39 (2005)7698-7705.

[36] AI.C. Morao, AM.B. Alves, M.D. Afonso, Concentration of c1avulanicacid broths: influence of the membrane smface charge density on NFoperation, J. Membr. Sci. 281 (2006) 417-428.

[2] M.A. Kamrin, Pesticide Profiles: Toxicity, Environmental Impact, and Fate,CRC Press, Boca Raton, 1997.

[3] H. Blanchoud, F. Farrugia, J.M. Mouchel, Pesticides uses and transfers inurbanized catchments, Chemosphere 55 (2004) 905-913.

[4] E.P. Lichtenstein, Persistence and fate ofpesticides in soil, water and crops:significance to humans, in: A.S. Tahori (Ed.), Pesticides Chemistry. Vol­ume VI: Fate of Pesticides in Environment, Gordon and Breach ScientificPublishers, Great Britian, 1972.

[5] R Gotz, H. Bauer, P. Friesel, K, Roth, Organic trace compounds in thewater of the River Elbe near Hamburg. Part n, Chemosphere 36 (9) (1998)2103-2118.

[6J S. EI-Kabbany, M.M. Rashed, M.A. Zayed, Monitoring of the pesticidelevels in some water supplies and agricultural land, in El-Haram, Giza(ARE.), J. Hazard. Mater. A72 (2000) 11-21.

[7] Z. Zhang, H. Hong, X. Wang, J. Lin, W. Chen, L. Xu, Determination andload of organophosphorus and organochlorine pesticides at water fromJiulong River Estuary, China, Mar. Poll. Bull. 45 (2002) 397-402.

[8] I.K. Konstantinou, D.G. Hela, T.A Albanis, The status of pesticide pol­lution in surface waters (rivers and lakes) of Greece. Part I. Review onoccurrence and levels, Environ. PoUut. 141 (2006) 555-570.

[9J M.T. Moore Jr., RE. Lizotte, S.S. Knight Jr., S. Smith, C.M. Cooper,Assessment of pesticide contamination in three Mississippi Delta oxbowlakes using Hyalella azteca, Chemosphere 67 (11) (2007) 2184­2191.

[IOJ RF. Carsel, C.N. Smith, Impact of pesticides on ground water contamina­tion, in: G.J. Marco, RM. Hollingworth, W. Durham (Eds.), Silent SpringRevisited, American Chemical Society, Washington DC, 1987.

[II] J.E. Davies, R Doon, Human health effects of pesticides, in: G.J. Marco,R.M. Hollingworth, W. Durham (Eds.), Silent Spring Revisited, AmericanChemical Society, Washington D. C, 1987.

[12] J. DouU, Pesticide carcinogenicity, in: N.N. Ragsdale, RE. Menzer (Carcinogenicity and Pesticides: Principles, Issues and Relationship, Aican Chemical Society, Washington DC, 1989.

[13] M. Younes, H. Galal-Gorchev, Pesticides in drinking water-a casFood Chern. Toxico\. 38 (2000) S87-S90.

[l4J B. Van der Bruggen, J. Schaep, D. Wilms, C. Vandecasteele, Inmolecular size, polarity and charge on the retention of organiby nanofiltration, J. Membr. Sci. 156 (1999) 29-41.

[15] Y. Kiso, Y. Sugiura, T. Kitao, K, Nishimura, Effects ofand molecular size on rejection of aromatic pesticides wimembranes, J. Membr. Sci. 192 (2001) 1-10.

[16] L. Braeken, R Ramaekers, Y. Zhang, G. Maes, B. VaVandecasteele, Influence of hydrophobicity on retenof aqueous solutions containing organic compou(2005) 195-203.

[17] C. Causserand, P. Aimar, J.P. Cravedi, E. Singlantion by nanofiltration membranes, Water Res. 3

[18] K. Kosutic, L. Furac, L. Sipos, B. Kunst, Remofrom drinking water by nanofiltration membr(2005) 137-144.

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Elsevier Editorial System(tm) for Chemical Engineering Journal

Manuscript Draft

Manuscript Number:

Title: Modeling of the retention of atrazine and dimethoate with nanofiltration

Article Type: Original Article

Section/Category: Environmental Chemical Engineering

Keywords: Nanofiltration; dimethoate; atrazine; organic molecules; Spiegler-Kedem.

