comparing biological responses to contaminants in darters...
TRANSCRIPT
Comparing Biological Responses to Contaminants
in Darters (Etheostoma spp.) Collected from Rural
and Urban Regions of the Grand River
Watershed, Ontario
A thesis submitted to the Committee on Graduate Studies
in Partial Fulfillment of the Requirements for the Degree of Master of Science in the
Faculty of Arts and Science
TRENT UNIVERSITY
Peterborough, Ontario, Canada.
© Copyright by Sam Diamond 2015
Environmental and Life Sciences M.Sc. Graduate Program
September 2015
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Abstract
Comparing Biological Responses to Contaminants in Darters (Etheostoma spp.)
Collected from Rural and Urban Regions of the Grand River Watershed, Ontario.
Sam Diamond
Urban and agricultural activities may introduce chemical stressors, including
contaminants of emerging concern (CECs) and current use pesticides (CUPs) into
riverine systems. The objective of this study was to determine if fish collected from sites
in a river show biomarkers of exposure to these classes of contaminants, and if the
biomarker patterns vary in fish collected from urbanized and agricultural sites. The
watershed selected for this study was the Grand River in southern Ontario, which
transitions from areas dominated by agricultural land use in the north to highly urbanized
locations in the southern part of the watershed. Rainbow darters (Etheostoma caerluem)
and fantail darters (Etheostoma flabellare) were collected from the Grand River in June,
2014 for biomarker analysis from two urbanized sites and three agricultural sites (n=20
per site). Over the same period of time, Polar Organic Chemical Integrative Samplers
(POCIS) were deployed for 2 weeks at each site to monitor for the presence of CUPs and
CECs. The amounts of the target compounds accumulated on POCIS, determined using
LC-MS/MS were used to estimate the time weighted average concentrations of the
contaminants at each site. Data on the liver somatic index for darters indicate site-
specific differences in this condition factor (p<0.05). Significant differences in the
concentrations of thiobarbituric acid reactive substances (TBARS) in gill tissue (p<0.05)
indicate differences in oxidative stress in fish collected from the various sites. Measured
concentrations of ethoxyresorufin-O-deethylase (EROD) in liver tissue were significantly
different between sites (p<0.05), indicating differences in CYP1A metabolic activity.
Finally, acetylcholinesterase (AChE) activity in brain tissue was significantly different
between fish from rural and urban sites (p<0.05). The analysis of these biomarkers
indicates that fish may be experiencing different levels of biological stress related to
different land uses. These data may be useful in developing mitigation strategies to
reduce impacts on fish and other aquatic organisms in the watershed.
Keywords: Biomarkers, darters, land use, POCIS, AChE, TBARS, EROD.
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Acknowledgements
A project of this magnitude could not have been completed by one person within
an appropriate amount of time. Many people helped along the way to achieve the goals
set out for this thesis. All efforts large and small were greatly appreciated, whether they
were simple words of encouragement, or help achieving project milestones, I appreciate it
all and thank everybody involved in the completion of this project.
First off, I would like to thank those involved in all field components of this
project. Craig Murray (Institute for Freshwater Science, Trent University) helped with
the deployment and retrieval of all passive samplers. The days were long and exhausting,
but without Craig’s help this would have been a daunting task. Thank you to the Servos
lab group (University of Waterloo) for their assistance in collecting the fish for this
project. If it wasn’t for their knowledge of the watershed and their portable field lab, fish
collection would have been much more difficult.
Next I would like to thank those involved in the laboratory components of this
project. Thank you to Brenda McIlwain for her patience and assistance in teaching me
the POCIS sampler extraction methods. I would also like to thank Tamanna Sultanna for
her assistance in developing the LC-MS/MS method for fungicide analysis. Their
assistance with POCIS extraction and analysis was greatly appreciated. Thank you to
Jonathan Martin for his tutorials on performing many of the bioassay’s used in this
project.
Finally, I would like to thank Chris Metcalfe (Trent University), Mark Servos
(University of Waterloo), and Gary Burness (Trent University) for their help and
guidance as my supervisory committee. Without their vast knowledge and experience I
would not have been able to complete such an intense, multi-disciplinary project within
the appropriate time. This would not have been possible without the NSERC Discovery
Grant awarded to Chris Metcalfe.
Thank you all. This project was truly a team effort from beginning to end.
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Table of Contents
Abstract
ii
Acknowledgements
iii
Table of Contents
iv
List of Figures
vi
List of Tables
vii
List of Abbreviations
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Chapter 1: Introduction
1
1.0 General Introduction
1
1.1 Biological Response
3
1.2 Municipal Wastewater
8
1.3 Runoff of Contaminants
9
1.4 Passive Sampling
12
1.5 Influences of Land Cover and Use
13
1.6 Project Overview
14
Chapter 2: Biological Responses in Darters (Etheostoma spp.) Exposed to Rural and Urban Influences in the Grand River Watershed, Ontario, Canada 19
1.0 Introduction
19
2.0 Methods and Materials
21
2.1 Materials and chemicals
21
2.2 Study area
21
2.3 POCIS deployment and extraction
22
2.4 POCIS extract analysis
24
2.5 Darter collection
28
2.6 Positive control treatments
28
2.7 Acetylcholinesterase assay
29
2.8 Ethoxyresorufin-O-deethylase (EROD) assay
30
2.9 2-thiobarbituric acid reactive substances (TBARS) assay 31
2.10 Protein assay
32
2.11 Statistical analyses
33
2.12 OFAT III
33
3.0 Results and Discussion
34
3.1 Site characterization
34
3.2 Contaminants
35
3.3 Fish somatic index data
44
3.4 EROD assay validation
46
3.5 EROD
47
3.6 TBARS
50
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3.7 AChE
54
4.0 Conclusion
57
Chapter 3: Conclusions and Future Steps
58
1.0 Major findings
58
2.0 Project objectives and hypotheses
59
3.0 Future work
63
References
64
Appendix 1: POCIS Sampling Rates for PPCPs
78
Appendix 2: POCIS Sampling Rates for CUPs
79
Appendix 3: Fungicide LC-MS/MS Parameters
80
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List of Figures
Figure 1: Study catchment within the Grand River watershed, showing the locations of
the 5 study sites……………………………………………………………………….. 23
Figure 2: Mean EROD activity ± S.E. (pmol/min/mg protein) in livers of rainbow trout
exposed to BNF, and control groups. Significance noted by different letter code
(p<0.05)………………………………………………………………………...….….. 46
Figure 3: Mean EROD activity ± S.E. (pmol/min/mg protein) in livers of rainbow darters
at each of the five sites. Significance noted by different letter code
(p<0.05)………………………………………………………………………………. 48
Figure 4: Comparison of mean EROD activity ± S.E. (pmol/min/mg protein) in livers of
rainbow (RBD) and fantail (FTD) darters at the rural sites.....…………………..…... 49
Figure 5: Mean levels of TBARS ± S.E. (nmol per g) in gill tissue collected from rainbow
darters sampled from each of the five sites. Significance is noted by different letters
(p<0.05)………………………………………………………………………………. 53
Figure 6: Comparison of mean levels of TBARS ± S.E. (nmol per g) in gill tissue
collected from rainbow (RBD) and fantail (FTD) darters sampled from each of the three
rural sites. ……………………………………………………………………..….…. 53
Figure 7: Mean AChE activity ± S.E. (µmol/min/mg protein) in brain tissue of rainbow
darters at all five sites. Significance noted by different letter (p<0.05)…………..….56
Figure 8: Comparison of mean AChE activity ± S.E. (µmol/min/mg protein) in brain
tissue of rainbow darters and fantail darters collected at the rural sites.
…………………………………………………………………...…………..…….... 56
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List of Tables
Table 1: List of all targeted analytes for POCIS analysis…………………………… 26
Table 2: Targeted fungicides, herbicides, biocides, and I.S. with the used MRM
transitions....................................................................................................................... 27
Table 3: OFAT III generated data on catchment area for each of the 5 sampling sites,
with the corresponding area for each land cover type (km2). Sites are arranged from
furthest upstream to the furthest
downstream………………………………………………………………………….... 35
Table 4a: Mean estimated TWA concentrations (ng/L) ±S.D. of CUPs at each of the five
study sites…………………………………………………………………………...… 42
Table 4b: Mean estimated TWA concentrations (ng/L) ±S.D. of CECs at each of the five
study sites………………………………………………………………………….……43
Table 5: Somatic index data for rainbow and fantail darters sampled at 5 locations in the
Grand River, including length, weight, liver somatic index (LSI) and condition factor (k).
Significant differences between sites are shown by a different letter code, and significant
differences between species are shown by a dagger symbol………………………….. 46
Table A1: Mean (±SD) sampling rates (Rs) in litres per day determined for the target
compounds in POCIS in static experiments at 15oC (n=3). Sampling rates were
determined by Li et al. (2010b)……………….………………………………………. 78
Table A2: Mean (±SD) sampling rates (Rs) in litres per day determined for the target
compounds in POCIS in static experiments at 20oC (n=3). Sampling rates were
determined by Metcalfe et al.
(submitted)……………………………………………..……………………………….79
Table A3.1: Ionization parameters for the pesticides targeted in this study………..….80
Table A3.2: Ionization parameters for all pesticide surrogates used in this study…… 81
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Table A3.3: Pesticide analytes with their corresponding I.S. used in the present
study…………………………………………………………………………………....82
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List of Abbreviations
7-ER: 7-ethoxyresorufin
Ach: Acetylcholine
AChE: Acetylcholinesterase
AhR: Arylhydrocarbon receptor
BMP: Best management practice
BNF: β-napthaflavone
BSA: Bovine serum albumin
CECs: Contaminants of emerging concern
CUPs: Current use pesticides
CYP450: Cytochrome P450
DMSO: Dimethyl sulfoxide
EROD: Ethoxyresorufin-O-deethylase
FTD: Fantail darter
GIS: Geographical Information Systems
HPLC: High pressure liquid chromatography
I.P. Injection: Intraperitonial injection
I.S.: Internal standard
k: Condition factor
Kow: Octanol-water partition coefficient
LC-MS/MS: Liquid chromatography tandem mass spectrometry
LMB: Liquid municipal biosolids
LOD: Limit of detection
LSI: Liver somatic index
MDA: Malondialdehyde
MRM: Multiple reaction monitoring
MWWE: Municipal wastewater effluent
NSAIDs: Non-steroidal anti-inflammatory drugs
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OFAT III: Ontario flow assessment tool III
OMNRF: Ontario Ministry of Natural Resources and Forestry
OPs: Organophosphate pesticides
pKa: Acid dissociation constant
POCIS: Polar Organic Chemical Integrative Sampler
PPCPs: Pharmaceuticals and personal care products
RBD: Rainbow darter
Rs: Sampling rate
S.D.: Standard deviation
S.E.: Standard error
TBA: Thiobarbituric acid
TBARS: 2-thiobarbituric acid reactive substances
TWA: Time weighted average
WWTP: Wastewater treatment plant
λ: Wavelength
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Chapter 1: Introduction
1.0 General introduction
A variety of contaminants are discharged into aquatic ecosystems from both point and
non-point sources (Tetreault et al. 2011; Metcalfe et al. 2008; Li et al. 2009). Many
aquatic organisms, including fish, have been shown to exhibit biological responses when
exposed to organic contaminants discharged in municipal waste water effluent (MWWE)
and in run off from urban and rural areas (Shelley et al. 2012; Lissemore et al. 2006;
Balch et al. 2004). Pharmaceuticals and personal care products (PPCPs) discharged in
MWWE as well as pesticides used to control fungal and plant pests in agriculture and turf
care have been shown to elicit a variety of sub lethal biological responses in fish,
including increased prevalence of gonadal intersex, increased gonadosomatic and
hepatosomatic indices, developmental deformities in early and late life stages, induction
of oxidative metabolism enzymes, inhibition of acetylcholinesterase and, an increase in
reactive oxygen species (Tanna et al. 2013; Tetreault et al. 2011; Smith and Wilson 2010;
Cattaneo et al. 2008).
