Detecting anti-estrogens and anti-androgens in surface...

Detecting anti-estrogens and anti-androgens in surface

waters impacted by municipal wastewater discharges

and agricultural runoff

A thesis submitted to the Committee of Graduate Studies

In Partial Fulfilment of the Requirements for the Degree of Master of Science in the

Faculty of Arts and Science

TRENT UNIVERSITY

Peterborough, Ontario, Canada

© Copyright by Shawna Corcoran 2016

Environmental and Life Sciences M. Sc. Graduate Program

January 2017

ii

ABSTRACT

Detecting anti-estrogens and anti-androgens in surface waters impacted by

municipal wastewater discharges and agricultural runoff

Shawna Corcoran

This study focused on detecting 22 target anti-estrogenic and anti-androgenic

compounds in surface waters influenced by both discharges of municipal wastewater and

agricultural runoff in Canada and Argentina. Polar organic chemical integrative samplers

(POCIS) were used to monitor the target compounds in surface waters. The removals of

the target compounds in a municipal wastewater treatment plant (WWTP) in Canada

were also evaluated. In both Canada and Argentina pesticides with potential anti-

estrogenic and anti-androgenic activities were detected in the surface waters. The highest

concentrations were found in Argentina (up to 1010 ng L-1

) in areas impacted by heavy

agricultural practices. Cyproterone acetate and bicalutamide were the only two anti-

cancer drugs detected only at the Canadian study site, the Speed River, ON. In the

Guelph WWTP, that discharges into the Speed River, these target compounds were not

all efficiently removed (>70%) during treatment. Overall, this study provides insight to

possible anti-estrogenic and anti-androgenic compounds that may be contributing to

endocrine disrupting activities in surface waters.

Keywords: Polar organic chemical integrative samplers, Pharmaceuticals, Personal care

products, Current used pesticides, Anti-estrogens, Anti-androgens, Wastewater, Surface

Water

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PREFACE

The work done in fulfillment of this Master’s thesis was completed through the

help of multiple contributors. Dr. Viviane Yargeau and her research group at McGill

University, Montreal, Quebec, and her PhD candidates Zeina Baalbaki and Paul

Westlund both contributed to the thesis. Zeina Baalbaki characterized the hydraulic

system of the Guelph WWTP, provided the load fractions and the flow data for the

influent and effluent for the days sampled. Paul Westlund contributed to the project by

determining the in vitro anti-estrogenic and anti-androgenic activity of POCIS extracts

from the Speed River. Dr. Mirta Menone at the National University of Mar del Plata,

Argentina and Dr. María Valeria Amè at the National University of Córdoba, Argentina

also contributed to this thesis. They provided water flow and water chemistry data for

sampling areas in Argentina, as well as laboratory space and resources for POCIS

extractions.

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ACKNOWLEDGEMENTS

First of all I would like to genuinely thank my supervisor, Dr. Chris Metcalfe for

his support, encouragement and guidance throughout the process of my Master’s thesis.

Without his help and advice this project would not have happened. In addition I would

like to thank all members of the Metcalfe Research Group for their support and help

throughout my thesis and research career at Trent University.

Secondly, I would like to thank the members of my thesis committee Dr. Céline

Guéguen and Dr. David Ellis for their helpful insight and advice throughout my thesis. I

would also like to thank Dr. Viviane Yargeau, Dr. Mirta Menone, Dr. María Valeria

Amè, and each of their research groups for providing help in the field, laboratory space,

and contributing their own time and work into making this project possible. Special

thanks to Dr. Tamanna Sultana, Brenda Seaborn, Dr. Naomi Stock and Mr. Michael

Doran for lending a hand when I needed help in the laboratory doing extractions or

during the analysis in the Trent Water Quality Centre. Also, for answering endless

questions throughout the thesis and never thinking any question was a dumb question.

I would like to acknowledge NSERC for the multiple sources of funding for

myself and also for funding the project. Without the funding and the help of everyone

involved this work would have not been able to be done. I will be forever grateful of the

opportunities provided to me over the course of this Master’s thesis and the relationships

I have developed throughout.

Finally, I would like to thank my friends and family for their encouraging words

and support throughout this degree.

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TABLE OF CONTENTS

ABSTRACT .................................................................................................................................... ii

PREFACE ...................................................................................................................................... iii

ACKNOWLEDGEMENTS ........................................................................................................... iv

TABLE OF CONTENTS ................................................................................................................ v

LIST OF FIGURES ..................................................................................................................... viii

LIST OF TABLES ......................................................................................................................... ix

LIST OF APPENDICES ................................................................................................................. x

LIST OF ABBREVIATIONS ........................................................................................................ xi

1 INTRODUCTION .................................................................................................................. 1

1.1 Overview .............................................................................................................. 1

1.2 Endocrine Disrupting Compounds ....................................................................... 3

1.2.1 Hormone antagonists .................................................................................... 4

1.2.2 Pharmaceuticals and personal care products ................................................. 5

1.2.3 Pesticides....................................................................................................... 9

1.3 Polar Organic Chemical Integrative Samplers ................................................... 12

1.4 Study Areas ........................................................................................................ 15

1.5 Study Objectives ................................................................................................ 17

2 DETECTION AND THE REMOVAL OF ENDOCRINE DISRUPTING

COMPOUNDS WITH ANTI-ESTROGENIC AND ANTI-ANDROGENIC ACTIVITY

IN A WASTEWATER TREATMENT PLANT .......................................................................... 20

2.1 Introduction ........................................................................................................ 20

2.2 Methods .............................................................................................................. 23

2.2.1 Chemicals and materials ............................................................................. 23

2.2.2 Study area and sampling ............................................................................. 24

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2.2.3 Method development for anti-cancer drugs ................................................ 26

2.2.4 Extraction and analysis ............................................................................... 30

2.2.5 Removals..................................................................................................... 31

2.3 Results and Discussion ....................................................................................... 33

2.3.1 Method optimization ................................................................................... 33

2.3.2 Levels of target compounds and removals.................................................. 34

2.4 Conclusion .......................................................................................................... 43

3 INVESTIGATION OF ENDOCRINE DISRUPTING COMPOUNDS WITH ANTI-

ESTROGENIC AND ANTI-ANDROGENIC ACTIVITY IN THE SPEED RIVER,

ONTARIO USING POLAR ORGANIC CHEMICAL INTEGRATIVE SAMPLERS ............... 44

3.1 Introduction ........................................................................................................ 44

3.2 Methods .............................................................................................................. 46


3.2.2 Study area and sampling ............................................................................. 47

3.2.3 POCIS and grab sample extraction ............................................................. 50

3.2.1 Determination of sampling rates for anti-cancer drug ................................ 52

3.2.2 Analysis....................................................................................................... 53

3.2.3 Statistical analysis ....................................................................................... 55


3.3.1 Anti-cancer drug uptake experiment ........................................................... 55

3.3.2 Target compounds ....................................................................................... 62

3.3.3 Potential for Endocrine Disruption ............................................................. 70

3.3.4 Limitations .................................................................................................. 71

3.4 Conclusion .......................................................................................................... 72

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4 DETECTION OF ANTI-ESTROGENIC AND ANTI-ANDROGENIC

COMPOUNDS IN ARGENTINIAN SURFACE WATERS USING POLAR ORGANIC

CHEMICAL INTEGRATIVE SAMPLERS ................................................................................ 74

4.1 Introduction ........................................................................................................ 74

4.2 Methods .............................................................................................................. 77


4.2.2 Study areas and POCIS deployments ......................................................... 78

4.2.3 POCIS extraction ........................................................................................ 80

4.2.4 Analysis....................................................................................................... 81

4.2.1 Statistical analysis ....................................................................................... 82


4.3.1 Estimated TWA concentrations .................................................................. 84

4.3.2 POCIS in surface waters ............................................................................. 87

4.3.3 Ecological risks ........................................................................................... 96

4.4 Conclusions ........................................................................................................ 99

5 CONCLUSIONS................................................................................................................. 100

5.1 GENERAL CONCLUSION AND OBSERVATIONS ................................... 100

5.2 RESEARCH CONTRIBUTIONS .................................................................... 103

5.3 FUTURE RESEARCH .................................................................................... 104

6 REFERENCES ................................................................................................................... 106

7 Appendices .......................................................................................................................... 125

viii

LIST OF FIGURES

Fig. 1.1: Three modes of action of EDCs. (A) EDCs compete with the natural hormone

for the receptor site. (B) Antagonistic activity – the EDC blocks the receptor site and (C)

agonistic activity – mimics the natural hormone (Modified from Rogers et al., 2013). ..... 4

Fig. 1.2. Chemical structures of selected PPCPs that are EDCs. ........................................ 9

Fig. 1.3. EDC chemical structures of target CUPs. .......................................................... 12

Fig. 1.4. Design of a pharmaceutical-POCIS. .................................................................. 14

Fig. 3.1: Map of sampling locations in the Speed River, Ontario. ................................... 48

Fig. 3.2: Plot of the decrease of target analytes a: bicalutamide, b: flutamide, c:

tamoxifen, d: 4 – hydroxy tamoxifen, e: cyproterone acetate, f: nilutamide and g: atrazine

in water by POCIS over the 8-day uptake experiment. .................................................... 58

Fig. 3.3: Estimated TWA concentrations (ng L-1

) for target compounds detected in the

POCIS deployed................................................................................................................ 63

Fig. 3.4: Concentrations of target compounds detected >LOQ in grab samples. ............. 63

Fig. 4.1: Sampling locations in the Brava Lake. ............................................................... 78

Fig. 4.2: Sampling locations in the Suquía River (Upstream, Downstream 1, and

Downstream 2) and in the Tercero River (Almafuerte, Puente los Proteros, and Villa

María). ............................................................................................................................... 80

Fig. 4.3: Mean estimated TWA concentrations (±S.D.) for CUP target compounds at the

Brava Lake estimated from POCIS deployment in the influent stream, El Peligro, and the

effluent stream, Tajamar. D1: First deployment; D2: Second deployment. ..................... 89

Fig. 4.4: Mean estimated TWA concentrations (±S.D.) for target compounds detected in

the three sampling locations in the Tercero River, Córdoba. ........................................... 92

ix

LIST OF TABLES

Table 2.1: List of target chemicals and the source of each compound. ............................ 25

Table 2.2: Summary of tandem mass spectrometry parameters used for multiple reaction

monitoring for target cancer drug analytes and internal standards. .................................. 28

Table.2.3: LC solvent gradient for the separation of analytes using ESI in positive ion

mode. ................................................................................................................................. 29

Table .2.4: LC solvent gradient for the separation of analytes using ESI in negative ion

mode. ................................................................................................................................. 30

Table 2.5: Summary of target compounds detected (>LOD) in the influent and effluent

during the sampling period. .............................................................................................. 36

Table 2.6: Estimated removals (%) of target compounds calculated using the fractionated

approach. ........................................................................................................................... 40

Table 3.1: List of target compounds and the source of contamination for each target

compound. ......................................................................................................................... 49

Table 3.2: Chemical structures and physio-chemical properties of anti-cancer target

compounds. ....................................................................................................................... 51

Table 3.3: Sampling rates and mass balances for target compounds and the control

compound atrazine. ........................................................................................................... 59

Table 4.1: List of pesticide and anti-cancer therapy target compounds and their usage. . 83

Table 4.2: Amount of target compound accumulated in POCIS sorbent (ng POCIS-1

) for

POCIS deployed in the Suquía River. ND (Not Detected): Amounts adsorbed onto

POCIS were <LOD; P (Present): Amounts adsorbed onto POCIS were <LOQ. ............. 94

x

LIST OF APPENDICES

Appendix 1: Summary of parameters used for multiple reaction monitoring for target

fungicide, herbicide and biocide analytes and their corresponding I.S. surrogates. ....... 125

Appendix 2: LC solvent gradient for the separation of fungicide, herbicide and biocide

analytes. .......................................................................................................................... 127

Appendix 3: Flow rates (L day-1

) for the three sampling days. ...................................... 127

Appendix 4: Load fractions for the WWTP. ................................................................... 127

Appendix 5: Extracted Ion Chromatograms (XICs) of cancer therapy drugs tamoxifen,

cyproterone acetate and 4-hydroxytamoxifen. ................................................................ 128

Appendix 6: Extracted Ion Chromatograms (XICs) of cancer therapy drugs flutamide,

nilutamide and bicalutamide. .......................................................................................... 128

Appendix 7: Summary of each sampling day influent and effluent concentrations (ng L-1

)

± S.D. of target compounds. ........................................................................................... 129

Appendix 8: Mean (± S.D.) sampling rates (Rs) in litres per day determined for the target

compounds in POCIS in static experiments at 20oC (n=3). Sampling rate data as reported

in Metcalfe et al. (in press). ............................................................................................ 131

Appendix 9: Summary of estimated TWA concentrations (ng L-1

) ± S.D. of PPCP and

CUP target in the Speed River, Ontario, Canada. ........................................................... 132

Appendix 10: Summary of target PPCP and CUPs concentrations (ng L-1

) ± S.D. found in

the grab samples in the Speed River, Ontario, Canada. .................................................. 134


) ± S.D. of target

compounds at Tercero River, Brava Lake and the amount accumulated in the sorbent (ng

POCIS-1

) ± S.D. of target compounds in the Suquía River.............................................136

xi

LIST OF ABBREVIATIONS

CEC: Contaminants of emerging concern

CUPs: Current use pesticides

DDT: Dichlorodiphenyltrichloroethane

EDC: Endocrine disrupting compounds

ESI: Electrospray ionization

HLB: Hydrophilic-lipophilic balance

HRT: Hydraulic retention time

I.S.: Internal standard

LC: Liquid chromatography

LC-MS/MS: Liquid chromatography tandem mass spectrometry

LMICs: Low to middle income countries

LOD: Limit of detection

LogKow: Octanol-Water Partition Coefficient

LOQ: Limit of quantification

MRM: Multiple reaction monitoring

PEC: Predicted environmental concentration

PES: Polyethersulfone

pKa: Acid dissociation constant

POCIS: Polar Organic Chemical Integrative Sampler

xii

PPCPs: Pharmaceuticals and personal care products

PRCs: Performance reference compounds

PSDs: Passive sampling devices

RTD: Residence time distribution

Rs: Sampling rate

S.D.: Standard deviation

S/N: Signal-to-noise ratio

SPM: Suspended particulate matter

TWA: Time weighted average

VTG: Vitellogenin

WWTP: Wastewater treatment plant

XIC: Extracted ion chromatogram

2,4-D: 2,4-Dichlorophenoxyacetic acid

1

1 INTRODUCTION

1.1 Overview

Pharmaceuticals, personal care products (PPCPs) and current use pesticides

(CUPs) have been detected in the aquatic environment at concentrations that are

potentially harmful to aquatic organisms (Hasenbein et al., 2015; Dalton et al., 2014;

Besse et al., 2012; Lissalde et al., 2011; Santos et al., 2010). Many of these compounds

are known as “contaminants of emerging concern” (CECs) because there is not sufficient

information at this time to set regulatory limits for protection of aquatic ecosystems,

although limits are under review for some compounds (Canadian Council of Ministers of

the Environment, 2015). Pharmaceuticals are of high concern among this class of

contaminants due to their ability to induce biological responses in aquatic biota at low

doses (Bhatia et al., 2014b; Deblonde et al., 2011). PPCPs released from wastewater

discharge can act as endocrine disrupting compounds (EDCs) that have the ability to

block, mimic or interfere with the binding of natural hormones to their specific receptors

in an organism (Bhatia et al., 2014b; Feng et al., 2016; Kavanagh et al., 2004; Tijani et

al., 2013). Also, several pesticides used in agricultural practices that are introduced into

the aquatic environment by agricultural runoff have been shown to be EDCs (Dalton et

al., 2014; Feng et al., 2016; Hatef et al., 2012; McKinlay et al., 2008; Mnif et al., 2011;

Orton et al., 2009). Several studies in Europe and North America have documented the

release of estrogenic chemicals into surface waters from wastewater discharges and

agricultural runoff (Allen et al., 1999; De Solla et al., 2002; Iwanowicz et al., 2016;

2

Jobling et al., 1998; Kavanagh et al., 2004; Liscio et al., 2009; Vajda et al., 2008).

Compounds with anti-estrogenic and anti-androgenic activities also released into the

aquatic environment have the potential to disrupt the endocrine system of aquatic

organisms (Bhatia et al., 2014; Jobling et al., 2009; Urbatzka et al., 2007).

There are analytical challenges for detecting and quantifying EDCs in surface

waters impacted by WWTP discharges and agricultural runoff because these compounds

are typically present at ultra-trace concentrations (i.e. 1 – 100 ng/L) and have different

physiochemical properties (Chang et al., 2009; Liscio et al., 2009). The Polar Organic

Chemical Integrative Sampler (POCIS) has been widely used for monitoring hydrophilic

pharmaceuticals, steroid hormones and pesticides that have an octanol-water partition

coefficient (log Kow) <4 (Arditsoglou and Voutsa, 2008; Belles et al., 2014; Dalton et

al., 2014; Li et al., 2010b; Liscio et al., 2014, 2009; Lissalde et al., 2014; MacLeod et al.,

2007; Sellin et al., 2009a, 2009b; Togola and Budzinski, 2007). The POCIS samplers

concentrate the trace contaminants to detectable levels (Li et al., 2010a). In addition,

POCIS measure the time weighted average (TWA) concentrations of target compounds in

water over several weeks of deployment, which is preferable to collecting “grab” samples

that represent contaminant concentrations at a single point in time (Bundschuh et al.,

2014). Therefore, passive sampling with POCIS is an efficient and cost-effective way to

quantify and identify EDCs, including anti-estrogenic and anti-androgenic compounds in

surface waters impacted by both WWTP discharges and agricultural runoff.

3

1.2 Endocrine Disrupting Compounds

Endocrine disrupting compounds (EDCs) are a heterogeneous group of

compounds that are naturally occurring hormones in organisms or synthetically produced

chemicals that have the ability to alter endocrine functions within an organism; often

through mimicking, enhancing or blocking the action of natural biological molecules,

such as estrogen, testosterone or thyroid hormones (Chang et al., 2009; Rogers et al.,

2013). The US Environmental Protection Agency (USEPA) defines an EDC as: “An

exogenous agent that interferes with the synthesis, secretion, transport, binding, action, or

elimination of natural hormones in the body that are responsible for the maintenance of

homeostasis, reproduction, development, and/or behavior.”(USEPA, 1997). EDCs

include a variety of compounds, such as pharmaceuticals, personal care products,

pesticides, industrial chemicals and heavy metals (Liu et al., 2009; Sellin et al., 2009b;

Rogers et al., 2013). Some EDCs can act as agonists or antagonists of the estrogen and

androgen receptors in organisms (Cevasco et al., 2008). Agonists (e.g. estrogens or

androgens) bind to the receptor and activate expression of the target genes, while

antagonists (e.g. anti-estrogens or anti-androgens) bind to the receptor and block the

natural hormone, thereby repressing expression of the target genes (Urbatzka et al., 2007)

(Fig. 1.1)

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Fig. 1.1: Three modes of action of EDCs. (A) EDCs compete with the natural hormone

for the receptor site. (B) Antagonistic activity – the EDC blocks the receptor site and (C)

agonistic activity – mimics the natural hormone (Modified from Rogers et al., 2013).

1.2.1 Hormone antagonists

Much of the research on the effects of EDCs released into the environment has

focused on the effects of hormone agonists, and in particular estrogenic compounds. For

instance, a whole lake addition study with the synthetic estrogen, 17α-ethinylestradiol

(EE2) (structure shown in Fig. 1.2) showed that exposure to this compound induced

gonadal intersex in fish and led to reproductive failure in a resident population of fathead

minnows, Pimephales promelus (Kidd et al., 2007). Estrogenic chemicals can induce

5

production of the egg yolk protein, vitellogenin (VTG) in male or juvenile fish (Jobling et

al., 1996; Van den Belt et al., 2002; Versonnen and Janssen, 2004). However, agonists

and antagonists can have the similar effects on reproductive development in organisms,

even though they have different modes of action. For instance, exposures of fish to both

estrogens and anti-androgens can skew sex ratios towards females (Kang et al., 2006;

Larsen et al., 2008; Nimrod and Benson, 1998; Parrott and Blunt, 2005; Seki et al., 2005),

delay the maturation of ovaries and reduce egg production (Kiparissis et al., 2003; Panter

et al., 2012; Van den Belt et al., 2002) and reduce or inhibit spermatogenesis (Jensen et

al., 2004; Jobling et al., 1996; Kiparissis et al., 2003). Exposure of fish to both androgens

and anti-estrogens can increase testis size and decrease ovary size (Örn et al., 2006;

Pawlowski et al., 2004; Seki et al., 2005), accelerate spermatogenesis (Ankley et al.,

2003) , reduce or inhibit ovulation and production of VTG in females (Ankley et al.,

2003) and skew sex ratio towards males (Hahlbeck et al., 2004; Örn et al., 2006, 2003).

In studies conducted in the Grand River, ON, biological responses in fish, such as

gonadal intersex that have been attributed to exposure to estrogenic EDCs discharged in

municipal wastewater (Tetreault et al., 2011) could have been induced by exposure to

anti-androgenic compounds (Arlos et al., 2015).

1.2.2 Pharmaceuticals and personal care products

Pharmaceutical and personal care products (PPCPs) include non-prescription and

prescription pharmaceuticals for human and veterinary use, and ingredients in products

that we use every day for personal care or hygiene (Daughton and Ternes, 1999).

Examples of personal care products includes fragrances, sun screens, mouth wash and

6

toothpaste, shampoos and cosmetics (Lishman et al., 2006). PPCPs are introduced into

the aquatic environment by different sources, but one of the main sources is through

discharges of WWTP effluents into surface waters (Luo et al., 2014) or by land

application of biosolids and subsequent leaching or run-off (Edwards et al., 2009;

Sabourin et al., 2009). Studies have shown that not all of the PPCPs are fully removed

in WWTPs and the removal efficiencies have ranged from <0 – 100%: Therefore the

remaining portion of the PPCPs after treatment can be discharged into the aquatic

environment (Luo et al., 2014; Verlicchi et al., 2012). Investigations of the biological

impacts of PPCPs in surface waters have focused on estrogenic effects, but recently it has

been observed that the endocrine effects may be due to exposure to a combination of anti-

androgens and estrogens in surface waters (Arlos et al., 2015; Bhatia et al., 2014b; Hill et

al., 2010; Jobling et al., 2009; Liscio et al., 2014).