Corresponding Author: Dr. Abdul Latif Ahmad,

Corresponding Author's Institution:

First Author: Abdul Latif Ahmad

Order of Authors: Abdul Latif Ahmad; Lian See Tan; Syamsul Rizal Abd. Shukor

Abstract: The present study aims to investigate the viability of using Spiegler-Kedem model to predict the

retention of atrazine and dimethoate with nanofiltration using NF90 in stirred cell condition. Spiegler-Kedem

model is the thermodynamics of irreversible processes in which no particular mechanism of transport and

structure of membrane is specified. The ~piegler-Kedem transport equations were used to derive the

reflection coefficient and solute permeabilitYilf the system. The model was successfully applied on the

modeling of the organic molecules tested. It was found that Spiegler-Kedem model provided a good

estimation of experimental value. The coefficient of determination (R2) obtained for the fitted data was

0.9871 and 0.9692 for atrazine and dimethoate, respectively.

Suggested Reviewers: Nidal Hilal PhD "

Head of Advance Water Treatment Research Group (AWTG), School of Chemical, Environmental and

Mining Engineering, The University of Nottingham

[email protected]

He is actively involved in research in membrane and modeling field

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Abdul Wahab Mohamad PhD

Head of Department, Department Of Chemical and Process Engineering, Universiti Kebangsaan Malaysia

[email protected]

He is an active researcher in membrane and modeling field

Mohamed Khayet PhD

Lecturer, Department of Applied Physics I, Faculty of Physics, Universiti Complutense of Madrid

[email protected]

He is an active researcher in membrane and modeling field

Opposed Reviewers:

,,

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Date: 31 st October 2007

Prof. L. R. Weatherley,Chair & Professor,Department of Chemical & Petroleum Engineering,The University of Kansas,Learned Hall,1530 W. 15th St., Lawrence,KS 66045, USA.

Dear Prof,

MS entitled; "Modeling of the retention of atrazine and dimethoatewith nanofiltration"

I am submitting a Manuscript for possible publication in Chemical Engineering Journal.The submission requirements are listed in the table below:

No Requirements Information1 Manuscript Modeling of the retention ofatrazine and dimethoate

Title with nanofiltration2 Corresponding/ Prof. Dr. Abdul LatifAhlllad

submitter's School of Chemical Engineering, Engineering CampusInformation Universiti Sains Malaysia, Seri Ampangan, 14300 Nibong Tebal

Penang, MalaysiaEmail : [email protected]: +60(4) 5941012Fax : +60(4) 5941013

3 Co-authors Lian See Tan, Syamsul Rizal Abd Shukor4 Keywords Nanofiltration; dimethoate; atrazine; organic molecules;

Spiegler-Kedem

Kindly acknowledge me the rec~ipt of the manuscript. If you have any enquiries, pleasedo not hesitate to contact at"" the above address or through my email [email protected]. Your cooperation regarding this matter is very much appreciated.

Thank You.

Yours sincerely,,,

PROF. ABDUL LATIF AHMAD

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Suggested Reviewer

1. Euro Ing. Dr. Nidal HilalLeader in Chemical Engineering,Head of Advance Water Treatment Research Group (AWTO),School of Chemical, Environmental and Mining Engineering,The University ofNottingham,University Park, Nottingham NO? 2RD,United Kingdom.Tel: 44 (0)1159514168Fax: 44 (0)115951 4115E-mail: [email protected]

2. Prof. Ir. Dr. Abdul Wahab MohamadHead of DepartmentDepartment Of Chemical and Process Engineering,Universiti Kebangsaan Malaysia,43600 UKM, Bangi, Selangor, Malaysia.Tel: 60 (3) 89296410Fax: 60 (3) 89252546Email: [email protected]

3. Prof. Dr. Mohamed Khayet,Department of Applied Physics I,Faculty of Physics, Universiti Complutense ofMadrid,Avda. Complutense sin, 28040 Madrid, SpainTel: +34 394 4511Fax: +34 394 5248E-mail: [email protected]

,,

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Modeling of the retention of atrazine and dimethoate

with nanofiltration

A.L. Ahmad*, L.S. Tan, S.R. Abd. Shukor

School of Chemical Engineering, Engineering Campus, Universiti Sains Malaysia

14300 Nibong Tebal, Seberang Prai Selatan, Pulau Pinang, Malaysia.

Email address:[email protected] (corresponding author*)

Phone: +60(4)5937788

Fax: +60(4)5941013

ABSTRACT,.

The present study aims to investigate..~e viability ofusing Spiegler-Kedem model

to predict the retention of atrazine and dimethoate with nanofiltration using NF90 in

stirred cell condition. Spiegler-Kedem model is the thermodynamics of irreversible

processes in which no particular mechanism of transport and structure of membrane is

specified. The Spiegler-Kedem transport equations were used to derive the reflection

coefficient and solute permeabifIty of the system. The model was successfully applied on<1/..

the modeling of the organic molecules tested. It was found that Spiegler-Kedem model

provided a good estimation of experimental value. The coefficient of determination (R2)

obtained for the fitted data was 0.9871 and 0.9692 for atrazine and dimethoate,

respectively. ,,

Keywords: Nanofiltration; dimethoate; atrazine; organic molecules; Spiegler-Kedem.