In order to monitor for the presence of PPCPs and pesticides, it is necessary to
measure the concentrations of these compounds at a variety of sites that are influenced by
point and non-point sources of these contaminants. Although collecting grab samples is a
cost effective method for monitoring contaminants in the aquatic environment, it is often
less reliable when compared to other monitoring methods due to the potential of missing
peak events or only sampling during periods of high input (Bundschuh et al. 2014;
Rujiralai et al. 2011). To obtain data that reflects concentrations over a longer period of
time, the Passive Organic Chemical Integrative Sampler (POCIS) can be deployed for an
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extended period of time (2 – 4 weeks) and will provide a time weighted average (TWA)
concentration for that site during the time of deployment (Li et al. 2010; Metcalfe et al.
2014). Extracts prepared from the use of POCIS also offer a less complex matrix
compared to extracts from other samples and therefore may result in higher quality
analytical data.
While sampling in surface waters to determine the presence of PPCPs and pesticides
using analytical methods provides data on the concentrations of specific compounds of
interest, these analytical data do not indicate the biological impacts of the contaminants to
aquatic organisms. In addition, analytical monitoring focuses on the target compounds
included in the analytical method and cannot indicate exposure to other unknown
chemicals present in the environment. In situ biomarker studies can indicate whether
there are impacts on biota within the system. While there are many different organisms
within an aquatic system that can be used as viable indicator species, fish are often used
in biomarker studies due to their complex biological responses to contamination (Bolger
and Connolly 1989). When there is a decline in water quality due to the presence
contaminants, fish may show responses through somatic changes, such as liver somatic
index (LSI), gonadosomatic index (GSI), as well as length – weight relationships when
compared to the seasonal average (Bolger and Connolly 1989; Tetreault et al. 2012).
Fish may also react to exposure to contaminants on a biochemical level through increases
or decreases in several biological parameters, including inhibition of neurotransmitter
function, an increase in metabolic enzyme activity and an increase in oxidative stress
(Scornaienchi et al. 2010; Sumith et al. 2012; Cattaneo et al. 2008).
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As land cover and land use changes across a region, so do the classes and
concentrations of contaminants present in the aquatic environment (Metcalfe et al. 2000;
Countway et al. 2003). For example, higher concentrations of pesticides would be
expected in an agricultural area, although inputs of these compounds may be mitigated by
the use of best management practices such as large riparian buffer zones adjacent to
surface waters. Likewise, higher concentrations of PPCPs would be expected in surface
waters in urban areas that are downstream of municipal wastewater treatment plants,
although investment in advanced wastewater treatment technologies could mitigate these
exposures. Therefore, fish and other aquatic organisms are subject to different levels of
exposure throughout a watershed, so sampling within one land cover type is not
representative of contaminant impacts over the entire watershed. By monitoring
responses in fish across different land covers within a watershed, it is possible to identify
how biological responses are influenced by the contaminants present and which portions
of the watershed exhibit the greatest impacts on fish. This becomes a powerful tool when
trying to identify and prioritize best management practices or technological solutions
across a watershed to reduce the impacts of contaminants to aquatic organisms.
1.1.Biological responses
Exposure of an organism to a biological, chemical or physical stressor induces
some form of biological response (Ings et al. 2011a/b; Uno et al. 2011; da Fonseca et al.
2008). Biological responses observed in situ may be early indicators of a population
based response (Bravo et al. 2011). The two main descriptors for biological responses
are “acute” and “chronic”. Acute responses refer to short term, high intensity events that
usually occur within 96 hours of initial exposure and usually cause organism mortality.
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While these endpoints are useful for determining the concentrations at which toxic effects
occur, they are typically less commonly observed in the natural environment. Chronic
responses are sublethal endpoints that usually develop at environmentally relevant
concentrations and last over long periods of time, ranging from days to years. Many
organisms, including fish, express a variety of sublethal responses, including: a change in
the length – weight ratio (ie. condition factor) compared to the seasonal mean, an increase
in LSI and GSI, physical abnormalities, gonadal intersex and, a variety of biochemical
fluctuations which regulate metabolism (Jasinka et al. 2015; Rajakumar et al. 2012;
Tetreault et al. 2011; Metcalfe et al. 2001).
Somatic indicators of exposure are rapid and relatively simple methods for
assessing the health of fish (Farkas et al. 2002; Bolger and Connolly 1989). These
methods may be either invasive or non-invasive. Commonly used, non-invasive physical
indicators include the condition factor (i.e. length to weight ratios), the presence of
tumors or other lesions around the mouth or body of the fish, secondary sex
characteristics as indicators of intersex (e.g. male fish with an ovipositor), physical
abnormalities such as spinal curvatures, etc. Invasive indicators include the LSI and GSI
compared to seasonal means, numbers of internal parasites or lesions, and the presence of
gonadal intersex. Many contaminants from municipal waste water (MWW) or from
agricultural origins have been shown to inhibit the growth of fish, as well as increase the
LSI and GSI of the organism (Anderson et al. 2015; Farkas et al. 2002). While somatic
indicators may be an effective measure of exposure to a chemical stressor, they may not
always be observed at environmentally relevant concentrations (Arellano – Aguilar et al.
2009). In addition, somatic changes may be induced by other stressors other than
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exposure to chemicals, such as changes in water temperature, pathogenic diseases,
invasive species or availability of food resources.
Biochemical responses, usually referred to as “biomarkers”, have been widely
used to evaluate whether fish are responding to exposures to waterborne pollutants.
Many biomarkers of exposure are compound specific and therefore will usually only be
regulated by specific classes of compounds. However many different compounds may
induce multiple biomarkers simultaneously (Smith and Wilson 2010; Sturve et al. 2008).
For example, several different pesticides, including diuron and atrazine have been shown
to induce oxidative stress, as well as inhibit acetylcholinesterase in fresh water fish
(Ahmed et al. 2012; Rossi et al. 2011). Biomarkers responses will vary, depending on
the compounds to which the organisms are exposed. For example, the activity of the
metabolic enzyme, ethoxyresorufin-O-deethylase is upregulated in fish by exposure to β
– napthoflavone, but is down regulated by hexabromo-cyclododecane (Martin et al. 2013;
Du et al. 2015).
In this study, the biomarkers used to assess exposure to contaminants in fish
included an indicator of oxidative stress, inhibition of an enzyme associated with
neurotransmission with cholinergic nerves, and changes in enzyme activity associated
with two classes of cytochrome P450 microsomal enzymes. The mechanisms by which
these biomarkers ca be used to indicate exposure to contaminants of specific classes are
discussed below.
1.1.1 Acetylcholinesterase
Acetylecholinesterase (AChE) is critical to the transmission of the acetylcholine
(ACh) as it responsible for terminating transmission at the synaptic cleft. As AChE
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inhibition increases in severity, the organism’s nervous system becomes overstimulated,
resulting in mortality, generally as a result of respiratory failure (Bretaud et al. 2000).
For fish exposed to chemicals that inhibit AChE, respiration is impaired and swimming
becomes more erratic, and this results in mortality (Bretaud et al. 2000).
Organophosphate (OPs), neonicotinoid and, carbamate insecticides are commonly used
throughout agricultural and urban areas and have been shown to inhibit AChE activity in
freshwater fish (Anderson et al. 2015; Xing et al. 2013; Xuereb et al. 2009). Due to the
extensive use of pesticides throughout diverse landscape, AChE can be used as a
biomarker of exposure to pesticides across different land uses.
1.1.2. 2-thiobarbituric acid reactive substances (TBARS)
Oxidative stress is the result of an overwhelming assault of reactive oxygen
species (ROS) on fatty, lipid rich substrates within an organism (Oakes et al. 2004; Kelly
et al. 1998). When ROS overwhelms the endogenous protection mechanisms within the
cells of an organism such as antioxidants and specific degradative enzymes, the result is
cellular damage. There are many ways to quantify oxidative stress within an organism
(Rossi et al. 2011; Oakes and Van der Kraak 2003). One of the most common methods is
through the production of 2-thiobarbituric acid reactive substances (TBARS). TBARS
are measured by the reaction of malondialdehyde (MDA), a degradation product of lipid
peroxidation, with 2-thiobarbituric acid (TBA). An elevation in TBARS within an
organism may be induced by exposure to a variety of organic contaminants, including
PPCPs, pesticides and, domestic and industrial wastewater (Nunes et al 2015; Scarcia et
al. 2012). Since the induction of TBARS has been observed in fish exposed to a variety
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of different contaminants, it is a viable indicator of exposure to a range of waterborne
contaminants.
1.1.3. Cytochrome P450
The cytochrome P450 (CYP450) family of monooxygenase enzymes is
responsible for the oxidative metabolism of xenobiotics in organisms, including fish
(Maier et al. 2014; Smith and Wilson 2010; Codi et al. 2004). There are 50 different
isoforms in the CYP450 family of enzymes are more easily induced by certain chemical
classes than others. For instance, changes in the activity of CYP450 enzymes have been
used as biomarkers of exposure to PPCPs, fungicides and herbicides (Scornaienchi et al.
2010; Hernandez-Moreno et al. 2008). For example, CYP4501A (CYP1A) is usually
induced by exposure to agonists of the aryl hydrocarbon receptor (AhR), such as
polycyclic aromatic hydrocarbons (PAHs), dioxins and other planar halogenated
compounds, and some pesticides such as organochlorine pesticides, OPs and carbamates
(Karaca et al. 2014; Whyte and Tillit 2000; Hodson et al., 1996). Other CYP450
isoforms such as CYP4503B (CYP3B) have been shown to indicate exposure to
pharmaceuticals. While all members of the CYP450 family may show some response to
PPCPs, CYP3B is the primary indicator of exposure in vertebrates (Smith et al. 2012;
Smith and Wilson 2010). Thus, the superfamily of CYP450 enzymes can be used as an
indicator of exposure to a variety of contaminants originating from rural and urban
sources.
