wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 7

Avai lab le a t www.sc iencedi rec t .com

journa l homepage : www.e lsev ie r . com/ loca te /wat res

Natural versus wastewater derived dissolvedorganic carbon: Implications for the environmentalfate of organic micropollutants

Peta A. Neale a,*, Alice Antony b, Wolfgang Gernjak c, Greg Leslie b, Beate I. Escher a

aThe University of Queensland, National Research Centre for Environmental Toxicology (Entox), Brisbane QLD 4108, AustraliabUNESCO Centre for Membrane Science and Technology, The University of New South Wales, Sydney NSW 2033, AustraliacThe University of Queensland, Advanced Water Management Centre (AWMC), Brisbane QLD 4072, Australia

a r t i c l e i n f o

Article history:

Received 21 February 2011

Received in revised form

27 May 2011

Accepted 27 May 2011

Available online 7 June 2011

Keywords:

Dissolved organic carbon

Micropollutants

Water recycling

Partition coefficient

* Corresponding author. Tel.: þ61 7 3274 922E-mail address: p.neale@uq.edu.au (P.A.

0043-1354/$ e see front matter ª 2011 Elsevdoi:10.1016/j.watres.2011.05.038

a b s t r a c t

The interaction of organic micropollutants with dissolved organic carbon (DOC) can

influence their transport, degradation and bioavailability. While this has been well estab-

lished for natural organic carbon, very little is known regarding the influence of DOC on the

fate of micropollutants during wastewater treatment and water recycling. Dissolved

organic carbonewater partition coefficients (KDOC) for wastewater derived and reference

DOC were measured for a range of micropollutants using a depletion method with poly-

dimethylsiloxane disks. For micropollutants with an octanolewater partition coefficient

(log KOW) greater than 4 there was a significant difference in KDOC between reference and

wastewater derived DOC, with partitioning to wastewater derived DOC over 1000 times

lower for the most hydrophobic micropollutants. The interaction of nonylphenol with

wastewater derived DOC from different stages of a wastewater and advanced water

treatment train was studied, but little difference in KDOC was observed. Organic carbon

characterisation revealed that reference and wastewater derived DOC had very different

properties due to their different origins. Consequently, the reduced sorption capacity of

wastewater derived DOC may be related to their microbial origin which led to reduced

aromaticity and lower molecular weight. This study suggests that for hydrophobic

micropollutants (log KOW > 4) a higher concentration of freely dissolved and thus

bioavailable micropollutants is expected in the presence of wastewater derived DOC than

predicted using KDOC values quantified using reference DOC. The implication is that

naturally derived DOC may not be an appropriate surrogate for wastewater derived DOC as

a matrix for assessing the fate of micropollutants in engineered systems.

ª 2011 Elsevier Ltd. All rights reserved.

1. Introduction removal by wastewater treatment processes micropollutants

Organic micropollutants can be defined as natural and

synthetic organic compounds found in the environment at

picogramme per litre (pg/L) to microgram per litre (mg/L)

concentrations (Schwarzenbach et al., 2006). Due to variable

1; fax: þ61 7 3274 9003.Neale).ier Ltd. All rights reserved

are often detected at low concentrations in secondary treated

effluent (e.g. Miao et al., 2004; Ying et al., 2009) as well as

surface waters (e.g. Kolpin et al., 2002; Yoon et al., 2010).

The implications of micropollutants in the environment are

wide ranging and can include feminisation of male fish by

.

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 74228

steroidal hormones (Jobling et al., 1998), increased bacterial

resistance by antibiotics (Reinthaler et al., 2003) and signifi-

cant risks for human health and the environment.

The fate and behaviour of micropollutants in the aquatic

environment can be influenced by their interaction with dis-

solved organic carbon (DOC), which is ubiquitous in natural

waters. Bioavailability and hence toxicity of micropollutants

can decrease when bound to organic carbon (e.g. Burgess

et al., 2005; Qiao and Farrell, 2002). In contrast, studies have

also shown that the presence of DOC can reduce micro-

pollutant sorption to soil, thus potentially increasing the

mobility of micropollutants in the environment (Huang and

Lee, 2001). This interaction can also influence the degrada-

tion of micropollutants by photodegradation (Lam and

Mabury, 2005; Latch and McNeill, 2006) and hydroxyl radicals

(Lindsey and Tarr, 2000). While many studies have observed

reduced degradation in the presence of DOC, Lam andMabury

(2005) found increased degradation of carbamazepine and

atorvastatin with DOC and attributed this to the increased

formation of reactive oxygen species upon irradiation. The

interaction of micropollutants with DOC can be quantified via

dissolved organic carbonewater partition coefficients (KDOC)

which represent the equilibrium distribution of a micro-

pollutant between the two phases. Quantification of KDOC can

be difficult as most analytical techniques cannot differentiate

between micropollutants that are sorbed to DOC and those

that are freely dissolved. However, through the use of a third

phase, such as a polymer fibre, this limitation can be over-

come (ter Laak et al., 2005).

The majority of studies have focused on quantifying

micropollutant interaction with reference or natural DOC

(e.g. Chefetz and Xing, 2009), with little known regarding

micropollutant interaction with wastewater derived DOC.

Wastewater derived DOC contains a range of components

including natural organic matter, microbially derived material

and organic micropollutants, and the properties can vary

significantly with season and location, while treatment

processes can modify both the quality and quantity of

wastewater derived DOC (Shon et al., 2006). An understanding

of micropollutant interaction with wastewater derived DOC is

important as many streams and rivers, particularly in arid or

semi-arid climates, can be dominated by discharges from

wastewater treatment plants (WWTP) (Brooks et al., 2006).

Further, given the increased use of secondary treated effluent

as the feed water for advanced water treatment processes in

non-potable and indirect potable applications (Hawker et al.,

2011), it is important to monitor the fate and behaviour of

micropollutants through the secondary treatment and subse-

quent advanced treatment processes.

There are few studies which have attempted to quantify

micropollutant interaction with domestic wastewater derived

DOC, though the importance of this interaction for micro-

pollutant fate during the secondary treatment stage has been

identified by Katsoyiannis and Samara (2007). This study

found decreasedmicropollutant sorption to wastewater solids

with increasing DOC concentration, suggesting that the

micropollutant-DOC interaction could interfere with the

micropollutant removal efficiency of the secondary treatment

process. The majority of studies fail to consider the dissolved

phase, instead only focus on the particulate andwater phases,

which will contain both freely dissolved and DOC-bound

micropollutants (e.g. Arditsoglou and Voutsa, 2010). The lack

of studies is related to the difficulty associatedwithmeasuring

the freely dissolved fraction (Barret et al., 2010). Quantification

techniques, such as equilibrium dialysis and solubility

enhancement, have been applied to measure partitioning of

micropollutants, including pesticides, antibiotics and fluo-

rotelomer alcohols, to wastewater derived DOC (Carmosini

and Lee, 2009, 2008; Ilani et al., 2005; Seol and Lee, 2000). In

the majority of studies KDOC for wastewater derived DOC was

significantly lower than reference or natural DOC, while KDOC

could not be measured for the antibiotic ciprofloxacin sug-

gesting it had no detectable affinity for wastewater effluent

(Carmosini and Lee, 2009).