Anti-estrogenic and anti-androgenic pharmaceuticals are used as endocrine

therapy drugs for the treatment of some cancers, such as estrogen responsive breast

cancers and androgen responsive prostate cancers (Besse et al., 2012). The detection of

anticancer drugs in hospital waste effluents, WWTP effluents and surface waters has

become a relatively new area of research due to the possibility that the drug or its active

metabolites excreted by cancer patients could cause adverse effects in aquatic organisms

(Booker et al., 2014; Ferrando-Climent et al., 2013). An example of an anti-estrogen

endocrine therapy drug that has been found in WWTP effluents and surface waters

impacted by discharges of municipal wastewaters is tamoxifen (Coetsier et al., 2009;

Ferrando-Climent et al., 2014; Liu et al., 2010; Roberts and Thomas, 2006). Tamoxifen

(structure shown in Fig. 1.2) is an anti-estrogen used for the treatment of estrogen

7

responsive breast cancer in women which is not readily biodegradable and therefore it is

not efficiently removed by WWTPs (Besse et al., 2012). Tamoxifen has been detected in

WWTP effluents at concentrations ranging from 0.2 – 102 ng L-1

(Ashton et al., 2004;

Coetsier et al., 2009; Liu et al., 2010) and has been detected in surface waters at

concentrations ranging from 25 - 200 ng L-1

(Coetsier et al., 2009; Roberts and Thomas,

2006). Tamoxifen has been reported to produce anti-estrogenic effects on fish, such as

reduced reproductive success and alterations in male to female sex ratios (Chikae et al.,

2004; Liu et al., 2010; Singh, 2013; Sun et al., 2007; van der Ven et al., 2007).

Anti-androgens used for the treatment of prostate cancer have also been found to

cause adverse effects on aquatic organisms. The steroidal anti-androgen, cyproterone

acetate (structure shown in Fig.1.2) has been reported to alter testicular development and

inhibit both oogenesis and spermogenesis in fish (Kiparissis et al., 2003). Cyproterone

acetate has been detected in Swiss rivers and WWTP effluents at concentrations below 27

ng L-1

(Ammann et al., 2014). The non-steroidal antiandrogen, flutamide that is also used

for the treatment of prostate cancer in men has been found to induce endocrine effects

and reduce reproductive success in aquatic organisms (Bhatia et al., 2014b; Panter et al.,

2012). Various studies with fish and mammalian test species have shown that flutamide

disrupts the endocrine system and reproductive success (Bayley et al., 2002; Bhatia et al.,

2014b; Chikae et al., 2004; Jensen et al., 2004; Jolly et al., 2009; Kinnberg and Toft,

2003; Rajakumar et al., 2012; Sebire et al., 2008; Vo et al., 2009). Even though the anti-

androgenic effects of flutamide are well known, there have been no studies on levels of

flutamide in WWTP effluents. Similar to cyproterone acetate and flutamide, the prostate

cancer drug bicalutamide is a known anti-androgen and has been found in WWTP

8

effluent in concentrations ranging from 8 – 1032 ng L-1

(Azuma et al., 2015; Singer et al.,

2016).

Triclosan (structure shown in Fig. 1.2) is a known anti-androgen that is added as

an antibacterial agent to many personal care products such as toothpaste, mouthwash, soft

soaps, and other cosmetic products (Arlos et al., 2015; Bedoux et al., 2012; Grover et al.,

2011). Triclosan has been widely detected in in WWTP effluents at concentrations

ranging from 1 – 919 ng L-1

(Arlos et al., 2015; Gómez et al., 2012; Hoque et al., 2014;

Lishman et al., 2006; Morrall et al., 2004; Reiss et al., 2002; Sabaliunas et al., 2003), and

has also been widely detected in surface waters at concentrations ranging from 0.29 –

102 ng L-1

(Arlos et al., 2015; Gómez et al., 2012; Hoque et al., 2014; Kasprzyk-Hordern

et al., 2009; Zhao et al., 2010). Triclosan is readily removed by WWTPs (>90%) as it

partitions into the sewage sludge and has been detected in sewage sludge in

concentrations of 1430 and 1581 ngg-1

in summer and winter seasons (Yu et al., 2013).

However, the proportion of triclosan that is discharged in wastewater from WWTPs has

been reported as a major source of anti-androgenic activity present in the bile of fish

exposed to WWTP effluents (Rostkowski et al., 2011). Triclosan has shown anti-

androgenic activity in a numerous in vitro androgen receptor screening assays and also in

in vivo studies with algae, fish, and mammals (Bedoux et al., 2012; Yueh and Tukey,

2016).

9

Tamoxifen Cyproterone Acetate Bicalutamide

Triclosan 17α-ethinylestradiol

Fig. 1.2. Chemical structures of selected PPCPs that are EDCs.

1.2.3 Pesticides

Pesticides include fungicides, herbicides, insecticides and biocides. Current Use

Pesticides (CUPs) that have replaced persistent “legacy” pesticides, such as

organochlorine insecticides (e.g. DDT) and are considered less environmentally

persistent and less likely to bioaccumulate in organisms (Orton et al., 2009; Smalling et

al., 2013). CUPs are used in agriculture and in turf farms, as well as for pest control in

recreational areas, such as parks, playing fields, golf courses and domestic lawns

(McKinlay et al., 2008). Pesticides are also used for medical applications, such as anti-

fungal agents (Kjærstad et al., 2010). These pesticides are introduced into the aquatic

environment through point and non-point sources. Point source contamination results

from runoff from accidental spills or improper use and disposal of pesticides. Non-point

10

source contamination results from spray drift, tile drain flow, atmospheric deposition,

surface run-off, or leaching into groundwater and surface water (Bereswill et al., 2013;

Bundschuh et al., 2014; Dalton et al., 2014; Holvoet et al., 2007; Sellin et al., 2009b).

There are mitigation strategies to reduce pesticide inputs into surface water and

groundwater, such as the use of vegetated buffer strips that been reported to reduce

pesticide transport by up to 60% (Reichenberger et al., 2007; Zhang et al., 2010). The

pesticides that do reach surface waters have the potential to adversely affect aquatic

organisms and some pesticides have been shown to be EDCs (Kjærstad et al., 2010;

McKinlay et al., 2008; Sellin et al., 2011).

The herbicide atrazine (structure shown in Fig. 1.3), primarily used for corn crops,

is the most commonly detected pesticide in surface waters in concentrations typically

ranging from low ng L-1

to low µg L-1

and is a known EDC (Chang et al., 2009; Hayes et

al., 2011; Lazorko-Connon and Achari, 2009). Atrazine has also been detected in WWTP

influents and effluents and has been shown to have a poor removal efficiency of <0 –

25% (Luo et al., 2014). Atrazine has been shown to demasculinize and feminize the

gonads of male vertebrates (Hayes et al., 2011). Studies have shown that the observed

effects are due to a decrease in androgens and there are multiple modes of actions

possible to explain the effect of atrazine (Hayes et al., 2011). The most plausible

mechanism of action for atrazine to explain the demasculinization and feminization in

male vertebrates is that atrazine inhibits the enzyme 5α-reductase, therefore decreasing

the conversion of testosterone to 5α-dihydrotestosterone, which leaves more testosterone

to convert to estrogen via aromatase (Kniewald et al., 1995; Sanderson, 2000). The

increase in estrogen synthesis can explain the feminization that occurs in male vertebrates

11

(Hayes et al., 2011). It is not likely that the increase in estrogen is due to atrazine acting

as an estrogen agonist because it has been shown that atrazine does not bind to the

estrogen receptor (Roberge et al., 2004; Sanderson, 2000; Wang et al., 2014). Atrazine

has also been shown to have anti-androgenic effects in in vitro tests (Orton et al., 2009;

Wang et al., 2014).

The fungicide vinclozolin (structure shown in Fig. 1.3) used to control fungal

diseases in fruits, grapes and vegetables is a well-known anti-androgen that has been

shown to have endocrine disruption effects in mammals and some fish species (Baatrup

and Junge, 2001; Bayley et al., 2003, 2002; Elzeinova et al., 2008; Eustache et al., 2009;

Golshan et al., 2014; Hatef et al., 2012; Kiparissis et al., 2003) A small number of studies

have reported detection of vinclozolin in surface waters at concentrations of 0.1 – 2.4

µgL-1

(El-Shahat et al., 2003; Readman et al., 1997). The class of fungicides known as

conazoles or azoles that are used as agricultural fungicides, biocides or as anti-fungal

pharmaceuticals have been shown to have anti-estrogenic and/or anti-androgenic activity

(Kjærstad et al., 2010; Orton et al., 2011). An example is the agricultural fungicide

propiconazole (structure shown in Fig. 1.3), which was shown to have weak anti-

androgenic activity when tested in vitro (Aït-Aïssa et al., 2010; Kjærstad et al., 2010;

Kjeldsen et al., 2013; Liscio et al., 2014). Propiconazole has also been detected in

WWTP effluents and surface waters at concentrations between 1 – 100 ngL-1

(Kahle et

al., 2008; Van De Steene et al., 2010). The pharmaceutical antifungal agent ketoconazole

(structure shown in Fig. 1.3) has been shown to have an anti-estrogenic and anti-

androgenic effects and has been detected at low ng L-1

concentrations in WWTP influents

(Falconer et al., 2006; Van De Steene et al., 2010). Ketoconazole and some other anti-

12

fungal pharmaceuticals are removed efficiently during wastewater treatment, but

fluconazole, propiconazole, and tebuconzaole are not completely removed and have been

detected in treated wastewater and in the receiving aquatic environment (Kahle et al.,

2008; Van De Steene et al., 2010).

Vinclozolin Atrazine

Ketoconazole Propiconazole

Fig. 1.3. EDC chemical structures of target CUPs.

1.3 Polar Organic Chemical Integrative Samplers

Because PPCPs and CUPs are typically present in the aquatic environment at

trace concentrations (<100 ngL-1

) there are analytical challenges to detecting these

compounds in surface waters. Traditional sampling methods include grab and composite

13

samples, but these methods often require enrichment of large amounts of water to detect

trace levels and they only offer a single “snap-shot” in time of what is present in the

water (Bundschuh et al., 2014). Passive sampling has become a common method for

monitoring emerging contaminants in water because the target analytes are concentrated

over time from the aqueous media onto a sorbent (Seethapathy et al., 2008).

The polar organic chemical integrative sampler (POCIS) is a widely used passive

sampler for monitoring for hydrophilic organic pollutants, such as PPCPs and CUPs in

water and wastewater (Harman et al., 2012). POCIS were first developed by Alvarez et

al., (2004) as an alternative sampling method to the traditional sampling technique of

grab samples. POCIS samplers measure the time-weighted average (TWA)

concentrations of contaminants over several weeks of deployment and concentrate the

trace contaminants to detectable levels (Li et al., 2011). POCIS have been previously

used for monitoring pharmaceuticals, steroid hormones and pesticides that have a log

Kow<4 in waters impacted from WWTP effluents or agricultural sources (Arditsoglou

and Voutsa, 2008; Belles et al., 2014; Dalton et al., 2014; Li et al., 2010b; Liscio et al.,

2014, 2009; Lissalde et al., 2014; MacLeod et al., 2007; Mazzella et al., 2010; Sellin et

al., 2009b, 2009a; Togola and Budzinski, 2007; Vallejo et al., 2013).

POCIS consist of a receiving phase (sorbent) placed between two microporous

polyethersulfone (PES) membranes that are compressed together with two stainless steel

rings (design shown in Fig. 1.4). There are two different configurations of POCIS (i.e.

pharmaceutical and pesticide) that differ in the sorbent used (Harman et al., 2012; Liscio

et al., 2014). The pharmaceutical-POCIS contains Oasis hydrophilic-lipophilic balance

(HLB) sorbent and the pesticide-POCIS contains a triphasic sorbent admixture (Li et al.,

14

2011; Liscio et al., 2014). However, the pharmaceutical-POCIS has been used more often

for monitoring hydrophilic pesticides from surface waters (Dalton et al., 2014; Lissalde et

al., 2011; Mazzella et al., 2007). It has also been shown that the pharmaceutical-POCIS

accumulates more anti-androgen compounds than the pesticide-POCIS configuration, as

extracts from pharmaceutical-POCIS revealed higher anti-androgenic activity when using

an in vitro androgen receptor antagonist screen (YAS) assay (Liscio et al., 2014). For the

determination of the estimated TWA concentrations for EDCs the sampling rate (Rs) in

litres per day must be determined theoretically or experimentally for the particular EDCs

of interest (Alvarez et al., 2004).

Fig. 1.4. Design of a pharmaceutical-POCIS.

The sampling rates for POCIS and other passive samplers depend on the

physiochemical properties of the chemicals and on the environmental conditions in the

waters being sampled. The effects of the environmental conditions, such as temperature,

water flow, pH and dissolved organic matter and biofouling on the sampling rates are

described in detail in the current review by Harman et al., (2012). If the uptake rate is

altered due to different environmental conditions than the conditions used to determine

15

the sampling rate experimentally, then the estimated TWA concentrations will not be

accurately estimated. A method to correct the differences in the laboratory sampling

rates to the environmental sampling rates is the use of performance reference compounds,

PRCs (Belles et al., 2014; Lissalde et al., 2014, 2011; Mazzella et al., 2010; Vallejo et al.,

2013). PRCs are commonly deuterated compounds that have a relatively high fugacity to

the receiving phase of the POCIS and are pre-loaded onto the sorbent before exposure.

Therefore, the rate of dissipation of the PRCs can be used to correct the in situ sampling

rates of the target contaminants. PRC corrections of laboratory sampling rates have been

shown in various studies to improve the quantification of ECDs in water (Belles et al.,

2014; Lissalde et al., 2014; Mazzella et al., 2010; Vallejo et al., 2013).

1.4 Study Areas

As described previously, there have been a few studies on the quantification and

identification of anti-estrogens and anti-androgens in surfaces waters in Europe.

However, with the exception of a recent study by Arlos et al., (2015) on the presence of

selected anti-androgens in the Grand River, ON, there have been no studies in Canada

focusing on anti-estrogenic and anti-androgenic substances in surface waters. In Canada,

the Grand River watershed has been studied because it is heavily impacted by both

wastewater discharges from 30 municipal WWTPs and agricultural runoff (Arlos et al.,

2015; Diamond et al., 2016). In vitro studies conducted in collaboration with colleagues

at McGill University have shown that there are anti-estrogenic and anti-androgenic

substances present in extracts of POCIS that were deployed in the Speed River, which is

a part of the Grand River watershed (Paul Westlund, unpublished data). The Speed River

16

is impacted by agricultural activities in the upper part of the watershed and by discharges

from the Guelph WWTP. Therefore, we selected the Speed River as a study site to

explore whether CUPs and PPCPs with known anti-estrogenic and anti-androgenic

activity are present in these surface waters.

In low to middle income countries (LMICs), pesticides are widely used for

agriculture, but there are few data on the distribution of these compounds in aquatic

environments. There are even fewer data available on the levels of PPCPs in municipal

wastewater in LMICs. However, in Argentina, studies on the presence and fate of

pharmaceuticals and pesticides in surface waters have recently been initiated (Bonansea

et al., 2013; Valdés et al., 2014a). Argentina is similar to Canada because it also has

federal and provincial environmental laws that regulate the water quality for the whole

country and for each individual province. However, one of the main differences between

the countries is the level of enforcement of the environmental laws and regulations.

The introduction of environmental regulations in Argentina has increased the

responsibilities of the provinces, but there was no or not enough funding provided to

implement or enforce the needed changes to meet the regulations, especially with regards

to sewage treatment (Sánchez-Triana and Enriquez, 2007). Due to the lack of

investments from the government there are decreased resources for operation and

maintenance, and the WWTP capacity was regularly exceeded, therefore leading to

spillage and the release of non-treated wastewater that may contain CECs into the

receiving waters (Sánchez-Triana and Enriquez, 2007). Also in regards to regulations of

pesticides in Argentina, there are few that incorporate CUPs and the regulations primarily

focus on the more persistent “legacy” pesticides. There have been few investigations of

17

these CECs in Argentina, such as the Suquía River in the province of Córdoba, and there

is potential for a variety of contaminants to be released into surface waters from

agricultural sources and from WWTPs. Previous work showed that in the Suquía River

basin, selected pharmaceuticals were present at detectable concentrations up to 70

kilometers downstream of a WWTP and various pesticides, including atrazine (433.9

ngL-1

), were also detected (Bonansea et al., 2013; Valdés et al., 2014a). Overall, there is a

need for more research investigating CECs, including anti-estrogenic and anti-androgenic

compounds to determine the risk of them to the aquatic environment and human health.

More research would help push for more regulations regarding CECs, as well as more

funding to enforce the regulations and more education for the people impacted by the

regulations.

1.5 Study Objectives

The objective of this research was to determine whether chemicals with anti-

estrogenic and anti-androgenic activity are present and at what concentrations in surface

waters impacted by discharges of municipal wastewater treatment plants and agricultural

runoff. The project focused on watersheds in Canada and Argentina; specifically, the

Guelph WWTP and the Speed River in Ontario, Canada and in the Suquía River and

Tercero River, in the province of Córdoba and in the Brava Lake in the province of

Buenos Aires in Argentina.

This thesis is written in manuscript style and is divided into three main chapters,

including chapters describing: i) research conducted at the WWTP for the municipality of

18

Guelph, ON, ii) research conducted in the Speed River, ON downstream of the Guelph

WWTP, and, iii) and research conducted in watersheds in Argentina.

The objectives of Chapter 2 entitled, Detection and the Removal of Endocrine Disrupting

Compounds with Anti-estrogenic and Anti-androgenic Activity in a Wastewater

Treatment Plant are to:

1. Develop analytical methods for the detection and analysis of known anti-

estrogenic and anti-androgenic pharmaceuticals that are used for cancer therapy.

2. Investigate the concentrations of known anti-estrogenic and anti-androgenic

PPCPs and CUPs in the influent and effluent of the Guelph WWTP and determine their

removals during wastewater treatment.

The hypothesis tested in this study is:

H0: Anti-estrogenic and anti-androgenic PPCPs and CUPs released into municipal

wastewater are removed effectively (i.e. > 70%) by treatment in a conventional activated

sludge wastewater treatment plant (i.e. Guelph WWTP).

The objective of Chapter 3 entitled, Investigation of Endocrine Disrupting Compounds

with Anti-estrogenic and Anti-androgenic Activity in the Speed River, Ontario using

Polar Organic Chemical Integrative Samplers is to:

1. Investigate the concentrations of anti-estrogenic and anti-androgenic PPCPs

and CUPs in the Speed River that is impacted by municipal wastewater discharges and

agricultural runoff.

19


H0: Anti-estrogenic and anti-androgenic target PPCPs and CUPs are present in the

Speed River at low concentrations (ng L-1

) that will not individually induce significant

biological effects.

The objective of Chapter 4, entitled, Detection of Anti-estrogenic and Anti-androgenic

Compounds in Argentinian Surface Waters Using Polar Organic Chemical Integrative

Samplers is to:

1. Investigate the concentrations of known anti-estrogenic and anti-androgenic

PPCPs and CUPs in the Suquía River and Tercero River, in the province of Córdoba and

in the Brava Lake in the province of Bueno Aires in Argentina.


H0: Anti-estrogenic and anti-androgenic target PPCPs and CUPs are present in

low concentrations (ng L-1

) in the watersheds impacted by discharges of municipal

wastewater and agricultural runoff.

The results from this research project will contribute to the understanding of

whether anti-estrogens and anti-androgens are a significant threat to aquatic organisms in

watersheds impacted by wastewater discharges and agricultural runoff in Canada and in

Argentina.

20

2 DETECTION AND THE REMOVAL OF ENDOCRINE DISRUPTING

COMPOUNDS WITH ANTI-ESTROGENIC AND ANTI-

ANDROGENIC ACTIVITY IN A WASTEWATER TREATMENT

PLANT

2.1 Introduction

Contaminants of emerging concern (CEC) are released with WWTP effluents into

surface waters, where they may cause biological effects in aquatic organisms (Deblonde

et al., 2011; Luo et al., 2014). CECs include several different classes of compounds, such

as pharmaceuticals and personal care products (PPCPs), current use pesticides (CUPs)

and steroid hormones ( Luo et al., 2014; Agüera et al., 2013). Some CECs have been

shown to be endocrine disrupting compounds (EDCs), but the majority of research on

EDCs has focused on the occurrence, fate and effects of compounds with estrogenic

activity (Iwanowicz et al., 2016; Liu et al., 2009). However, WWTP effluents also have

anti-androgenic activity, as well as estrogenicity (Jobling et al., 2009). Therefore, there is

potential for endocrine disruption in organisms impacted by WWTP discharges due to

exposure to a combination of estrogenic and anti-androgenic CECs (Arlos et al., 2015;

Liscio et al., 2014; Bhatia et al., 2014b; Hill et al., 2010; Jobling et al., 2009;). Recently,

there has been a change in focus from research on estrogenic activity to anti-androgenic

and anti-estrogenic activity in WWTP effluents and in surface waters (Sumpter and

Jobling, 2013). However, there have been only a few studies that have looked into

21

identifying the contaminants in effluents and surface waters with the potential to induce

anti-estrogenic and anti-androgenic effects.

Some PPCPs and CUPs that have been detected in wastewater are known to have

anti-estrogenic or anti-androgenic activity. Known anti-estrogens and anti-androgens

detected in domestic wastewater include drugs used to treat estrogen responsive cancers

(e.g. tamoxifen) or androgen responsive cancers (e.g. bicalutamide), personal care

products (e.g. triclosan) and pharmaceuticals (e.g. ketoconazole) used to treat fungal

infections (Arlos et al., 2015; Besse et al., 2012; Kjærstad et al., 2010). Also there are

known anti-estrogenic and anti-androgenic CUPs, such as tebuconazole and myclobutanil

(McKinlay et al., 2008). All of the anti-estrogens and anti-androgens have been found in

concentrations ranging from low ng L-1

to higher concentrations of µg L-1

for the anti-

androgen triclosan. However, there is relatively little information on how efficiently

WWTPs remove these classes of compounds during the treatment process. Removal

efficiencies for CECs in WWTPs that use conventional treatment processes vary widely,

from 12.5 – 100 % (Luo et al., 2014). Since the removal rate will determine how much of

a CEC is introduced into receiving surface waters and the potential risk to aquatic

organisms, it is critical to determine the rates of removal of anti-estrogenic and anti-

androgenic compounds during wastewater treatment in order to assess ecological risks.

However, determining removals of CECs in WWTPs is not a simple task, as the

choice of sampling method is critical for producing accurate estimates (Ort et al., 2010).