The increase in catalytic activity of ethoxyresorufin-O-deethylase (EROD) is a
common biomarker of CYP1A activity in an organism (Hodson et al. 1996). EROD
activity describes the rate at which CYP1A catalyzes the de-ethylation of the substrate, 7-
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ethoxyresorufin (7-ER) to form the fluorescent product, resorufin (Maier et al. 2014;
Martin et al. 2013; Whyte and Tillit 2000). The catalytic activity is an indication of the
amount and/or activity of the enzyme present in the tissue sample (Whyte et al. 2000).
This study will focus on CYP1A in the livers of fish to monitor for differences in
oxidative metabolism between study sites.
1.2. Municipal wastewater
A major point source of contaminants in aquatic ecosystems is the discharges
from municipal wastewater treatment plants (Helm et al. 2012; Wang et al. 2012;
Metcalfe et al. 2009). Several contaminants of emerging concern (CEC) associated with
municipal wastewater effluents (MWWE) have been linked to biological responses in
aquatic organisms, including fish (Helena et al. 2013; Togunde et al. 2012; Tetreault et al.
2011; Gagne et al. 2006; Metcalfe et al. 2001). Wastewater treatment plants (WWTPs)
operate at several different levels of efficiency and are diverse in the technologies
employed between municipalities (Holeton et al 2011). The wastewater treatment
process begins by removing large debris including gravel, sand and, garbage utilizing a
screen and settling tank. Secondary treatment focuses on removing the remaining
suspended and particulate matter from the wastewater using clarifiers (i.e. physical
settling), followed by aerobic digestion (i.e. microbial activity). Solid matter (i.e. sludge)
that settles out of suspension is often sent to anaerobic digesters for treatment, which can
include production of biogas which is used to generate electricity. Some WWTPs
employ a tertiary treatment step designed to remove dissolved organic matter,
phosphorous and other nutrients, or residual contaminants. However, this step is not
commonly used in WWTPs in North America. The final effluent then undergoes a
9
disinfection process, which is usually by chlorination or UV-irradiation in North
American WWTPs.
In Canada, most municipal WWTPs typically do not include a tertiary treatment
step; although many of these plants are now being upgraded. Municipal WWTPs that use
chlorination for disinfection have been shown to have higher concentrations of CECs in
their effluent, compared to WWTPs that disinfect using ozonation or UV-irradiation prior
to effluent discharge (Gurke et al. 2015a; Rodayan et al. 2014; Larcher et al. 2012).
Although there is a trend in Canada to improve treatment, the introduction of CECs into
the aquatic environment and into sources of drinking water through discharges of
MWWE still remains a concern (Metcalfe et al. 2014; Servos et al. 2005). The presence
of PPCPs in Canadian surface waters is generating concern due to the capacity of PPCPs
to induce sublethal responses in fish at low concentrations (Jasinka et al. 2015; Johnson et
al. 2015; Ings et al. 2011b; Tetreault et al. 2011). In some cases, wastewater treatment
has been shown to increase the concentrations of PPCPs throughout the treatment
process. For example, many prescribed pharmaceuticals are conjugated in the human
body with large biomolecules (e.g. glutathione, glucuronide) in order to facilitate
excretion (Gurke et al. 2015a/b; Gracia – Lor et al. 2012). During the treatment process,
these compounds may de-conjugate and are released as the parent compound in the final
effluent (Gurke et al. 2015a).
1.3. Runoff of contaminants
Runoff of contaminants from the terrestrial environment into the aquatic
environment is a continuing concern in urban and rural areas (Kurt-Karakus et al. 2011;
Li et al. 2009; Metcalfe et al. 2008) Typically the peak season for runoff of contaminants
10
in Canada is from April to late May, as this coincides with the spring freshet, as well as
the pre-growing season of most crops, and the post-winter maintenance of turf (Moreau-
Guigon et al. 2007). For chemicals applied to agricultural souls, both surface and sub-
surface (typically through tile drainage) runoff peaks after the first major rain event. The
rates of chemical runoff are mediated by several factors including the physical and
chemical properties of the chemicals, the quality and extent of riparian buffer zones, the
volume and duration of precipitation and, the permeability of the soils (Moore et al. 2014;
Struger et al. 2004).
The physicochemical properties of a compound strongly influence whether or not
it is readily transported to aquatic ecosystems (Palma et al. 2015). Attributes such as
water solubility, volatility, KOW, pKa and, chemical degradation rates greatly influence
the potential for runoff of a pesticide (Struger et al 2004; Poissant et al 2008). Certain
compounds that have a lower water solubility, short half-life and a higher affinity for
binding to the organic matter present in soils will be less susceptible to runoff during a
rainfall event.
Riparian buffers are considered a best management practice (BMP) for mitigating
surface runoff into the aquatic environment (Weissteiner et al. 2014; Bereswill et al.
2012). A healthy riparian buffer zone consists of a substantially vegetated area that
separates clear cut areas from waterbodies. In the absence of a healthy riparian buffer,
there is an increase in runoff directly entering the aquatic environment, which introduces
higher volumes of particulate matter, including soils, along with recently applied current
use pesticides (CUPs) that are still present on the surface or that have bound to surface
soils.
11
Many of the CUPs used in Canada have been shown to have impacts on
freshwater fish. Sub-lethal responses including endocrine disruption, oxidative stress,
AChE inhibition and, CYP450 enzyme induction have been observed in fish exposed to
CUPs in toxicity studies (Rajakumar et al 2012; Shelley et al. 2012; da Fonseca et al
2008; Metcalfe et al. 2008). Fish express toxic responses to many CUPs at low
concentrations. CUPs have been detected in both rural and urban surface waters in
Canada, and they are not necessarily geographically confined to areas of high use (Byer
et al. 2011; Garcia-Ac et al 2009; Poissant et al 2008).
Some agricultural lands are subject to the application of biosolids, which typically
consists of treated sludge from WWTPs (Wallace et al. 2013). Often biosolids contain
residuals of PPCPs from the wastewater treatment process (Wallace et al. 2013;
Gottschall et al. 2012). Rainfall events occurring post application of biosolids may lead
to the introduction of PPCPs, artificial sweeteners and other compounds commonly found
in MWWE. Many of these compounds, such as triclosan, have the potential to move into
the tile drainage of an agricultural field during a rain event where it is then transported
into aquatic environment (Topp et al 2008; Lapen et al. 2008). The potential for transport
into surface waters is greatly dependant on the application method used (Edwards et al
2009; Sabourin et al. 2009). Liquid municipal biosolids (LMB) applied via injection
have been shown to facilitate quick movement of PPCPs through soils into tile drainage
systems where they are easily released into surface waters following rain events (Lapen et
al. 2008). Dewatered biosolids have been shown to have a slower release rate of PPCPs
when compared to LMB, which aids in the degradation of PPCPs prior to entry into
surface waters (Edwards et al. 2009; Sabourin et al. 2009).
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1.4. Passive sampling
Monitoring for the presence of CECs within a watershed can be conducted using a
variety of sampling techniques and technologies. Many WWTPs employ time flow
proportional (TFP) sampling to actively monitor for target compounds present in different
stages of treatment (Gurke et al. 2015a; Verlicchi et al. 2012). TFP sampling has the
benefit of being accurate for generating 24-h composite samples. However it is generally
too expensive and difficult to use in a field study due to its running costs and need for
electrical power. Grab samples are an inexpensive method for acquiring sample but there
is a high risk of sampling bias towards the time of collection and the risk of missing
critical events, such as increases in flow rates and chemical input (Bundschuh et al 2014).
Passive sampling offers a relatively inexpensive, low maintenance and, reliable option for
estimating contaminant concentrations over a period of time (Helm et al. 2012; Li et al.
2009).
The Polar Organic Compounds Integrative Sampler (POCIS) is a passive
sampling technology widely used to monitor for PPCPs, endocrine disrupting chemicals
and pesticides over a time period of several weeks (Metcalfe et al. 2014; Kaserzon et al.
2014; Miege et al. 2012; Mazzella et al. 2008). POCIS passive samplers contain a solid
phase sorbent trapped between two permeable membranes, held together with a stainless
steel washer and, placed in a stainless steel cage designed to allow water to freely flow
through the sampler while keeping out debris that may damage the POCIS. Organic
pollutants are concentrated into the solid phase sorbent, where they remain relatively
stable throughout their deployment period.
13
After deployment, the POCIS are disassembled and the sorbent is extracted using
an organic solvent, which is typically methanol. The extracts are then evaporated and
brought to final volume where they can be analyzed via liquid chromatography coupled
with tandem mass spectrometry (LC-MS/MS). Data from the analysis of POCIS extracts
can be used to estimate the time weighted average (TWA) concentration of target
contaminants at a site over the period of deployment. Sampling rates (Rs) in litres per
day for each target compound are determined experimentally in the lab at different
temperatures to generated TWA concentrations under different environmental conditions.
Due to their ability to remain deployed unattended for an extended period of time,
POCIS offer an inexpensive alternative to TFP sampling, and a more robust alternative to
grab samples. Extended periods of deployment mean that peak events occurring during
that time will be accounted for, and the sample is ultimately more representative of the
site concentration when compared to the snap shot provided by using conventional grab
sampling techniques.
1.5. Influences of land cover and use
As outlined in previous sections of this chapter, there are multiple sources
contributing to the contamination of the aquatic environment, particularly in riverine
systems. Rural and urban areas both have the potential to introduce contaminants into
riverine systems (Kurt-Karakus et al 2011; Metcalfe et al. 2010). However, due to
differences in land use and population sizes between rural and urban areas, contaminants
may be introduced into watersheds at different rates. For instance, there may be
differences in PPCP concentrations in effluents of WWTPs due to differences in
population size and prescription rates (Gurke et al. 2015b). Areas of higher population
14
are more likely to have upgraded WWTPs to manage the higher volume of municipal
influent. On the other hand, in rural areas, concentrations of CUPs will most likely be
higher than in urban areas due to land usage for agriculture (Byer et al. 2011; Garcia-Ac
et al. 2009). Golf courses and other urban turf care practises may introduce contaminants
into riverine systems (Metcalfe et al., 2008); but it would be expected that the total
application volume of CUPs in urban areas will be less than in rural areas.
When considering these factors it becomes clear that land use patterns and land
cover within watersheds may have an influence on biological responses in aquatic
organisms, including fish. In order to monitor biological responses in fish from areas
with different land uses and covers, it is first necessary to characterize exactly what
differences in land use are occurring within a watershed. The Ontario Flow Assessment
Tool III (OFAT) is a coarse, watershed delineation tool developed by the Ontario
Ministry of Natural Resources and Forestry (OMNRF). By analyzing topographic
features and archived flow data, OFAT is an effective tool for creating maps of catchment
areas and calculating the different land uses, as well as land cover types within a
catchment.