1

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1. Introduction

Public attention on the potential long-term consequences ofpesticides on human

health and environment has started since 1962 when Carson [1] highlighted the matter in

her book 'Silent Spring'. Ballantyne and Marrs [2] stated that the word 'pesticides' is

used to cover substances that control organisms (insects, fungi, plants, slugs, snails,

weeds, micro-organism, nematodes, etc) which destroy plant life and interfere with food

chain, and which act as vectors to disease organism to man and animals. Pesticide

pollution in water may arise from runoff and leaching [3, 4].

The implementation on the control of water quality is important because different

type ofpesticides have different decaying period. Unlike heavy metals and other

pollutants, pesticides are lethal to the envirom)J.~nt even at micro level of concentrations

[5]. Nanofiltration is a promising membrane technique with a growing number of

applications for the treatment of drinking water and wastewater [6]. Nanofiltration

membranes differ from reverse osmosis membranes mainly because they are designed to

selectively remove compounds such as multivalent ions or organic contaminants while

allowing other compounds to pass~[7]. Furthermore, the energy requirements are much.,.

lower for nanofiltration than with reverse osmosis because the transmembrane pressures

applied in nanofiltration are significantly lower than those in reverse osmosis [8].

Some nanofiltration models take into account the mechanism of transport while

other models are independent of the mechanism transport. The solution-diffusion model,

solution-diffusion imperfection and extended Nernst-Planck model belong to the former

2

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category while the Spiegler-Kedem (SK) model represents the latter [9]. Spiegler-Kedem

model is the thermodynamics of irreversible processes which indicates that the flow of

each component in a solution is related to the flows of other components. In this model,

the membrane is treated as a 'black box' in which no particular mechanism oftransport

and structure of membrane is specified [10]. It was relatively slow process near

equilibrium where the mechanisms of transport and the structure of the membrane are

ignored [11]. The nature of the membrane such as charge and compactness also does not

affect the transport activities through it [9]. The Spiegler-Kedem model has been

extensively used in predicting data for the transport of charged and unchanged solute

through the membrane in nanofiltration system [6, 10, 12-14]. However, modeling on the

retention of organic molecules has received less attention so far [6].

Atrazine was selected as subject of study because this herbicide is commonly used

in the plantations around the world as well as in Malaysia [15]. Extensive amount of its

usage has ranked it among the most common pesticides found in surface water and

groundwater [16]. On the other hand, dimethoate is also widely used in Malaysia and it is

being regulated in guidelines for drl~king water by World Health Organization.

Nevertheless, data on effectiveness ofdfmethoate retention using membranes has not

been found so far [17]. Previous studies [18, 19] found that NF90 showed superior

rejection characteristics for atrazine and dimethoate compared to other nanofiltration

membranes tested. Therefore, the objective of the pre~ent study is to investigate the,

viability ofusing Spiegler-Kedem model to predict the retention of atrazine and

dimethoate with NF90 in stirred cell condition. The measurable objectives are:

3

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(1) To estimate the parameters ofthe model from the experimental data obtained from the

nanofiltration system.

(2) To validate the proposed model by comparing the simulated results with the

experimental results.

2. Theory

The Spiegler-Kedem model states that the fluxes of solute and solvent are directly

related to the chemical potential differences between the two sides of the membrane. The

chemical potential gradient is caused by either concentration or pressure gradient. The

solvent transport is due to the pressure gradient across the membrane and the solute

transport is due to the concentration gradient and/or convective coupling of the volume

flow [9].

2.1 Transport Equations

The transport equation expressed by Spiegler-Kedem model is as follows [20]:

For solvent,

-(dP d7T)J =-P --CF-v wdx sdx

For solute,

J =_p_ dCs+(l_CF)cJs s dx s s v

(1)

(2)

Diffusion is represented by the first term in Equation (2); the second term represents the

contribution of convection to the transport ofuncharged molecules [8]. In an ideally

semipermeable membrane, CF = 1. In an entirely unselective membrane in which a

4

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concentration gradient does not cause volumetric flow at all, (j = O. Thus, (j is a measure

of the degree of semipermeability of the membrane reflecting its ability to pass solvent in

preference to solute and solvent and (j = 0 indicates complete coupling [9].