The method typically used for estimating the removal efficiencies of CECs, which is to

collect samples of untreated wastewater (influent) and treated wastewater (effluent) on

the same day has been questioned due to sampling bias because it is assumed that there is

22

quantitative coverage of the influent load present in the effluent; however it has been

shown that there is less than half of the initial influent load present in the effluent of the

same day (Majewsky et al., 2011). Therefore this method is not accurately presenting the

removal efficiencies of a WWTP and this method often generates “negative” elimination

data as a result of higher concentrations being detected in the effluent than concentrations

detected in the influent. A more accurate approach is to determine the influent mass load

for a certain day and the effluent mass load of a later day that has been time shifted to

account for the hydraulic retention time (HRT) of wastewater within the WWTP.

Majewsky et al. (2011) developed a method for calculating removal efficiency by

comparing the mass loads of the effluent (g day-1

) with reference mass loads of the

influent (g day-1

) that take into account the residence time distribution (RTD) of

wastewater in the WWTP; thus accounting for mixing regime and plant configurations.

This method is referred to as the “fractionated approach” and this method requires

sampling of wastewater over several days, development of a hydraulic model of the

WWTP and a tracer (e.g. conductivity) to determine the RTD (Majewsky et al., 2011).

This method has resulted in excellent estimates of removals of CECs in WWTPs,

without negative removal data (Baalbaki et al., 2016a, 2016b; Majewsky et al., 2013).

The removal of anti-estrogenic and anti-androgenic CECs during conventional

wastewater treatment has not been fully investigated. The present study is focused on

determining the removals of known and potential anti-estrogenic and anti-androgenic

CECs in a WWTP with conventional activated sludge treated, plus nitrification and sand

filtration (i.e. tertiary treatment). The fractionated approach was used to determine the

removal efficiencies of the target CECs accounting for the hydrodynamics of the WWTP

23

located in Ontario, Canada. Using the fractionated approach, 24-h composite samples

were collected every day over a 3-day period in the influent and the effluent of the

WWTP. Estimates of removals were calculated based on a hydraulic model of the

WWTP that was developed to determine the RTD (Baalbaki et al., 2016b). A new

analytical method was developed to determine the concentrations of anti-androgenic and

anti-estrogenic cancer drugs using solid phase extraction (SPE) and liquid

chromatography with tandem mass spectrometry (LC-MS/MS). Other PPCPs and CUPs

in wastewater were analyzed using previously developed methods (Diamond et al., 2016).

2.2 Methods

2.2.1 Chemicals and materials

Analytical standards for all target compounds and stable isotope surrogates were

purchased from Toronto Research Chemicals (Toronto, ON, Canada), Sigma Aldrich

Canada (Oakville, ON, Canada) or CDN Isotopes (Pointe-Claire, QC, Canada). Stock

solutions and working standards were made up in HPLC grade methanol and stored at

4°C or -20°C. Ammonium acetate was also purchased from Sigma Aldrich Canada

(Oakville, ON, Canada). HPLC grade acetonitrile, hexane, acetone, acetic acid, sulfuric

acid (96%) and formic acid (88%) were obtained from Fisher Scientific (Ottawa, ON,

Canada). Oasis HLB cartridges were purchased from Waters (Milford, MA, USA) and

Strata-X X cartridges were purchased from Phenomenex Inc. (Torrance, CA, USA).

24

2.2.2 Study area and sampling

The removals of the target anti-estrogens and anti-androgens were determined in a

WWTP located in southern Ontario, Canada. The WWTP serves a population of

approximately 134,894 and has a rated capacity of 64,000 m3 d

-1 (Arlos et al., 2015). The

WWTP uses conventional activated sludge treatment and extended biological (nitrifying)

treatment. Primary treatment includes bar screens (n=4), grit removal units (n=2) and

primary clarifiers (n=4). Secondary treatment occurs in four parallel treatment trains that

include aeration basins with retention times of 4-6 hours, followed by treatment in final

clarifiers. After passage through the final clarifiers, the treatment trains are combined for

tertiary treatment, including nitrification in rotating biological contactors (n=4) and

filtration in sand filters (n=4). The product is then combined and disinfected with

chlorine, followed by dechlorination of the effluent prior to discharge into the Speed

River; a small river that is a tributary within the Grand River watershed in southern

Ontario (Arlos et al., 2015).

Over a three day period from June 17 – June 19, 2015, influent and effluent

samples were collected daily from the WWTP. The influent samples were collected prior

to the primary clarifier and the effluent samples were collected after dechlorination.

Automated 24-hour composite samplers were used to collect the water samples and 1 L

sub-samples from the composite samples were collected in solvent washed polyethylene

bottles each day. The samples were placed in a refrigerated location over the sampling

period and then were returned to the lab, where they were frozen and stored at – 20 ̊C

until extracted. The target compounds chosen for this study and the sources of these

compounds are listed in Table 2.1.

25

Table 2.1: List of target chemicals and the source of each compound.

Chemical Class Target Compound Source

Fungicides

Propiconazole Agriculture

Tebuconazole Agriculture

Ketoconazole Personal Care Product

Fluconazole Pharmaceutical

Climbazole Personal Care Product

Carbendazim Agriculture

Iprodione Agriculture; Lawn/turf

Triclosan Personal Care Product

Azoxystrobin Agriculture

Herbicides/Biocides

Atrazine Agriculture

Terbutryn Antifouling Additive

Dicamba Agriculture; Lawn/turf

2,4 – D Agriculture; Lawn/turf

Mecoprop Agriculture; Lawn/turf

Irgarol 1051 Antifouling Additive

Anti-cancer Drugs

Tamoxifen Breast Cancer Therapy

Bicalutamide Prostate Cancer Therapy

Flutamide Prostate Cancer Therapy

Nilutamide Prostate Cancer Therapy

Cyproterone acetate Prostate Cancer Therapy

26

2.2.3 Method development for anti-cancer drugs

There is currently no method reported in the literature to analyze the complete

array of target anti-cancer drugs selected for this study (Table 2.1). An optimal SPE

method was developed, based on previously reported extraction methods for several of

the target analytes (Ammann et al., 2014; Bhatia et al., 2014a; Grabic et al., 2012; Grover

et al., 2011; Liu et al., 2010; Roberts and Thomas, 2006). Two trial SPE methods were

tested using a series of extractions at pH 3.0 and 6.5 performed using Oasis HLB

polymeric reversed-phase sorbent cartridges and the Strata-XX polymeric reversed-phase

sorbent cartridges, both of which are recommended for extraction of neutral, acidic or

basic compounds.

Amber glass bottles were spiked with 50 µL of a 10 mg L-1

stock mixture

containing the anti-cancer drug analytes (tamoxifen, bicalutamide, cyproterone acetate, 4-

hydroxytamoxifen, nilutamide and flutamide) dissolved in methanol, and the methanol

was allowed to evaporate. Once the methanol had evaporated, 150 mL of Milli-Q water

was added to each of the bottles and the pH of the samples was adjusted to either pH 3 or

6.5 using dilute sulfuric acid. Each sample was spiked with 50 µL of a 10 mg L-1

internal

standard mixture in methanol containing flutamide-d7, tamoxifen – d5 and bicalutamide-

d4.

The spiked water samples were extracted using two different SPE cartridges and

elution solvents. Oasis HLB cartridges were pre-conditioned with 6 mL of acetone, 6 mL

of methanol, and 6 mL of Milli-Q water (either pH 3.0 or 6.5 depending on the adjusted

pH of the water samples). Samples were loaded onto the SPE sorbent and then the

sorbent was washed with 2 mL of Milli-Q water (either pH 3.0 or 6.5). The HLB sorbent

27

then was dried under vacuum for 10 minutes prior to elution. The cartridges were eluted

with 3 x 3 mL 60:40 methanol:acetone. Strata-X X cartridges were pre-conditioned with

6 mL 0.1 % ammonium hydroxide in methanol, 6 mL of methanol, 6 mL Milli – Q water

(either pH 3.0 or 6.5). Samples were loaded onto the SPE sorbent and then the sorbent

was washed with 2 mL of Milli-Q water (either pH 3.0 or 6.5). The sorbent then was

dried under vacuum for 10 minutes prior to elution. The cartridges were eluted with 6 mL

0.1 % ammonium hydroxide in methanol and 6 mL of 50:50 methanol:ethyl acetate.

All extracts were eluted into 15 mL conical centrifuge tubes and were then

evaporated to near dryness using a centrifuge evaporator. Samples were reconstituted to a

final volume of 0.4 mL in 70:30 HPLC grade methanol:Milli-Q water for the Oasis HLB

extracts or in HPLC grade methanol for the Strata-XX extracts. The results were

compared to determine which SPE sorbent cartridge gives the best recoveries and

selectivity for the target compounds and surrogates. Based on optimal recoveries of the

spiked compounds, the method with the Oasis HLB SPE cartridge was chosen for all

water extractions performed in this study. This SPE method is similar to one previously

described by Metcalfe et al. (2016) for extraction of CUPs in water.

A method was also developed for separation and analysis of the target anti-cancer

drugs and their stable isotope surrogates using liquid chromatography coupled with

tandem mass spectrometry (LC–MS/MS) with an electrospray ionization source (ESI).

Analysis was conducted using a QTrap 5500 instrument equipped with an Agilent 1100

series HPLC separation system purchased from Sciex (Concord, ON, Canada). The

MS/MS operating parameters for anti-cancer drug analytes and internal standards were

first optimized by direct infusion using auto-selected multiple reaction monitoring

28

(MRM) mode with both positive and negative ionization to determine the precursor and

product ions for each analyte. The optimized MS/MS parameters and MRM transitions

for the selected two transitions are listed in Table 2.2. The first transition for each target

compound was the transition used for quantification and the second one was used for

confirmation.

Table 2.2: Summary of tandem mass spectrometry parameters used for multiple reaction

monitoring for target cancer drug analytes and internal standards.

Analyte

Q1

(m/z)

Q3

(m/z)

Polarity DP

(V)

EP

(V)

CE

(V)

CXP

(V)

Tamoxifen

372.2

372.2

72.1

70.1

+ 31

31

10

10

49

67

10

10

4-Hydroxytamoxifen

388.0

388.1

72.0

128.9

+ 216

181

10

10

57

35

10

18

Cyproterone Acetate

417.2

417.2

147.2

90.9

+ 101

101

10

10

33

79

16

10

Flutamide

275.0

275.0

185.9

181.9

- -140

-140

-10

-10

-44

-44

-17

-17

Bicalutamide

429.1

429.1

184.5

172.9

- -5

-5

-10

-10

-42

-32

-15

-15

Nilutamide

316.0

316.0

205.0

227.0

- -125

-125

-10

-10

-30

-44

-9

-23

Tamoxifen-d5

377.5

377.5

134.2

72.1

+ 71

121

10

10

35

63

22

54

Bicalutamide-d4

433.2

433.2

177.0

185.0

- -95

-95

-10

-10

-34

-56

-19

-15

Flutamide-d7

282.0

282.0

181.9

98.1

- -55

-55

-10

-10

-26

-46

-17

-11

29

A variety of solvents and solvent gradients were tried to optimize the separation

of the target analytes by liquid chromatography using a Genesis C18 column (150mm x

2.1mm ID; 4mm particle size) purchased from Chromatographic Specialties, coupled

with a guard column with the same packing material (4mm x 2.0mm) purchased from

Phenomenex. Two different methods were developed; one for separation of the target

analytes using ESI operated in positive ion mode, and one for the separation of the target

analytes using ESI in negative ion mode. The binary solvents shown to produce the best

separation of the target analytes were the same for both the positive and negative ESI

methods, but differed in the gradients used. The binary solvents were: [A] Milli-Q water

with 0.1% formic acid, and [B] acetonitrile with 0.1% acetic acid. The solvent gradient

that showed the best separation for the analytes for the positive ESI and negative ESI

methods are listed below in Table 2.3 and Table 2.4, respectively.

Table.2.3: LC solvent gradient for the separation of analytes using ESI in positive ion

mode.

Total Time (min)

Flow Rate (µL/min) A (%) B (%)

0.01 340 75 25

1.00 340 75 25

2.00 340 50 50

5.00 340 30 70

8.00 340 5 95

10.00 340 1 99

13.00 340 75 25

17.00 340 75 25

30

Table .2.4: LC solvent gradient for the separation of analytes using ESI in negative ion

mode.

Total Time (min)

Flow Rate (µL/min) A (%) B (%)

0.01 340 60 40

1.00 340 60 40

2.00 340 30 70

4.00 340 15 85

7.00 340 7 93

10.00 340 60 40

13.00 340 60 40

2.2.4 Extraction and analysis

Samples of influent and effluent (i.e. 24-h composite) collected at the WWTP

over a 3-day period were extracted using the optimized SPE method described in Section

2.3.3. Prior to extraction, subsamples were passed through glass-fiber filters (1.0 µm) that

had been pre-cleaned by Soxhlet using a 55:45 mixture of hexane:dichloromethane.

Volumes of 100 mL wastewater were prepared in triplicate and spiked with 100 µL of the

0.5 µg L-1

internal standard mixture in methanol. Laboratory blanks were prepared and

extracted for each location.

All target compounds listed in Table 2.1 were analyzed by LC–MS/MS with ESI

in either negative ion mode or positive ion mode. The optimized MS/MS parameters for

all compounds, except the anti-cancer drugs were previously described by Li et al.

(2010a) and Metcalfe et al. (2016), and these parameters are listed Appendix 1. The anti-

cancer drugs and triclosan were separated using the solvent gradients previously

described for analysis in positive and negative ion modes (Section 2.3.3).

The other PPCPs and CUPs were extracted by SPE and were separated

chromatographically using the same C18 column used for the analysis of anti-cancer

31

drugs, but with a different solvent gradient previously described by (Metcalfe et al.,

2016) and Diamond et al. (2016). The binary solvents used were: [A] 10 mM ammonium

acetate with 0.1% acetic acid and, [B] 100% acetonitrile, using the gradient listed in

Appendix 2. For quantification of the anti-cancer drug analytes, an internal standard

method was used with a seven-point calibration graph covering the range of anticipated

analyte concentration in the samples plotted with a weighted (1/concentration) linear

regression. The data from the analysis of internal standard (I.S.) were used to correct for

analyte recovery and matrix effects. For the PPCPs and CUPs, an external standard

calibration with a seven-point calibration graph was used because the water samples were

not spiked with the isotopically labelled surrogates for these target compounds.

Therefore, it is important to note that the concentrations determined for these target

compounds were not corrected for analyte recovery and matrix effects.

2.2.5 Removals

The removals of the target CECs in the WWTP were determined using the

fractionated approach (Majewsky et al., 2011). The hydraulic system within the WWTP

was previously characterized (Baalbaki et al., 2016a) and the load fractions in the effluent

(i.e. proportion of Day 1, 2 and 3 influent present in the effluent on Day 3) were

determined. The data provided are shown in Appendix 3 and Appendix 4. With the

available data, the removals were calculated as described by Majewsky et al. (2011). The

mass load from each of the influent days was determined using Equation 1.

𝐿𝑖 = 𝑄𝑖 ∗ 𝐶𝑖 (1)

32

Where L,i is the load of a target compound (mg d-1

) on the ith

day, C i is the concentration

of the target compound (mg L-1

) on the ith

day and Qi is the flow rate (L day-1

) on the ith

day. Using the mass loads for each of the influent days and the load fractions previously

determined, the fractionated influent load (reference load) was determined using

Equation 2.

𝐿𝑟𝑒𝑓 = ∑ 𝑓𝑖 ∗ 𝐿𝑖𝑛, 𝑖𝑖=3𝑖=1 (2)

Where Lref is the reference mass load of the target compound in the influent (mg day-1

)

over several sampling days, fi is the fraction of incoming target compound load on the ith

day of sampling that is contained in the outgoing load on the last day of sampling, and

Lin, i is the mass load of the target compound in the influent (mg day-1

) on the ith

day of

sampling.

Finally, using the reference mass load (Lref) the removal efficiency was calculated for

each target compound using Equation 3.

𝑅 =𝐿𝑟𝑒𝑓−𝐿𝑜𝑢𝑡

𝐿𝑟𝑒𝑓∗ 100% (3)

Where R is the removal (%) of the target compound, Lref is the reference mass load, and

Lout is the mass load of the target compound (mg day-1

) determined on the last sampling

day.

33

2.3 Results and Discussion

2.3.1 Method optimization

A novel analytical method was developed in this study for detecting a variety of

anti-cancer drugs used for prostate and breast cancer. The method consisted of SPE

extraction of wastewater samples and quantification using LC-ESI-MS/MS. The

quantification of the target compounds was done in MRM mode with two transition ions

to increase the confidence for analysis of the target compounds. The optimal transitions

and MS conditions for each target compound were determined by direct infusion. For

each target compound, two sensitive and representative transitions (precursor ion →

product ion) were chosen for quantitation and for confirmation purposes. The liquid

chromatographic conditions were determined by trying numerous gradients and solvent

combinations. The mobile phase of Milli-Q water with 0.1% formic acid and acetonitrile

with 0.1% acetic acid provided the best analyte resolution and ionization of the target

compounds. Example Extracted Ion Chromatograms of the target cancer therapy drugs

are shown in Appendix 5 and Appendix 6. Good linearity of the method (R2 > 0.98) was

obtained using standard mixtures of the target compounds ranging from 1 – 200 µg L-1

.

The instrumental limit of detection (LOD) and limit of quantification (LOQ) were

determined as the target compound concentration that produced a peak with a signal-to-

noise ratio (S/N) of 3 and 10, respectively. The LODs ranged from 5 – 300 ng L-1

and the

LOQs ranged from 20 – 1000 ng L-1

, respectively. Cyproterone acetate had the highest

LOD and LOQ and all other target compounds had significantly lower LODs (5 – 60 ng

L-1

) and LOQs (20 – 200 ng L-1

). The LODs and LOQs determined were sufficient to

investigate the target compounds.

34

Two SPE methods were tested in this study at two different pH levels to

determine best recoveries for the target compounds and internal standards. The method

with the Oasis HLB cartridges proved to have the better recoveries at a pH of 3, ranging

from 80% for bicalutamide and 160% for nilutamide. The recoveries >100% for

nilutamide may be due to signal enhancement from the sample matrix in Milli-Q water or

the flutamide stable isotope surrogate used for quantification is not an appropriate

internal standard for nilutamide. Unfortunately, there was no known commercially

available isotope labeled surrogate for nilutamide. Cyproterone acetate also had a high

recovery (144%) and this high recovery could also be due to an inappropriate IS, as there

is no isotopically labeled surrogate available for cyproterone acetate. The concentrations

of nilutamide and cyproterone acetate should therefore be used with caution due to not

having more appropriate I.S.s to account for any analytical uncertainties.

2.3.2 Levels of target compounds and removals

The concentrations of target anti-estrogenic and anti-androgenic compounds were

investigated in this study using a novel analytical method for anti-cancer drugs, along

with a previously developed analytical method for pesticides. The concentrations (ng L-1

)

for all target compounds in the influent and effluent for each day are shown in Appendix

7. The concentrations of all the target compounds >LOD in the influent or effluent of any

day during the sampling regime are shown in Table 2.5 and the estimated removal

efficiencies calculated using the fractionated approach for the target compounds found

>LOQ are shown in Table 2.6. The estimated removal efficiencies were calculated using

the mean concentrations for the influent for each sampled day and using the mean

concentration for the effluent on the final day of sampling (Day 3). All samples were

35

collected at the same time and the replicates of the WWTP influent samples were not

matched to the replicates of the effluent. Therefore, only the mean concentrations of

influent replicates and the mean concentration of the effluent replicates could be

compared. The means were calculated using the target compounds LOD and LOQ

concentrations when target compounds had replicates <LOD and <LOQ, therefore the

removal efficiencies may be higher than estimated in this study.

The CUPs were detected with a high frequency in the WWTP influent and

effluent. Of the target compounds detected, five azole fungicides (i.e. tebuconazole,

fluconazole, climbazole, propiconazole and carbendazim) were present at concentrations

>LOD in all influent and in almost all effluent samples. Compounds from the azole class

of fungicides have been shown to be poorly removed by conventional treatment

technologies used in WWTPs (Kahle et al., 2008; Lindberg et al., 2010; Luo et al., 2014;

Van De Steene et al., 2010). The present study was consistent with previous studies for

the azole fungicides, with the exception of tebuconazole that showed to be removed more

efficiently than previously reported (69.8%). The agricultural fungicide/biocide

tebuconazole was determined to be removed relatively efficiently (69.8%) when

determined using the fractionated approach, and the removal efficiency was higher than

removal efficiencies determined in previous studies, where removals in WWTPs were <0

– 57% (Campo et al., 2013; Kahle et al., 2008; Singer et al., 2010; Stamatis et al., 2010).

Tebuconazole was found in the influent and effluent at low ng L-1

concentrations (<6.3

ng L-1

) and the low concentrations of this compound is consistent with other studies of

tebuconazole in WWTP influents and effluents (Huang et al., 2010; Kahle et al., 2008).

36

Table 2.5: Summary of target compounds detected (>LOD) in the influent and effluent

during the sampling period.

Day 1 Day 2 Day 3

Influent Effluent Influent Effluent Influent Effluent

Fungicides

Propiconazole P P P P P ND

Tebuconazole 4.6 ± 1.0 5.3 ± 0.0 5.6 ± 1.3 3.9 ± 0.3 6.5 ± 0.6 4.3*

Fluconazole 63.7 ± 5.0 68.5 ± 7.3 74.9 ± 6.2 34. 8 ± 7.9 80.7 ± 4.8 86.9 ±

19.4

Climbazole P P 6.2 ± 1.5 P 6.3 ± 2.2 ND

Carbendazim 81.2 ± 5.6 29.6 ± 2.4 164.5 ± 24.7 8.0 ± 0.3 143.4 ± 10.2 41.6 ± 4.5

Myclobutanil 85.3 ± 6.4 ND 53.9 ± 3.7 ND 58.1 ± 3.5 ND

Triclosan

148.5 ± 12.4 ND 264.7 ± 44.8 ND 274.3 ± 51.9 ND

Herbicides/

Biocides

Atrazine ND P P P P P

Dicamba 22.4 ± 4.4 11.2 ± 0.7 20.5 ± 2.6 8.9 ± 0.4 47.0 ± 5.1 54.8 ± 2.3

2, 4 – D 24.0 ± 5.6 7.7 ± 0.1 25.4 ± 5.8 4.9 ± 0.6 52.1 ± 4.3 57.1 ± 4.7

Mecoprop 22.3 ± 5.7 37.3 ± 4.2 16.3 ± 1.1 20.6 ± 1.5 37.9 ± 2.3 62.3 ± 2.5

Anti-cancer drugs

Bicalutamide 4.9 ± 1.0 6.7 ± 0.9 6.7 ± 0.6 5.0 ± 1.1 6.4 ± 0.6 9.3 ± 1.7

Cyproterone

acetate

56.1 ± 17.7 8.1*

29.3 ± 15.6 6.4* 7.5 ± 2.0 18.6*

ND (Not Detected): Concentrations were <LOD; P (Present): Concentrations were <LOQ

* One or two of the sample replicates were below <LOD or <LOQ

37

However, tebuconazole has also been found at relatively high concentrations, up to 1893

ng L-1

in WWTP influent and up to 691.1 ng L-1

in the effluent after agricultural

application (Singer et al., 2010; Stamatis et al., 2010).