1.6.Project overview
By analyzing in situ biomarkers of exposure to contaminants, it is possible to
evaluate the impacts of chemical contaminants on fish in a watershed between sites
dominated by rural or urban influences. Physical traits, such as deformities and intersex,
along with biochemical indicators such as oxidative stress, metabolic enzyme induction
and, neurotransmitter inhibition can be used to monitor sub-lethal responses associated
with exposure to waterborne pollutants. In this study, two species of darters (Etheostoma
15
sp.) were collected from sites primarily experiencing agricultural or urban influences in
the Grand River watershed in southern Ontario. The rainbow darter (E. caerulem) was
collected across all sites and the fantail darter (E. flabellare) was collected only at the
agricultural sites, allowing for response comparisons between the two species. Darters
were selected due to their overall abundance and range throughout the Grand River
watershed, as well as their previous use as indicator organisms for exposure to chemical
contaminants (Wang et al. 2012; Tetreault et al. 2011; Brown et al. 2011). Rainbow and
fantail darters feed on small aquatic invertebrates in the benthic community of rivers and
streams. Both species of darters reach sexual maturity within one to two years, and
change microhabitats from rapids into cobble pools within the stream during their mating
season (Hubbs 1985). In addition, these fish species are philopatric and stay within a
home range of a few square meters throughout their entire life history (Hubbs 1985).
The Grand River watershed covers a substantial portion of southern Ontario, with
a total catchment area of 6,965 km2 (GRCA 2005). With a total reach of around 300 km,
the Grand River watershed stretches from as far north as Dundalk, Ontario and ultimately
drains at Port Maitland into Lake Erie. As a result of its large size, the Grand River
watershed is highly diversified in terms of its land use and coverage, having a range of
activity from low intensity agriculture to dense urban centers. Due to this diverse
landscape, the watershed is impacted by several classes of chemical contaminants which
enter through point and non-point sources.
Many contaminants associated with urban and agricultural land use types have
been shown to induce toxic responses in aquatic organisms, including fish (Vajda et al.
2008; Whitehead et al. 2004). Since the Grand River watershed is so diverse in terms of
16
waterborne pollutants and land uses, it is essential to monitor responses across sites
experiencing both rural and urban influences in order to identify the sources of the
contaminants that impact the watershed. Once these responses are understood, it may be
possible to develop mitigation strategies, such as the use of BMPs in agricultural areas
and installation of advanced wastewater treatment technologies in urban areas. While it is
useful to monitor waters for contaminants known to induce toxic responses using
analytical techniques, this approach cannot indicate whether there are biological impacts
on fish and other aquatic organisms.
Two approaches to monitoring were employed for this project: i) contaminant
monitoring, and ii) biomarker analysis. Sites were monitored for contaminants using
POCIS passive samplers, as they offer the ability to calculate the estimated TWA during
their time of deployment for a diverse group of organic compounds (i.e. PPCPs and
CUPs). Analysis of the POCIS extracts was conducted using LC-MS/MS, which allows
for the detection of organic compounds at trace concentrations. Biomarker analysis was
performed for several known indicators of exposure to waterborne contaminants. Two
species of darters were sampled for brain, liver and, gill tissue, which were analyzed for
AChE inhibition, CYP1A induction and, TBARS respectively, using spectrophotometric
and fluorescence methods. Biomarker responses were compared across sites influenced
by rural (n=3) and urban (n=2) land uses within the Grand River watershed. To assess the
severity of the response, the measured biomarker responses were compared to data from
the literature where fish were similarly exposed. Hepatosomatic indices and condition
factors were analyzed to compliment biomarker response data.
17
Differences in biomarker responses are expected between the rural and urban
study sites. Inhibition of AChE is expected in the agricultural portions of the watershed
due to a greater presence of CUPs, while greater induction of CYP450 enzymes and
TBARS are expected at sites more strongly influenced by urban development, including
WWTPs. A relationship is expected between targeted contaminants measured in POCIS
extracts and biomarker responses in darters. However, there may be impacts on fish from
contaminants that were not monitored using the passive samplers. Overall a trend of
increasing biomarker response is expected heading downstream, due to cumulative
effects from agricultural and urban areas.
It is expected that the cumulative influence of contaminants from the different
land types will result in increased biomarker responses in darters collected in the Grand
River. Fish collected at the urban sites are expected to have more severe biological
responses compared to those collected at the rural sites due to an increase in contaminant
inputs and cumulative effects from upstream and downstream sources. Fish collected at
the most downstream sites in both rural and urban areas are expected to have the highest
levels of biological response due to cumulative effects from several contaminant inputs
(i.e. agriculture, WWTPs, golf courses, etc.).
The objectives for this study are:
1) To determine the presence of several targeted organic chemical contaminants
linked to agricultural and municipal wastewater sources at study sites within the
Grand River watershed.
2) To evaluate biomarkers of exposure to contaminants in darter species collected
from agriculturally and urban impacted sites.
18
3) To compare biomarker responses between two species of darters collected at the
agriculturally impacted sites.
My hypotheses are as follows:
H1: Darters collected at the study sites will display biological responses indicative of
exposure to chemical contaminants from agricultural and urban origins.
H2: Biomarker responses in fantail and rainbow darters collected at the same locations
in the Grand River will not be significantly different; indicating similar sensitivities of
these species to exposure to chemical contaminants.
H3: Estimated concentrations of chemical contaminants at the darter collection sites in
the Grand River will increase with distance downstream due to cumulative exposures,
and biomarker responses will reflect exposure to specific chemicals.
19
Chapter 2: Biological Responses to Contaminants in Darters
(Etheostoma spp.) Collected from Rural and Urban Regions of
the Grand River Watershed
1.0 Introduction
Contaminants from both point and non-point sources are discharged into riverine
systems (Tetreault et al. 2012; Metcalfe et al. 2008). As land use patterns change, so do
the primary chemical stressors (Byer et al. 2011; Countway et al. 2003). Municipal
wastewater treatment plants (WWTPs) and surface runoff are common contributors of
pharmaceuticals and personal care products (PPCPs), artificial sweeteners, and current
use pesticides (CUPs) into riverine systems (Li et al. 20009; Edwards et al. 2009; Struger
et al. 2004). Several contaminants of emerging concern (CECs), including PPCPs and
CUPs have been shown to induce sublethal responses in fish at environmentally relevant
concentrations (Jasinka et al. 2015; Shelley et al. 2012; Bereswill et al. 2012). Common
biological indicators of exposure in fish include increased prevalence of gonadal intersex,
increased gonadosomatic and hepatosomatic indices, physiological deformities in early
and later life stages, induction of oxidative detoxification enzymes, inhibition of
acetylcholinesterase (AChE) and an increase in impacts from reactive oxygen species
(Tanna et al. 2013; Tetreault et al. 2011; Smith and Wilson 2010; Cattaneo et al. 2008).
The sampling and analysis of surface waters for the presence of CECs is an
important tool in understanding the frequency and magnitude of concentrations within
riverine systems, but this approach does not indicate impacts on biota. In situ biomarker
studies in combination with environmental sampling allows for a more holistic approach
to monitoring the impacts of CECs in riverine systems (Jasinska et al., 2015; Fonseca et
al., 2011; Vajda et al. 2008). When there is a degradation of water quality due to the
20
presence contaminants, fish may show responses through somatic changes such as liver
somatic index (LSI), as well as length – weight relationships when compared to the
seasonal average (Bolger and Connolly 1989; Tetreault et al. 2012). Fish may also react
to exposure to contaminants on a biochemical level through increases or decreases in
several biological parameters, including neurotransmitter inhibition, an increase in
metabolic detoxification activity and an increase in oxidative stress (Scornaienchi et al.
2010; Sumith et al. 2012; Cattaneo et al. 2008).
This project aims to monitor the biological responses in fish collected at
agriculturally impacted and urban impacted sites throughout the Grand River watershed
in southern Ontario, Canada. Female rainbow darters (Etheostoma caerluem) and fantail
darters (Etheostoma flabellare) were sampled across five study sites, including three rural
sites and two urban sites. The darters were analyzed for the induction of Phase I
microsomal enzymes (CYP1A), the TBARS indicator of oxidative stress, and AChE
inhibition. The passive organic chemical integrative sampler (POCIS) passive sampler
was used to monitor for CECs at each of the five study sites. Previous studies have
typically focused on the response of a single species in areas influenced by either rural or
urban chemical stressors. This study aims to compare the responses of darters exposed to
chemical contaminants in urban and rural sites. It is expected that there will be
differences in the biological responses of darters between the five study sites, and that
they will be reflective of the estimated time weighted average concentrations of
contaminants known to induce the selected biomarkers.
21
2.0 Methods and Materials
2.1. Materials and chemicals
Analytical standards for all target compounds were purchased from Sigma
Aldrich Canada (Oakville, ON, Canada) and their stable isotope surrogates were
purchased from C/D/N Isotopes (Pointe-Claire, QC, Canada), except for the surrogate for
sucralose, which was purchased from Toronto Research Chemicals (Toronto, ON,
Canada). Ammonium acetate was also purchased from Sigma Aldrich Canada. All stock
solutions for analysis were made up in HPLC grade methanol (VWR International,
Mississauga, ON, Canada). Acetonitrile and hexane were HPLC grade and were
purchased from VWR International, Mississauga, ON, Canada). Glacial acetic acid and
reagent grade acetone were purchased from ACP Chemicals (Montreal, QC, Canada).
The POCIS containing Waters OASIS HLB sorbent were purchased from Environmental
Sampling Technologies (St. Joseph, MO, USA). For protein determination, the Bio-Rad
Protein Assay Reagent was purchased from Bio-Rad Laboratories Canada (Mississauga,
ON, Canada). The sources of the bioassay reagents are listed in the sections describing
these methods.
2.2. Study area
This study focused on sampling at sites located within the Grand River watershed
in southern Ontario, Canada. The Grand River watershed covers a total area of 6965 km2
and is comprised of densely populated urban centers, small towns and a large agricultural
landscape (GRCA 2005), although the landscape is changing due to an increasing
population. By the year 2051 the Grand River Conservation Authority predicts that there
22
will be 1,530,000 people living within the watershed compared to approximately 960,000
inhabitants residing there today.
Figure 1 illustrates the locations of the 5 study sites. The three upstream sites at
Gordonville (43°54’15.70” N, 80°32’48.32” W), Petherton (43°52’20.72” N,
80°35’21.91” W), and FMCDS (43°49’32.60” N, 80°36’58.58” W) are primarily
dominated by agricultural and rural land use, with small rural communities. The two
downstream sites at Horse Ranch (43°24’05.43” N, 80°25’44.57” W) and Pioneer Tower
(43°23’55.87” N, 80°24’58.32” W) are located within the city of Kitchener, Ontario.
Horse Ranch is located 500 m upstream from the Doon WWTP serving the city of
Kitchener, and Pioneer Tower is located approximately 500 m downstream of the Doon
wastewater discharge. According to the Ontario Clean Water Agency’s Performance
Assessment Report in 2008, the Doon WWTP services approximately 211,000 people,
with an average daily discharge of about 74,000 m3/day. In 2012-13, the Doon WWTP
was upgraded with a new UV-irradiation disinfection system, and an upgrade to Plant 2
with the installation of fine bubble diffusers to the aerobic treatment system.