2.2 Model Development

The transport phenomena of nanofiltration membranes in the pressure-driven

process can be described by the irreversible thermodynamics. In general, the transport

equations for the components through a nanofiltration membrane consist of two

component which is diffusion component and convection component. This is reflected by

the transport equation of Spiegler-Kedem. For a system involving a single solute in

aqueous solution, the solute retention can be described by three transport coefficients:

1. Specific hydraulic permeability, Pw'

11. Local solute permeability, p.

iii. Reflection coefficient, (js

Permeability is the flux ofa component (solvent or solute) through the membrane

per unit driving force (the effective tfansmembrane pressure).The reflection coefficient is

a measure of the portion ofthe membrane through which the solute cannot be transferred

[12]. The assumptions made for this work are:

i. The Spiegler-Kedem model is assumed to adequately predict the transport ofI,

solutes and solvent regardless the type of solutes and its charges, solvent and

membrane.

11. The pressure and concentration gradient are the driving forces.

5

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111. Solutes present in the system are semi-permeable to the membrane.

IV. In the concentration polarization layer thickness, each solute has its

independent value of the diffusion and mass transfer coefficients.

v. Pw ' P. and (j s are assumed to be constants across the uncharged membranes

so that the equation for the integration of Equation (1) and (2) of the

membrane can be simplified.

The simplified version of model transport equation can be written as [21]:

For solvent,

For solute,

Osmotic pressure, 1r, can be estimated using tHe Vant-Hoffs equation [10]:

Equation (3) and (4) can be sini~lifiedas

(3)

(4)

(5)

(6)

(7)

(8)

The imperfection of the membrane is chamcterized by the reflection coefficient,

(j • This reflection coefficient can express the degree of solute-membrane interaction

whose values are in the range of O.:s (j .:sl. An osmotic difference (111r) across an

imperfectly semi permeable membranes is compensated by an applied pressure ( 11P) so

6

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that the solvent flux is zero (Jv =0) and M is smaller than I1n. The ratio between these

two is defined as (]" .

(9)

Where,

(]" = 1, for in ideally semi permeable membrane (l00% rejection)

(]" = 0, no rejection

Reflection coefficient, (]", is characteristic of the convective transport of the

solute. An (]" of 100 % indicates that the convective solute transport is totally hindered or

that no transport by convection takes place at all. This is the case for ideal RO

membranes where the membranes have a dense structure and no pores are available for,.

convective transport. The retention may how~v~rbe lower than 100 % because solute

transport may take place by solution-diffusion. As it has been shown that nanofiltration

membranes have pores, a reflection coefficient below 100 % will be found if the solutes

are small enough to enter the membrane pores.

I

The Spiegler-Kedem model assumes the membrane to be uncharged. In neutral~.

membranes, solute permeability, ~ and the reflection coefficient, (]" have constant

values characterizing a given solute-membrane system. At low pressure, both terms

contribute to the transport of solute through the membrane. However, at higher pressure,,,

the relative importance of convection in the transport will be higher. In the hypothetical

case ofan infinite pressure, diffusion is negligible compared to the infinite convection

7

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flux. Since diffusion of solutes will result in an increase of transport relative to the water

transport, the relative transport solutes is at the lowest at infinite pressure. The

permeation for solute is defined as [10]:

CR =1-~

s Cms

The true rejection in term of reflection coefficient, 0" and solute driving force, F:

R = O"s(I-FJs I-O"sFs

Where Fs is defined as,

(10)

(11)

(12)

The observed retention coefficient, Ros is defined by the solute concentration in feed, eft.and the permeate Cps'

(13)

As the Spiegler-Kedem bodel relates the membrane surface concentration to the

.".permeate concentration, it needs to be combined with concentration polarization if the

permeate concentration is to be related to the bulk feed concentration. This results in the

Combined Film Theory-Spiegler-Kedem or CFSK models. This phenomenon is

expressed in the Film Theory Model [10]. Mass transfer coefficient, ks ' is an important

parameter for concentration polarization where this parameter is dependent on several

factor like feed flow rate, temperature and cell geometry.

8

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Relationship between membrane surface concentration to the permeate concentration in

concentration polarization is expressed in Equation (14). The concentration polarization

usually exists in nanofiltration process because of the formation of a boundary layer

separating the membranes surface from the bulk solution [10].

Cms -Cps (J ]__----'-_ = exp _v

Cbs - Cps ks

which ks is defined as,

k = Dsw

s 8

where Dsw is the diffusion coefficient of solute in water and 8 is the concentration

(14)

(15)

polarization layer thickness. By using the rejection fractions instead of concentrations,

the Film Theory Model can be expressing as:

Ros Rs (Jv]-=--=--exp --I- Ros 1-Rs ks

By substituting the equation (11) into equation (16):

Ros (J"s(l-Fs) (Jv]-=--= exp --I- Ros 1- (J"s ks

Substitute equation (12) to (17) give~,

(16)

(17)

\,On the other hand, the following equation is applied for estimation of diffusion

coefficient in water, D w [22]:

9

(18)

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D = 2.7xlO-4w mO.71

Meanwhile, for estimation for mass transfer coefficient, ks [23]:

Sherwood number, Sh:

Reynold number, Re:

Schmidt number, Sc:

3. Experimental

3.1 Materials

Dimethoate with 99.8% purity and atrazine with 97.4% purity were purchased

from Riedel-de Haen (Germany). TIle molecular structures and properties of both.,.

pesticides are presented in Table 1. The nanofiltration membrane used in this study is

(19)

(20)

(21)

(22)

(23)

NF90 (Dow/Filmtec). Table 2 provides the specification of the membrane used as given

by the manufacturers.