Carbendazim is another agricultural fungicide that is used as a biocide, like

tebuconazole, and was also present in the WWTP influent and effluent. Carbendazim was

present in relatively high concentrations in the influent and effluent, at concentrations up

to 165 ng L-1

and 42 ng L-1

, respectively. Carbendazim has been detected previously in

WWTP influent and effluent at concentrations up to 530 ng L-1

(Chen et al., 2014, 2012;

Morasch et al., 2010; Singer et al., 2010), so the results determined in the present study

are consistent with other studies. There was a 73.3 % removal of carbendazim determined

using the fractionated approach and this removal rate is higher than previously reported

rates of 9 and 36% (Morasch et al., 2010; Singer et al., 2010). It is possible that the

differences in removals are due to the method used to calculate the removals, as

previously determined removals did not consider the hydraulic regime of the WWTPs.

Also, in these previous studies, the 24-h composite samples were only taken for 1 day, so

the effluent mass loads of carbendazim, and all other target compounds in their studies,

were not accounting for the majority of the influent mass loads (Majewsky et al., 2011).

Two azole fungicides, fluconazole and climbazole, that are used as pharmaceuticals to

treat fungal infections were also detected in the influent and effluent samples.

Fluconazole was present in the influent and effluent samples with little variation between

the influent and effluent concentrations on each day, and ranged from 35 – 87 ng L-1

.

Fluconazole has been detected previously at concentrations of 10 – 488 ng L-1

in the

influent and effluent of WWTPs (Casado et al., 2014; Chen et al., 2014, 2012; Kahle et

38

al., 2008; Lindberg et al., 2010). There was poor removal of fluconazole (-6.2%), which

is consistent with poor removals reported before for this compound (Kahle et al., 2008;

Lindberg et al., 2010).

Triclosan, an antibacterial compound widely used in personal care products and

the agricultural fungicide/biocide, myclobutanil were both present in the WWTP influent

at relatively high concentrations of up to 274 ng L-1

for triclosan and 85 ng L-1

for

myclobutanil. However, these compounds were not detected in the effluent on any

sampling day, resulting in removals >99 %. To the best of our knowledge no other study

has looked at the presence or removal of myclobutanil in WWTPs. Myclobutanil likely

partitions into biosolids because it is relatively hydrophobic with a log Kow of 2.9 and has

poor solubility in water (132 mg L-1

). Triclosan is also effectively removed from

wastewater because it partitions into the biosolids ( Yu et al., 2013; Stasinakis et al.,

2010). Previous studies have also found triclosan in WWTP influents at high

concentrations in the µg L-1

range, but it is always removed efficiently (>70%) using

different WWTP treatment technologies (Luo et al., 2014).

The herbicides, dicamba, 2,4-D and mecoprop were detected each day in the

influent and effluent at concentrations ranging from 5 – 62 ng L-1

, and atrazine was also

present in wastewater each day, except for the influent sample collected on the first

sampling day. Herbicides have been commonly detected in the influent and effluent of

WWTPs at concentrations up to 1,010 ng L-1

( Köck-Schulmeyer et al., 2013; Hope et al.,

2012; Morasch et al., 2010; Singer et al., 2010). The removals of these herbicides

calculated using the fractionation approach were poor, at up to -102% for mecoprop,

which means that mass loads for the herbicides were much greater in the effluent than in

39

the influent. The presence of these herbicides, and other pesticides at higher

concentrations in the effluent than the influent has been reported in other studies (Campo

et al., 2013; Morasch et al., 2010; Singer et al., 2010).

There are several possible explanations for these negative removals of herbicides.

The pesticide may enter the WWTP as a conjugate and/or ester, or bound to particulate

matter and through the treatment process of the WWTP the parent compound is released

by hydrolysis or desorption from particulate matter (Köck-Schulmeyer et al., 2013). For

example, it has been proposed that the low or negative removals of mecoprop are due to

mecoprop being sold as an ester, and de-esterification during wastewater treatment results

in a higher concentration in the effluent than the influent (Singer et al., 2010). Another

possible explanation for the negative removals may be due to the assumption for the

fractionated approach that there is a continuous contribution into the WWTP of the target

compounds (Majewsky et al., 2013). The presences of agricultural herbicides in WWTPs,

and other pesticides, are largely influenced by rain events and may not meet the

assumption of a continuous contribution to the influent, as typically observed for

pharmaceuticals and other micropollutants of wastewater origin that enter a WWTP.

Finally, there could be negative removals due to matrix effects in the influent samples

that may have supressed the target compound signal. The pesticide target compounds

were not corrected for matrix effects using isotopically labeled surrogates, and the sample

matrix is much more complex in the influent samples than in the effluent.

40

Table 2.6: Estimated removals (%) of target compounds calculated using the fractionated

approach.

CLASS COMPOUND Removal (%)

PPCP fungicides

Fluconazole -6.2

Climbazole 95.7*

Triclosan 99.6*

Agriculture/turf/biocide

fungicides

Tebuconazole 69.8*

Carbendazim 73.3

Myclobutanil 99.9*

Herbicides/biocides

Dicamba -43.8

2, 4-D -32.0

Mecoprop -102.0

Anti-cancer drugs

Bicalutamide -37.9

Cyproterone acetate 40.0*

*Estimated removal efficiencies were calculated using the LOD for target compounds

<LOD in sample replicates, and the LOQ for target compounds in sample replicates

<LOQ.

41

The only two anti-cancer target compounds detected in wastewater were the two

anti-androgenic prostate cancer therapy drugs, bicalutamide and cyproterone acetate.

Bicalutamide was detected at low concentrations, up to 9.3 ng L-1

and showed poor

removal of -37.9%. The presence of these anti-cancer drugs in WWTPs has only recently

been investigated and only two studies have reported the detection of bicalutamide in

WWTP effluents (Azuma et al., 2015; Singer et al., 2016). Singer et al. (2016) found

bicalutamide in 5 of the 6 WWTPs investigated at low concentrations similar to those

found in the present study, and these researchers also found poor removals of

bicalutamide (i.e. 2.6%) as seen in this study. Bicalutamide is not readily degradable and

has a relatively high excreta factor (portion of compound excreted from the body once

consumed) of 0.55, so its presence in WWTPs influents and effluents could be expected

(Besse et al., 2012). Azuma et al. (2015) detected bicalutamide in effluent samples at

concentrations ranging from 49 – 1032 ng L-1

and found that with ozonation treatment,

the frequency of detection of bicalutamide decreased from 100% to 50% and

bicalutamide. Therefore, enhanced removal of bicalutamide may be possible in WWTPs

that use ozonation for effluent disinfection.

Cyproterone acetate was detected in the influent and the effluent of the WWTP,

with the highest concentration (56 ng L-1

) being in the influent sample collected on the

first day. This target compound has been detected previously at very low concentrations

in a WWTP influent and effluent, but was found in a hospital effluent at a concentration

of 27 ng L-1

(Ammann et al., 2014). The present study is the first to report the removal of

cyproterone acetate in a WWTP, which was not efficiently removed (40%). There are no

excretion data available for cyproterone acetate, but there was data available for a few of

42

the other target anti-cancer drugs. Both nilutamide and flutamide show low excreta

factors of <0.1 (Besse et al., 2012), therefore it is not surprising that these compounds

have not been widely reported in wastewater. As with cyproterone acetate, there are no

data available on excretion factors for tamoxifen, but this anti-estrogen has been detected

previously in WWTPs effluents at concentrations up to 102 ng L-1

( Liu et al., 2010;

Coetsier et al., 2009; Ashton et al., 2004). Tamoxifen was not detected in any of the

wastewater samples in the present study. This is likely due to tamoxifen and its

metabolite, 4-hydroxytamoxifen, having high log Kow values of >5.8. Therefore, there is a

high probability that these compounds are partitioning into the biosolids.

The poor removals of the two anti-cancer drugs, as well as the anti-fungal

pharmaceutical, fluconazole may be explained by these target compounds entering the

WWTP as a conjugate/metabolite and then being hydrolytically converted back to the

parent compound. The removals of target compounds in WWTPs is also highly

dependent on the treatment process within the WWTP (Köck-Schulmeyer et al., 2013),

although the tertiary treatment technologies used in the WWTP monitored in the present

study would presumably represent a best-case-scenario for removals of micropolutants

from wastewater. In future investigations on anti-estrogenic and anti-androgenic

compounds, extraction of the biosolids would provide a clearer picture of the fate of the

target compounds in the WWTP. Also, the use of isotopically labelled internal standards

for all target compounds will improve the accuracy of removals determined.

43

2.4 Conclusion

This study was the first to develop a method to detect and quantify a variety of

anti-cancer drugs in wastewater. The poor removals from wastewater of herbicides,

fluconazole, and two prostate cancer therapy drugs show that there are potential sources

of anti-androgenic compounds in WWTP effluent that could be contribute to endocrine

disruption downstream of discharges from WWTPs. There are limitations to this study,

including not using isotopically labeled internal standards to correct for matrix effects for

CUPs and some other target compounds. Overall, the study contributed to identifying

possible anti-androgenic compounds that may be working in combination with other

endocrine disrupting compounds in surface waters to induce the endocrine disruption.

Future research should focus on investigating the fate of anti-estrogenic and anti-

androgenic compounds within WWTPs, with a focus on determining the rate of

partitioning to biosolids.

44

3 INVESTIGATION OF ENDOCRINE DISRUPTING COMPOUNDS

WITH ANTI-ESTROGENIC AND ANTI-ANDROGENIC ACTIVITY

IN THE SPEED RIVER, ONTARIO USING POLAR ORGANIC

CHEMICAL INTEGRATIVE SAMPLERS

3.1 Introduction

The presence of endocrine disrupting compounds (EDCs) in surface waters

impacted by municipal WWTP discharge or/and agricultural areas has become a large

field of research in the past couple of decades (McKinlay et al., 2008; Schug et al., 2011).

A large portion of these EDCs are known as contaminants of emerging concern (CECs);

and these contaminants include a variety of chemical classes such as, pharmaceuticals

and personal care products (PPCPs), steroid hormones, and current use pesticides (CUPs)

( Luo et al., 2014; Agüera et al., 2013). The majority of research on CECs that are EDCs

has focused on the compounds with estrogenic activity (Iwanowicz et al., 2016; Liscio et

al., 2014; Liu et al., 2009). However, in the last decade it has been shown that the

endocrine disruption in organisms impacted by WWTP discharges are likely due to the

combination of both estrogenic and anti-androgenic CECs (Arlos et al., 2015; Bhatia et

al., 2014b; Hill et al., 2010; Jobling et al., 2009; Liscio et al., 2014). Due to new evidence

of anti-androgenic activity in WWTP effluents and surface waters, current studies are

moving away from investigating estrogenic activity and are focusing on anti-estrogenic

and anti-androgenic activity in WWTP effluents and surface waters (Sumpter and

Jobling, 2013). There are only a few studies that have taken on the challenge to identify

the contaminants with anti-estrogenic and anti-androgenic activity in the surface water.

45

Identifying and quantifying possible anti-estrogenic and anti-androgenic CECs

can be problematic, similar to identifying other CECs, because they are usually present at

trace levels (<100 ng L-1

) in surface waters. Various types of sampling methods have

been utilized to detect these CECs and all have their benefits and limitations. The use of

traditional grab samples provides insight of contamination at one single point in time, but

often a large volume is needed and time consuming preparation steps are required to

detect the target contaminants (Bundschuh et al., 2014). The use of passive samplers have

been used to overcome these limitation, specifically the use of polar organic chemical

integrative samplers (POCIS) has been used to quantify hydrophilic (log Kow <4) PPCPs

and CUPs in surface waters (Harman et al., 2012). POCIS and other passive samplers

offer the advantage of providing insight on the contaminations over a period of time,

usually a few weeks at a time. CECs accumulate on a sorbent located within two

microporous polyethersulfone (PES) membranes that are held together with two stainless

steel rings, therefore the CECs are concentrated over the time period to be at quantifiable

levels (Seethapathy et al., 2008). Once the amount of CEC accumulated is known the

estimated time weighted average (TWA) concentration can be calculated based on

amount accumulated, the length of the deployment and the target CEC specific sampling

rate (Rs), as shown below.

Estimated TWA concentration in water (ng/L) =Amount accumulated in POCIS (ng)

[Rs (L d-1

) * days of deployment]

The Grand River in Ontario, Canada is an example of an area that is heavily

impacted by municipal WWTP discharges and agricultural practices that has been

previously investigated for the presence of personal care products with anti-androgenic

46

activity throughout the watershed (Arlos et al., 2015). CUPs have been previously

investigated using POCIS in the Grand River Watershed (Diamond et al., 2016). There

have also been investigations on the anti-estrogenic and anti-androgenic activity using in

vitro studies in the Speed River, a tributary of the Grand River, showing that anti-

estrogenic and anti-androgenic contaminants were present in the river (Paul Westlund,

unpublished data). The areas sampled are shown in Fig. 3.1 and are the same locations

sampled in the present study.

The Speed River, like the Grand River is also impacted by agricultural activities

in the upper part of the river and by discharges from a municipal WWTP. Therefore, the

Speed River was selected as a study site to explore whether CUPs and PPCPs with

known anti-estrogenic and anti-androgenic activity are present in WWTP effluent and

surface waters. POCIS were deployed in the Speed River upstream of the WWTP

discharge, two locations downstream of the discharge and in the WWTP effluent. The

sampling rates (Rs) for anti-estrogenic anti-cancer drugs (tamoxifen and its metabolite 4-

hydroxytamoxifen) and anti-androgenic anti-cancer drugs (flutamide, nilutamide,

bicalutamide and cyproterone acetate) were determined in the laboratory and all samples

throughout the study were analyzed using LC-MS/MS.

3.2 Methods


A list of target compounds and their usage is shown in Table 3.1. All target

compound analytical standards and their corresponding stable isotope surrogates were

47

purchased from Sigma Aldrich Canada (Oakville, ON, Canada), Toronto Research

Chemicals (Toronto, ON, Canada) or C/D/N Isotopes (Pointe-Claire, QC, Canada) and

Toronto Research Chemicals (Toronto, ON, Canada). All stock solutions and working

standards were prepared in HPLC grade methanol and stored at 4°C or -20°C. HPLC

grade acetonitrile, hexane, acetone, acetic acid, sulfuric acid (96%) and formic acid

(88%) were obtained from Fisher Scientific (Ottawa, ON, Canada). Ammonium acetate

was purchased from Sigma Aldrich Canada (Oakville, ON, Canada). Pharmaceutical-

POCIS samplers containing Waters OASIS HLB sorbent were purchased from

Environmental Sampling Technologies (St. Joseph, MO, USA) and Oasis HLB cartridges

were purchased from Waters (Milford, MA, USA).

3.2.2 Study area and sampling

The Speed River located in southern Ontario, Canada receives the effluent

discharge from a municipal WWTP and there are agricultural areas located upstream of

the WWTP. The WWTP serves the surrounding population of approximately 126,000

(estimated in 2012) and has a rated capacity of 64,000 m3 d

-1 (Arlos et al., 2015). The

WWTP uses conventional activated sludge treatment and utilizes tertiary treatment,

including nitrification and sand filters before chlorination for disinfection. The product is

then dechlorinated and the final effluent is discharged into the Speed River. POCIS were

deployed in the Speed River upstream of the WWTP effluent discharge, in the effluent of

the WWTP, and two downstream locations of the discharge as shown in Fig. 3.1. The

POCIS were deployed from October 14th to October 31st, 2014. POCIS were stored at –

20°C prior to transportation to the sampling location in an ice filled cooler. At each

location three POCIS were deployed in stainless steel cages which had been previously

48

solvent washed with HPLC grade hexane and reagent grade acetone. The stainless steel

cages containing the POCIS were secured between two metal poles that were hammered

into the sediment and the cages were positioned to be facing the direction of the flow. At

each location grab samples (1 L) were also taken in methanol washed bottles and rinsed 3

times before taking the final sample. Also, POCIS field blanks were left uncovered and

exposed to air to account for any contamination that may have occurred when preparing

the samplers. The POCIS were retrieved after the desired deployment time and all POCIS

were gently cleaned of any debris present on the samplers, wrapped in solvent washed

aluminum foil and put into plastic Ziploc® bags. All samples, including the POCIS trip

blanks and grab samplers were transported back to the laboratory in a cooler and stored at

– 20°C until extraction

Fig. 3.1: Map of sampling locations in the Speed River, Ontario.

49

Table 3.1: List of target compounds and the source of contamination for each target

compound.

Chemical Class Target Compound Source

Fungicides










Herbicides/Biocides







Anti-cancer Drugs






50

3.2.3 POCIS and grab sample extraction

The method for the POCIS extraction was based on previously developed

methods that used POCIS to investigate PPCP, EDCs and CUPs (Diamond et al., 2016;

Li et al., 2010a; Metcalfe et al., 2016). Briefly, glass chromatography columns (1 cm ID

x 30 cm length) were fitted with glass wool, stopcock and were packed with

approximately 15 – 17 g of solvent washed anhydrous sodium sulfate. Each column, one

for each POCIS, was pre-conditioned for extraction using HPLC grade methanol. While

setting up and conditioning the columns the POCIS stored in a – 20°C freezer were taken

out and allowed to thaw for approximately 30 minutes. After the POCIS were thawed any

debris and biofouling material on the surface of the PES membranes was gently removed

with water. The POCIS were dis-assembled and the sorbent was transferred to the

conditioned columns and the membranes were gently rinsed with HPLC grade methanol

as well to prevent any sorbent from being lost. Each sorbent in the columns were spiked

with 100 μL of an internal standard mixture containing 0.5 µg m L-1

of each surrogate

compound (tamoxifen-d5, flutamide-d7, and bicalutamide-d4). After three minutes 100

mL of HPLC grade methanol was used to eluate target compounds from the sorbent in

each column and the eluate was collected into round bottom flasks. Each flask was rotary

evaporated to reduce the volume of eluate to approximately 1 mL and then transferred to

15 mL conical centrifuge tube, rinsing the round bottom flask three times with HPLC

grade methanol. Samples were evaporated to near dryness using a centrifuge evaporator,

and then made up to a final volume of 0.4 mL in HPLC grade methanol. All extracts were

stored at – 20°C until analysis.

51

The 1 L grab samples from the Speed River and WWTP effluent were extracted

using the method developed in Chapter 2, which uses Oasis HLB cartridges. As in

Chapter 2 three 100 mL subsamples were taken from the 1 L sample and were extracted,

along with prepared laboratory blanks for each location.

Table 3.2: Chemical structures and physio-chemical properties of anti-cancer target

compounds.

Target Compound

M.W.

(g mol-1

)

Structure Log Kow pKa

Tamoxifen

371.51

6.35 8.8

4-hydroxytamoxifen

387.51

5.69 8.7

Flutamide

276.21

3.35 13.1

Bicalutamide

430.37

4.14

12.6

Nilutamide

317.22

1.93

7.6

Cyproterone Acetate

416.94

3.64 17.8

Physio-chemical properties from: www.drugbank.ca; Ferrando-Climent et al., 2013;

Zhang et al., 2013.

http://www.drugbank.ca/

52

3.2.1 Determination of sampling rates for anti-cancer drug

Sampling rates (Rs) were determined using a static depletion calibration method,

which determines the Rs by monitoring the decrease in concentration of the target

compound in the water over a time period. The method used was similar to ones

previously described by Li et al. (2010a) and MacLeod et al. (2007).

The static depletion calibrations were conducted in triplicate in 4-L amber bottles

filled with 3 L of Milli-Q water. POCIS were presoaked overnight in Milli-Q water the

night before the experiment was to start and the Milli-Q water to be used in the 4-L

amber jars was put into the temperature-controlled environmental chamber set to 15°C

that the experiment was to take place in. The 4-L amber jars were spiked with 1 mL of a

10 mg L-1

stock mixture containing all the anti-cancer drug analytes in methanol

(tamoxifen, bicalutamide, cyproterone acetate, 4-hydroxytamoxifen, nilutamide and

flutamide) and the herbicide atrazine as a control analyte. The methanol was allowed to

evaporate and then 3 L of Milli-Q water was added to each of the amber jars. Magnetic

stirrers were used to mix the water throughout the experiment. The water stirred for an

hour to reach an equilibrium resulting in nominal concentrations of the analytes of 3 ng

mL-1

. One presoaked POCIS was suspended vertically in the water within each 4-L

amber jar and exposed for 8 days. Positive and negative blank control experiments were

also done simultaneously throughout the 8-day exposure. The positive control consisted

of only spiked water and no POCIS sampler suspended in the water to account for any

losses due to processes other than sampler accumulation, such as degradation or

volatilization. The negative blank control had a POCIS sampler suspended in un-spiked

Milli-Q water to assess contamination during the experiment. The pH of the water in the

53

amber jars were adjusted to a pH of 8 at the start of the experiment and re-adjusted

throughout the exposure time every other day. All amber jars were also covered in

aluminum foil to reduce the exposure of light and volatilization of the analytes in the

water.

Throughout the experiment 40 mL water samples were taken every 24 hours, and

the first water sample was taken after the first hour of stirring before the POCIS samplers

were suspended into the 4-L amber jars. The water samples collected were stored at

stored at – 20 ̊C until extraction. The water extractions were done using the SPE method

previously described in Chapter 2.

3.2.2 Analysis

All samples throughout this study were analyzed for the target compounds using

liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) with an

electrospray ionization source (ESI) using an AB Sciex QTrap 5500 instrument equipped

with an Agilent 1100 series HPLC separation system (Sciex, Concord, ON, Canada). All

target compounds were separated by liquid chromatography using a Genesis C18 column

(150mm x 2.1mm ID; 4mm particle size) purchased from Chromatographic Specialties

(Brockville, ON, Canada), coupled with a guard column with the same packing material

(4mm x 2.0mm) purchased from Phenomenex (Torrance, CA, USA). The instrument was

operated in multiple reaction monitoring (MRM) mode with two ion transitions used; one

for quantification and one for confirmation.