2.3. POCIS deployment and extraction
All POCIS were stored at -20°C prior to the deployment. The POCIS were
deployed in stainless steel cages which had been previously solvent washed with HPLC
grade hexane and reagent grade acetone. All POCIS were deployed from June 18th to
July 7th, 2014. POCIS cages were secured between two steel posts, facing the direction
of flow, with the cages positioned approximately 20 cm from the bottom. . One cage
containing three POCIS was deployed at each of the five sites. During the deployment
23
and retrieval of the POCIS, trip blanks were exposed to the atmosphere to monitor for
contamination that may occur when preparing the samplers.
Figure 1: Study catchment within the Grand River watershed, showing the locations of
the 5 study sites.
Upon retrieval, all POCIS were gently cleared of any debris, wrapped in clean foil
and temporarily stored in a cooler for transport. Once transported to the laboratory, all
POCIS were then stored at -20°C until extraction. The extraction procedures for POCIS
were similar to those described by Li et al (2009). Each POCIS was briefly rinsed with a
Gordonville
Petherton
FMCDS
Horse Ranch
Pioneer Tower
24
gentle stream of water to remove any debris adhering to the outside of the membrane.
POCIS membranes were then disassembled and the sorbent medium was carefully
transferred to a glass chromatography column (1cm ID x 30cm) which was fitted with
glass wool and stop cocks. The membranes were then gently rinsed with HPLC grade
methanol to transfer any remaining sorbent into the column. Immediately, each sample
was spiked with 100 µL of 500 ng/mL internal standard (I.S.) mixture and allowed to sit
for three minutes before elution. The sorbent was eluted with 100 mL of HPLC grade
methanol into a 250 mL flask which was then reduced to 1 mL using rotary evaporation,
transferred to a centrifuge tube and evaporated to near dryness. This volume was then
centrifuged to remove any remaining particulate matter and then transferred into an
amber autosampler vial with HPLC grade methanol and brought up to a final volume of
400 µL for analysis. Final volumes were stored at -20°C until analysis.
2.4. POCIS extract analysis
All target compounds (Table 1) were analyzed using liquid chromatography
coupled with tandem mass spectrometry (LC-MS/MS) and an electrospray ionization
source (ESI) using an AB Sciex QTrap 5500 instrument equipped with an Agilent 1100
series HPLC separation system (Applied Biosystems-Sciex, Mississauga, ON, Canada).
The analytes were separated chromatographically using a reverse phase Genesis – C18
column (150 mm x 2.1 mm ID; 4µm particle size) with a guard column (Genesis C18,
10mm x 2.1 mm ID; 4µm particle size) of the same stationary phase (Chromatographic
Specialties, Brockville, ON, Canada).
PPCPs and the artificial sweetener, sucralose were separated by HPLC using a
gradient elution with a total run time of 18 minutes. The mobile phases used for
25
chromatographic separation were [A] MilliQ Water (100%) with 0.1% acetic acid, and
[B] Acetonitrile (100%) with 0.1% acetic acid, as described by Metcalfe et al. (2014).
The gradient used for both positive and negative polarity modes was adapted from the
method described by Topp et al. (2008). The LC-MS/MS was run in multiple reaction
monitoring mode (MRM) for the detection of precursor and product ions. The ion
transitions used for analysis of the target compounds and their corresponding IS, as well
as the POCIS sampling rates (Rs) for PPCPs were previously described by Li et al.
(2010b). The Rs value for sucralose was determined in Metcalfe et al. (2014). The Rs
values selected for this study are listed in Appendix 1.
Fungicides, herbicides, and biocides were separated by HPLC using a gradient
elution with a total run time of 18 minutes. The mobile phases used for chromatographic
separation were [A] 10 mM Ammonium Acetate with 0.1% acetic acid and, [B] 100%
Acetonitrile. The gradient performed as follows for both positive and negative polarity
modes: [B] 30% for 1 minute, increasing to [B] 90% over 5 minutes and held for an
additional 5 minutes, then dropped back to [B] 30% over another 5 minutes and held for
an additional 2 minutes. The LC-MS/MS was run in MRM mode for the detection of
precursor and product ions. These ion transitions for the target CUPs and their
corresponding I.S. are listed in Table 2. Ionization parameters are listed in Appendix 3.
An external standard method was used for quantification, with adjustments made using
analytical responses for the respective surrogate internal standards. The POCIS sampling
rates of CUPs were previously described by Metcalfe et al. (submitted). The sampling
rates used for this study are described in Appendix 2.
26
Table 1: List of all target analytes for monitoring by POCIS and their sources.
Chemical Family Compound Source
Fungicide
Tebuconazole Agricultural
Propiconazole Agricultural
Fluconazole Pharmaceutical
Ketoconazole Personal care product
Climbazole Personal care product
Carbendazim Turf Care/Biocide
Azoxystrobin Agricultural/Turf Care
Myclobutanil Agricultural/Turf Care
Iprodione Agricultural/Turf Care
Herbicide
Mecoprop Agricultural/Turf Care
Atrazine Agricultural
Dicamba Agricultural/Turf Care
2,4-D Agricultural/Turf Care
Biocide
Irgarol 1051 Antifouling
Terbutryn Antifouling
PPCP
Estrone Hormone
Androstenedione Hormone
Ibuprofen Anti-inflammatory
Naproxen Anti-inflammatory
Acetaminophen Pain Killer
Sucralose Artificial Sweetener
Trimethoprim Antibiotic
Gemfibrozil Cholesterol regulator
Carbamazapine Anti-convulsant
27
Table 2: Target pesticides and internal standards, with the MRM transitions used for
analysis.
Compound Formula MRM Transition Polarity
Azoxystrobin C22H17N3O5 404 → 86 +
Fluconazole C13H12F2N6O
307 → 238 +
Climbazole C15H17ClN2O2 293 → 197 +
Myclobutanil C15H17ClN4 289 → 70 +
Propiconazole C15H17Cl2N3O2 342 → 159 +
Tebuconazole C16H22ClN3O 308 → 70 +
Carbendazim C9H9N3O2 192 → 160 +
Ketoconazole C26H28Cl2N4O4 531 → 489 +
Iprodione C13H13Cl2N3O3 328 → 141 -
Atrazine C8H14ClN5 216 → 174 +
Dicamba C8H6Cl2O3 219 → 161 -
2,4-D C8H6Cl2O3 220 → 162 -
Mecoprop C10H11ClO3 213 → 141 -
Irgarol C11H19N5S 254 → 198 +
Terbutryn C10H19N5S 242 → 186 +
Ketoconazole-d4 C26H24D4Cl2N4O4 535 → 81 +
Carbendazim-d4 C9H5D4N3O2 196 → 164 +
Fluconazole-d4 C13H8D4F2N6O 311 → 70 +
Propiconazole-d5 C15H17Cl2N3O2D5 347 → 279 +
Atrazine-d5 C8H9D5ClN5 221 → 72.9 +
2,4-D-d3 C8H3Cl2D3O3 222 → 164 -
2,4-C-d3 C10H8D3ClO3 216 → 144 -
3,6-D-d3 C8D3H3Cl2O3 222 → 178 -
Iprodione-d5 C13H8D5Cl2N3O3 333 → 97 -
Terbutryn-d5 C10D5H14N5S 247 → 173 +
28
2.5. Darter collection
The two species of darters were collected at the study sites in the Grand River
during June 23rd 2014 to June 27th, 2014, which compliments the time of POCIS
deployment from June 19 to July 7, 2014. All collections were conducted according to
Animal Care Protocols approved by the Trent Animal Care Committee. A total of 20
female rainbow darters (E.caeruleum) were collected at each of the five study sites. A
total of 15 female fantail darters (E. flabellare) were collected at each of the three stations
in the upper watershed (i.e. rural sites), due to their regional distribution. Darters were
collected using a backpack electrofishing unit (Smith-Root LR-24, Vancouver,
Washington, USA) by a three person team consisting of two netters and one electrofisher.
The darters were kept alive in aerated buckets containing site water, before they were
sacrificed for dissection. The length and mass of the fish were measured to calculate
condition factor before the fish were sacrificed by spinal severance. Liver weight was
taken for the calculation of LSI. Each fish was dissected for brain, gill and, liver tissue
samples, which were immediately placed in cryovials (Cole-Parmer Canada, Montreal,
QC, Canada) and snap frozen in liquid nitrogen. All tissue samples were stored in an
ultra-low temperature freezer at -80°C until the time of analysis.
2.6. Positive control treatments
In order to validate the methods used for measuring the hepatic assay response for
EROD in darters, juvenile rainbow trout (Oncorhynchus mykiss) ranging from 25 to 30
cm in size were exposed in the wet lab at Trent University to chemicals known to induce
these biomarkers and liver tissue collected from these fish was evaluated for the
29
biochemical responses. All procedures were conducted according to Animal Care
Protocols approved by the Trent Animal Care Committee. Trout were purchased from
Linwood Acres Trout Farm (Campbellcroft, Ontario, Canada) and acclimated for a period
of two weeks in a 600 L tank with fresh water flow through at a temperature of 11 °C.
The trout were exposed via intraperitoneal (I.P.) injection to a known CYP1A inducer.
The I.P. injections were performed with a 25G tuberculin needle and 1 mL syringe in the
ventral-posterior section of the fish beneath the anal fin. Stocks of the positive control
compound, β – napthoflavone (BNF) were prepared using DMSO and then diluted in
corn oil to a final concentration with less than 10% DMSO. Treatments consisted of six
fish for each of the treatments with BNF at a dose of 10 µg/g for CYP1A induction
(Martin et al. 2014; Smith and Wilson 2010; Hodson et al. 1996). One negative control
group exposed to the corn oil and <10% DMSO and one blank (no injection) group were
tested simultaneously. After 72 hours, the fish were sacrificed by spinal severance. Liver
samples were collected in a similar fashion as outlined in section 2.5.
2.7. Acetylcholinesterase assay
Acetylcholinesterase (AChE) was determined using the Ellman et al (1961)
protocol adapted to a 96 well microplate spectrophotometric reader, as described by
Fisher et al (2000). In this assay, AChE activity is determined by cholinesterase
catalyzing the breakdown of acetylcholine into acetate and thiocholine. Enzyme activity
associated with this reaction was monitored at λ405 nm using a SpectraMAX Plus 384
UV-Vis plate reader (Molecular Devices, Sunnyvale, CA, USA) at λ405 nm. An increase
in yellow colouration marks the production of thiocholine when it reacts with the added
30
reagent 5,5’-dithio bis-2-nitrobenzoate which was purchased from Sigma-Aldrich Canada
(Oakville, ON).