From the literature, it appears that micropollutants

interact differently with wastewater derived DOC compared

to reference or natural DOC, however, this interaction is

poorly understood. The aim of this study was to assess

micropollutant partitioning to DOC taken from different

stages of the wastewater and advanced water treatment train

and compare with reference and natural DOC. The studied

DOC was characterised with liquid chromatography-organic

carbon detection (LC-OCD) to understand how composition

and size distribution influence partitioning. KDOC was

measured using polydimethylsiloxane (PDMS) disks which act

as a third phase, with desorption of micropollutants from

preloaded disks in the presence and absence of DOC allowing

for the derivation of KDOC. The proposed PDMS disk method

was developed to measure partitioning of proteins and lipid

vesicles (Kwon et al., 2009) and was recently applied to DOC

(Kim et al., 2010).

2. Materials and methods

2.1. Dissolved organic carbon

Water samples were collected from Bundamba Advanced

Water Treatment Plant (AWTP) and South Caboolture WWTP,

Queensland, Australia. Bundamba AWTP receives primarily

domestic secondary treated effluent from four WWTPs

including Bundamba, Oxley, Goodna and Wacol (Queensland,

Australia). The treatment processes used at Bundamba AWTP

includes pre-treatment with coagulation and clarification,

followed by microfiltration, reverse osmosis and advanced

oxidation, while South Caboolture WWTP applies biological

nutrient removal. Wastewater derived DOC was collected

from the WWTP influent (South Caboolture), secondary

treated effluent (Bundamba and South Caboolture), reverse

osmosis feed (ROF) and reverse osmosis concentrate (ROC)

(both from Bundamba). Sodium thiosulphate was added to

ROF and ROC to quench chloramines. All samples were

filtered using 0.45 mm nylon filters to remove particulate

matter. The non-purgeable DOC concentration in the samples

was measured using an Analytik Jena multi N/C 3100 instru-

ment (Jena, Germany) and the concentration ranged from 9 to

70 mg of carbon per litre (mgC/L). All samples were concen-

trated to 2 mgC/mL by freeze drying after freezing with liquid

nitrogen. Aldrich humic acid (HA) sodium salt (Castle Hill,

Australia), Suwannee River standard HA (2S101H) and fulvic

Fig. 1 e Concentration in PDMS in the presence of DOC

relative to the initial concentration in PDMS (CPDMS t [ 96,

with DOC/CPDMS t [ 0) as a function of time with 95%

confidence intervals (pH 7.8, 100 mM phosphate buffer,

average CPDMS t [ 0 3711 mg/L PDMS, Aldrich HA

concentration 2 mgC/mL).

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 7 4229

acid (FA) (2S101F) (International Humic Substance Society, St.

Paul, US) were selected as the reference DOC as they are

commonly used in the literature.

2.2. Chemicals

All chemicals were of analytical grade. The 100 mM phosphate

bufferatpH7.8wascomposedofpotassiumphosphate (KH2PO4

and K2HPO4). The studied micropollutants included pharma-

ceuticals, pesticides, endocrine disrupting chemicals and

polycyclic aromatic hydrocarbons (PAH). Specifically, these

were 4-n-nonylphenol (Alfa Aesar, Heysham, UK), irgarol, ter-

butryn, pyrene, metolachlor (Fluka, Buchs, Switzerland),

methoxychlor (Riedel-de Haen, Seelze, Germany), chlorpyrifos

(Dow Chemical Company, Midland, US), benzo(a)pyrene, car-

bamazepine (Sigma Aldrich, Castle Hill, Australia) and diben-

zo(ah)anthracene (Supleco, Bellefonte, US). The chemicalswere

selected as they represent a wide range of octanolewater

partition coefficients (KOW) covering more than four orders of

magnitude (log KOW 2.3e6.75). All chemicalswere neutral at the

studied pH.

All chemicals, except for chlorpyrifos and methoxychlor,

were analysed using a Shimadzu High Performance Liquid

Chromatography (HPLC) system with an LC-20AD pump

and a SIL-20AHT auto sampler (Rydalmere, Australia). PAHs

were analysed using a Supelcosil LC-PAH column

(150 mm� 4.6 mm, 5 mm) (Supleco, Bellefonte, US) at 40 �C and

detected using an RF-10AXL fluorescence detector. Pyrene had

excitation and emission wavelengths of 330 and 375 nm,

respectively, while benzo(a)pyrene and dibenzo(ah)anthracene

both had excitation and emission wavelengths of 290 and

430 nm, respectively. The other chemicals were analysed using

a Nucleodur C18 Gravity column (125 mm � 4.6 mm, 5 mm)

(MachereyeNagel, Duren, Germany) at 40 �C and detected

using an SPD-M20A diode array detector. For all chemicals the

flow rate was 1 mL/min. The mobile phase consisted of MilliQ

grade water and methanol, though a phosphate buffer (20 mM

K2HPO4 pH 3) was used for nonylphenol instead of water.

Methoxychlor and chlorpyrifos were analysed using

a Hewlett Packard 5890 Gas Chromatography-Electron

Capture Detector (GC-ECD) Series II with an HP-7673A auto

sampler (Palo Alto, US). For methoxychlor the column

temperature started at 150 �C and increased to 220 �C at a rate

of 30 �C/min followed by 10 �C/min until 270 �C. The column

temperature for chlorpyrifos also started at 150 �C and

increased to 220 �C at a rate of 30 �C/min followed by 10 �C/min

until 250 �C and 30 �C/min until 300 �C, which was then held

for 1 min. Both chemicals were analysed using a DB-5 column

(30 m � 0.25 mm i.d.) (J&W Scientific, Folsom, US).

2.3. Dissolved organic carbonewater partitioncoefficient

Partitioning between DOC and water for the studied micro-

pollutants wasmeasured using a depletionmethod developed

initially by ter Laak et al. (2005) using solid-phase micro-

extraction (SPME) fibres and adapted to PDMS disks by Kwon

et al. (2009). Prior to the experiment, disks with a volume of

approximately 1.4 mL were cut and cleaned by soxhleting with

hexane and methanol for 2 h each. The studied chemicals

were loaded to the disks in methanol:water solutions (60:40)

for 4 days with concentrations ranging from 0.0002 to 4 mg/

mL, depending on detection limit. Consequently, the initial

concentrations in the PDMS disks were in the mg/L PDMS

range (3e3500

mg/L PDMS).