54

All POCIS, grab samples and uptake experiment extracts were analyzed for the

anti-cancer drugs using the analysis method described in Chapter 2. The tandem mass

spectrometry parameters used for MRM and the quantification ion transition for the anti-

cancer drug target analytes and internal standard surrogates used are shown in Chapter 2.

The LC solvents and the gradients used for each ESI mode method are also shown in

Chapter 2. All POCIS and grab sample extracts were analyzed for the target PPCPs and

CUPs using a previously described methods by Metcalfe et al. (2016) and Diamond et al.

(2016). As with the anti-cancer drug analysis method there was a positive and negative

ESI mode method and each method used the same solvents and gradient. The solvents

used for chromatographic separations were: [A] 10 mM ammonium acetate with 0.1%

acetic acid and [B] 100% acetonitrile, using the gradient shown in Appendix 2. The

tandem mass spectrometry parameters used for MRM and the quantification ion

transitions for the PPCP and CUP target compounds and their corresponding internal

standard surrogates are summarized in Appendix 1. These parameters and solvent

gradient were previously described by Metcalfe et al. (2016) and Diamond et al. (2016).

For quantification of the anti-cancer drug analytes an internal standard method

was used and for the quantification of the PPCPs and CUPs an external standard method

was used. An external method was used for the quantification of the PPCPs and CUPs

because the POCIS and grab samples were not spiked with the isotopically labelled

surrogates for those target compounds. Due to not being spiked the concentrations

determined for these target compounds were not corrected for recovery and matrix

effects. All concentrations for the anti-cancer drug target compounds were corrected for

55

recovery and matrix effects. Both methods used a seven-point calibration graph ranging

from 0.78 – 200 ng mL-1

plotted with a weighted (1/concentration) linear regression.

3.2.3 Statistical analysis

Non-parametric statistics were performed to assess any significant differences in

the concentrations determined for the target compounds in the sampled locations. The

non-parametric equivalent to an ANOVA, the Kruskal – Wallis test, was performed and

if found significant (p < 0.05), a Dunn post hoc test was performed to test for differences

in locations. All statistics were conducted on excel using the statistical add-in XL STAT

2016 (XLSTAT Version 2016.04.3221).


3.3.1 Anti-cancer drug uptake experiment

A static depletion calibration method was used to determine the sampling rates

(Rs) of a variety of anti-cancer drugs. The sampling rates were determined by monitoring

the decrease in concentration of the target compound in the water over an 8-day period.

According to MacLeod et al. (2007), the decline in the concentration of the target

compound in the water over a time period can be modelled by first-order kinetics

according to the following equation:

Cw(t)=Cw(0)e[-kt]

Where Cw(t) is the water concentration at time t, Cw(0) is the initial water concentration

on day 1 of the experiment and k is the rate constant. The value for the rate constant (k) is

56

estimated from the natural logarithm (ln) of the slope of the change in water

concentrations over the 8 day experiment.

The rate of uptake by the POCIS (kU) can then be found by subtracting any

changes in concentration not caused by the POCIS (kD), which was determined from the

negative control. The target compounds were not detected in samples from the negative

control treatments in this study. The POCIS sampling rate (Rs) in litres per day were

calculated using the following equation:

Rs = kUVT

Where VT is the total volume of the water in the amber glass jars, which was 3 L in this

study.

The decrease in water concentration over the 8-day exposure for each of the target

compounds were plotted and there was relatively good linearity (R2 = 0.85 – 0.99). The

plots for the decrease of water concentration for the target anticancer drugs and the

control analyte atrazine are shown in Fig. 3.2.

In the positive control treatments, bicalutamide, flutamide and cyproterone acetate

also showed minimal loss over time, as shown in Fig. 3.2. a, b and e, respectively.

Tamoxifen and its metabolite, 4-hydroxytamoxifen, both showed a linear decrease in

water concentration in the positive control treatments (Fig. 3.2. c and d). The decrease in

concentrations of these compounds in the positive control treatments could be due to

degradation and/or volatilization, but it is possible that tamoxifen and its metabolite

adsorbed onto the surface of the glass jar. Tamoxifen and its metabolite have high log

Kow values (i.e. >5.8) and tamoxifen has been suspected of having strong sorption to

57

glass surfaces in a previous study (Hörsing et al., 2011). In a previous attempt to

determine the uptake of tamoxifen by POCIS, Morin et al. (2013) observed that

tamoxifen had little to no accumulation in the sorbent.

The two anti-androgenic prostate cancer drugs cyproterone acetate and flutamide

showed the best linearity for the target compounds (R2 >0.98), but there was also

reasonably good linearity for cyproterone acetate and atrazine (Fig. 3.2.). There was poor

linearity for nilutamide, so a sampling rate could not be calculated (Fig. 3.2. f). The

uptake of nilutamide onto the sorbent could have been affected by the adjustment of the

pH of the water to 8, because the pKa of nilutamide is 7.6. It is possible that the change

from neutral to ionized species influenced the uptake of nilutamide.

The sampling rates for the target compounds were determined from the slopes on

the plots and were adjusted to account for any losses in the positive controls. Mass

balances involving analysis of the amount of target compound adsorbed into the POCIS

sorbent have been used in previous static depletion studies to confirm sampling rates

determined by losses over time in water (Li et al., 2010a; MacLeod et al., 2007). Mass

balances were determined by comparing estimates of the mass (ng) of each target

compound accumulated on the sorbent over the experiment to the measured mass of the

compound extracted from the POCIS at the end of the experiment. The sampling rates

and mass balances are shown in Table 3.3.

58

Fig. 3.2: Plot of the decrease of target analytes a: bicalutamide, b: flutamide, c:

tamoxifen, d: 4 – hydroxy tamoxifen, e: cyproterone acetate, f: nilutamide and g: atrazine

in water by POCIS over the 8-day uptake experiment.

59

The sampling rates for compounds with a larger log Kow (>4) have been

previously shown to be overestimated using depletion experiments because these

compounds have a high affinity for the POCIS membranes, which is not included in the

analysis (Harman et al., 2012). Overall, there were poor mass balances for every target

compound, including the control compound (Table 3.3). All mass balances were < 42%

and tamoxifen and its metabolite had the worst mass balances of 2%. Also, all water

samples were frozen until extraction in 50 mL polypropylene FalconTM

centrifuge tubes

so it is possible that the target compounds adsorbed onto the plastic surface in the tube

prior to extraction. There are uncertainties in the sampling rates determined in this study

due to the low mass balances and because there appears that the uptake rates change after

day five for most of the target compounds. The sampling rate may be changing as the

concentration decreases in the water due to uptake by the POCIS.

Table 3.3: Sampling rates and mass balances for target compounds and the control

compound atrazine.

Target Compounds R(s)

(L day-1

)

Mass Balance

(%)

Bicalutamide 0.82 ± 0.03 41

Flutamide 1.07 ± 0.03 32

Cyproterone acetate 0.75 ± 0.03 41

Nilutamide ND ND

Tamoxifen 1.05 ± 0.09 2

4-hydroxytamoxifen

1.44 ± 0.06 2

Control Compound

Atrazine 0.46 ± 0.03 42

60

The use of a different calibration method, such as the static, renewal method

would eliminate this uncertainty. The static, renewal calibration method is more labour

intensive, as the concentration in the water is maintained at a relatively constant level

throughout the whole exposure period. The target compounds are renewed with freshly

spiked water throughout the experiment to keep the concentrations relatively constant and

the sampling rate is determined from the amounts of the target compounds accumulated

by POCIS removed periodically over the exposure time (Harman et al., 2012).

However, the sampling rate determined for atrazine of 0.46 ± 0.03 L day-1

is in

the range of POCIS sampling rates previously determined using a variety of calibration

methods, which range from 0.19 – 0.57 L day-1

(Fauvelle et al., 2012; Lissalde et al.,

2011; Mazzella et al., 2007; Metcalfe et al., 2016; Morin et al., 2013; Poulier et al.,

2014). The POCIS sampling rates determined in the literature for atrazine average 0.25 ±

0.03 L day-1

(Harman et al., 2012). Also, the sampling rate for atrazine was determined to

be 0.21 ± 0.07 L day-1

using the same calibration method at 20oC (Metcalfe et al., 2016).

Sampling rates for compounds by POCIS increase with temperature, but the differences

in sampling rates have been found to be a two-fold or less increase over a wide range of

temperatures (Li et al., 2010a; Togola and Budzinski, 2007). The pH may have also

influenced the sampling rate of atrazine to a small degree because the pH has been shown

to cause 50% or less variation of a target compound sampling rate determined between

pH 7 and 9 (Li et al., 2011). Overall the sampling rates determined for flutamide,

bicalutamide, cyproterone acetate and atrazine should be confirmed using another

calibration method, such as the static renewal method. The estimates of time weighted

average (TWA) concentrations for these anti-androgens determined using POCIS should

61

be considered as semi-quantitative. The sampling rates for nilutamide, tamoxifen and 4-

hydroxytamoxifen could not be determined.

The sampling rates determined for the pesticide target compounds previously by

Metcalfe et al. (2016) were used to determine the estimated TWA concentration for those

target compounds. The sampling rates for all target compounds are shown in Appendix 8.

The calibration experiments for the pesticide target compound were performed at 20 ̊C

(Metcalfe et al., 2016) and the calibration experiment for triclosan was performed at the

same temperature as the anti-cancer drug experiment at 15 ̊C (Li et al., 2010a). The

sampling rates for the pesticide target compound determined by Metcalfe et al. (2016)

were comparable to other sampling rates determined in the literature. Differences in

sampling rates are likely contributed to using different calibration experiments under

difference physical conditions, such as pH, temperature and flow rate. As discussed the

temperature and pH both influence the sampling rates and the flow rate also influences

the sampling rate. As with temperature, the increase in flow rate is expected to increase

the sampling rate of a target compound and it has been shown that there is < x2 increase

when the flow rate is increased (Harman et al., 2012). The sampling rates for pesticides

and triclosan used in the present study should provide reasonable estimates of the TWA

concentrations for those target compounds, but once again, these should be considered as

semi-quantitative and caution should be taken when interpreting the estimated

concentrations.

62

3.3.2 Target compounds

POCIS, as well as grab samples were used to investigate the presence of anti-

estrogenic and anti-androgenic compounds in the Speed River, ON, Canada. The

estimated TWA concentrations of these target compounds were determined by using data

on the amount of each target compound accumulated in the sorbent (ng), the sampling

rates previously discussed and the length of the deployment (i.e. 17 days). Summary

tables of the estimated TWA concentrations, as well as the concentrations determined in

the grab samples are shown in Appendix 9 and Appendix 10. Of the target analytes, eight

compounds were found in both the POCIS and grab samples at levels above the limit of

detection (LOD) at one or more of the sampling locations. These target compounds

included the CUPs, atrazine, mecoprop, carbendazim, tebuconazole, fluconazole,

climbazole and dicamba, and there was only one anti-cancer compound present in both

the POCIS and grab samples, cyproterone acetate. Fig 3.3 shows the estimated TWA

concentrations of the target compounds found to be greater than the limit of

quantification (LOQ) at each sampling location. Fig. 3.4 represents the concentrations of

the target compounds found in the grab samples at each location.

The presence of atrazine in the Speed River was expected because it is one of the

most commonly detected CUP in surface waters (Hayes et al., 2011) and this herbicide is

heavily used in Ontario for treatment of corn crops. In both the POCIS and grab samples

the highest concentration of atrazine was found upstream of the WWTP discharge,

indicating that the major source of atrazine is likely due to agricultural practices in the

area.

63

Fig. 3.3: Estimated TWA concentrations (ng L-1

) for target compounds detected in the

POCIS deployed.

Fig. 3.4: Concentrations of target compounds detected >LOQ in grab samples.

0

5

10

15

20

25

30

Upstream Effluent Downstream 1 Downstream 2

Est

imate

d T

WA

con

cen

trati

on

(ng/L

)

Atrazine

Mecocrop

Fluconazole

Climbazole

Tebuconazole

Carbendazim

Cyproterone Acetate

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Upstream Effluent Downstream 1 Downstream 2

Con

cen

trati

on

(n

g/L

)

AtrazineMecocropDicambaFluconazoleClimbazoleCarbendazimTriclosanCyproterone AcetateBicalutamide

64

Atrazine has been detected previously at concentrations up to 3,910 ng L-1

in

Ontario surface waters (Byer et al., 2011), at concentrations up to 400 ng L-1

in the

Grand River watershed (Arlos et al., 2015; Diamond et al., 2016; Tanna et al., 2013) and

at concentrations in the Speed River < 50 ng L-1

(Arlos et al., 2015). Sampling of the

surface waters in the majority of the previous studies were performed during the summer

season and were done closer to the application of atrazine compared to this study, where

the sampling period was mid to late October. Atrazine is usually applied onto corn crops

in late April through to July, and has been detected at elevated concentrations in Ontario

surface waters, including the Grand River during the spring/summer months relative to

lower concentrations in October (Arlos et al., 2015; Byer et al., 2011). Arlos et al. (2015)

detected atrazine at mean concentrations <90 ng L-1

in the Grand River for the months of

October and November, which is somewhat higher than the concentration in the upstream

Speed River grab sample (i.e. 26.0 ± 6.7 ng L-1

) from the present study. The presence of

atrazine months after application indicates that it is persistent in the aquatic environment,

but the concentrations detected in this study are well below the Canadian water quality

guideline concentration of 1,800 ng L-1

for the protection of aquatic life in freshwater

(CCME, 2007).

Although atrazine was not detected in the POCIS deployed in the WWTP effluent

(Fig. 3.3), this compound was detected at very low concentrations in a grab sample of the

WWTP effluent (Fig. 3.4). Atrazine was not the only herbicide detected in the WWTP

effluent. Mecoprop was detected at each sampling site, except the location upstream of

the effluent discharge with both the POCIS and the grab samples, so it appears that the

main source of mecoprop is the sewage that passes through the WWTP. Mecoprop is

65

used for lawn/turf care and can be introduced into the WWTP through the combined

sewage system. As mentioned in Chapter 2, herbicides have been commonly detected in

the influent and effluent of WWTPs ( Köck-Schulmeyer et al., 2013; Hope et al., 2012;

Morasch et al., 2010). Singer et al. (2010) previously detected mecoprop in WWTP

effluent at concentrations up to 1,010 ± 590 ng L-1

and this herbicide was also present

downstream of the discharge at a concentration of 520 ng L-1

.

In the current study, mecoprop was found in the highest concentration in the

effluent of the WWTP and was present in lower concentrations in both downstream

locations for the grab and POCIS samples. The concentrations determined were relatively

similar and ranged from 2.8 – 3.6 ng L-1

. Mecoprop has been investigated in Ontario

streams and lakes before and has been found at concentrations <830 ng L-1

, with the

highest concentrations observed during the summer months, but still detectable in the fall

and winter (Glozier et al., 2012; Kurt-Karakus et al., 2010, 2008; Struger and Fletcher,

2007). Mecoprop concentrations were higher in urban areas and was linked to urban use

(Glozier et al., 2012; Kurt-Karakus et al., 2010, 2008). The concentrations determined in

the present study for mecoprop were low, as expected due to the timing of the sampling

period in the fall. The herbicide dicamba is also used frequently for lawn/turf

applications. Dicamba was only present in POCIS at estimated concentrations <LOQ at

the two downstream locations and was detected at very low concentrations in grab

samples (i.e. 2.2 – 2.7 ng L-1

). Dicamba has also been found in Ontario streams and lakes

at concentrations <80 ng L-1

(Diamond et al., 2016; Glozier et al., 2012; Struger and

Fletcher, 2007). Diamond et al. (2016) investigated the Grand River watershed by

deploying POCIS at both agricultural and urban sites and found that dicamba was only

66

detected at an urban site at an estimated concentration of 31.1 ± 18.7 ng L-1

, and was

absent from all agricultural sites. As with atrazine and mecoprop, the low concentrations

of dicamba are likely due to the timing of the sampling period.

The fungicides used in pharmaceuticals, fluconazole and climbazole are members

of a class of chemical compounds called azole fungicides. The removal of compounds in

this chemical class from WWTPs has previously been found to be relatively poor (Kahle

et al., 2008; Lindberg et al., 2010; Luo et al., 2014; Van De Steene et al., 2010). Both of

these pharmaceuticals were found at the highest concentrations in the effluent, as

determined in both POCIS and grab samples, and concentrations were <LOD and <LOQ

in the upstream grab samples and POCIS. The TWA concentration of climbazole

estimated from POCIS deployed in the effluent was extremely low (0.9 ± 0.2 ng L-1

) was

similar to the low concentrations (ND – 1.3 ± 0.3 ng L-1

) found in the grab samples. Out

of all the target compounds detected in the Speed River and the WWTP effluent,

fluconazole was present at the highest concentration in both POCIS and grab samples.

The TWA concentrations of fluconazole estimated from POCIS deployed at downstream

locations in the Speed River are comparable with previously determined estimated TWA

concentrations (2.4 ± 0.4 ng L-1

) of fluconazole determined from POCIS deployed in an

urban area of the Grand River (Diamond et al., 2016). Fluconazole has been detected in

previously in WWTP effluents at concentrations up to 140 ng L-1

(Casado et al., 2014;

Chen et al., 2012; Kahle et al., 2008; Lindberg et al., 2010) and in effluent impacted

surface waters at concentrations up to 53 ng L-1

(Chen et al., 2014; Kahle et al., 2008).

The agricultural fungicides/biocides, tebuconazole, propiconazole and

carbendazim are also under the chemical class azoles. The agricultural fungicide

67

propiconazole was only detected in the POCIS at estimated concentrations <LOQ.

Tebuconazole was also detected in POCIS at estimated concentrations <LOQ, except for

an estimated concentration in the effluent just above the LOQ at 0.6 ± 0.1 ng L-1

. The

presence of tebuconazole upstream of the discharge indicates that there are possible

agricultural sources. Tebuconazole was also present at concentrations <LOQ in the grab

samples from all locations. Once again, the timing of the sampling period in the fall was a

factor affecting the levels detected. Tebuconazole has been previously detected in the

Grand River watershed in POCIS deployed in agricultural areas in the spring at low

estimated TWA concentrations ranging from 2.1 – 3.6 ng L-1

(Diamond et al., 2016). The

low concentrations determined in this study are consistent with these concentrations

previously determined in the Grand River watershed.

The agricultural fungicide/biocide carbendazim has also previously been detected

in POCIS deployed in the Grand River watershed in an urban area at a low estimated

TWA concentration of 2.7 ± 0.7 ng L-1

(Diamond et al., 2016). The results for the POCIS

in the Speed River are similar to these concentrations determined previously in the Grand

River. The estimated TWA concentrations for carbendazim was highest in the effluent

(12.8 ± 0.6 ng L-1

) and was lower at both downstream locations (4.2 ± 1.1 ng L-1

and 3.9

± 0.3 ng L-1

). The concentrations of carbendazim in the grab samples showed that there

were similar concentrations of carbendazim in the first downstream location (i.e. 21.0 ±

1.2 ng L-1

) and the effluent (i.e. 19.0 ± 2.1 ng L-1

) and the concentration decreased

slightly at the site further downstream (i.e. 13 ± 1.3 ng L-1

). There was no carbendazim

detected upstream of the WWTP discharge using both sampling methods. The

concentration of carbendazim was higher in the grab samples than the POCIS, but there

68

could have been a large flux of the target compound at the moment in time the grab

samples were taken. Carbendazim has been found previously in WWTP effluents at

concentrations up to 530 ng L-1

(Chen et al., 2014, 2012; Morasch et al., 2010; Singer et

al., 2010) and in surface waters receiving effluent discharges at concentrations up to 49

ng L-1

(Chen et al., 2014; Singer et al., 2010).

The anti-bacterial chemical used in personal care products, triclosan was detected

at low concentrations in the grab samples, but was not detected in all of the POCIS

samples. Triclosan has a relatively high log Kow of 4.76, which is higher than the range

(i.e. log Kow < 4) that POCIS are typically used for (Alvarez et al., 2004). Triclosan in

WWTP effluent has been widely investigated, and concentrations vary widely, depending

on the WWTP (Luo et al., 2014). Triclosan has also been investigated previously in the

Grand River watershed and was detected at concentrations up to 960 ng L-1

in the effluent

of WWTPs that did not nitrify and detected at concentrations up to 135 ng L-1

in surface

waters at locations receiving discharges of the effluent from these WWTPs (Arlos et al.,

2015). In the same study by Arlos et al. (2015), triclosan was monitored in the Speed

River, but was not detected at any of the sampling sites. In grab samples, triclosan was

present at low concentrations in the effluent (4.5 ± 1.7 ng L-1

) and was detected at slightly

higher concentrations at the two downstream locations (7.6 ± 2.2 ng L-1

and 15.8 ± 2.0 ng

L-1

). The higher concentrations of triclosan in the downstream locations are probably due

to the timing of the sampling, as grab samples reflect contamination at a certain point in

time. It was previously observed in the Grand River that the concentrations of triclosan

decreased fairly rapidly with distance downstream (Arlos et al., 2015). Due to triclosan

69

having a high Log Kow it is probable that there is partitioning of this compound into the

sediment or other hydrophobic media in the aquatic environment.

Relative to studies of CUPs and triclosan, there have been few investigations into

the presence of anti-cancer drugs in WWTP effluents and receiving waters. Two drugs

used for prostate cancer therapy, bicalutamide and cyproterone acetate were the only anti-

cancer drugs detected. Bicalutamide followed a similar trend as triclosan in that it was

only present in the grab samples and not in the POCIS. Similarly to triclosan,

bicalutamide has a log Kow greater than 4, and so this may have affected sampling rates.

We determined an Rs value for this compound of 0.82 ± 0.03 (Table 3.3), but a

significant amount of the compound may have been adsorbed to the membrane in this

calibration experiment, which is not included in the analysis of the sorbent. In grab

samples, bicalutamide was found in the WWTP effluent at a mean concentration of 5.6 ±

0.1 ng L-1

, which is much lower than concentrations previously observed in WWTP

effluents up to 1,032 ng L-1

(Azuma et al., 2015; Singer et al., 2016). To the best of our

knowledge, the present study is the first to monitor for bicalutamide in surface waters. As

in the WWTP effluent, the concentrations of bicalutamide in grab samples were very low

in the two downstream sites, as concentrations of 4.5 ± 1.0 ng L-1

and 2.1 ± 0.3 ng L-1

,

respectively.