Approximately 10 mg of brain tissue was homogenized in 350 µL of ice cold
0.02M phosphate buffer (PB) containing 1% Triton-X-100 (Sigma Aldrich Canada) at
pH 8.0 in a 1.5 mL polypropylene centrifuge tube. Samples were then centrifuged at
13,000 g for 10 minutes at 3°C. Supernatants were removes and put in a clean 1.5 mL
centrifuge tube and stored on ice prior to analysis. Each plate included a quality control
consisting of Electric Eel (Electrophorus electricus) AChE purchased from Sigma
Aldrich (Oakville, ON, Canada). Additions to each well were as follows: 1) 100 µL of 8
mM 5,5’-dithio bis 2-nitrobenzoate in PB, 2) 50 µL of undiluted homogenate, quality
control enzyme, or assay blank (PB with 1.0% Trition-X-100) 3) 50 µL 16 mM
acetylcholine Iodide in PB. All samples were run in triplicate. Plates were then
incubated at 30°C for 3 minutes to initiate the reaction. Samples were read in the plate
reader over a 10 minute period, with intermittent shaking. Protein determination was
performed as outlined in section 2.13. Enzyme activity in µmoles/min/mg protein was
calculated using Equation 1 from Ellman et al (1961):
𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = ∆𝑂𝐷/𝑚𝑖𝑛
𝑀𝐸𝐶 𝑋 𝐶
Where: MEC = molar extinction coefficient (1.36 x 104/cm), OD = Optical density as
determined using the spectrophotometric method and, C = supernatant protein
concentration in the assay well (mg/L).
(1)
31
2.8. Ethoxyresorufin-O-deethylase (EROD) assay
The EROD assay procedure using S9 preparation used for this study was adapted
from Hodson et al. (1996). For this assay, darter liver tissues from two fish were pooled,
resulting in a sample size of 10 for rainbow darters and a sample size of 7 for fantail
darters collected at each site. Approximately 30 mg of liver tissue was homogenized in
250 µL of HEPES grinding buffer (pH 7.5) and then brought up to 750 µL by adding an
additional 500 µL of HEPES solution. These samples were then centrifuged at 9,000 g
for 20 minutes at 3°C to generate an S9 preparation. The supernatant (i.e. S9) layer was
gently aspirated and transferred into a clean cryovial and stored at -80°C until analysis.
The frozen homogenates were thawed on ice and mixed using a vortex mixer prior to
analysis. A standard curve ranging from 0 to 5 ug/mL resorufin dissolved in DMSO was
prepared and stored in the dark at room temperature until analysis.
Additions to the microplate wells were as follows: 1) 50 µL vortexed S-9 fraction,
in triplicate, 2) 50 µL 7-ER/HEPES solution. Plates were then incubated in the dark at
room temperature for 10 minutes. Finally 10 µL of nicotinamide adenine dinucleotide
phosphate (NADPH) was added quickly to each well to initiate the reaction.
Fluorescence was read every 30 seconds for 12 minutes at λexc 530 nm and λem 586 nm
using a Gemini EM fluorescence plate reader (Molecular Devices, Sunnyvale, CA, USA.
Protein was determined as outlined in section 2.13. All reagents for this assay were
purchased from Sigma-Aldrich (Oakville, Ontario, Canada).
32
2.9. 2-thiobarbituric acid reactive substances (TBARS) assay
The TBARS assay measures lipid peroxidation that results from oxidative stress
within an organism. The procedure for TBARS analysis followed in this study was
adapted from the protocol described by Hermes-Lima et al. (1995). Approximately 10
mg of gill tissue was homogenized in 1.1% H3PO4 (19 µL mg-1 tissue) in a 1.5 mL
centrifuge tube. The reaction mixture for the assay consisted of: 150 mg thiobarbituric
acid (TBA), 1.5 mL of 1mM butylated hydroxytoluene (BHT), and 13.5 mL of 56 nM
NaOH. Assay results were compared against a standard curve of malondialdehyde
(MDA) ranging from 0 to 20 mM concentrations in 1.1% H3PO4. Additions to clean
centrifuge tubes were made as follows: 1) 200 µL of reaction mixture 2) 200 µL of
homogenate, standard or 1.1% H3PO4 blank 3) 100 µL of 7% H3PO4. All samples and
standards were placed in a boiling water bath for 15 minutes, then immediately cooled
down on ice. Each sample was brought up to volume with 750 µL of butanol and mixed
with a vortex mixer to initiate the reaction. Immediately after mixing the samples were
centrifuged at 10,000 g for 5 minutes. Standards were run in duplicate and homogenates
were run in triplicate by adding 200 µL and 100 µL per well, respectively. Absorbance
was then read at λ 532 nm using a SpectraMAX Plus 384 UV-Vis plate reader. All
reagents for the TBARS assay were purchased from Sigma Aldrich Canada, Oakville,
Ontario.
2.10. Protein assay
For protein determination for the AChE and EROD assays, the protein
concentrations were compared against a standard curve of BSA in MilliQ water at
33
concentrations ranging from 0 to 0.25 mg mL-1. For the EROD assay, S-9 homogenates
were diluted twenty-one-fold in MilliQ water, to 50 µL to 1000 µL respectively. Brain
homogenates for AChE were diluted using the same proportions. Standards were run in
unison and samples were run in triplicate. Additions to the microplate wells were as
follows: 1) 10 µL dilute homogenate or standards 2) 200 µL dilute Bio-Rad (1:4 MilliQ).
The plates were then incubated in the dark at room temperature for 5 minutes.
Absorbance was read λ 600 nm using a SpectraMAX Plus 384 UV-Vis plate reader.
2.11. Statistical analyses
When sample groups had equal variances, a One Way Analysis of Variance
(ANOVA) was performed. In cases where statistically significant differences (p < 0.05)
were observed, the Tukey Honestly Significant Difference post hoc test was applied to
test for differences between specific study sites. If the data for the sample groups did not
meet the criteria to perform a one way ANOVA, the Kruskal – Wallis test was substituted
with Nemenyi post hoc test, in case significant differences (p < 0.05) were observed.
When comparing the data on biological responses for rainbow darters to fantail darters, a
Two Way ANOVA was performed with a pairwise post hoc in the event of statistical
significance. All statistical analysis was conducted using the statistical software R
(v3.2.0; The R Foundation).
2.12. OFAT III model
The OFAT III model was developed by the Ontario Ministry of Natural Resources
and Forestry (OMNRF) for the detailed delineation of watersheds. Catchments were
generated for each of the five study sites based on the site of the POCIS cage deployment.
34
Based on the surrounding topography, detailed descriptions of each study site were
generated. OFAT III is capable of modelling average and seasonal flow dynamics, land
geography, and land use patterns based off of existing GIS databases. For this study,
OFAT III was used to generate land cover and land use data for each of the five study
sites to illustrate differences in land cover and catchment sizes.
3.0 Results and Discussion
3.1. Site characterization
When comparing the land cover types and associated coverage, it becomes clear
that the catchments influencing each site are primarily agricultural, but the two urban
sites are located within the city of Kitchener and therefore are expected to be primarily
influenced by contaminants of urban origin. Table 3 displays the watershed
characterization as determined by the OFAT III model. Communities and infrastructure
land use ranges from 1.09 km2 at the most upstream site to 166.03 km2 for the most
downstream site. Although the agricultural proportions remain dominant at the
downstream sites (Table 3), agriculture may have a lesser influence because these land
use patterns are over 100 km away, while the urban infrastructure is immediately adjacent
to the sampling sites. Gordonville, Petherton and FMCDS are primarily agricultural,
with approximately equivalent coverage by small rural communities (~2.1%). Although
there are several small WWTPs and septic systems throughout the upper Grand River
watershed, agricultural land usage is expected to have the most significant influence on
the watershed at these sites. Wetlands cover approximately 8-11% of each catchment.
Previous studies have shown that wetlands have a significant impact on the degradation
35
of CUPs and therefore, may aid in mediating their transport into a riverine system
(Maillard et al 2011; Poissant et al. 2008).
Table 3: OFAT III generated data on catchment area for each of the 5 sampling sites, with
the corresponding area for each land cover type (km2). Sites are arranged from furthest
upstream sample site to the furthest downstream site.
Criteria (% coverage) Gordonville Petherton FMCDS
Horse
Ranch
Pioneer
Tower
Drainage Area (km2) 52.06 71.78 117.18 2502.71 2504.23
Clear Open Water 1.05 0.76 0.54 0.90 0.90
Marsh 0.67 0.66 0.54 1.45 1.45
Swamp 10.89 9.34 8.09 10.35 10.35
Fen 0.00 0.00 0.00 0.01 0.01
Bog 0.00 0.00 0.00 0.23 0.23
Treed Upland 0.60 0.54 0.56 0.37 0.37
Deciduous Treed 1.49 1.38 1.27 2.28 2.29
Mixed Treed 0.17 0.14 0.10 0.08 0.08
Coniferous Treed 0.15 0.14 0.24 0.45 0.45
Plantations 2.68 1.96 1.31 1.37 1.37
Hedge Rows 0.51 0.65 0.83 0.42 0.42
Sand/Gravel 0.08 0.06 0.04 0.00 0.23
Infrastructure 2.09 2.04 2.09 6.60 6.63
Agriculture 79.61 82.34 84.39 75.27 75.23
3.2. Contaminants
The estimated TWA concentrations estimated for each analyte are listed in Tables
4a and 4b. A total of 28 analytes were measured at each of the five study sites. Of these
target analytes, 10 compounds were not detected at any of the sites, including the steroid
hormones, estrone and androstenedione (Table 4b). Atrazine was found at the highest
estimated TWA concentrations (70 – 420 ng/L) and was detected at all five sites.
Naproxen (0.1 – 2.60 ng/L) and carbamazepine (0.1 – 4.20 ng/L) were also found at each
of the five sites. Typically, atrazine is applied to corn crops as a pre-emergence broad
36
leaf herbicide in the early spring and has a half-life of approximately 30 days in soils
(Nwani et al 2010). The highest estimated TWA concentration of atrazine was below the
current Canadian Council of Ministers of the Environment (CCME) guidelines for
aquatic organism toxicity (i.e. 1.8 µg/L). However, due to the late deployment of the
POCIS, the measured concentrations are estimated to be about one month post
application and therefore may only account for the end of the peak runoff period. A 55%
increase in atrazine was observed downstream of the urban WWTP compared to the site
immediately upstream. The increase in atrazine downstream of the WWTP may be due
to the introduction of contaminated sewage from septic systems as well as through storm-
water overflows (Gerecke et al 2002). Kolpin et al. (2006) examined the concentrations
of atrazine throughout a municipal wastewater treatment process, and the results
indicated that atrazine is minimally removed from WWTP effluent before discharge.
There is a large golf course upstream of the urban sites that may also be a source of
atrazine, even though there is a municipal ban on the pesticides application. Arlos et al.
(2014) reported atrazine at the urban sites in Kitchener at concentrations around 207 ± 36
ng/L. Tanna et al. (2013) reported atrazine concentrations at urban sites in Kitchener to
be around 50 ng/L. The concentrations of atrazine observed in the present study fall
within the ranges reported in the literature. Differences in the detected concentrations of
atrazine at the urban study sites may be due to difference in seasonal sampling times,
sampling technologies used (i.e. grab samples vs POCIS), and the river flows during
sample collection.