In 2 mL HPLC vials, a preloaded disk was added to

a suspension containing 100 mM phosphate buffer (pH 7.8)

and DOC at concentrations ranging from 1 to 2 mgC/mL.

Sodium azide (0.05%) was added for preservation. The vials

were shaken for 96 h in an incubator at 25 �C. While equilib-

rium between DOC and water is expected to be reached

instantaneously, equilibrium between the PDMS and DOC

suspensionwas only reached at 96 h for themore hydrophobic

compounds, such as nonylphenol (Fig. 1). This was due to

rate-limited desorption from the PDMS caused by the aqueous

diffusion layer around the disk (ter Laak et al., 2008). Preloaded

diskswere added to vials containing phosphate buffer only for

96 h controls. After 96 h the disks from the DOC suspension

(CPDMS t ¼ 96, with DOC) and t ¼ 96 h controls (CPDMS t ¼ 96, without

DOC) were removed and added to vials containing 500 mL of

methanol or 200 mL of hexane and desorbed by shaking for 2 h

in an incubator at 25 �C. Given the high solvent volume to disk

volume ratio, the extraction efficiency should be exhaustive.

Preloaded disks were also added directly to vials containing

500 mL of methanol (HPLC) or 200 mL of hexane (GC-ECD) for

time zero (t ¼ 0) controls (CPDMS t ¼ 0). The methanol extracts

were analysed using HPLC and the hexane extracts were

analysed using GC-ECD. The disks were dried and weighed to

determineCPDMS t ¼ 0, CPDMS t ¼ 96, without DOC andCPDMS t ¼ 96, with

DOC. All experiments were repeated in triplicate.

The PDMS-water partition coefficient (KPDMS-w) represents

the equilibrium distribution of a micropollutant between the

PDMS disk and water in the absence of DOC. KPDMS-w was

measured independently for hydrophobic micropollutants

(log KOW > 4) using the aqueous boundary layer (ABL)

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 74230

permeation method (Kwon et al., 2007). For hydrophilic

micropollutants (log KOW < 4), KPDMS-w was measured in situ

using a full mass balance as there was significant depletion

from the disks in the presence of buffer alone (20e70%).

The full mass balance is shown in Equation (1), where ntot was

the total amount in the disk at time zero, nPDMS1 was the

amount in the disk after 96 h in phosphate buffer and nw1 was

the freely dissolved amount in water (Fig. 2). KPDMS-w was then

determined using Equation (2) where Vw was the solution

volume (L) and VPDMS was the PDMS volume (L). All KPDMS-w

values used in this study are shown in Table 1.

ntot ¼ nPDMS1 þ nw1 (1)

KPDMS�w ¼ nPDMS1

nw1$

Vw

VPDMS(2)

As the presence of DOC reduced the amount of freely dis-

solved micropollutants in water (nw2), a new mass balance

equation was required (Equation (3)) where nPDMS2 was the

amount in the disk after 96 h in DOC suspension and nDOC was

the amount sorbed to DOC (Fig. 2). In both Equations (1) and

(3), 100% mass balance was assumed, though sorption to

glass vials and volatilisation was possible. Such losses were

minimised by the high sorptive capacity of the PDMS and the

small headspace. KDOC (L/kg) was determined using Equation

(4) where mDOC was the mass of DOC in suspension (kg).

ntot ¼ nPDMS2 þ nw2 þ nDOC (3)

KDOC ¼ntot

nPDMS2$KPDMS�w,VPDMS � Vw � ðKPDMS�w,VPDMSÞ

mDOC(4)

As KDOC is a concentration ratio, the fraction of micro-

pollutant sorbed to DOC ( fDOC) can changewith changing DOC

concentration. This is particularly relevant to wastewater

derived DOC as the quantity of DOC can be altered throughout

the treatment train. fDOC was calculated using Equation (5).

fDOC ¼ 1

1þ Vw

ðmDOC,KDOCÞ(5)

2.4. Dissolved organic carbon characterisation

The studied DOC was characterised using liquid chromatog-

raphy combined with an organic carbon detector (LC-OCD)

(DOC-Labour, Karlsruhe, Germany). This technique combines

size exclusion chromatography with organic carbon detection

to separate DOC into different fractions, such as biopolymers,

DOCSuspension

Phosphate buffer

nPDMS1 nPDMS2

nw1 nw2

ntot = ntot

nDOC

Fig. 2 e Full mass balance in the absence and presence of

DOC.

humic substances, building blocks (degraded humic

substances) and low molecular weight (LMW) neutrals and

acids. DOC is separated via steric interactions with the size

exclusion chromatography resin, while the LMW organic acid

fraction is separated by amphiphilic elution (Ciputra et al.,

2010). LC-OCD can also provide information on humic

substance molecular weight and aromaticity, as indicated by

specific UV absorbance (SUVA) at 254 nm. A size exclusion

column (HW-50S) (Tosoh, Stuttgart, Germany) with a particle

size of 30 mm was used. The mobile phase was 28 mM phos-

phate buffer (pH 6.58). For each sample 1000 mL was injected

and each sample ran for 150 min. The chromatograms were

interpreted using DOC-Labor ChromCALC. Further informa-

tion on the LC-OCD method used and instrument calibration

can be found in Ciputra et al. (2010) and Huber et al. (2011).

3. Results and discussion

3.1. Isotherms

To assess the influence of the preload concentration on par-

titioning the freely dissolved (Cw) and sorbed (CDOC) concen-

trations were studied over a 10 fold concentration range for

nonylphenol. Within the literature, nonlinear isotherms have

been observed for DOC with increasing micropollutant

concentration (Laor and Rebhun, 2002) and this could be

a potential limitation for the chemicals with a higher detec-

tion limit, such as nonylphenol. Using the Freundlich equa-

tion, the slope of the log regression was close to 1 which

suggests that sorption was linear on a nonlogarithmic scale

over the studied concentration range (Fig. 3). Consequently, it

was a partitioning process and the sorption sites were not yet

saturated indicating that it was still acceptable to measure

partitioning at higher concentrations.