I,

10

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3.2 Membrane Stirred Cell

A 300 mL stirred cell (Sterlitech), model Sterlitech™ HP4750, USA, was used to

conduct the dead-end filtration experiments. The effective membrane area is 1.46 x 10.3

m2• The maximum operating pressure for this cell was 69xl05 Pa.

3.3 Experimental Set-up and Procedure

Dead-end filtration experiments were carried out with the stirred cell (Sterlitech™

HP4750). The pesticide solution in the cell was stirred by a Teflon-coated magnetic bar.

The cell was pressurized using compressed high purity nitrogen gas. The pressure in the

permeate side was approximately atmospheric under all condition. The feed pesticide and

stirring rate were kept constant at 10 mg/L and 1000 rpm while the operating pressure

were varied from 5xl05 to 15xl05 Pa. The membran'e was immersed for 24 hours in

deionized water before being used in any experimental work. Membrane permeability

was determined by initially filtering it using deionized water at 16xl05 Pa for

approximately 8 hours for compaction to avoid compression effect in the later stage of

experiment. Then, stabilized water flux at different operating pressures was obtained and

membrane permeability values (Lp)~could be determined from the slope of flux against

pressure graph.

For separation process, the same compaction process was carried out before the

test cell was emptied and 1.8 litres of feed solution ",as filled into the test cell and,

solution reservoir. The cell was then pressurized at the operating pressure indicated by a

pressure regulator. Permeate from the bottom of the cell was collected and its weight was

11

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measured with an electronic balance of ± 0.01 g accuracy. The cumulative weight were

converted to cumulative volume and the permeate flux could be obtained. Permeate flux,

vw (m3/m2.s), was obtained using equation (24):

LlVv =-­

W Llt.A(24)

where Ll V is the cumulative volume difference (m3), M is the time difference (s) and A is

the membrane area (m2), respectively.

Samples were collected at every 20 minutes for four times and the average values

obtained from the samples were used as the results in this work. All experiments were

conducted at room temperature (25 ± 2 QC). A schematic diagram of the experimental set

up is shown in Fig. 1.

3.4 Analytical Method

Concentration ofatrazine and dimethoate in feed and permeate was analysed

using High Performance Liquid Chromatography (HPLC) by Perkin Elmer (USA). The

HPLC column used was Zorbax S~-CN (51!, 4.6mm i.d.x 150 mm long, Agilent

Technologies). The mobile phase wata mixture of35% acetonitrile and 65% deionized

water while the flow rate was set at 1.0mllmin. The UV detector was operated at a

wavelength of200nm. The peak for dimethoate was detected at around 3.5 minute while

the peak for atrazine was detected at around 5.3 mi~te. The value of retention was

obtained with the following equation:

(25)

12

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where R is the pesticide retention, Cp is the concentration of permeate (mg/L) and Cf is

the concentration of feed (mgIL)

4. Results and Discussions

4.1 Parameter Estimation

The estimation ofparameters for the membrane transport model is an important

aspect of this study. The results obtained from the experimental test of the membrane

system were employed for parameter estimation for the model. The Spiegler-Kedem

model was characterized by the hydraulic permeability of the membrane, Pw ' reflection

coefficient, (J' , solute permeability, p. and mass transfer coefficient, ks ' Result of the

parameter estimation for NF90 is shown in Table 3.,.

The retention ofpesticide against permeate flux curve is presented in Fig. 2. It can

be seen from the comparison between the experimental data and predicted data that the

Spiegler-Kedem model provided good regression based on the model applied. Thus, the

parameters estimated can be accepted. In fact, the coefficient of determination (R2)

I

obtained for the fitted data was 0.9871 and 0.9692 for atrazine and dimethoate,.,.respectively.

The reflection coefficient, (J' , was in good agreement with the results obtained in\

the experimental work as it showed that NF90 had the value of an almost ideal membrane.