The pharmaceuticals, naproxen and carbamazepine were also detected at all five
sites, with the highest concentrations detected immediately downstream of the WWTP
37
(Table 4b). Low TWA concentrations of naproxen and carbamazepine were estimated at
sites in the rural portions of the watershed. These pharmaceuticals may have been
introduced at the rural sites through septic leakage or through biosolid applications to
agricultural lands. Carbamazepine is poorly removed in WWTPs and is highly persistent
in surface waters, while naproxen is moderately persistent in WWTPs, but has been
widely detected in surface waters (Gurke et al. 2015b; Lissemore et al., 2006; Tixier et al.
2003). The removal of naproxen is believed to be seasonally influenced, as the majority
of its degradation is due to photodegradation, rather than the wastewater treatment
process itself (Hijosa-Valsero et al. 2010). Both carbamazepine and naproxen are mobile
in surface runoff or tile drain leachate after applications of biosolids onto agricultural
fields (Topp et al., 2008; Lapen et al., 2008). Lissemore et al. (2006) monitored the
presence of several pharmaceuticals at rural and urban study sites in a southern Ontario
watershed. When comparing the concentrations measured in the present study, they are
generally in the lower range of those reported by Lissemore et al. (2006). The differences
in concentrations may be due to dilution caused by river flow, or the choice of sampling
technology. Lissemore et al. (2006) collected grab samples, which may have been
collected during peak runoff events or low flow events, whereas the passive samplers
used in the present study monitor over an extended period of time and provide an
estimated time-weighted-average. Gillis et al. (2014) monitored for PPCPs in the Grand
River watershed using POCIS samplers, and the estimated TWA at each site are similar
to those observed in the present study.
The differences in the concentrations of CUPs across the rural sites are most
likely influenced by riparian buffer quality, application method and rate, and stream flow,
38
which will be discussed later in this section. The furthest upstream site (Gordonville) had
the smallest buffer zone of the agricultural sites and had two active and intensive
agricultural fields adjacent to it, with less than 10 m of buffer on either side. The second
rural site (Petherton) was adjacent to a single, moderately intense agricultural field with
over 15 m of riparian buffer zone between the field and stream bank. The furthest
downstream site (FMCDS) was adjacent to two active, low intensity agricultural fields,
with over 30 m of riparian buffer on one side, and less than 10 m on the opposite side.
The composition and quality of riparian buffer have been shown to mediate the runoff of
pesticides into the aquatic environment, but they are not entirely effective (Weissteiner et
al. 2014). The sites with a lower quality of riparian buffer exhibit higher in situ
concentrations of contaminants compared to those sites with a higher quality of buffer
zone. However, the intensity of agricultural practices in these areas may also influence
concentrations. It can be assumed that the application rates of pesticides are proportional
to the size and intensity of the farm (Boithias et al. 2014; Sattler et al. 2007). While it is
possible that local site conditions, including riparian buffers, may have had an influence
on the contaminants detected at each study site, the influence of upstream factors cannot
be ignored. The quality of buffer zones, and agricultural intensity upstream of the
sampling sites may have had a compounding effect on the concentrations of the targeted
analytes detected at each of study sites.
The physicochemical properties and application methods of these fungicides
greatly influence their ability to be transported into adjacent surface waters (Bundschuh
et al. 2014). Atrazine, tebuconazole, and propiconazole are all highly water soluble at
concentrations up to 35, 36, and 100 mg/L, respectively (U.S. Environmental Protection
39
Agency 2015). The relatively high water solubility of these pesticides suggests that they
are easily leached into surface runoff during precipitation events. Iprodione is less water
soluble at 12 mg/L (U.S. Environmental Protection Agency 2015) and is therefore more
likely to remain in soils when it is applied. Since pesticide application was not observed
at the study sites, it is assumed that they were applied following best management
practices, including reasonable control of drift, and respecting no spray zones. However,
given the properties and functions of the pesticides used, it can be assumed that they were
applied via broadcast spray and that drift into nearby surface water is a possibility
(Bereswill et al. 2012; Reichenberger et al. 2007).
The agricultural herbicides 2,4-D and dicamba were detected downstream of the
urban WWTP at concentrations of 38.9 and 31.1 ng/L, respectively. Neither compound
was detected at any other site, including those within the rural watershed. Previous
studies have shown the presence of these two herbicides in municipal wastewater effluent
generally around the concentrations estimated in the present study (Kuster et al. 208;
Petrovic et al. 2003). As mentioned earlier with regards to the presence of atrazine at
urban sites, this is most likely due to contaminated septic waste or storm water overflow
that entered the WWTP. The influence of distant agricultural applications must also be
considered as the source of atrazine in the urban watershed. Atrazine may be transported
downstream from the agricultural sites to the urban sections of the Grand River.
Carbendazim, a broad spectrum fungicide widely used on golf courses, was also detected
downstream of the WWTP. A golf course is located adjacent to the Horse Ranch site,
upstream of the WWTP and roughly 1 km away from the site of POCIS deployment.
Carbendazim was below the LOD at Horse Ranch, and therefore, the point of entry of this
40
fungicide is located somewhere between the upstream and downstream sites. The
introduction of carbendazim and propiconazole are typically influenced by wet-dry
events (Bollman et al. 2014; Singer et al. 2010). Golf courses typically apply
carbendazim early in the season as a casting worm control agent. Carbendazim was only
detected downstream of a large golf course and the Doon WWTP, but not at the site
immediately adjacent to the golf course. This suggests that the primary source of
carbendazim at this site is through discharges of WWTP effluent (Singer et al. 2014).
Propiconazole is commonly mixed with permethrin as a wood preserver that may be
found in barn board and wood fencing. Since propiconazole was only detected at the
rural study sites, it was likely introduced by leachate of treated woods in the upper
portion of the watershed. Byer et al. (2011) monitored for the presence of atrazine across
surface waters in Ontario. The concentrations measured in southern Ontario in this study
are comparable to those measured in the present study.
Studies have shown that ibuprofen is efficiently removed at a rate of 75-90% in
WWTPs (Hijosa-Valsero et al. 2010; Tixier et al. 2003), and therefore, it appears that
there was little addition of this compounds from the Doon WWTP. The primary
contributor of ibuprofen to these sites may be a less efficient WWTP located upstream of
the study sites (Arlos et al. 2014). The pharmaceutical fungicides, climbazole and
fluconazole were detected at the site below the WWTP at concentrations estimated to be
in the low ng/L range. Azole class fungicides have been shown to have poor removal
efficiencies during the wastewater treatment process (Stamatis et al. 2010). However,
WWTPs that employ UV-irradiation as a part of their treatment process have
significantly higher success when eliminating azole fungicides as many of them are
41
readily removed by photodegradation (Chen et al. 2014). The antibiotic trimethoprim
was detected upstream and downstream of the WWTP with a higher estimated
concentration below the outfall (~400%). Concentrations were still in the low ng/L range
(< 5ng/L) downstream of the outfall. Trimethoprim has been shown to be effectively
removed in MWWE by UV-irradiation (Ryan et al. 2011). Trimethoprim is usually
prescribed in combination with the antibiotic, sulfamethoxazole, so it is difficult to
explain why the latter compound was not detected downstream of the WWTP (Table 4b).
The artificial sweetener, sucralose was detected upstream and downstream of the
WWTP, with estimated concentrations of sucralose 280% higher at the downstream
location (Table 4b). Several studies have shown that artificial sweeteners are present in
high concentrations in wastewater, are very poorly removed during the wastewater
treatment process and may be persistent in the environment for months or years
(Mawhinney et al. 2011; Buerge et al. 2009; Scheurer et al 2009); all of which makes
artificial sweeteners such as sucralose ideal tracers of wastewater contamination.
Spoelstra et al. (2013) observed concentrations of sucralose in the Grand River watershed
at concentrations as high as 21 µg/L. The elevated concentrations of sucralose
throughout the watershed may be due to differences in seasonal sampling periods,
sampling technologies, or low flow conditions. It is instructive that this persistent
compound was not detected at the rural sites, unlike the presence of carbamazepine and
naproxen at these upstream sites.
During the deployment of the POCIS, a significant precipitation event occurred
across southern Ontario. This led to an increase in flow rates in the Grand River during
the deployment. The increased flow at each of the sites may have led to the increased
42
dilution of target analytes. However, the precipitation event may also have carried
pesticides from agricultural land into the watershed. This increase in flow may be
responsible for several compounds not being detected. In situ sampling rates for POCIS
vary due to fluctuations in temperature, flow, water chemistry and fouling of the sampler
membranes (Harman et al. 2009). One approach to correcting for these environmental
factors is to use Performance Reference Compounds (Mazzella et al. 2010) but this
approach was not used in the present study due to the short monitoring period.
Table 4a: Mean estimated TWA concentrations (ng/L) ±S.D. of current use pesticides at
each of the five study sites.
Site
Gordonville Petherton FMCDS Horse Ranch Pioneer Tower
Fungicides
Tebuconazole 3.61 ± 0.98 2.07 ± 0.44 2.29 ± 0.69 <LOD <LOD
Propiconazole 0.40 ± 0.28 1.22 ± 0.34 1.42 ± 0.44 <LOD <LOD
Ketoconazole <LOD <LOD <LOD <LOD <LOD
Climbazole <LOD <LOD <LOD <LOD 0.24 ± 0.04
Fluconazole <LOD <LOD <LOD <LOD 2.42 ± 0.44
Carbendazim <LOD <LOD <LOD <LOD 2.65 ± 0.72
Azoxystrobin <LOD <LOD <LOD <LOD <LOD
Myclobutanil <LOD <LOD <LOD <LOD <LOD
Iprodione 1.62 0.28 ± 0.29 0.78 ± 0.54 <LOD <LOD
Herbicides
Mecoprop <LOD <LOD <LOD <LOD <LOD
Atrazine 396.65 ± 31.23 398.46 ± 13.40 418.38 ± 33.38 71.44 ± 5.59 129.66 ± 14.07
Dicamba <LOD <LOD <LOD <LOD 31.14 ± 18.68
2,4-D <LOD <LOD <LOD <LOD 38.57 ± 19.75
Biocides
Irgarol 1051 <LOD <LOD <LOD <LOD <LOD
Terbutryn <LOD <LOD <LOD <LOD <LOD
43
Table 4b: Mean estimated TWA concentrations (ng/L) ±S.D. of contaminants of steroid
hormones, pharmaceuticals and sucralose at each of the five study sites.
Site
Gordonville Petherton FMCDS Horse Ranch Pioneer Tower
Hormone
Estrone <LOD <LOD <LOD <LOD <LOD
Androstenedione <LOD <LOD <LOD <LOD <LOD
Painkiller
Acetaminophen <LOD <LOD <LOD 0.19 ± 0.06 0.30 ± 0.32
Anti-inflammatory
Naproxen 0.38 ± 0.11 0.13 ± 0.23 0.33 ± 0.57 1.81 ± 1.12 2.56 ± 1.00
Ibuprofen <LOD <LOD <LOD 5.72 ± 1.15 4.88 ± 1.22
Artificial
Sweetener
Sucralose <LOD <LOD <LOD 40.87 ± 10.25 156.54± 30.12
Antibiotic
Sulfamethoxazole <LOD <LOD <LOD <LOD <LOD
Trimethoprim <LOD <LOD <LOD 0.48 ± 0.20 2.42 ± 0.17
Cholesterol
reducer
Gemfibrozil <LOD <LOD <LOD 0.21 ± 0.06 0.62 ± 0.03
Anti-convulsant
Carbamazepine 0.1 ± 0.04 0.14 ± 0.01 0.15 ± 0.03 1.63 ± 0.12 4.00 ± 0.17
44
3.3. Fish somatic index data
Table 5 summarizes the data on the average total length and weight of the
rainbow darters before sacrifice (Table 6). On average, both length and weight did not
differ across all sites significantly (p>0.05). However, the fish caught at the most
downstream rural site were significantly longer (p≤0.01) and heavier (p≤0.03) relative to
the other sites. Fantail darters sampled simultaneously across the rural sites did not vary
significantly in length (p≥0.75) and weight (p≥0.87).