3.2. Dissolved organic carbonewater partitioncoefficients

To compare micropollutant interaction with reference and

wastewater derived DOC KDOC was measured for a range of

micropollutants with Aldrich HA and ROC (Table 1). Given the

increased interest in water recycling using advanced water

treatment processes, such as membrane filtration, ROC was

selected as a representative wastewater derived DOC. As well

as being rich in DOC (up to 70 mgC/L) and salts (conductivity

around 5.55 mS/cm), it can also contain elevated levels of

micropollutants (Watkinson et al., 2007). Prior to being

disposed in the estuarine Brisbane River, ROC is treated using

nitrifying and denitrifying processes to reduce nutrient levels,

however, the presence of micropollutants in treated ROCmay

pose an environmental hazard to the receiving waters.

A strong relationship was observed between log KOW and

log KDOC for Aldrich HA (Fig. 4). The slope and intercept were

not statistically different from 1 and 0, respectively (Table 2).

The correlation suggests that octanol was a perfect surrogate

for Aldrich HA. The quantitative structureeactivity relation-

ship (QSAR) obtained here was similar to previous studies

with HA and hydrophobic micropollutants (Table 2), and

indicates that partitioning was driven by non-specific

Table 1 e Octanolewater partition coefficients (KOW), PDMS-water partition coefficients (KPDMS-w) and dissolved organiccarbonewater partition coefficients (KDOC) for a range of chemicals with Aldrich HA and reverse osmosis concentrate fromBundamba Advanced Water Treatment Plant.

log KOWa KPDMS-w log KDOC

Aldrich HAblog KDOC ROCb Fraction

sorbed to ROCcModelledlog KOC

dLiterature log KOC

(Aldrich HA)

Carbamazepine 2.30 � 0.35 179e 2.87 � 0.06 3.14 � 0.24 8.85% 2.23 e

Metolachlor 3.13 � 0.32 657e 2.95 � 0.03 2.86 � 0.24 4.85% 2.39 e

Irgarol 3.38 3188e 3.21 � 0.06 3.12 � 0.41 8.48% 2.63 e

Terbutryn 3.74 � 0.23 2254e 3.31 � 0.07 2.80 � 0.36 4.25% 2.78 e

Methoxychlor 4.95 � 0.52 30903f 4.99 � 0.19 3.06 � 0.53 7.47% 4.43 e

Chlorpyrifos 4.96 � 0.34 22863g 4.36 � 0.12 3.12 � 0.28 8.48% 3.86 4.28i

Pyrene 5.00 � 0.27 22909h 5.15 � 0.08 3.16 � 0.37 9.22% 4.74 5.18,j 5.02,k 5.36,l

5.55,m 5.51n

Nonylphenol 5.76 32359f 5.25 � 0.15 3.25 � 0.13 11.11% 4.58 4.83�

Benzo(a)pyrene 6.35 � 0.33 123027h 6.84 � 0.15 3.75 � 0.26 28.33% 5.32 6.28m7.16n6.31p

Dibenzo(ah)

anthracene

6.75 � 0.34 295121h 6.96 � 0.09 4.05 � 0.62 44.10% 5.68 7.56n

a Recommended experimental octanolewater partition coefficient (log KOW) with standard deviation (Sangster, 2006).

b L/kg.

c Calculated using Equation (5).

d Organic carbonewater partition coefficient (KOC) modelled using KOCWIN (estimated using log KOW) (US EPA, 2008).

e Measured in situ using Equation (2).

f Measured using the ABL permeation method (see Kwon et al. (2007) for further details).

g van der Voet (2008).

h Kwon et al. (2007).

i Huang and Lee (2001).

j Chin et al. (1997).

k Gauthier et al. (1987).

l Perminova et al. (1999).

m ter Laak et al. (2005).

n Kim and Kwon (2010).

o Yamamoto et al. (2003).

p McCarthy and Jimenez (1985).

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 7 4231

interactions, such as Van derWaals forces. In contrast, a weak

correlation was observed between log KOW and log KDOC for

ROC (r2 ¼ 0.58), with a slope of 0.20 and an intercept of 2.30

(Table 2). Previous studies have attributed such changes in

slope to the hydrophobicity of organic carbon, with

Schwarzenbach and Westall (1981) finding a reduction in

Fig. 3 e Nonylphenol linear isotherm with Cw as the

concentration freely dissolved in water (mol/L) and CDOC as

the concentration sorbed to DOC (pH 7.8, 100 mM

phosphate buffer, average CPDMS t [ 0 2776e23013 mg/L

PDMS, Aldrich HA concentration 2 mgC/mL).

slope as the organic carbon became more hydrophilic.

A number of studies have indicated that wastewater derived

DOC contains more hydrophilic carbon than reference DOC as

certain treatment processes, such as ozonation and

membrane filtration, can significantly reduce the hydrophobic

fraction in wastewater derived DOC (Imai et al., 2002).

The different slopes for Aldrich HA and ROCmay also indicate

different intermolecular interactions between the studied

DOC and micropollutants (Niederer et al., 2007).

There was no significant difference between KDOC for

Aldrich HA and ROC for micropollutants with a log KOW less

than 4. For these compounds minimal depletion from the

PDMS disk was observed in the presence of both ROC and

Aldrich HA. These micropollutants are more soluble than the

other studied compounds and previous work by Chiou et al.

(1986) has shown that DOC concentration and properties can

have little influence on the solubility enhancement of such

micropollutants which is related to partitioning. Conse-

quently, it appears that the difference in DOC properties have

minimal influence on the sorption of these more soluble

micropollutants. In contrast, partitioning of the most hydro-

phobic micropollutants, such as benzo(a)pyrene, to Aldrich

HA was over 1000 times greater than ROC. These compounds

are non-polar and have a planar conformation, promoting

strong interactions with the hydrophobic Aldrich HA, with

depletion from the PDMS disk up to 99% for the most hydro-

phobic micropollutants.

Using Equation (5), the fraction of micropollutants sorbed

to ROC was estimated (Table 1). For the majority of the

Fig. 4 e Relationship between octanolewater partition

coefficients (KOW) and dissolved organic carbonewater

partition coefficients (KDOC) for studied micropollutants for

Aldrich HA and Bundamba reverse osmosis concentrate

(pH 7.8, 100 mM phosphate buffer, average CPDMS t [ 0

3e3500 mg/L PDMS, DOC concentration 1e2 mgC/mL). The

error bars represent standard deviation, with some error

bars, particularly for Aldrich HA, smaller than the symbol

size.

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 74232

compounds, the fraction sorbed to DOC was less than 10%

despite the high carbon concentration of ROC. Sorption to

DOC in ROC was more significant for the highly hydrophobic

micropollutants, such as benzo(a)pyrene and dibenzo(ah)

anthracene (28% and 44%, respectively). However, as most

micropollutants present in secondary treated effluent are

expected to be more hydrophilic, as the more hydrophobic

compounds are already removed by sorption to biosolids

during secondary treatment, the majority can be considered

freely dissolved.

