detecting anti-estrogens and anti-androgens in surface...
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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
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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
3.2.1 Chemicals and materials ............................................................................. 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 Results and Discussion ....................................................................................... 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
4.2.1 Chemicals and materials ............................................................................. 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 Results and Discussion ....................................................................................... 84
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
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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
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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
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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
Appendix 11: Summary of estimated TWA concentrations (ng L-1
) ± 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
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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
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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
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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;
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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.
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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
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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
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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
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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
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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).
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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
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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
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(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-
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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
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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.,
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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
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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
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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
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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
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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.
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The hypothesis tested in this study is:
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.
The hypothesis tested in this study is:
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.
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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
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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
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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
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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).
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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.
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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
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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
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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
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(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
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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
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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
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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)
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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.
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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.
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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
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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).
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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
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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
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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
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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.
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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.
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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
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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.
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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.
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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.
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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
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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
3.2.1 Chemicals and materials
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
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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
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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.
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Table 3.1: List of target compounds and the source of contamination for each target
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
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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.
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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.
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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
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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.
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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
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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 Results and Discussion
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
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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
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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.
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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.
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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
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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
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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.
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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.
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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
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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
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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
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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
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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
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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
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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
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<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.,
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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.
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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
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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.
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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.
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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
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(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)
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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
4.2.1 Chemicals and materials
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).
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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.
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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
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(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.
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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.
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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).
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Table 4.1: List of pesticide and anti-cancer therapy target compounds and their usage.
Chemical Family Target Compound Usage
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
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4.3 Results and Discussion
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
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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
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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.
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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
)
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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
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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
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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
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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
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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
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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
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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
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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
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<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 ±
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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
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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).
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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.
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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
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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
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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-
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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
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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-
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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.
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41–7. doi:10.1177/0748233709103033
Yu, Y., Wu, L., Chang, A.C., 2013. Seasonal variation of endocrine disrupting
compounds, pharmaceuticals and personal care products in wastewater treatment
plants. Sci. Total Environ. 442, 310–316. doi:10.1016/j.scitotenv.2012.10.001
Yueh, M.-F., Tukey, R.H., 2016. Triclosan: A Widespread Environmental Toxicant with
Many Biological Effects. Annu. Rev. Pharmacol. Toxicol. 56, 251–272.
doi:10.1146/annurev-pharmtox-010715-103417
Zhang, J., Chang, V.W.C., Giannis, A., Wang, J.Y., 2013. Removal of cytostatic drugs
from aquatic environment: A review. Sci. Total Environ. 445–446, 281–298.
doi:10.1016/j.scitotenv.2012.12.061
Zhang, X., Liu, X., Zhang, M., Dahlgren, R.A., Eitzel, M., 2010. A Review of Vegetated
Buff ers and a Meta-analysis of Their Mitigation Effi cacy in Reducing Nonpoint
Source Pollution. J. Environ. Qual. 39, 76–84. doi:10.2134/jeq2008.0496
Zhao, J.L., Ying, G.G., Liu, Y.S., Chen, F., Yang, J.F., Wang, L., 2010. Occurrence and
risks of triclosan and triclocarban in the Pearl River system, South China: From
source to the receiving environment. J. Hazard. Mater. 179, 215–222.
doi:10.1016/j.jhazmat.2010.02.082
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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
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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
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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
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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
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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
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*
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
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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
Influent Effluent Influent Effluent Influent Effluent
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
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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
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132
Appendix 9: Summary of estimated TWA concentrations (ng L-1
) ± 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
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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
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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
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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
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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
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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