Cyproterone acetate was detected in both POCIS and grab samples at higher

concentrations, but the TWA concentrations estimated from POCIS were low in

comparison to the concentrations determined in the grab samples. Cyproterone acetate

had the highest estimated TWA concentration in the effluent of the WWTP (2.3 ± 0.4 ng

L-1

), was not detectable upstream of the discharge and was present at concentrations

70

<LOQ at both downstream locations. In the grab samples cyproterone acetate was also

found at a mean concentration of 34.1 ± 12.9 ng L-1

in the effluent, but the concentrations

of cyproterone acetate at the downstream locations were close to those determined in the

effluent. As mentioned previously, the temporal and spatial limitations of grab sampling

should be considered when interpreting the results. To the best of our knowledge, there

has been only one other study that has looked into determining the concentrations of

cyproterone acetate in effluents and receiving waters, and this anti-cancer drug was not

detected above the LOD (i.e. <1 ng L-1

) in the effluent and receiving river (Ammann et

al., 2014).

3.3.3 Potential for Endocrine Disruption

The target compounds detected in this study have all been shown to have anti-

estrogenic and anti-androgenic activity or have the potential to be endocrine disrupting

chemicals (EDC) through other mechanisms. Several of the azole fungicides used as

agricultural fungicides, biocides or as anti-fungal pharmaceuticals have been previously

shown to have anti-estrogenic and/or anti-androgenic activity using in vitro methods

(Kjærstad et al., 2010; Orton et al., 2011). However, even though fluconazole was

detected at the highest concentration in the POCIS and grab samples, other studies have

reported that fluconazole poses a minimal threat in surface waters and exhibits no anti-

androgenic activity in an in vitro assay (Chen and Ying, 2015; Roelofs et al., 2014). The

fungicide carbendazim was also detected in the POCIS and grab samples at low

concentrations and has been shown to be an EDC (Lu et al., 2004; Morinaga et al., 2004;

Rama et al., 2014; Vandenberg et al., 2012), although the mechanism of endocrine

disruption is not through binding to the estrogen or androgen receptors (Kojima et al.,

71

2010; Yamada et al., 2005). Triclosan, bicalutamide, and cyproterone acetate are all

well-known anti-androgens and the presence of these compounds has the potential to

induce anti-androgenic effects on organisms in the receiving environment.

The herbicides atrazine, dicamba and mecoprop were detected at low

concentrations in the study area. Atrazine is a known EDC (Hayes et al., 2011) and has

been shown to alter gonadal differentiation and metamorphosis in frogs at concentrations

as low as 100 ng L-1

(Langlois et al., 2010). The other herbicides have been suspected as

being EDCs, but the possible adverse effects and mode of actions are still not fully

understood. The concentrations of all the herbicides were well below the Canadian water

quality guideline concentrations, but the combination of these compounds, even at low

concentrations may cause adverse effects in the receiving environment. This sampling

campaign was also not conducted at the expected peak for herbicide contamination so it

is possible in the late spring/summer months the concentrations of these herbicides could

reach concentrations harmful to aquatic organisms.

3.3.4 Limitations

It is important to note the limitations in this study, as there are a few that could

influence interpretation of the results. The sampling rates for the target compounds in

POCIS determined in this study and in previous studies introduce uncertainty into

estimates of TWA concentrations. Performance Reference Compounds (PRC) that are

spiked into POCIS and monitored for loss over the deployment period could be used to

account for the differences in in situ sampling rates due to environmental conditions (e.g.

72

temperature, pH, flow/turbulence, biofouling), but this approach has yet to be fully

accepted as a correction technique (Harman et al., 2012; Miège et al., 2015). Due to the

uncertainty and further need to validate the use of PRCs in POCIS, this approach was not

used in this study. Even with the limitations in the sampling rates, the results obtained

from the POCIS probably give a more representative estimate of the average

concentrations of the target compounds over the time of deployment in comparison to the

concentrations determined by the grab samples (Bundschuh et al., 2014).

There are also limitations in the grab sample results for the CUPs, as no internal

standard calibration using isotopically labelled surrogates were used to adjust the

concentrations based on method recovery or any matrix effects. This is particularly

problematic for wastewater samples, where co-extractives could have caused signal

suppression or enhancement for the LC-ESI-MS/MS analysis of grab sample extracts.

3.4 Conclusion

Several compounds with anti-estrogenic and anti-androgenic activity or other

modes of endocrine disruption were detected in the Speed River and in the effluent of a

WWTP that discharges into the river. The anti-androgen used for therapy of prostate

cancer, cyproterone acetate was the only anti-cancer drug to accumulate in the POCIS

deployed in the WWTP effluent and the Speed River. All target compounds detected in

the WWTP effluent and Speed River using both POCIS and grab sampling were found at

low concentrations. Individually the compounds detected in this study have a low

potential to induce endocrine disrupting modes of action to any organisms in the Speed

73

River, but it is possible that the mixture of these compounds could cause adverse effects.

Overall, the combination of these target compounds may be contributing to the anti-

estrogenic and anti-androgenic activity previously observed in vitro in the Speed River.

74

4 DETECTION OF ANTI-ESTROGENIC AND ANTI-ANDROGENIC

COMPOUNDS IN ARGENTINIAN SURFACE WATERS USING

POLAR ORGANIC CHEMICAL INTEGRATIVE SAMPLERS

4.1 Introduction

Contaminants of emerging concern (CEC) include newly identified pollutants for

which there may or may not be regulatory standards and for which the health effects on

humans and the aquatic environment are not completely known (Deblonde et al., 2011).

CECs include, but are not are not limited to pharmaceuticals and personal care products

(PPCPs), natural steroid hormones, and pesticides (Agüera et al., 2013; Luo et al., 2014).

Some CECs have been shown to be endocrine disrupting compounds (EDCs) that

interfere with the endocrine system and can produce adverse developmental,

reproductive, neurological, and immune effects in both humans and wildlife (Schug et al.,

2011). Studies of EDCs in wastewater and in surface waters around the world have

focused mainly on estrogenic compounds (Iwanowicz et al., 2016; Liu et al., 2009).

However, the focus on EDCs in the environment is transitioning to studies of anti-

estrogenic and anti-androgenic contaminants, which may include PPCPs and CUPs

(Sumpter and Jobling, 2013). In low and middle income countries, such as Argentina,

investigations have been initiated to determine the distribution of PPCPs and CUPs in

surface waters, but few studies have focused on contaminants from these classes that are

EDCs. The present study focuses on PPCPs and CUPs in Argentina that are known to or

potentially have anti-estrogenic or anti-androgenic activity.

75

Argentina is one of the world’s leading countries in agricultural production and

there has been an increase in pesticide use over the past couple of decades (Bonansea et

al., 2013). The extensive use of pesticides has sparked interest in determining the

potential for pesticide contamination in surface waters from agricultural runoff, drainage

and spray drift. Unlike countries in North America and Europe, Argentina has poor

regulation and enforcement to limit pesticide contamination of surface waters. Out of the

list of organic contaminants for which there are currently water quality standards in

Argentina, only 10% of the compounds are CUPs (De Gerónimo et al., 2014). Atrazine,

which is a known EDC and the most widely detected CUP in waters around the world

(Hayes et al., 2011), has been detected in numerous surface waters in Argentina in

concentrations (0.6 to 1400 ng L-1

) similar to those found in other agricultural areas of the

world (Bonansea et al., 2013; De Gerónimo et al., 2014). Fungicides from the azole class

are used in agriculture, as well as for biocides and in anti-fungal pharmaceuticals, and

several of these compounds have anti-estrogenic or anti-androgenic activity (Kjærstad et

al., 2010; Orton et al., 2011). The azole fungicide, tebuconazole was previously detected

in a study of pesticides in surface waters in Argentina (De Gerónimo et al., 2014).

CECs with endocrine disrupting activity may not be fully removed from

municipal wastewater treatment plants (WWTPs), and the potential for release of these

compounds from wastewater discharges into surface waters is a current research topic in

Argentina. Studies on the detection and quantification of CECs in wastewater and surface

waters in Argentina have recently been published (Elorriaga et al., 2013a,b; Valdés et al.,

2014a,b), and these studies have shown that known EDCs, including 17β-estradiol and

17α-ethinylestradiol are present in the wastewater effluent and in receiving waters

76

(Valdés et al., 2014b). It was shown that pharmaceuticals were still at quantifiable levels

up to 70 km downstream of the WWTP serving the city of Córdoba (Valdés et al.,

2014a). No studies have been conducted to determine whether pharmaceuticals with anti-

estrogenic and anti-androgenic activity of wastewater origin are present in surface waters

in Argentina.

The previous studies on CECs in Argentina were conducted by analyzing grab

samples of surface water and wastewater. Grab sampling provides contaminant

monitoring data at a single point in time and does not provide information on the levels of

contamination over a longer time period (Bundschuh et al., 2014). Grab sampling also

requires large volumes to detect CECs that are present at trace levels (ng L-1

) and grab

samples of water require various extraction and clean-up steps prior to analysis. Passive

samplers have been used to overcome the limitations of grab samples, and these

techniques can detect even trace levels (<100 ng L-1

) of CECs by concentrating the

contaminants from the water phase onto a sorbent over the period of deployment

(Seethapathy et al., 2008). Polar organic chemical integrative samplers (POCIS) are a

types of passive sampler that have been used to monitor for hydrophilic contaminants that

have a log Kow <4, which includes detection of PPCPs and CUPs (Harman et al., 2012).

POCIS provide an estimate of the time weighted average (TWA) concentration in water,

based on the length of deployment, individual sampling rate (Rs) of a target contaminant

and the amount (ng) of the target contaminant accumulated on the sorbent after the

deployment, as shown in the equation below.

Estimated TWA concentration in water (ng/L) =Amount accumulated in POCIS (ng)

(Rs (L d-1

) * days of deployment)

77

POCIS have never been used previously in Argentina to monitor for CECs in

surface waters, and the present study was the first to use this passive sampling technology

to investigate whether anti-estrogenic and anti-androgenic contaminants of PPCP and

CUP origin are present in Argentinean surface waters. In this study, POCIS were

deployed in three watersheds in Argentina; in the Suquía River and Tercero River in the

province of Córdoba, and in Brava Lake in the province of Buenos Aires. These

watersheds are all impacted by agriculture, but the Suquía River is also impacted by

discharges of municipal wastewater from the WWTP serving the city of Córdoba.

4.2 Methods


All analytical standards were purchased from Sigma Aldrich Canada (Oakville,

ON, Canada) or Toronto Research Chemicals (Toronto, ON, Canada). All stable isotope

surrogates were purchased from C/D/N Isotopes (Pointe-Claire, QC, Canada) and

Toronto Research Chemicals. All stock solutions and working standards were made up in

HPLC grade methanol and stored at 4°C or -20°C. Ammonium acetate was also

purchased from Sigma Aldrich Canada. HPLC grade acetonitrile, acetic acid, sulfuric

acid (96%) and formic acid (88%) were obtained from Fisher Scientific (Ottawa, ON,

Canada). HPLC grade methanol was obtained from Avantor Performance Materials

(Center Valley, PA, U.S.A). Acetone and hexane used for washing glassware were of

pesticide residual grade obtained from Sintorgan (Buenos Aires, Argentina). The

pharmaceutical-POCIS samplers containing Waters OASIS HLB sorbent were purchased

from Environmental Sampling Technologies (St. Joseph, MO, USA).

78

4.2.2 Study areas and POCIS deployments

The provinces Córdoba and Buenos Aires both have extensive agricultural

production and the main crops grown are soy, corn, wheat, and sunflowers. Córdoba is a

semi-arid region and two rivers, the Suquía River and Tercero River, were investigated

because these rivers are surrounded by agricultural fields that are probable sources of

CUPs runoff. The Suquía River also receives wastewater discharged from the WWTP for

the city of Córdoba that serves approximately 700,000 people, and also receives sewage

from several small towns that are located along the river (Valdés et al., 2014a). The river

is used as the main source of drinking water for the city of Córdoba, and is also used for

recreational purposes and as a source of irrigation water for crops (Bonansea et al., 2013).

The river is heavily influenced by agricultural areas downstream of Córdoba city, up to

where the river terminates at Mar Chiquita Lake. The Tercero River is similar to the

Suquía River and receives domestic effluent and is heavily impacted by agriculture. The

Brava Lake is situated in the province of Buenos Aires, which has a more temperate

climate, and this watershed is also surrounded by agricultural fields.

Fig. 4.1: Sampling locations in the Brava Lake.

79

The POCIS samplers were stored at – 20°C and then transported to the sampling

location in a cooler. At each location, three POCIS were placed into stainless steel cages

and were secured between two metal poles that had been hammered into the bottom

sediment. The cages were positioned to be facing the direction of the flow. During

deployment, a POCIS field blank was exposed to air to account for any contamination

that may have occurred when preparing the samplers. The POCIS were retrieved after the

deployment time of approximately 2 weeks and all POCIS were gently cleaned of any

debris present on the samplers, wrapped in solvent washed aluminum foil and placed into

plastic Ziploc® bags. All samples were transported back to the laboratory in a cooler and

stored at – 20°C until extraction.

POCIS samplers were deployed in the Brava lake at two different times, in the

influent stream, El Peligro (37°54´7.5"South; 57° 59´37.6´´West), and the effluent

stream, Tajamar (37°52´54´´South; 57°58´11.8"West) (shown in Fig. 4.1). The first

deployment was from December 19, 2014 – January 3, 2015 and the second deployment

was from March 2 – March 16, 2015. In the Tercero River, three sampling locations

were selected: Villa María (32°25'35.08"South; 63°13'35.43"West), Puente los Proteros

(32°9'3.12"South; 64°1'41.43"West), and Almafuerte (32° 9'34.99"South;

64°12'34.47"West) (shown in Fig. 4.2). The POCIS were deployed on February 24, 2015

at each location and were all retrieved on March 12, 2015. In the Suquía River, there was

one sampling location upstream and two sampling locations downstream of the Córdoba

WWTP: approximately 400 m upstream (31°24'21.28"South; 64°6'50.50"West) of the

discharge and at 10.1km (31°25'45.80"South; 64°1'41.73"West) and 16 km

80

(31°26'50.19"South; 63°59'26.58"West) downstream of the discharge (shown in Fig. 4.2).

The POCIS were deployed in the Suquía River from April 8 – April 20, 2015.

Fig. 4.2: Sampling locations in the Suquía River (Upstream, Downstream 1, and

Downstream 2) and in the Tercero River (Almafuerte, Puente los Proteros, and Villa

María).

4.2.3 POCIS extraction

The extraction procedure for POCIS was modified from previously developed

methods used to monitor for PPCPs and EDCs (Li et al., 2010a) and monitor for CUPs

(Diamond et al., 2016; Metcalfe et al., 2016). The POCIS were removed from the freezer

and allowed to thaw for approximately 30 minutes. Once thawed, each POCIS was gently

washed with water to remove any debris and biofouling material from the membrane.

Glass chromatography columns (1 cm ID x 30 cm length) that were used for the

extraction were pre-packed with a glass wool plug above the stopcock and were then

packed with approximately 15 to 17 g of solvent washed anhydrous sodium sulfate.

81

The columns were pre-conditioned for extraction using HPLC grade methanol. The

POCIS were dis-assembled and the sorbent was transferred to the conditioned columns.

The membranes were gently rinsed with methanol to ensure that all sorbent was

transferred into the column. The sorbent in the columns were then spiked with 100 μL of

a 0.5 mg L-1

internal standard mixture and allowed to sit for three minutes before elution.

Elutions were done using 100 mL of HPLC grade methanol and the eluate was collected

in an Erlenmeyer flask. The eluate volume was reduced to approximately 1 mL by rotary

evaporation and transferred to a 10 mL conical centrifuge tube, including rinses from the

boiling flask with HPLC grade methanol. Samples were evaporated to near dryness under

a gentle stream of nitrogen gas, and then made up to a final volume of 0.5 mL in HPLC

grade methanol.

4.2.4 Analysis

All target compounds were analyzed by liquid chromatography coupled with

tandem mass spectrometry (LC–MS/MS) with an electrospray ionization source (ESI)

using an ABS Sciex QTrap 5500 instrument equipped with an Agilent 1100 series HPLC

separation system (Applied Biosystems-Sciex, Mississauga, ON, Canada). The target

compounds were separated by liquid chromatography using a Genesis C18 column

(150mm x 2.1mm ID; 4mm particle size) purchased from Chromatographic Specialties

(Brockville, ON, Canada), coupled with a guard column with the same packing material

(4mm x 2.0mm) purchased from Phenomenex (Torrance, CA, USA). Two different

methods were developed for analysis of the target compounds, as described in Chapter 2,

one for target compounds using ESI in positive ion mode and one for the target analytes

using ESI in negative ion mode.

82

The solvents used for liquid chromatography (LC) were [A] Milli-Q water with

0.1% formic acid and [B] acetonitrile with 0.1% acetic acid. The solvent gradients used

to separate target compounds using the methods in positive and negative ion mode are

summarized in Chapter 2 as well. The analytical method for analysis of the pesticide

target compounds was previously described by Metcalfe et al. (2016) and Diamond et al.

(2016) and both the positive and negative ESI mode methods use the same solvents and

gradient. The solvents used for chromatographic separations were: [A] 10 mM

ammonium acetate with 0.1% acetic acid and [B] 100% acetonitrile, using the gradient

shown in Appendix 2. The LC-MS/MS conditions for analysis of the pesticide target

compounds and their corresponding internal standard surrogates are summarized in

Appendix 1. These parameters were previously described by Metcalfe et al. (2016) and

Diamond et al. (2016). An internal standard method was used for quantification, with a

seven-point calibration curve covering the range of anticipated analyte concentrations

fitted to a weighted (1/concentration) linear regression.

4.2.1 Statistical analysis

Due to small sample sizes non-parametric statistics were performed. The non-

parametric equivalent to a t-test, the Mann – Whitney test, was performed to look for

significant differences between the influent stream and effluent stream estimated TWA

concentrations in the Brava Lake. The non-parametric equivalent to an ANOVA, the

Kruskal – Wallis test, was used to look for significant differences in the locations

sampled in the Tercero River. If found significant (p < 0.05), a Dunn post hoc test was

performed to test for differences in locations. All statistics were conducted on excel using

the statistical add-in XL STAT 2016 (XLSTAT Version 2016.04.3221).

83

Table 4.1: List of pesticide and anti-cancer therapy target compounds and their usage.

Chemical Family Target Compound Usage

Fungicides










Herbicides/Biocides







Anti-cancer Drugs






84


4.3.1 Estimated TWA concentrations

POCIS were used to monitor contamination by anti-estrogenic and anti-

androgenic target compounds in three different Argentinean surface waters. The

estimated TWA concentrations of the target compounds were determined based on the

amount of the compound accumulated on the sorbent (ng/POCIS), the individual

sampling rate (Rs) and the number of days of deployment in each watershed. There are

no results to report for the second deployment in the effluent stream in the Brava Lake,

Tajamar, because the cage containing the POCIS was stolen before the POCIS were

retrieved. The sampling rates used to determine the estimated TWA concentrations were

previously determined by Metcalfe et al. (2016) using a static non-renewal protocol at a

water temperature of 20oC. The sampling rates are similar to sampling rates determined

in other studies using different methods to determine the sampling rates, such as the

batch, static-renewal and flow-through methods. For example, the sampling rate for the

herbicide atrazine determined by Metcalfe et al. (2016) was 0.21 ± 0.07 L day-1

and the

sampling rates reported in the literature using different methods and conditions ranged

from 0.19 – 0.57 L day-1

(Fauvelle et al., 2012; Lissalde et al., 2011; Mazzella et al.,

2007; Morin et al., 2013; Poulier et al., 2014). Also, the sampling rate for the fungicide,

carbendazim of 0.34 ± 0.03 L day-1

, was comparable with sampling rates previously

determined using various methods, ranging from 0.21 – 0.30 Lday-1

(Ahrens et al., 2015;

Fauvelle et al., 2012; Morin et al., 2013; Poulier et al., 2014). The variations in sampling

rates could be due to the different methods used to determine the sampling rates, but also

85

due to the different experimental conditions used, since the uptake of compounds changes

with the chemical/physical conditions (e.g. pH, flow rate, temperature).

Sampling rates determined in laboratory experiments can differ from in situ

sampling rates based on environmental conditions, thereby leading to misrepresentation

of the estimated TWA concentrations (Harman et al., 2012). The flow rate of the water

in which the POCIS are deployed is thought to have a significant effect on the

adsorption/desorption of contaminants on the sorbent in the POCIS (Alvarez et al., 2004;

Harman et al., 2012; Li et al., 2010a, 2010b; MacLeod et al., 2007; Mazzella et al., 2007).

However, increased flow only causes small increases (< 2 fold) in uptake rate (Harman et

al., 2012). During the deployment in the Tercero River, the flow rate in the river was high

at times throughout the deployment due to heavy rainfall, as indicated by flooding in

Argentina that occurred over the period of the deployment (International Federation of

Red Cross and Red Crescent Societies, 2016). The sampling rates were likely elevated

due to high flow rates, but dilution due the heavy rainfall may have reduced the

concentrations of target analytes in the watersheds. The deployment in the Suquía River

was also influenced by heavy rainfall throughout the deployment period and so the target

compounds were likely diluted. Also, the cages holding the POCIS in the two

downstream locations were covered in debris upon retrieval and were in contact with the

sediment because the metal poles had collapsed due to the heavy rainfall or drag from the

debris. It is unclear how long the POCIS were exposed in the water column, or how much

the debris hindered the water flow through the POCIS cage. There was also a thick,

biofouling layer on the POCIS deployed in the Suquía River which could have also

hindered uptake into the POCIS. Due to these problems with the POCIS deployed in the

86

Suquía River, the estimated TWA concentrations were not calculated for this watershed

and the results are reported as ng POCIS-1

.