In Table 1 experimental KDOC values for Aldrich HA and

ROC were compared with modelled organic carbonewater

partition coefficients (KOC) predicted using KOCWIN (US EPA,

Table 2 e Quantitative activityestructure relationships (QSAR)coefficients (KDOC) and octanolewater partition coefficients (KOW

3 log KOW D intercept).

Dissolved organic carbon Slope � std. error Inter

Bundamba ROC 0.20 � 0.06

Aldrich HA 1.01 � 0.01

Aldrich HAa 0.76 � 0.08

Aldrich HAb 1.23 � 0.13

Suwannee River FAb 0.82 � 0.09

Roth HAc 0.92 � 0.04

Roth HAc 0.98 � 0.06

Aldrich HAd 1.19 � 0.07

a Durjava et al. (2007).

b Kim and Kwon (2010).

c Poerschmann and Kopinke (2001).

d ter Laak et al. (2005).

2008). Above a log KOW of 4, the modelled KOC values gener-

ally fit better with the Aldrich HA KDOC values compared to

ROC. As a result, suchmodelled values are not suitable for the

prediction of micropollutant interaction with wastewater

derived DOC. Within the literature, the interaction of some of

the studied chemicals, including chlorpyrifos, nonylphenol

and dibenzo(ah)anthracene, have been quantified with

Aldrich HA using a variety of techniques (e.g. Huang and Lee,

2001; Kim and Kwon, 2010; Yamamoto et al., 2003). The liter-

ature KDOC values fit well with the Aldrich HA KDOC values in

this study (Table 1).

The potential for DOC uptake to the disks was explored

using the method described in Section 2.3 with clean PDMS

disks. In the presence of wastewater derived DOC, particularly

ROC, some small peaks were observed at the beginning of the

HPLC chromatograms and it was assumed that these were

hydrophilic micropollutants which were poorly removed by

conventional treatment processes. However, the concentra-

tions of these compounds on the disks were insignificant

compared to the concentrations of the studied micro-

pollutants. No changes in HPLC chromatograms were

observed for reference DOC suggesting that DOC was not

bound to the disks. Further, no visible fouling, such as colour

change, was observed indicating that DOC uptake to the disks

was not significant.

3.3. Nonylphenol sorption throughoutthe treatment train

During water treatment processes the quality and quantity of

DOC can be altered, and this is expected to have implication

for micropollutant fate. The interaction of nonylphenol with

influent and secondary treated effluent from South Cabool-

tureWWTP and secondary treated effluent, ROF and ROC from

Bundamba AWTP is shown in Fig. 5A and compared to parti-

tioning to reference DOC, including Aldrich HA and Suwannee

River HA and FA. Nonylphenol was selected for study as it has

been found in concentrations up to 0.069 mg/L in purified

recycled samples taken from Bundamba AWTP (Hawker et al.,

2011), indicating that it was not removed effectively during

conventional wastewater treatment processes and persists

between dissolved organic carbonewater partition) from the current study and the literature (logKDOC[ slope

cept � std. error r2 Studied micropollutants

2.30 � 0.29 0.58 Current study

�0.07 � 0.48 0.93 Current study

1.55 � 0.55 0.94 PCBs

�0.82 � 0.75 0.94 PAHs

0.31 � 0.53 0.93 PAHs

�0.47 � 0.26 0.99 PCBs

�0.39 � 0.25 0.99 PAHs

�0.62 � 0.40 0.99 PAHs

Fig. 5 e A) Dissolved organic carbonewater partition coefficients (KDOC) for nonylphenol for reference and wastewater

derived DOC and B) DOC concentration and fraction of nonylphenol sorbed to wastewater derived DOC (fDOC) (pH 7.8, 100mM

phosphate buffer, average CPDMS t [ 0 3500 mg/L PDMS; DOC concentration 1e2 mgC/mL).

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 7 4233

through the advanced water treatment train despite being

highly hydrophobic (log KOW 5.76). Fig. 5A indicates that there

was no significant difference in partitioning for the waste-

water derived DOC, despite treatment processes, such as

coagulation and microfiltration, expected to alter the quality

of DOC. The quantity of the DOC decreased throughout the

treatment train, for example, the influent at South Caboolture

WWTP had a DOC concentration of 49 mgC/L which decreased

to 15 mgC/L in the secondary treated effluent (Fig. 5B). The

change in DOC concentration will influence the fraction of

nonylphenol sorbed to wastewater DOC. For example,

approximately 10e15% of nonylphenol was expected to be

sorbed to DOC in the WWTP influent and ROC, compared to

only 1e2% sorbed DOC in the secondary treated effluent and

ROF, despite similar KDOC values.

For the reference DOC, KDOC for Aldrich HAwas an order of

magnitude larger than Suwannee River HA, while KDOC for

Suwannee River FA was similar to the wastewater derived

DOC (Fig. 5A). A similar order of partitioning was observed

previously in the literature (e.g. Chin et al., 1997; Niederer

et al., 2007) and the differences may be related to the

different origins and properties of the reference DOC. It has

been suggested previously that commercial HA, such as

Aldrich HA, are not representative of naturally occurring DOC

(Malcolm and MacCarthy, 1986), however it was still included

in this study as it has been used widely in the literature and

served to validate the experimental method. The decreased

partitioning of Suwannee River FA compared to Suwannee

River HA may be related to the higher content of carboxyl

groups (Ritchie and Perdue, 2003). The carboxyl groups were

deprotonated at the studied pH, making FA more polar than

HA, which consequently reduced its sorption capacity.

The low depletion of nonylphenol from the disk in the pres-

ence of Suwannee River FA added increased uncertainty to the

results. However, it was not possible to increase the volume of

suspension as this would lead to the freely dissolved fraction

no longer being insignificant.

3.4. Dissolved organic carbon characterisation

To understand why micropollutants have a lower affinity for

wastewater derived DOC compared to reference DOC, the DOC

was characterised using LC-OCD. This technique revealed that

the reference DOC contained a higher fraction of humic

substances compared to wastewater derived DOC, which

contained more biogenic organic carbon, including biopoly-

mers and LMW neutrals (Table 3). Consequently, wastewater

derived DOC had a lower weight-averaged molecular weight

(MW) compared to reference DOC (578e800 Vs. 928e1469

g/mol). Compared to previous studies, such as Chin et al.

(1994), the MW of Aldrich HA is low (1092 V 4100), however it

is important to note that this is the MW of the humic

substance fraction only, not the whole sample. This also

explains why there is little difference in polydispersity

between wastewater derived and reference DOC (Table 3).