This is because the value close to 1 meant that it had high ability to pass solvent in

preference to solute [20], resulting in high retention of solute by NF90. Meanwhile,

13

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atrazine had slightly higher mass transfer coefficient than dimethoate due to its slightly

lower molecular weight [22]. However, atrazine had obviously lower solute permeability,

p., compared to dimethoate. This lower solute permeability value possessed by atrazine

explains its higher retention compared to dimethoate. This behaviour was due to the

higher hydrophobicity (log Kow) and heterocyclic aromatic structure of atrazine [18]

4.2 Comparison between Experimental and Modeling Data

As confirmed by the irreversible thermodynamics model, the retention of solute

increased with the increasing permeate flux (i.e. increasing applied pressure). The solute

retention and permeate flux are plotted against applied pressure in Fig. 3 and Fig. 4,

respectively. It is observed that while the solute retention against pressure curve for

predicted value by Spiegler-Kedem model fitte&well with the experimental data, the

model was unable to match the slope of the experimental flux against pressure curve as

good as it did in the case for retention. However, the trend of experimental data was still

in agreement with the predicted data by the model and did not deviate far from each other.

I4.3 Concentration Polarization Profile

"if.

Fig. 5 provides the concentration polarization profiles for atrazine and dimethoate

at different operating pressure. The profiles were gauged based on the ratio of membrane

wall concentration to bulk concentration (Cm/Cb) [24]. Based on the membrane wall

concentration calculated from the Spiegler-Kedem model, the concentration polarization

profile was depicted to increase with the increasing pressure. Both solutes demonstrated

similar trends on concentration polarization where the solute concentrations increased

14

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from the initial bulk concentration to the maximum concentration (wall concentration) at

the maximum pressure applied. Although previous results showed that the retention

increased with the increasing pressure, these profiles show that the effect of concentration

polarization would be magnified with the increasing pressure. The same trend was also

observed by [25]. Thus, due consideration should be given when choosing the suitable

applied pressure for nanofiltration system.

5. Conclusions

Comparisons were made between the Spiegler-Kedem model with the

experimental data obtained for nanofiltration ofatrazine and dimethoate. The model was

successfully applied on the modeling of the organic molecules tested. It was found that

Spiegler-Kedem model provided a good estimation of the experimental value. The

coefficient of determination (R2) obtained for the fitted data was 0.9871 and 0.9692 for

atrazine and dimethoate, respectively. Although the model was unable to match the slope

of the experimental flux against pressure curve as good as it did for the case for retention,

the trend of experimental data was still in agreement with the predicted data by the model

and did not deviate far from eac~ other. It was also found from concentration polarization

profiles that the effect of concentration polarization would be magnified with the

increasing pressure.

,,

15

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Acknowledgement

Authors would like to thank Universiti Sains Malaysia for funding this research

with Short Term Grant (Account 6035167). Appreciation also goes to Dow/Filmtec for

providing the membrane.

Nomenclature

J v solvent fluxes (mls)

Pw specific hydraulic permeability (m4/N.s)

dx vertical distance from the membrane surface (m)

J s solute flux (mollm2.s)

~ 2s local solute permeability (m Is)

dCs solute concentration different in solution (mollm3)

Cs solute concentration in solution (mollm3)

Pw hydrodinamic permeability (m3/N.s)

M hydrostatic pressure driverl difference (N/m2)

J s solute flux (mollm2.s)

~ solute permeability (mollN.s)

Cs average solute concentration in solution (mollm3)

\,

a an osmotic constant (m3Palg),

Rg ideal gas constant (8.314 m3pa/mo1.K),

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T

m

Sh

operating temperature (Kelvin),

solute molar mass (g/mol)

true rejection

solute concentration at the permeate side (mg/L)

solute concentration at the wall of feed side (mg/L)

solute bulk concentration (mg/L)

mass transfer coefficient (m/s)

Sherwood number (dimensionless)

diffusion coefficient in water (m2/s)

rsc radius of stirred cell (m)

Kow octanol/water partition coefficient

Lp membrane permeability

Vw permeate flux

~v cumulative volume difference

M time difference

A membrane area of·

R pesticide retention

Cp concentration ofpermeate

Cf concentration of feed

Greek letters

P density of solution (kg/m3)

OJ stirring rate (S·l)

17

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f.l viscosity of solution (kg/m.s)

!1;r osmotic pressure difference (N/m2)

a s reflection coefficient (dimensionless)

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33 (2003) 115-126.

20

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[26] M.A. Kamrin, Pesticide Profiles: Toxicity, Environmental Impact, and Fate, CRC

Press, Boca Raton, 1997.

[27] Y. Kiso, Y. Nishimura, T. Kitao, K. Nishimura, Rejection properties ofnon-phenylic

pesticides with nanofiltration membranes, J. Membr. Sci. 171 (2000) 229-237.

"if.

I,

21

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List of figures

Fig. I: Diagram of experimental set-up.

Fig. 2: Solute retention against permeate flux curve from experimental data and the

predicted results from Spiegler-Kedem model.

Fig. 3: Solute retention plotted against pressure using the experimental data and predicted

results from Spiegler-Kedem model.