The temperature of the surface waters investigated ranged from 23 – 28oC during

the deployments and the sampling rates for target compounds were determined at 20oC;

with the exceptions of triclosan, which was calibrated at 25oC; (Li et al., 2010a) and the

anti-cancer target compounds, which were calibrated at 15oC, as reported in an earlier

thesis chapter. Increased water temperature has been found to increase the sampling rate

in POCIS. However, Alvarez et al. (2004) estimated a maximum of a 50% increase in

sampling rates over a 20oC temperature range, and laboratory experiments investigating

the effect of temperature on sampling rates have found only a two-fold or less increase in

sampling rates over a wide range of temperatures (Li et al., 2010a; Togola and Budzinski,

2007). The rate of uptake of compounds by POCIS is also influenced by pH. In the

present study, the sampling rates were determined using a protocol with deionized water

at a pH of 6.5, which is lower than the pH of the surface waters in the present study,

which ranged from 7.3 – 8.3. Li et al. (2011) studied the effect of pH on POCIS sampling

rates for ionisable pharmaceuticals and reported a 50% or less variation in sampling rates

between pH 7 and 9 (Li et al., 2011). The majority of the target compounds do not have

pKa values in the pH range of the surface waters investigated and therefore no or only

slight variation is expected in the sampling rates due to the pH. The sampling rate for

ketoconazole, which has a pKa of 6.51 (Skiba et al., 2000), may vary in the field from the

uptake rates calibrated in the laboratory.

The use of POCIS as a quantitative tool has been questioned due to the variety of

environmental factors that influence the uptake of hydrophilic contaminants into POCIS.

87

Since the use of performance reference compound (PRC) spiked into POCIS has yet to be

fully accepted as a method to correct for the variations between laboratory derived and

field sampling rates (Harman et al., 2012; Miège et al., 2015), PRCs were not used in this

study. The sampling rates used in the present study should give a reasonable estimate of

the TWA concentrations. However, due to the uncertainties in estimating concentrations

in water from POCIS data, the results are considered to be semi-quantitative and caution

should be taken when interpreting results (Miège et al., 2015). However, it must be

stressed that POCIS data are probably more representative of the concentrations over the

deployment period than data generated by grab samples (Bundschuh et al., 2014).

4.3.2 POCIS in surface waters

The estimated TWA concentrations for target compounds at each sampling

location are summarized in Appendix 11. The PES membrane in one of the POCIS in the

cage in the upstream location in the Suquía River was punctured at retrieval and no

sorbent was present when the POCIS was opened for extraction. Due to punctured

POCIS, the data determined from the other two POCIS in the cage are reported

individually.

Some of the target compounds were present at most or all locations investigated.

The fungicides, tebuconazole, carbendazim and azoxystrobin, and the herbicides,

atrazine, dicamba and 2,4-D were detected at one or more sampling locations in each

watershed. In the Brava Lake and the Tercero River the herbicides atrazine, dicamba and

2,4-D had the highest estimated TWA concentrations in comparison to the fungicides

detected in those watersheds. In the Brava Lake, the highest estimated TWA

concentration was for atrazine in the effluent stream at Tajamar, (i.e. >1,000 ng L-1

)

88

monitored during the first deployment, but no data were collected at the same location for

a second deployment due to the cage being stolen. The estimated TWA concentration of

atrazine was significantly lower in the influent stream at El Peligro, (i.e. >60 ng L-1

) and

this compound was not detected (i.e. <LOD) at the same location during the second

deployment. There is only one known study investigating the presence of CUPs in

surface waters in Bueno Aires province and it showed that in a similar agricultural area,

atrazine was present at concentrations ranging from 25 – 1400 ngL-1

(De Gerónimo et al.,

2014). It was not unexpected to find atrazine, since this herbicide is the most widely

detected CUP in surface waters (Hayes et al., 2011). The concentrations of atrazine

reported in other studies are comparable to the ones determined in this study.

The herbicides dicamba and 2, 4-D have been used in combination with atrazine

for crop application (Samanic et al., 2006) and showed a similar trend with atrazine. The

estimated TWA concentrations of the two herbicides were high (i.e. <300 ng L-1

) in the

Brava Lake effluent stream and were lower in the influent stream (i.e. <30 ng L-1

). Also,

dicamba and 2,4-D were detected in the influent stream at estimated concentrations

<LOQ during the second deployment. In a study in Chile, 2,4 –D was widely detected in

surface waters in agricultural areas at concentrations ranging from 800 – 9700 ng L-1

in

surface waters (Palma et al., 2004). The TWA concentrations of 2,4 –D estimated in the

present study in Argentina are lower than those reported in the study in Chile, which may

be due to the different sampling methods, timing of application of the herbicide and the

crops grown in the study areas. To the best of our knowledge, there are no studies that

investigated the presence of dicamba in South American countries. The estimated TWA

concentrations from the second deployment in the Brava Lake were lower when

89

compared the first deployment, which may be explained by the timing of pesticide

application. The crops surrounding the Brava Lake are sprayed with pesticides near the

end of December, so the concentration of these pesticides would be expected to be the

highest at that time, rather than the March deployment period.

Fig. 4.3: Mean estimated TWA concentrations (±S.D.) for CUP target compounds at the

Brava Lake estimated from POCIS deployment in the influent stream, El Peligro, and the

effluent stream, Tajamar. D1: First deployment; D2: Second deployment.

The fungicides tebuconazole, carbendazim and azoxystrobin were also detected in

the Brava Lake. These fungicides are used to increase soy and corn yields, so the

detection of these fungicides was not unexpected (Battaglin et al., 2011). The fungicides

generally followed the same trend as the herbicides, with higher concentrations in the

effluent stream compared to the influent stream, with the exception of azoxystrobin. The

mean estimated TWA concentration of azoxystrobin (i.e. 70.9 ng L-1

) was higher in the

1.0

10.0

100.0

1000.0

El Peligro D1 Tajamar D1 El Peligro D2

Est

imat

ed T

WA

conce

ntr

atio

n (

ng/L

)

TebuconazoleCarbendazimAtrazineAzoxystrobinDicamba2,4-D

90

influent stream relative to the estimated concentration in the effluent stream (i.e. 3.9 ng L-

1). The difference may be due to different crops surrounding these locations. In the same

study that detected atrazine in surface waters in Buenos Aires province, tebuconazole was

detected at concentrations ranging from 30 – 35 ng L-1

(De Gerónimo et al., 2014). These

results are similar to the estimated mean concentration determined for the effluent stream

in the Brava Lake (i.e. 26.1 ng L-1

), but the estimated TWA concentrations of

tebuconazole in the influent stream were estimated to be lower from both deployments

(i.e. D1 - 7.0 ng L-1

; D2 - 1.8 ng L-1

). Carbendazim was detected in POCIS in the present

study, but estimated TWA concentrations were low relative to concentrations detected in

watersheds from agricultural areas of Chile, which varied from 200 – 4500 ng L-1

(Palma

et al., 2004). This may be due to the different methods used or the surrounding crops in

the study areas. Carbendazim was recently banned in Europe, so it is also possible that

there are different regulatory procedures for this fungicide in Chile and Argentina.

The fungicide azoxystrobin has been frequently detected in surface waters in the

United States at concentrations up to 1130 ng L-1

(Battaglin et al., 2011; Reilly et al.,

2012). The concentrations determined in these studies were from grab water samples, so

concentrations estimated for the Brava Lake may differ due to the sampling technique. It

has been shown that there is an equal balance of azoxystrobin accumulated in POCIS in

the sorbent and in the PES membrane (Lissalde et al., 2014), and therefore the

concentrations determined in this study may not accurately represent the level of

azoxystrobin contamination. The fungicides used in pharmaceuticals and personal care

products (i.e. ketoconazole, climbazole, fluconazole, and triclosan) and the

pharmaceutical anticancer drugs were not detected in POCIS in amounts >LODs. This

91

probably indicates that there were no nearby sources of municipal wastewater in the

Brava Lake. The biocides, terbutryn and Irgarol 1051 were also not present at

concentrations >LOD. These compounds are primarily used in urban locations as

antifouling additives to construction materials and paints; so once again, their absence is

probably due to the lack of urban development in the region.

There was found to be no significant differences (p > 0.05) between the El Peligro

and Tajamar locations for any target compound using non-parametric statistics even with

large differences seen for some target compounds, such as atrazine. This is likely due to

the sample size being small.

The POCIS deployment in the province of Córdoba was done later in the year

compared to the Brava Lake deployment because agricultural spraying of pesticides in

the province of Córdoba occurs near the end of February due to the dry climate in the

province. Therefore, it was expected that the POCIS deployment period at sites in

Córdoba province would coincide with the period of pesticide applications. The results

from the POCIS deployed in the Tercero River showed that the estimated TWA

concentrations for the herbicides were higher than the estimated TWA concentrations for

the fungicides. The herbicides, dicamba and 2,4-D, were present at the highest estimated

TWA concentrations. In a previous study, 2,4-D was monitored in the Tercero River

using a less sensitive gas chromatography analytical method and this compound was not

detected at concentrations <LOD in all samples (Lerda and Prosperi, 1996). In the

Tercero River the concentrations of dicamba and 2,4-D were similar at each location and

the highest concentrations of the two herbicides were at Puente los Proteros (i.e.

Dicamba: 417.8 ng L-1

; 2, 4-D: 440.4 ng L-1

), and were detected in significantly lower

92

concentrations (p = 0.004) in the Almafuerte location (Dicamba: 27.0 ng L-1

; 2,4-D: 24.4

ng L-1

). The Almafuerte sampling location was closer to a city in comparison to the other

two locations, so there may have been differences in how close the agricultural areas

were to the river. However, the estimated TWA concentrations for atrazine remained

fairly constant across all locations (73.1 – 91.9 ng L-1

) and Almafuerte had the highest

estimated TWA concentration for atrazine so it may be possible that the decrease in

dicamba and 2,4-D was due to different crops growing around the sampling location.

Also, the farmers near the Almafuerte location may use a different combination of the

herbicides on their crops than the farmers at the two other locations.

Fig. 4.4: Mean estimated TWA concentrations (±S.D.) for target compounds detected in

the three sampling locations in the Tercero River, Córdoba.

1.0

10.0

100.0

1000.0

Villa María Puente los Proteros Almafuerte

Est

imat

ed T

WA

conce

ntr

atio

n (

ng/L

)

TebconazoleCarbendazimAtrazineAzoxystrobinDicamba2,4-D

93

In the Tercero River, the estimated TWA concentrations for the fungicides,

azoxystrobin, carbendazim and tebuconazole were relatively low (<7 ng L-1

) in

comparison to the herbicides. The two biocides investigated were not detected at

concentrations >LOD, which was also seen in the Brava Lake. The fungicides used in

personal care products (i.e. ketoconazole, climbazole, and triclosan) and the

pharmaceutical target compounds were not accumulated on POCIS in amounts >LODs.

However the pharmaceutical, fluconazole was detected in POCIS in amounts <LOQ;

therefore indicating there is some degree of contamination from municipal wastewater in

the watershed. Also, as mentioned previously there was heavy rainfall during the

deployment period so it is possible that the estimated TWA concentrations are low due to

dilution.

In the Suquía River, the same agricultural herbicides and fungicides found in the

Brava Lake and the Tercero River were found in one or more of the monitoring locations

(Table 4.2). As discussed previously, the TWA concentrations were not estimated at

these sites because of concerns about fouling of the sampling gear and/or placement of

samplers in contact with river sediments. None of the anticancer therapy drugs were

detected in the POCIS. Among the target compounds that are agricultural herbicides and

fungicides, atrazine accumulated to the greatest extent in the POCIS sorbent with

comparable amounts accumulated in the upstream and downstream 1 locations (Table

4.2). The downstream 2 POCIS accumulated more than double the amounts accumulated

in POCIS deployed at the upstream and downstream 1 locations likely due to more

agriculture in areas downstream of the Córdoba WWTP discharge (Bonansea et al.,

2013). The presence and concentration of atrazine has been investigated before in the

94

Suquía River with grab samples collected at the same downstream 2 location and the

annual maximum concentration of atrazine was determined to be 63.7 ng L-1

(Bonansea et

al., 2013). The concentrations of atrazine is close to the estimated TWA concentration of

52.5 ng L-1

calculated if it is assumed the POCIS was not affected by the environmental

factors discussed in the previous section. Atrazine was also detected by Bonansea et al.

(2013) at relatively high concentrations up to 433.9 ng L-1

further down the Suquía River

in areas that are more heavily impacted by agricultural practices. The herbicides dicamba

and 2,4-D were also accumulated in the POCIS sorbent in amounts just above the LOQ,

but for 2,4-D, not every POCIS in the cages accumulated amounts above the LOD and

LOQ; possibly because of fouling.

Table 4.2: Amount of target compound accumulated in POCIS sorbent (ng POCIS-1

) for

POCIS deployed in the Suquía River. ND (Not Detected): Amounts adsorbed onto

POCIS were <LOD; P (Present): Amounts adsorbed onto POCIS were <LOQ.

Compound Sampling Locations

Upstream

Downstream 1 Downstream 2

Fluconazole 65.4; 86.5 89.4 ± 12.5 156.0 ± 62.1

Tebuconazole 9.6; 11.4 67.3 ± 16.3 31.8 ± 17.7

Carbendazim 31.1; 43.3 86.0 ± 10.0 99.5 ± 4.3

Atrazine 59.5; 65.9 45.6 ± 15.9 134.8 ± 10.6

Azoxystrobin 6.9; 7.4 ND ND

Climbazole ND P P

Dicamba ND 6.7 ± 3.1 5.7 ± 1.6

2,4-D ND 8.1* 6.7

*

*Only one of the three POCIS had detectable amounts of target compound in sorbent and

other two were either <LOD or <LOQ.

The fungicides tebuconazole and carbendazim were detected in POCIS deployed

at all locations in the Suquía River, while azoxystrobin was only detectable in POCIS

95

deployed at the upstream location. The amounts of accumulated tebuconazole and

carbendazim were higher in POCIS deployed at the two downstream locations. The

increase in concentrations downstream may be due to increased agricultural use

downstream or due to addition of the two fungicides by discharges of WWTP effluent.

Both tebuconazole and carbendazim are used as biocides for wood or coating

preservatives and have previously been detected in the influent and effluent of WWTPs

(Chen et al., 2012; Kahle et al., 2008). These fungicides have also been found in surface

waters receiving discharges from WWTPs at concentrations up to 49 ng L-1

(Chen et al.,

2014, 2012; Kahle et al., 2008), so WWTPs may be an important source in the Suquía

River. The fungicide, fluconazole which is used as a pharmaceutical to treat fungal

infections was also detected in all the sampling locations, with the highest amount

accumulated in POCIS at the Downstream 2 location (Table 4.2).

Compounds from the azole class of fungicides have been shown to be poorly

removed using conventional treatment technologies used in WWTPs (Kahle et al., 2008;

Lindberg et al., 2010; Luo et al., 2014; Van De Steene et al., 2010). Fluconazole has been

found in concentrations of 10 – 488 ng L-1

in the influent and effluent of WWTPs

(Casado et al., 2014; Chen et al., 2014; Kahle et al., 2008; Lindberg et al., 2010). This

compound has also been detected in surface waters impacted by WWTP discharges at

concentrations up to 53 ng L-1

(Chen et al., 2014; Kahle et al., 2008). Fluconazole was

accumulated in the POCIS located upstream in comparable amounts to those at the first

downstream location. The presence of fluconazole upstream may be due to sewage

discharges from small villages along the river upstream of the Córdoba WWTP. The

fungicide climbazole used in personal care products was also present, but in amounts

96

<LOQ in POCIS deployed at the two downstream locations. As mentioned previously,

the accumulation of target analytes may have been reduced in POCIS deployed at

downstream locations because they were in contact with sediment, accumulation of

debris or biofouling. The deployment was done in early April, which is late relative to

application of pesticides in February in Córdoba, but due to the heavy rainfall throughout

the month of March it was too dangerous to deploy the POCIS any earlier.

4.3.3 Ecological risks

The target compounds detected included several EDCs which have the potential

for anti-estrogenic and anti-androgenic effects, as well as endocrine disruption by other

mechanisms. Atrazine is a known EDC and has been shown to induce endocrine

disrupting effects at low concentrations (Hayes et al., 2011; Kjeldsen et al., 2013;

Vandenberg et al., 2012). For example, atrazine was found to alter gonadal differentiation

and metamorphosis in Northern leopard frogs (Rana pipiens) exposed to concentrations

as low as 100 ng L-1

(Langlois et al., 2010). Atrazine has also been found to have anti-

estrogenic and anti-androgenic activity in the yeast screening assays at high

concentrations ranging from 125,000 – 1,000,000 ng L-1

(Orton et al., 2009). Overall,

there is potential for endocrine disruption of aquatic organisms exposed to these

compounds in Argentinean surface waters, especially at the Brava Lake where the

concentrations of atrazine were highest, but it is not likely to occur through direct binding

to the estrogen and androgen receptor sites. The estimated TWA concentrations of

atrazine determined in the sampling locations were below the Canadian water quality

guideline concentration of 1,800 ng L-1

for the protection of aquatic life in freshwater

(CCME, 2007), but the concentration in the Brava Lake effluent stream was high (1018 ±

97

92.8 ng L-1

) and may be harmful to more sensitive aquatic species. The estimated TWA

concentrations of 2,4–D and dicamba are also significantly lower (<440. 4 ± 124.5 ng L-

1) than the Canadian water quality guideline concentrations of 4,000 ng L

-1 for 2,4-D and

10,000 ng L-1

for dicamba (CCME, 2007). The relatively high concentrations of 2,4–D

and dicamba in the Tercero River may still have the potential to cause adverse effects,

including endocrine disruption because the EDC potential for these herbicides has yet to

be fully characterized. In an environmental modelling study to investigate the theoretical

endocrine disruption potential for 220 different pesticides, 2,4–D and dicamba were

reported to be antagonists for the androgen receptor (Devillers et al., 2015). However, a

study looking at the potential for 2,4–D to be an EDC concluded that there was a low risk

for this herbicide (Coady et al., 2014).

The fungicide carbendazim has been found to be an EDC (Lu et al., 2004;

Morinaga et al., 2004; Rama et al., 2014; Vandenberg et al., 2012). Carbendazim does

not bind to the estrogen and androgen receptors and behave as an agonist or antagonist

(Kojima et al., 2010; Yamada et al., 2005), but it has been found to alter estrogen

production by increasing aromatase activity (McKinlay et al., 2008). Also, carbendazim

has been found to affect spermatogenesis in male rats, resulting in reduced fertility (Lu et

al., 2004; Yu et al., 2009). Several compounds from the azole class of fungicides have

been shown have anti-androgenic and anti-estrogenic activity (Kjærstad et al., 2010;

Orton et al., 2011). The agricultural fungicide, tebuconazole, was detected in all the

surface waters investigated at relatively low concentrations (1.8 – 26.1 ng L-1

) and in

amounts of 9.6 – 67.3 ng POCIS -1

in the Suquía River, and this compound has been

found to have anti-androgenic potential in in vitro assays (Kjærstad et al., 2010). The

98

azole compound that is used in anti-fungal medications, fluconazole was detected in the

present study in the Suquía River. This compound is not efficiently removed during

treatment in WWTPs and is commonly detected at low concentrations in effluents and in

surface waters impacted by WWTP discharges (Chen and Ying, 2015). However,

fluconazole is expected to be a minimal hazard in surface waters and was not anti-

androgenic in an in vitro study (Chen and Ying, 2015; Roelofs et al., 2014).

The anti-estrogenic and anti-androgenic anticancer drugs were not detected at any

of the sampling locations, even downstream of the Córdoba WWTP. The absence of

these target compounds may be due to differences in health care and demographics in the

urban area served by the WWTP. Unfortunately, data on drug therapy were not available

in order to determine whether significant amounts of anticancer drugs are used in the

region. Based on drug consumption data in France, the predicted environmental

concentrations (PEC) of these target compounds are estimated to be low (Besse et al.,

2012). The possible low concentrations of these compounds may have also been

influenced by dilution in the river by the heavy rainfall during the majority of the

deployments. Therefore, the results indicate that there is little risk to the aquatic

environment due to exposure to the target anticancer drugs.

It is important to note that individually the compounds detected in Argentinian

watersheds may not be present at concentrations high enough to induce the endocrine

disruption or other biological effects in aquatic organisms, but mixtures of these EDCs

may have adverse effects (Kojima et al., 2010). Therefore, it is important to consider

mixture of contaminants when assessing risks to the aquatic environment (Kjeldsen et al.,

2013).

99

4.4 Conclusions

This study was the first to investigate the presence of anti-estrogenic and anti-

androgenic compounds in Argentinean surface waters using POCIS. There was a high

presence of herbicides in each of the studied surface waters, with the highest

concentration resulting from atrazine in the Brava Lake. The high concentrations of

herbicides, specifically in the Tercero River and Brava Lake, and presence of fungicides

in each of the surface waters investigated have the possibility to induce endocrine

disrupting effects on aquatic organisms in the surface waters. The possibility of the

combination of these target compounds and other contaminants in the surface waters to

cause endocrine disruption and other adverse effects should be further investigated.

Continued monitoring on the levels of contamination in these areas should also be

considered and introducing better agricultural practices/further treatment processes for

WWTPs.

100

5 CONCLUSIONS

5.1 GENERAL CONCLUSION AND OBSERVATIONS

The overall objective of this study was to determine whether anti-estrogenic and

anti-androgenic compounds originating from pharmaceuticals and personal care products

(PPCP) and current use pesticides (CUP) are present in surface waters impacted by both

municipal WWTP effluents and agricultural runoff. The study focused on representative

surface waters in Canada and in Argentina. In Canada, the study focused on a WWTP

and its receiving surface water to evaluate the removal of these target compounds and to

determine the TWA concentrations of the target compounds estimated from POCIS in the

receiving waters. In Argentina, three surface waters were investigated for the target

compounds using POCIS. The study also involved development of an analytical method

for the extraction and quantification of target anti-estrogenic and anti-androgenic

anticancer drugs. Also, sampling rates for the uptake of each anticancer target compounds

into the POCIS sorbent were determined in this study.

This study revealed that there was a high occurrence of herbicides in both

Canadian and Argentinean surface waters impacted by both municipal WWTP effluent

and agricultural sources. In Argentina, the herbicides atrazine, 2,4-D and dicamba were

present at relatively high TWA concentrations in the surface waters. These herbicides

were found at the highest estimated TWA concentrations in the surface waters

surrounded by agricultural areas and were less influenced by discharges from municipal

WWTPs. In Canada, the herbicides dicamba, 2,4-D, mecoprop and atrazine were all

present in the WWTP influent and effluent samples and were poorly removed during the

101

treatment process. The presence in the WWTP indicated that these herbicides are used in

urban areas for lawn/turf purposes and are poorly removed by wastewater treatment and

are released into the aquatic environment. The herbicides, dicamba, atrazine, and

mecoprop were present in the WWTP effluent in samples collected in October and only

the herbicide atrazine was present in receiving waters upstream of the discharge,

indicating agricultural sources of atrazine. Azole fungicides were also detected in both

the Argentinean and Canadian surface waters in this study.