Wastewater derived DOC also had a lower SUVA value

which suggests that wastewater derived DOC is less aromatic

than reference DOC. Low SUVA values have been previously

found in effluent impacted waters and this was attributed to

the microbial or autochthonous origin of wastewater derived

DOC (Rosario-Ortiz et al., 2007). Further, the biopolymer frac-

tion of wastewater derived DOC contained a significant

fraction of proteins which is also an indicator of microbial

activity (Drewes and Croue, 2002). The different properties of

the reference and wastewater derived DOC reflect their

different origins.

3.5. Influence of dissolved organic carbon properties onmicropollutant partitioning

To improve understanding of micropollutant interaction with

DOC many studies have focused on the relationship between

KDOC and DOC properties, such as MW and polarity (Chiou

et al., 1986). Using the LC-OCD results in Table 3, the rela-

tionship between KDOC for nonylphenol and weight-averaged

Table 3 e Liquid chromatography-organic carbon detector analysis of reference and wastewater derived DOC.

Bio-polymersa

(%)

Biopolymersb

(%)Humic

Substances(%)

BuildingBlocksc

(%)

LMWNeutrals

(%)

MWd

(g/mol)

Mne

(g/mol)

MW/Mn

fSUVA-HS254 nmg (L/(mg∙m))

DOCh

(mgC/L)

Aldrich HA e e 61.2 9.6 18.8 1092 730 1.50 9.80 e

Suwannee

River

HA

e 0.2 78.3 9.7 14.9 1469 1000 1.47 7.74 e

Suwannee

River

FA

e e 79.0 8.9 11.8 928 613 1.51 5.89 e

South

Caboolture

WWTP

influent

9.2 4.4 35.1 17.3 28.1 710 495 1.43 2.20 48.58

South

Caboolture

secondary

effluent

2.0 5.0 34.1 16.3 35.0 800 636 1.26 3.99 14.68

Bundamba

secondary

effluent

12.3 16.2 33.7 12.6 20.1 634 473 1.34 2.12 9.71

Bundamba

ROF

0.4 1.8 44.5 18.6 24.9 601 455 1.32 1.97 9.11

Bundamba

ROC

1.4 1.9 46.6 18.6 24.4 578 451 1.28 2.22 70.30

NB: Remaining DOC fraction was non-chromatographic DOC which was retained on the column.

a Protein biopolymers.

b Polysaccharides and aminosugars biopolymers.

c Humic acid breakdown products.

d Weight-averaged molecular weight of humic substances.

e Number-averaged molecular weight of humic substances.

f Polydispersity of humic substances.

g Specific UV absorbance of humic substances at 254 nm.

h DOC concentration in the studied wastewater and advanced water treatment plants.

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 74234

MW and SUVA for all reference and wastewater derived DOC

samples was studied (Fig. 6). The majority of studies have

focused on non-polar micropollutants, particularly PAHs.

While nonylphenol has a high log KOW value, it also contains

a bipolar functional group, allowing it to interact with DOC

through hydrogen bonding in addition to Van der Waals

forces.

Fig. 6 e Relationship between dissolved organic carbonewater

averaged molecular weight (MW) and B) specific UV absorbance

A weakly positive relationship was observed between KDOC

and MW (Fig. 6A). Chin et al. (1997) found a strong positive

relationship between the increasing MW and KDOC for pyrene

and suggested that the additional aromatic functional groups

in the larger DOC molecules contributed to stronger sorption.

HurandSchlautman (2003)alsoobservedasimilar relationship

betweenKDOCandMWforpyrene, butwarned thatpartitioning

partition coefficients (KDOC) for nonylphenol and A) weight-

(SUVA) of humic substances for the studied DOC.

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 7 4235

was not only dependent on physical properties but also on

structure and origin. Given the different sources of the refer-

ence and wastewater derived DOC this may explain the weak

relationship observed in the current study. Further, the fact

that the measured MW only represents the humic substance

fraction may also contribute to the weak relationship.

A moderately positive relationship was observed between

KDOC and SUVA (Fig. 6B). Gauthier et al. (1987) found increasing

organic carbon aromaticity led to increased interaction with

pyrene, and suggested that this was due to increased polariz-

ability of the organic matter. Increased polarizability can

increase non-specific molecular interactions through induced

dipole interactions (Schwarzenbach et al., 2003) and this

may contribute to stronger partitioning for hydrophobic

compounds. A correlation between aromaticity and KDOC for

reference DOC has also been observed in several other studies

(e.g. Chin et al., 1997; Perminova et al., 1999). In contrast,

Carmosini and Lee (2008) found no relationship between

aromaticity and KDOC for fluorotelomer alcohols with both

reference and wastewater derived DOC. Therefore, similar to

MW, the variability may be related to the studied DOC and

micropollutant.

While Suwannee River FA was smaller and less aromatic

than the other reference DOC, Fig. 6 cannot fully explain why

its sorption capacity was so similar to wastewater derived

DOC for nonylphenol. To improve understanding and

prediction of micropollutant sorption to reference and

wastewater derived DOC in future studies, polyparameter

linear free energy relationships (pp-LFER) can be applied.

pp-LFERs can take into account specific and non-specific

interactions, as well as cavity formation in DOC, and have

been successfully applied by Niederer et al. (2007) to predict

natural organic matter-air and -water partition coefficients.

4. Conclusions

The fate of micropollutants in the aquatic environment and

engineered systems can be influenced by the properties of

DOC. Within the literature the majority of studies focus on

reference or natural DOC, with little known regarding micro-

pollutant interaction with wastewater derived DOC. Given the

different properties, reference DOC, particularly Aldrich HA,

was not an appropriate surrogate forwastewater derivedDOC.

This is because KDOC measured using reference DOC will

underestimate the freely dissolved and thus bioavailable

fraction of moderately hydrophobic micropollutants (log

KOW > 4) in water recycling or water bodies receiving signifi-

cant wastewater effluent discharges. These findings also have

relevance to other wastewater applications including use of

biosolids in agriculture. As minimal sorption of micro-

pollutants to wastewater derived DOC is expected this may

lead to more sorption to biosolids and thus higher micro-

pollutant release during land application than predicted.

This study also illustrated the importance of DOC concentra-

tion for micropollutant fate, with micropollutants present in

secondary treated effluent expected to be more bioavailable

than in DOC richwaste streams, such as ROC. Suwannee River

FA had a similar KDOC to wastewater derived DOC for non-

ylphenol, but further research is required to understand its

sorption capacity and interaction with other micropollutants

before it can be used as a model for wastewater derived DOC.