Fig. 4: Permeate flux plotted against pressure using the experimental data and

predicted results from Spiegler-Kedem model.

Fig. 5: Concentration polarization profile plotted against pressure.

I,

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Figure 1

Permeate

GasNz

Legend:@ :Pressure regulator

t>i<l :Valve

StainlessSteelFeed Tank Membrane

Stirred Cell

IMagnetic Stirrer I

\,

AnalyticalBalance

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Figure 2

3.00E-05 3.50E-05

.--.--.----+.~~~~.-~-.

./

/

5.00E-06 1.00E-05 1.50E-05 2.00E-05 2.50E-05

Flux (m3/m2.s)

1.00

0.90

0.80

0.70

a 0.60~.e 0.50

~ 0.40

0.30

0.20

0.10

0.00 _---,-------r----,.-----,------,----,.--------,

O.OOE+OO

• Experiment atrazine

--_.~~- SK model atrazine

• Experiment dimethoate

--SK model dimethoate

,,

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Figure 3

1614121086

+. - .. - . -+- .. - .. -+ +

2 4

,

:" _-----1.-------111----,,,,

,,,,,,,,,,,,,,,,,

,

1.00

0.90

0.80

0.70

5 0.60;c 0.50

~... 0040

0.30

0.20

0.10

0.00 -----,----.,.------,----,-----,----,-----,-------,

oPressure x105 (Pa)

+ Experiment atrazine•••••. SK model atrazine

• Experiment dimethoate

--- SK model dimethoate

'If.

I,

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Figure 4

4.00E-05

3.50E-05

3.00E-05

.......II! 2.50E-05....

",:€2.00E-05E.....

)(~ 1.50E-05ii:

1.00E-05

5.00E-06

O.OOE+OO

0 2 4 6 8 10 12 14 16

Pressure x1 05 (Pa)

I • Experiment atrazine • Experiment dimethoate -- SK model atrazine&dimethoate I

;,

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Figure 5

18

16

14

12

... 10()

E() 8

6

4

2

00 2 4 6 8 10 12 14 16

Pressure x105 (Pa)

I· . + ..Atrazine ---Dimethoate 1

I,

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List of tables

Table 1: Properties of dimethoate and atrazine [26]

Table 2: Specification of membrane used

Table 3: Parameters estimated based on the experimental results

I,

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Table 1

Pesticide Dimethoate Atrazine

Chemical structure

Molecular weight (Da)

Solubility in water

LogKow

229.28

25 giL @21°C

0.70

;,

215.69

20 mglL @ 20°C

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Table 2

Membrane

Manufacturer

Material

Maximum operating pressure, Pa

Maximum operating temperature, °C

pH range

aour measurements.

NF90

Dow/Filmtec

Polyamide

1.90xl0-11

45

3-10

,,

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Table 3

Parameter Value

Atrazine Dimethoate

Hydraulic permeability, Pw 2.3611E-ll 2.3611E-ll

Reflection coefficient, (J' 0.9835 0.9560

Solute permeability, P. 3.4317E-07 2.4142E-06

Mass transfer coefficient, ks 1.2894E-05 1.2524E-05

"if.

I,

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APPENDIX 4

Award

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Tan Datuk Dr Augustine S. H. OngPresident

Malaysian Invention and Design Society

heldfrom

18th- 20th lYIay 2007,

~Y~~~~Y~~~Y~T~T~~Y~

• 0 f~~. ~,~',:~, ~ ;.... ~~.'." c~.· ~ /.' _ Invention - Innovation Q ~r;~ '_"'_-':..__.._~"6'j .L 1 t::-. /\ _ Industrial Design - Technology ~~ ... "",.~ ..'. ~ i'~ MINISTRY OF SCIENCE, . MAL A Y 5 I A 0 ~, TECHNOLOGY & INNOVATION • ~ t, MIN0 S "

~ ~~ Ce~tlficate of~wa~d ~~ ~~ This is to certify that .~~ ~~ PROF ABDUL LATIF AHMAD, TAN LIAN SEE, ~~ DR SYAMSUL RIZAL,ABD SHUKOR ~~ ~~ has been awarded the ~~ ~~ ITEX SILVER MEDAL ~I~ • ~~. for the 'invention .~~ ~"~ A NOVEL NANOFILTRATION TREATMENT SYSTEM ~~, FOR PESTICIDES CONTAMINATED WATER: L~~ ~