The azole fungicides of PPCP and agricultural/biocide origin were found at low

concentrations in the Argentinean surface waters. The pharmaceutical fungicide,

fluconazole was present at concentrations >LOD in the Tercero River, signifying WWTP

effluents as a source for the introduction of anti-estrogenic and anti-androgenic

contaminates into the river. Fluconazole was also accumulated in the POCIS deployed in

the Suquía River, with the highest accumulation at the downstream locations; further

supporting the conclusion that WWTP effluents are a source of fluconazole in surface

water. The azole agricultural and biocide fungicides, tebuconazole and carbendazim were

both present in low concentrations in the Tercero River, but were detected at higher

concentrations in the effluent stream from the Brava Lake. The two fungicides were also

accumulated in the POCIS deployed in the Suquía River. The same azole fungicides were

found in the Canadian WWTP and in the receiving waters. Generally, these fungicides

were efficiently removed by wastewater treatment (>70%), but there was poor removal of

fluconazole during the treatment process, explaining why this compound was present at

the highest concentrations of the target analytes in the WWTP effluent and receiving

waters. The anti-bacterial, triclosan and the fungicide, myclobutanil were both found at

102

high concentrations in untreated wastewater (i.e. influent) at the Canadian WWTP, but

these compounds were efficiently removed within the WWTP (>99%).

A method for the extraction and quantification of target anticancer drugs was

successfully developed, and using this method, it was possible to detect anticancer drugs

in the Canadian WWTP and in the river downstream of the discharge from the WWTP.

The sampling rates for these anticancer target compounds in POCIS were also

successfully determined, but due to uncertainties around the method used to calibrate the

sampling rates, these rates need to be confirmed using other methods. The anti-

androgenic prostate cancer drugs, cyproterone acetate and bicalutamide were detected in

untreated and treated wastewater in the WWTP and in the receiving waters. The absence

of target anticancer drugs in the Argentinean surface waters can be explained by the

physicochemical properties of a few of the target compounds. For instance, tamoxifen

has a high log Kow, and is susceptible to partitioning into sediments. The distribution of

these compounds could also be influenced by the prescription rates for these anticancer

drugs in the country, but information on this was unavailable.

Overall, the target compounds were found in surface waters at low (i.e. ng L-1

)

concentrations, with the exception of some of the herbicides detected in Argentinean

surface waters at some locations. Herbicides were detected at high concentrations in the

effluent stream, Tajamar, in the Brava Lake and were also relatively high in the Villa

María and Puente los Proteros locations in the Tercero River. These herbicides are

endocrine disrupting chemicals (EDCs) with well characterized modes of actions, so

these compounds have the potential to be harmful to organisms in the aquatic

environment. The azole fungicides are a class of chemicals that have shown to be anti-

103

estrogenic and anti-androgenic activity, except fluconazole has shown to not have the

same activity as other azole fungicides. The prostate cancer drugs are potent anti-

androgenic substances, and even though they were present in Canadian surface waters at

low concentrations, they may still have the potential to induce anti-androgenic activity.

These anti-androgenic prostate cancer drugs and other EDCs, including the ones detected

in this study, may be contributing to increased occurrences of inter-sex observed in darter

fish previously observed in the Grand River (Tanna et al., 2013; Tetreault et al., 2011).

Even though all target compounds were found at low concentrations, it is possible that

the mixture of target compounds can induce endocrine disruption in aquatic organisms,

such as increased occurrence of inter-sex, in the surface waters impacted by discharges of

domestic wastewater and agricultural runoff.

5.2 RESEARCH CONTRIBUTIONS

The research conducted in this study will assist in further understanding the

potential for anti-estrogenic and anti-androgenic compounds to contribute to endocrine

disruption in surface waters. Our colleagues at McGill University have generated data

(unpublished) from in vitro testing of extracts from the POCIS deployed in the Speed

River that show there is anti-estrogenic and anti-androgenic activity in the extracts. The

results from this study show that the anti-androgenic target compounds cyproterone

acetate, bicalutamide, triclosan, and tebuconazole were present at low concentrations in

the Speed River and that these compounds originate from domestic wastewater. The

combination of these anti-androgenic compounds may be contributing to the in vitro anti-

androgenic activity detected in the river. Other EDCs were also present in the Canadian

104

and Argentinean watershed that could be inducing anti-estrogenic and anti-androgenic

effects, or endocrine disruption through different mode of actions (e.g. atrazine). The

results from Argentina were also one of the first studies to investigate PPCPs and CUPs

in surface waters in that country, and the results can help in formulating environmental

policies and regulations of the target compounds determined.

5.3 FUTURE RESEARCH

This study provided insight on anti-estrogenic and anti-androgenic target

compounds in surface waters in Canada and Argentina that are influenced by both

agricultural practices and urban inputs from WWTPs. The study area in Canada was

focused on one WWTP and receiving waters, but in the future, more WWTPs and their

receiving waters should be investigated to monitor for the target compounds. A larger

sampling campaign would allow for comparisons between WWTPs and temporal and

spatial trends. In Canada and Argentina, larger sampling campaigns and during different

periods/seasons would provide insight on the persistence and fate of the target

compounds in the surface waters. Sampling in Canada for CUPs in WWTPs and in

surface waters should be conducted in the spring rather than the fall to provide better

representation of contamination when it would be expected to be at the highest.

Investigating sources of CUPs in WWTPs and how the CUPs are being introduced into

the sewage system should also be further investigated. In Argentina investigations should

focus on confirming anti-estrogenic and anti-androgenic activities using in vitro studies

and tailoring the analysis of the target compounds based on the CUPs and PPCPs used in

Argentina. Future studies should include more target compounds with known anti-

105

estrogenic and anti-androgenic activity to help further understand what individual

compounds are contributing to the activity detected.

The POCIS sampling rates for a variety of anti-cancer drugs were determined in

this study and these sampling rates should be confirmed using different calibration

methods. The method used has previously been used to estimate sampling rates for other

hydrophilic CECs, but due to suspected issues with the method the sampling rates should

be confirmed before future use. Sampling rates can differ from in situ sampling rates

because of different environmental factors and the use of performance reference

compounds (PRCs) to correct for the differences has become a possible solution. The use

of PRCs would allow sampling rates to be corrected to account for environmental factors

and future work should focus on determining possible PRCs for PPCPs and CUPs, as

well as validating the use of the PRCs. The use of POCIS as sampling tools for future

research has great promise and offer advantages over other sampling techniques. POCIS

offer a more representative picture of contamination and with future research into

accepting an universal calibration method and using PRCs will eliminate any possible

uncertainties in the estimated concentrations of target compounds in the future.

106

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125

7 Appendices

Appendix 1: Summary of parameters used for multiple reaction monitoring for target

fungicide, herbicide and biocide analytes and their corresponding I.S. surrogates.

Analyte

Q1

(m/z)

Q3

(m/z)

Polarity DP

(V)

EP

(V)

CE

(V)

CXP

(V)

Fungicides

Propiconazole

342.122 158.900 + 136 10 37 18

Tebuconazole

308.117 69.900 + 126 10 45 8

Fluconazole

306.99 238.000 + 121 10 23 22

Ketoconazole

531.233 489.000 + 166 10 43 30

Climbazole

293.006 197.000 + 131 10 23 18

Carbendazim

192.097 159.900 + 116 10 23 18

Azoxystrobin

404.145 85.500 + 146 10 33 18

Myclobutanil

289.008 69.900 + 121 10 23 10

Iprodione

328.007 140.800 - -80 -10 -16 -17

Ketoconazole-d4

535.041 81.100 + 211 10 107 10

Carbendazim-d4

196.050 164.00 + 56 10 7 18

Fluconazole-d4

311.021 70.100 + 131 10 51 12

Propiconazole-d5

347.023 279.100 + 66 10 13 28

Tebuconazole-d6

313.300 91.200 + 14 10 28 4

Iprodione-d5

333.030 96.900 - -40 -10 -38 -11

Herbicides

Mecoprop

212.948 140.900 - -90 -10 -20 -19

Atrazine

216.189 174.000 + 101 10 23 16

Dicamba

218.867 160.800 - -55 -10 -18 -17

2,4-D

219.906 161.900 - -50 -10 -18 -13

126

2,4-D-d3

221.722 163.900 - -25 -10 -18 -19

Atrazine-d5

220.996 72.900 + 176 10 29 10

2,4-C-d3

216.00 143.800 - -25 -10 -17 -10

3,6-D-d3

221.816 164.00 - -60 -10 -18 -7

Biocides

Irgarol 1051

254.076 198.000 + 76 10 25 20

Terbutryn

242.133 186.000 + 121 10 25 22

Terbutryn-d5

247.045 172.900 + 151 10 23 20

127

Appendix 2: LC solvent gradient for the separation of fungicide, herbicide and biocide

analytes.

Total Time (min) Flow Rate (µL/min) A (%) B (%)

0.01 340 70 30

1.00 340 70 30

2.00 340 10 90

5.00 340 10 70

11.00 340 70 95

17.00 340 70 99

Appendix 3: Flow rates (L day-1

) for the three sampling days.

Location Q1 Q2 Q3

Influent

57664449.66 53866816.12 56172510.28

Effluent

54345196.83 53870625.43 53381546.98

Appendix 4: Load fractions for the WWTP.

f1 f2 f3

4.8

37.7

58.9

128

Appendix 5: Extracted Ion Chromatograms (XICs) of cancer therapy drugs tamoxifen,

cyproterone acetate and 4-hydroxytamoxifen.

Appendix 6: Extracted Ion Chromatograms (XICs) of cancer therapy drugs flutamide,

nilutamide and bicalutamide.

T

4-

Hydroxytamox

ifen

129

Appendix 7: Summary of each sampling day influent and effluent concentrations (ng L-1

)

± S.D. of target compounds.

Day 1 Day 2 Day 3


Fungicides

Propiconazole P P P P P ND

Tebuconazole 4.6 ± 1.0 5.3 ± 0.0 5.6 ± 1.3 3.9 ± 0.3 6.5 ± 0.6 4.3*

Ketoconazole ND ND ND ND ND ND

Fluconazole 63.7 ± 5.0 68.5 ± 7.3 74.9 ± 6.2 34. 8 ± 7.9 80.7 ± 4.8 86.9 ± 19.4

Climbazole P P 6.2 ± 1.5 P 6.3 ± 2.2 ND

Carbendazim 81.2 ± 5.6 29.6 ± 2.4 164.5 ± 24.7 8.0 ± 0.3 143.4 ± 10.2 41.6 ± 4.5

Triclosan 148.5 ± 12.4 ND 264.7 ± 44.8 ND 274.3 ± 51.9 ND

Myclobutanil 85.3 ± 6.4 ND 53.9 ± 3.7 ND 58.1 ± 3.5 ND

Azoxystrobin ND ND ND ND ND ND

Iprodione

ND ND ND ND ND ND

Herbicides/Biocides

Atrazine ND P P P P P

Terbutryn ND ND ND ND ND ND

Dicamba 22.4 ± 4.4 11.2 ± 0.7 20.5 ± 2.6 8.9 ± 0.4 47.0 ± 5.1 54.8 ± 2.3

2, 4 – D 24.0 ± 5.6 7.7 ± 0.1 25.4 ± 5.8 4.9 ± 0.6 52.1 ± 4.3 57.1 ± 4.7

Mecoprop 22.3 ± 5.7 37.3 ± 4.2 16.3 ± 1.1 20.6 ± 1.5 37.9 ± 2.3 62.3 ± 2.5

Irgarol 1051 ND ND ND ND ND ND

130

Summary of each sampling day influent and effluent concentrations (ng L-1

) ± S.D. of

anti-cancer drug target compounds.

Day 1 Day 2 Day 3


Anti-cancer

Drugs

Tamoxifen ND ND ND ND ND ND

4-

hydroxytamoxifen

ND ND ND ND ND ND

Bicalutamide 4.9 ± 1.0 6.7 ± 0.9 6.7 ± 0.6 5.0 ± 1.1 6.4 ± 0.6 9.3 ± 1.7

Flutamide ND ND ND ND ND ND

Nilutamide ND ND ND ND ND ND

Cyproterone

acetate

56.1± 17.7 8.1*-

29.3 ± 15.6 6.4* 7.5 ± 2.0 18.6*

ND (Not Detected): Concentrations were <LOD;

P (Present): Concentrations were <LOQ

* One or two of the samples were below <LOD or <LOQ

131

Appendix 8: Mean (± S.D.) sampling rates (Rs) in litres per day determined for the target

compounds in POCIS in static experiments at 20oC (n=3). Sampling rate data as reported

in Metcalfe et al. (in press).

1Triclosan sampling rate previously determined by Li et al. (2010a) at 25

oC using the same sampling rate

experiment.

2Triclosan sampling rate previously determined by Li et al. (2010a) at 15

oC using the same sampling rate

experiment.

3Sampling rates estimated by analysis of POCIS (pooled) to determine total amount of target compound

accumulated over the 8 days from water.

CLASS COMPOUND Rs

PPCP Fungicides

Fluconazole 0.38 ± 0.05

Climbazole 0.65 ± 0.04

Ketoconazole 0.47 ± 0.04

Triclosan1 1.93 ± 0.2

Triclosan2 1.44 ± 0.2

Agriculture/Turf/Biocide Fungicides

Propiconazole 0.47 ± 0.05

Tebuconazole 0.44 ± 0.05

Carbendazim 0.34 ± 0.03

Iprodione 0.49 ± 0.01

Myclobutanil 0.29 ± 0.03

Azoxystrobin 0.32 ± 0.01

Herbicides/Biocides

Atrazine 0.21 ± 0.07

Irgarol 1051 0.40 ± 0.02

Terbutryn 0.46 ± 0.03

Dicamba3

0.03

2, 4-D3

0.03

Mecoprop3

0.07

Pharmaceutical

Tamoxifen 1.05 ± 0.09

4-Hydroxytamoxifen 1.44 ± 0.06

Flutamide 1.07 ± 0.03

Nilutamide ND

Bicalutamide 0.82 ± 0.03

Cyproterone acetate 0.75 ± 0.03

132


) ± S.D. of PPCP and

CUP target in the Speed River, Ontario, Canada.

Sampling Locations

Effluent Upstream

Downstream 1

Downstream 2

Fungicides

Propiconazole P P P P

Tebuconazole 0.6 ± 0.1 P P P

Ketoconazole ND ND ND ND

Fluconazole 23.5 ± 1.4 ND 6.4 ± 1.2 7.3 ± 0.6

Climbazole 0.9 ± 0.2 ND ND ND

Carbendazim 12.8 ± 0.6 ND 4.2 ± 1.1 3.9 ± 0.3

Iprodione ND ND ND ND

Myclobutanil

ND ND ND ND

Triclosan ND ND ND ND

Azoxystrobin ND ND ND ND

Herbicides/Biocides

Atrazine P 8.9 ± 0.4 7.5 ± 1.4 6.1 ± 0.5

Terbutryn ND ND ND ND

Dicamba ND ND P P

2,4 – D ND ND ND ND

Mecoprop 3.4 ± 0.5 ND 3.6 ± 0.7 2.8 ± 0.2

Irgarol 1051 ND ND ND ND

133

Sampling Locations

Effluent

Upstream Downstream 1 Downstream 2

Anti-cancer drugs

Tamoxifen

ND ND ND ND

4-hydroxytamoxifen

ND ND ND ND

Bicalutamide

ND ND ND ND

Flutamide

ND ND ND ND

Nilutamide

ND ND ND ND

Cyproterone acetate

2.3 ± 0.4 ND P P

ND (Not Detected): Amounts adsorbed onto POCIS were <LOD;

P (Present): Amounts adsorbed onto POCIS were <LOQ

134

Appendix 10: Summary of target PPCP and CUPs concentrations (ng L-1

) ± S.D. found in

the grab samples in the Speed River, Ontario, Canada.

Sampling Locations

Effluent Upstream

Downstream 1

Downstream 2

Fungicides

Propiconazole ND ND ND ND

Tebuconazole P P P P

Ketoconazole ND ND ND ND

Fluconazole 81.0 ± 6.7 P 39.5 ± 5.6 22.5 ± 0.3

Climbazole 1.3 ± 0.3 ND 0.8 ± 0.4 ND

Carbendazim 19 ± 2.1 ND 21.0 ± 1.2 13.3 ± 1.3

Iprodione ND ND ND ND

Myclobutanil

ND ND ND ND

Triclosan 4.5 ±1.7 P 7.6 ± 2.2 15.8 ± 2.0

Azoxystrobin ND ND ND ND

Herbicides/Biocides

Atrazine 2.2 ± 0.3 26.0 ± 6.7 7.3 ± 1.8 9.1 ± 1.3

Terbutryn ND ND ND ND

Dicamba 2.5 ± 0.3 P 2.7 ± 0.1 2.2 ± 0.3

2,4 – D ND ND ND ND

Mecoprop 19.2 ± 0.9 ND 10.6 ± 0.7 5.2 ± 0.3

Irgarol 1051 ND ND ND ND

135

Sampling Locations

Effluent

Upstream Downstream 1 Downstream 2

Anti-cancer drugs

Tamoxifen

ND ND ND ND

4-hydroxytamoxifen

ND ND ND ND

Bicalutamide

5.6 ± 0.1 ND 4.5 ± 1.0 2.1 ± 0.3

Flutamide

ND ND ND ND

Nilutamide

ND ND ND ND

Cyproterone acetate

34.1 ± 12.9 P 19.4 ± 3.4 32.2 ± 11.1

ND (Not Detected): Concentrations were <LOD;

P (Present): Concentrations were <LOQ

136

Appen

dix

11:

Sum

mar

y o

f es

tim

ated

TW

A c

once

ntr

atio

ns

(ng L

-1)

± S

.D.

of

targ

et c

om

pounds

at T

erce

ro R

iver

, B

rava

Lak

e an

d t

he

amount

accu

mula

ted i

n t

he

sorb

ent

(ng P

OC

IS-1

) ±

S.D

. of

targ

et c

om

poun

ds

in t

he

Suquía

Riv

er.

Sam

pli

ng L

oca

tion

s T

erce

ro

Riv

er

Bra

va L

ak

e

Su

qu

ía R

iver

(n

gP

OC

IS-1

)

V

illa

Ma

ría

P

uen

te l

os

Pro

tero

s

Alm

afu

erte

E

l P

elig

ro

D1

Ta

jam

ar

D1

El

Pel

igro

D2

Up

stre

am

D

ow

nst

rea

m

1

Do

wn

stre

am

2

Fu

ng

icid

es

Pro

pic

onaz

ole

N

D

ND

N

D

ND

N

D

ND

N

D

ND

N

D

Teb

uco

naz

ole

4

.6 ±

0.8

7

4.4

± 0

.58

2

.6 ±

0.2

4

7.0

± 0

.4

26

.1 ±

2.3

1

.8 ±

0.2

9

.6;

11.4

6

7.3

± 1

6.3

3

1.8

± 1

7.7

Ket

oco

naz

ole

N

D

ND

N

D

ND

N

D

ND

N

D

ND

N

D

Flu

conaz

ole

P

P

P

N

D

ND

N

D

65

.4;

86

.5

89

.4 ±

12.5

1

56

.0 ±

62

.1

Cli

mb

azo

le

ND

N

D

ND

N

D

ND

N

D

ND

P

P

Car

ben

daz

im

6.7

± 1

.6

5.6

± 0

.4

4.6

± 0

.6

8.2

± 0

.6

67

.1 ±

5.1

4

.9 ±

0.1

3

1.1

; 43

.3

86

.0 ±

10.0

9

9.5

± 4

.3

Ipro

dio

ne

ND

N

D

ND

N

D

ND

N

D

ND

N

D

ND

Tri

clo

san

ND

N

D

ND

N

D

ND

N

D

ND

N

D

ND

Azo

xyst

rob

in

3.0

± 0

.8

2.6

± 0

.3

2.4

± 0

.18

7

0.9

± 1

6.7

3

.9 ±

0.3

P

6

.9;

7.4

N

D

ND

Her

bic

ides

/

Bio

cid

es

Atr

azin

e

73

.1 ±

17.3

8

7.2

± 3

.3

91

.9 ±

7.4

6

6.3

± 8

.2

10

18

.4 ±

92

.8

ND

5

9.5

; 65

.9

45

.6 ±

15.9

1

34

.8 ±

10

.6

Ter

butr

yn

N

D

ND

N

D

ND

N

D

ND

N

D

ND

N

D

Dic

amb

a

24

1.5

± 1

2.8

4

17

.8 ±

10

9.4

2

7.0

± 0

.7

30

.6 ±

1.6

3

03

.3 ±

12

.0

P

ND

6

.7 ±

3.1

5

.7 ±

1.6

2,4

– D

2

46

.9 ±

2.7

4

40

.4 ±

12

4.5

2

4.4

± 1

.6

34

.3 ±

0.5

3

31

.4 ±

25

.0

P

ND

8

.1

6.7

Mec

op

rop

ND

N

D

ND

N

D

ND

N

D

ND

N

D

ND

137

Sum

mar

y o

f es

tim

ated

TW

A c

once

ntr

atio

ns

(ng L

-1)

± S

.D.

of

targ

et p

har

mac

euti

cal

com

pounds

at e

ach s

ampli

ng

loca

tion.

Sam

pli

ng L

oca

tion

s

Ter

cero

Riv

er

Bra

va L

ak

e

Su

qu

ía R

iver

V

illa

Ma

ría

Pu

ente

los

Pro

tero

s

Alm

afu

erte

E

l

Pel

igro

D1

Ta

jam

ar

D1

El

Pel

igro

D2

Up

stre

am

D

ow

nst

rea

m

1

Do

wn

stre

am

2

An

ti-C

an

cer D

rug

s

Tam

oxif

en

N

D

ND

N

D

ND

N

D

ND

N

D

ND

N

D

4-h

yd

rox

yta

mo

xif

en

N

D

ND

N

D

ND

N

D

ND

N

D

ND

N

D

Bic

aluta

mid

e N

D

ND

N

D

ND

N

D

ND

N

D

ND

N

D

Flu

tam

ide

ND

N

D

ND

N

D

ND

N

D

ND

N

D

ND

Nil

uta

mid

e

ND

N

D

ND

N

D

ND

N

D

ND

N

D

ND

Cyp

rote

rone

acet

ate

ND

N

D

ND

N

D

ND

N

D

ND

N

D

ND

ND

(N

ot

Det

ecte

d):

Am

ount

adso

rbed

onto

PO

CIS

wer

e <

LO

D;

P (

Pre

sent)

: A

mounts

adso

rbed

onto

PO

CIS

wer

e <

LO

Q

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