Acknowledgements

The National Research Centre for Environmental Toxicology

(Entox) is a joint venture of The University of Queensland and

Queensland Health Forensic and Scientific Services (QHFSS).

This study was supported under the Australian Research

Council (ARC) Linkage Project funding scheme (LP100200276)

with industry partners WaterSecure, Water Quality Research

Australia Limited (WQRA) and Veolia Water Australia. Julien

Reungoat (AWMC, UQ) is thanked for sample collection and

Ben Mewburn and Sibylle Rutishauser (Entox, UQ) are

acknowledged for laboratory assistance. Jorg Drewes (Colo-

rado School of Mines) is thanked for helpful discussions, while

Yvan Poussade (Veolia Water Australia) and Cedric Robillot

(WaterSecure) are acknowledged for providing access to the

Bundamba AWTP, as well as useful discussions.

r e f e r e n c e s

Arditsoglou, A., Voutsa, D., 2010. Partitioning of endocrinedisrupting compounds in inland waters and wastewatersdischarged into the coastal area of Thessaloniki, NorthernGreece. Environmental Science and Pollution Research 17,529e538.

Barret, M., Patureau, D., Latrille, E., Carrere, H., 2010. A three-compartment model for micropollutants sorption in sludge:methodological approach and insights. Water Research 44,616e624.

Brooks, B., Riley, T., Taylor, R., 2006. Water quality of effluent-dominated ecosystems: ecotoxicological, hydrological, andmanagement considerations. Hydrobiologia 556, 365e379.

Burgess, R.M., Pelletier, M.C., Gundersen, J.L., Perron, M.M.,Ryba, S.A., 2005. Effects of different forms of organic carbon onthe partitioning and bioavailability of nonylphenol.Environmental Toxicology and Chemistry 24, 1609e1617.

Carmosini, N., Lee, L.S., 2009. Ciprofloxacin sorption by dissolvedorganic carbon from reference and bio-waste materials.Chemosphere 77, 813e820.

Carmosini, N., Lee, L.S., 2008. Partitioning of fluorotelomer alcoholsto octanol and different sources of dissolved organic carbon.Environmental Science and Technology 42, 6559e6565.

Chefetz, B., Xing, B., 2009. Relative role of aliphatic and aromaticmoieties as sorption domains for organic compounds: a review.Environmental Science and Technology 43, 1680e1688.

Chin, Y.-P., Aiken, G., Danielsen, K.M., 1997. Binding of pyrene toaquatic and commercial humic substances: the role ofmolecular weight and aromaticity. Environmental Science andTechnology 31, 1630e1635.

Chin, Y.-P., Aiken, G., O’Loughlin, E., 1994. Molecular weight,polydispersity and spectroscopic properties of aquatic humicsubstances. Environmental Science and Technology 28,1853e1858.

Chiou, C., Malcolm, R.L., Brinton, T.I., Kile, D.E., 1986. Watersolubility enhancement of some organic pollutants andpesticides by dissolved humic and fulvic acids. EnvironmentalScience and Technology 20, 502e508.

Ciputra, S., Antony, A., Phillips, R., Richardson, D., Leslie, G., 2010.Comparison of treatment options for removal of recalcitrantdissolved organic matter from paper mill effluent.Chemosphere 81, 86e91.

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 74236

Drewes, J.E., Croue, J.P., 2002. New approaches for structuralcharacterization of organic matter in drinking water andwastewater effluents. Water Science and Technology: WaterSupply 2, 1e10.

Durjava, M.K., ter Laak, T.L., Hermens, J.L.M., Struijs, J., 2007.Distribution of PAHs and PCBs to dissolved organic matter:high distribution coefficients with consequences forenvironmental fate modeling. Chemosphere 67, 990e997.

Gauthier, T.D., Seitz, W.R., Grant, C.L., 1987. Effects of structuraland compositional variations of dissolved humic materials onpyrene Koc values. Environmental Science and Technology 21,243e248.

Hawker, D.W., Cumming, J.L., Neale, P.A., Bartkow, M.E.,Escher, B.I., 2011. A screening level fate model of organiccontaminants from advanced water treatment in a potablewater supply reservoir. Water Research 45, 768e780.

Huang, X., Lee, L.S., 2001. Effects of dissolved organic matter fromanimal waste effluent on chlorpyrifos sorption by soils.Journal of Environmental Quality 30, 1258e1265.

Huber, S.A., Balz, A., Abert, M., Pronk, W., 2011. Characterisationof aquatic humic and non-humic matter with size-exclusionchromatography - organic carbon detection - organic nitrogendetection (LC-OCD-OND). Water Research 45, 879e885.

Hur, J., Schlautman, M.A., 2003. Using selected operationaldescriptors to examine the heterogeneity within a bulk humicsubstance. Environmental Science and Technology 37,880e887.

Ilani, T., Schulz, E., Chefetz, B., 2005. Interactions of organiccompounds with wastewater dissolved organic matter: role ofhydrophobic fractions. Journal of Environmental Quality 34,552e562.

Imai, A., Fukushima, T., Matsushige, K., Kim, Y.-H., Choi, K., 2002.Characterization of dissolved organic matter in effluents fromwastewater treatment plants. Water Research 36, 859e870.

Jobling, S., Nolan, M., Tyler, C.R., Brighty, G., Sumpter, J.P., 1998.Widespread sexual disruption in wild fish. EnvironmentalScience and Technology 32, 2498e2506.

Katsoyiannis, A., Samara, C., 2007. The fate of dissolvedorganic carbon (DOC) in the wastewater treatment processand its importance in the removal of wastewatercontaminants. Environmental Science and PollutionResearch 14, 284e292.

Kim, H.-J., Lee, D.S., Kwon, J.-H., 2010. Sorption of benzimidazoleanthelmintics to dissolved organic matter surrogates andsewage sludge. Chemosphere 80, 256e262.

Kim, S.-J., Kwon, J.-H., 2010. Determination of partitioncoefficients for selected PAHs between water and dissolvedorganic matter. CLEAN e Soil, Air, Water 38, 797e802.

Kolpin, D.W., Furlong, E.T., Meyer, M.T., Thurman, E.M., Zaugg, S.D., Barber, L.B., Buxton, H.T., 2002. Pharmaceuticals,hormones, and other organic wastewater contaminants inU.S. streams, 1999-2000: a national reconnaissance.Environmental Science and Technology 36, 1202e1211.

Kwon, J.-H., Wuethrich, T., Mayer, P., Escher, B.I., 2009.Development of a dynamic delivery method for in vitrobioassays. Chemosphere 76, 83e90.