l ENHANCEMENT OF WATER TREATMENT PLANT ~

at the ~

I ~18th International Invention, Innovation & Technology Exhibition ~

..,- ITEX 2007 .~

Kuala Lumpllr, Malaysia ~

~

~~~f~~)l

~~,

~~~

~~~~~~~~~.A.~#

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~ROFESORABDUL LATIF AHMAD

304.P.TKIMIA.6035167rtJMLAH GERAN ;- 39,86620

PrIOPROJEK ~-

F:~:.:~:S - ,~~~r~~~K

~J~I:5I:.N~1 ,

UNIT KUMPULAN WANG AUANAHUNIVERSm SAINS MAlAYSIA

KAMPUS KEJURUTERAANSERl AMPANGAN

PENVATA KUMPULAN WANG

TEMPOH BERAf(HIR 311121 2007

~.I;,o!)tJLA1"8) !\!ANOJ:Tl,.TRATION PROCESS FOR PESTICIt>ES 'lltEATMENT

-D'T'e"'M~

Tempoh ProjeIc15f10~05-1~/'~tib\t4 ~a

UNIT EITD",J...,.,ih s..... M....Vfj~~

PENAJA;- JANGKA PENOEK

Pemelanjaan~m..qg.g~

31/1212006(bJ

\

Tanggungan Perbelanjaen Jumlah Jumleh Bald Peruntukansemasa Semasa Perbelanjaan Perbetanjsan Semasa

2007 ~-~~ :::;7 T~$!#L~::-'" 2007f-.",<

(e) (d) (c+d) (b+c+d) (a-(b+c+d)

--0.00 6,500.00 6,500.00 6,500.00 2,436.00

0.00 2,249.4{I 2,249.40 2,249.40 1,15fl.60

0.00 0.00 0.00 4.80 195.2fl

0.00 0.00 0.00 0.00 400.00

731.00 11,071.51 11,808.51 21,059.84 (4,92.9.84)

0.00,· 0.00 0.00 0.00 1,200.00

0.00 • 2,441.60 2,441.60 5,664.50 (1,664.50)

0..00 0.00 0.00 1,145.70 3,854.30

737.00 22.262.51 22,999.51 36,624.24 3.241.76

737.00 22.262.51 22,999.51 36,624.24 3,241.16

a.on0.00

4.80

0.00

9,251.33

0.00

3,222.90

1,145.10

13.624.73 -----

13,624.13

39,866.00

39,866.00

8,936.00

4,000.00

200.00 ~

400.00

16.130.00

1,200.00

4,000.00

5,000.00

(8)

~!"Jf'lhl"l/In

Jumlah Besar

Vat

~Jti_GAJI KAKlTANGAN AWAM

~J PERBEtANJAAN PERJA.tANAN DAN SARAHI

~~: PERHUBUNGAN DAN UTIUTI

~~_SEWMN

~BEKALAN DA.N AtAT PAKAI HABlS

~PENYELENGGARMN & PEMBAIKAN KECLL

~~~ PERKHIDMATAN IKTISAS & HosprrAUTL

~;HARTA-HARTAMODAlLAIN

Pagel UfJ· ~.g~e:-tT/).

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Senarai edaran

Profe~or Madya Hamidi Abdul Aziz @ Abdul RahmanProfesor Madya Mohamad Razip SelamatProfesor Madya Ismail AbustanProfesor Madya Dr Ir. Hj. Mohd Nordin AdlanDr. Mohd Suffian YusoffProfesor Madya Sr. Mohd Sanusi S. AhamadProfesor Madya Fauziah AhmadCik Nor Habsah Md. Sabiani

Pusat Pengajian Kejuruteraan Awam

Profesor Abdul Latif AhmadProfesor Madya Ridzuan ZakariaDr. Mashitah Mat DonDr. Ahmad Zuhairi AbdullahDr. Lee Keat TeongDr. Mohd Azmier Ahmad

Pusat Pengajian Kejuruteraan Kimia

Profesor Madya Zainal Alimuddin Zainal AlauddinPusat Pengajian Kejuruteraan Mekanik

Profesor Hanafi IsmailProfesor Madya Luay Bakir HussainDr. Norlia BaharunDr. Zulkifli Mohamad Ariff

Pusat Pengajian Kejuruteraan Bahan dan Sumber Mineral

Profesor Mohd Omar Abd. KadirProfesor Wan Rosli Wan DaudProfesor Madya Mahamad~Hakimi IbrahimDr. Norli Ismail

Pusat Pengajian Tekn1)logi Industri

Profesor Mohd Asri Mohd NawiProfesor Lim Poh EngProfesor Madya Ahmad Md. NoorProfesor Madya Seng Chye EngDr. Amat Ngilmi Ahmad Sujari

Pusat Pengajian Sains Kimia

I,

Profesor Madya Mohd Nawawi Mohd NordinPusat Pengajian Sains Fizik

Profesor Madya Nik Norulaini Nik Ab. RahmanProfesor Madya Misni SurifDr. Issham Ismail

Pusat Pengajian Pendidikan Jarak Jauh