Kwon, J.-H., Wuethrich, T., Mayer, P., Escher, B.I., 2007. Dynamicpermeation method to determine partition coefficients ofhighly hydrophobic chemicals betweenpoly(dimethylsiloxane) and water. Analytical Chemistry 79,6816e6822.

Lam, M.W., Mabury, S.A., 2005. Photodegradation of thepharmaceuticals atorvastatin, carbamazepine, levofloxacin,and sulfamethoxazole in natural waters. Aquatic Sciences 67,177e188.

Laor, Y., Rebhun, M., 2002. Evidence for nonlinear binding of PAHsto dissolved humic acid. Environmental Science andTechnology 36, 955e961.

Latch, D.E., McNeill, K., 2006. Microheterogeneity of singletoxygen distributions in irradiated humic acid solutions.Science 311, 1743e1747.

Lindsey, M.E., Tarr, M.A., 2000. Inhibition of hydroxyl radicalreaction with aromatics by dissolved natural organic matter.Environmental Science and Technology 34, 444e449.

Malcolm, R.L., MacCarthy, P., 1986. Limitations in the use ofcommercial humic acids in water and soil research.Environmental Science and Technology 20, 904e911.

McCarthy, J.F., Jimenez, B.D., 1985. Interactions betweenpolycyclic aromatic hydrocarbons and dissolved humicmaterial: binding and dissociation. Environmental Scienceand Technology 19, 1072e1076.

Miao, X.-S., Bishay, F., Chen, M., Metcalfe, C.D., 2004. Occurrenceof antimicrobials in the final effluents of wastewatertreatment plants in Canada. Environmental Science andTechnology 38, 3533e3541.

Niederer, C., Schwarzenbach, R.P., Goss, K.-U., 2007. Elucidatingdifferences in the sorption properties of 10 humic and fulvicacids for polar and nonpolar organic chemicals.Environmental Science and Technology 41, 6711e6717.

Perminova, I.V., Grechishcheva, N.Y., Petrosyan, V.S., 1999.Relationships between structure and binding affinity of humicsubstances for polycyclic aromatic hydrocarbons: relevance ofmolecular descriptors. Environmental Science andTechnology 33, 3781e3787.

Poerschmann, J., Kopinke, F.D., 2001. Sorption of veryhydrophobic organic compounds (VHOCs) on dissolvedhumic organic matter (DOM) 2. Measurement of sorptionand application of a Flory-Huggins concept to interpret thedata. Environmental Science and Technology 35,1142e1148.

Qiao, P., Farrell, A.P., 2002. Influence of dissolved humic acid onhydrophobic chemical uptake in juvenile rainbow trout.Comparative Biochemistry and Physiology Part C: Toxicologyand Pharmacology 133, 575e585.

Reinthaler, F.F., Posch, J., Feierl, G., Wust, G., Haas, D.,Ruckenbauer, G., Mascher, F., Marth, E., 2003. Antibioticresistance of E. coli in sewage and sludge. Water Research 37,1685e1690.

Ritchie, J.D., Perdue, E.M., 2003. Proton-binding study of standardand reference fulvic acids, humic acids, and natural organicmatter. Geochimica et Cosmochimica Acta 67, 85e96.

Rosario-Ortiz, F.L., Snyder, S.A., Suffet, I.H., 2007.Characterization of dissolved organic matter in drinking watersources impacted by multiple tributaries. Water Research 41,4115e4128.

Sangster, J., 2006. LOGKOW: A databank of evaluated octanol-water partition coefficients (LogP) (accessed 08.11.2010). http://logkow.cisti.nrc.ca/logkow.

Schwarzenbach, R.P., Escher, B.I., Fenner, K., Hofstetter, T.B.,Johnson, C.A., vonGunten, U.,Wehrli, B., 2006. The challenge ofmicropollutants in aquatic systems. Science 313, 1072e1077.

Schwarzenbach, R.P., Gschwend, P.W., Imboden, D.M., 2003.Environmental Organic Chemistry. John Wiley & Sons, Inc,Hobeken.

Schwarzenbach, R.P., Westall, J., 1981. Transport of nonpolarorganic compounds from surface water to groundwater.Laboratory sorption studies. Environmental Science andTechnology 15, 1360e1367.

Seol, Y., Lee, L.S., 2000. Effect of dissolved organic matter intreated effluents on sorption of atrazine and prometryn bysoils. Soil Science Society of America Journal 64,1976e1983.

Shon, H.K., Vigneswaran, S., Snyder, S.A., 2006. Effluent organicmatter (EfOM) in wastewater: constituents, effects, andtreatment. Critical Reviews in Environmental Science andTechnology 36, 327e374.

wat e r r e s e a r c h 4 5 ( 2 0 1 1 ) 4 2 2 7e4 2 3 7 4237

ter Laak, T.L., Busser, F.J.M., Hermens, J.L.M., 2008.Poly(dimethylsiloxane) as passive sampler material forhydrophobic chemicals: effect of chemical properties andsampler characteristics on partitioning and equilibrationtimes. Analytical Chemistry 80, 3859e3866.

ter Laak, T.L., Durjava, M., Struijs, J., Hermens, J.L.M., 2005.Solid phase dosing and sampling technique to determinepartition coefficients of hydrophobic chemicals in complexmatrixes. Environmental Science and Technology 39,3736e3742.

US EPA, 2008. Estimation Programs Interface Suite� forMicrosoft� Windows, v4.0. United States EnvironmentalProtection Agency, Washington, DC, USA.

van der Voet, J. (2008) Passive sampling of polar compounds:development of a performance reference system, MSc Thesis,Swiss Federal Institute of Aquatic Science and Technology(Eawag), Dubendorf.

Watkinson, A.J., Murby, E.J., Costanzo, S.D., 2007. Removal ofantibiotics in conventional and advanced wastewatertreatment: implications for environmental discharge andwastewater recycling. Water Research 41, 4164e4176.

Yamamoto, H., Liljestrand, H.M., Shimizu, Y., Morita, M., 2003.Effects of physical-chemical characteristics on the sorption ofselected endocrine disruptors by dissolved organic mattersurrogates. Environmental Science and Technology 37,2646e2657.

Ying, G.-G., Kookana, R.S., Kolpin, D.W., 2009. Occurrence andremoval of pharmaceutically active compounds in sewagetreatment plants with different technologies. Journal ofEnvironmental Monitoring 11, 1498e1505.

Yoon, Y., Ryu, J., Oh, J., Choi, B.-G., Snyder, S.A., 2010. Occurrenceof endocrine disrupting compounds, pharmaceuticals, andpersonal care products in the Han River (Seoul, South Korea).Science of the Total Environment 408, 636e643.