The LSI data for the rainbow darters showed significant differences among sites
(p<0.001). The LSI was significantly lower in rainbow darters collected at the two
upstream sites located in the rural part of the watershed relative to fish collected at the
FMCDS site and the two urban sites (Table 6). The observed increase in LSI for the
rainbow darters collected at the urban sites suggests that contaminant inputs from
wastewater or other urban origins may be increasing energy storage within the liver.
Previous studies have shown a general elevation in fish LSI sampled in urban areas
(Tetreault et al. 2011; Hanson and Larsson 2009). As shown in Table 6, there was no
significant difference observed in the LSI of fantail darters collected at the 3 rural sites
(p≥0.39). Significant differences in LSI were observed between species of darters at
Petherton (p≤ 0.01) only. The observed LSI for female rainbow darters taken from the
urban sites in the present study were much lower than those reported by Fuzzen et al.
(2015) and Bahamonde et al. (2014) when they sampled female rainbow darters at the
same study sites. This may be primarily due to the sampling season, as the sampling
period in the above mentioned studies was during the spawning season, and the present
45
study sampled approximately one month after spawning. This suggests that the female
rainbow darters had lower energy reserves during the later sampling period.
The condition factor (k) relating length to weight calculated for rainbow darters
did not differ statistically between rural and urban sites (p≥0.11). Rainbow darters
collected previously at the urban study sites by Fuzzen et al. (2015) and Tanna et al.
(2013) had higher condition factors than those reported in the present study. The
differences in the observed condition factors may be due to the difference in seasonal
sampling (i.e. spring vs summer), but it cannot be ruled out that these changes are due to
technology upgrades made to the Doon WWTP in 2015. A trend of a decreasing
condition factor for fantail darters was observed from the most upstream to the most
downstream rural sites, but the only significant difference for this parameter was between
darters collected at Gordonville and Petherton (p<0.001). Fantail darters have been
shown to require warmer water temperatures to spawn, which typically results in a
spawning season roughly 1 month later than rainbow darters (Hubbs et al 1985). The end
of the fantail’s spawning season could have potentially coincided with the sampling
period and therefore sampled fantail darters may have had reduced condition factors due
to post-spawning exhaustion.
46
Table 5: Somatic index data for rainbow and fantail darters sampled at 5 locations in the
Grand River, including length, weight, liver somatic index (LSI) and condition factor (k).
Significant differences between sites are shown by a different letter code.
*LSI=(Wliver/Wfish) X 100
**k=(Wfish X 100) / (L3)
RBD=Rainbow darter
FTD=Fantail darter
3.4. EROD assay validation
Because of the low enzyme activity observed with S9 preparations of liver tissue
from darters, we conducted studies with rainbow trout exposed to a known CYP1A
inducer to validate our protocol for the EROD assay (Figure 2). The EROD activity
observed in the rainbow trout was low, but a >5-fold change in activity was observed
Site Species Length (cm) Weight (g) LSI * k **
Gordonville
RBD 5.18 ± 0.12 a 1.71 ± 0.14 a,b 0.99 ± 0.08 a 1.18 ± 0.02
FTD 5.35 ± 0.22 1.49 ± 0.19 1.03 ± 0.09 0.92 ± 0.01 a
Petherton
RBD 5.20 ± 0.10 a 1.62 ± 0.11 a 0.92 ± 0.04 a 1.12 ± 0.02
FTD 5.38 ± 0.03 1.31 ± 0.02 1.10 ± 0.06 0.84 ± 0.01 b
FMCDS
RBD 5.67 ± 0.09 b 2.12 ± 0.09 b 1.20 ± 0.08 a,c 1.15 ± 0.01
FTD 5.28 ± 0.04 1.34 ± 0.03 1.06 ± 0.08 0.88 ± 0.01 a,b
Horse Ranch
RBD 5.35 ± 0.12 a,b 1.91 ± 0.16 a,b 1.40 ± 0.05 b,c 1.19 ± 0.02
Pioneer Tower
RBD 5.39 ± 0.12 a,b 1.89 ± 0.15 a,b 1.45 ± 0.06 b,c 1.16 ± 0.02
47
0.0
0.5
1.0
1.5
2.0
2.5
Blank Solvent BNF
ERO
D A
ctiv
ity
(pm
ol/
min
/mg
pro
tein
)
Treatment
between the groups treated with BNF and the two control groups (p≤0.006). Comparable
trends were observed in the literature using BNF as an inducer of this CYP1A enzyme
(Hodson et al. 1996). The EROD activity generated from S9 preparations of rainbow
trout liver was comparable to activity observed for darters collected from the Grand River
(see data below). Greater activity would have been expected if microsomal preparations
had been tested for the fish species.
Figure 2: Mean EROD activity ± S.E. (pmol/min/mg protein) in livers of rainbow
trout exposed to BNF, and two control groups. Significance is noted by different
letter codes (p<0.05).
3.5. EROD
From the most upstream rural site to the most downstream rural site there was an
increase in EROD activity measured in the livers of rainbow darters (Figure 3). A
significant difference in EROD activity was observed between rainbow darters collected
at Gordonville and FMCDS (p≤0.007), and between this species collected at FMCDS and
Horse Ranch (p≤0.03). EROD activity is compared in Figure 4 among the rural study
sites for rainbow and fantail darters. A significant site effect was observed (p≤0.0006) on
a
a
a
a
a
a
b
a
a
48
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Gordonville Petherton FMCDS Horse Ranch Pioneer Tower
ERO
D A
ctiv
ity
(pm
ol/
min
/mg
pro
tein
)
Site
the EROD activity measured in both darter species. No significant species effects or
interactions between the different species with their sample sites were observed. The
high standard deviation in EROD activity may be explained by biological variability in
metabolism of xenobiotics. A review of the literature shows that site effects such as
water temperature and pH in combination with nutritional status, age and reproductive
state may influence EROD activity in fish as enzyme activity is increased to compensate
for lower reaction rates that result from environmental stress (Sole et al. 2015; Ribalta et
al. 2015).
Figure 3: Mean EROD activity ± S.E. (pmol/min/mg protein) in livers of rainbow
darters at each of the five sites. Significance noted by different letter code
(p<0.05)
a
a
a
ab
a
a
b
a
a
ac
a
a
abc
49
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Gordonville Petherton FMCDS
ERO
D A
ctiv
ity
(pm
ol/
min
/mg
pro
tein
)
Site
RBD
FTD
Figure 4: A comparison of mean EROD activity ± S.E. (pmol/min/mg protein) in
livers of rainbow (RBD) and fantail (FTD) darters at the rural sites.
The mean EROD activity measured in the livers of the darter species was
relatively low when compared to other studies. Hoeger et al. (2004) reports EROD
activity from 4-12 pmol/mg/min in the livers of rainbow trout exposed to a 10% MWWE.
Jasinka et al. (2015) exposed caged fathead minnows (Pimephales promelas) upstream
and downstream of a WWTP and measured EROD activity in liver tissue between 30-35
pmol/mg/min at the reference sites and between 40-70 pmol/mg/min immediately
downstream of the WWTP discharge, decreasing to below 20 pmol/mg/min at a site 10
km downstream of the discharge. However, in these other studies, microsomal
preparations from liver tissue were used in the EROD assays, as opposed to S-9
preparations used in the present study. Biological differences between species and the
sampling seasons may have also influence the level of EROD activity observed and
account for the different responses between the fish studied.
50
Exposure to endocrine disrupting compounds has been shown to influence the
hepatic metabolism of xenobiotics in fish (Guillette and Gunderson 2001). Several
studies conducted on darters in the Grand River watershed have documented gonadal
intersex related to the presence of endocrine disrupting compounds (Bahamonde et al.
2015; Tanna et al. 2013; Tetreault et al. 2011). Endocrine disrupting compounds have
been shown to reduce hepatic metabolism in female fish, thus reducing CYP450 activity
within the liver (Mortensen and Arukwe 2007; Guillette and Gunderson 2001).
Therefore, endocrine disrupting compounds at the five study sites may be down-
regulating hepatic EROD activity in the darters, resulting in relatively low EROD activity
in the liver tissue.
3.6. TBARS
A general trend of an increase in the measured levels of TBARS was observed
heading downstream through the agriculturally impacted sites into the urban impacted
sites (Figure 5). The slight decrease in mean TBARS between fish collected at
Gordonville and Petherton was not significantly significant (p>0.05). Fish collected at
the most downstream rural site, FMCDS, had significantly higher TBARS compared to
the other two rural sites (p<0.001). An increase in TBARS was observed between the
urban sites at Horse Ranch and Pioneer Tower (p<0.001). Darters collected at Pioneer
Tower, which is below the Kitchener WWTP, exhibited an increase in TBARS of
approximately 50% compared to the site immediately upstream, and a range in increase
between 50-300% when compared to the rural sites.
Significant differences in biological responses related to the site (p<0.0001) and
species (p<0.0001) were observed among darters at Gordonville and FMCDS, but no
51
significant species-site interaction was observed. Fantail darters were found to have
significantly higher levels of TBARS compared to rainbow darters at each site (Figure 6).
Fantail darters sampled at the most upstream site, Gordonville, and at the most
downstream rural site, FMCDS, were observed to have more than two-fold the
concentration of measured TBARS compared to the rainbow darters sampled at the same
sites (p<0.001). Reasons for the significant difference between the species is unknown at
this time. However, it may be due to some intrinsic factor influencing anti-oxidant
defense systems in the two species, or differences in the sensitivity to reactive oxygen
species. Temperature and pH have been shown to influence TBARS in fish species,
making these possible confounding factors for the differences in responses observed
between rainbow and fantail darters (Maqsood and Sootawat 2011). Differences in the
reproductive cycles of the two fish species may also be responsible for the differences in
biological responses between species.
Typically TBARS are measured using liver tissue in fish (Oakes and Van der
Kraak 2003; Pedrajas et al. 1995). However, due to the small size of the darters and the
tissues required for other biomarker analyses, gill tissue was substituted in place of liver
for this assay. Although the liver is ideal due to its ability to express oxidative stress, the
collected gill tissue performed well to screen for differences in response of this particular
biomarker between sites. When compared to results in the literature, the observed
TBARS concentrations are within the range reported by Sanchez et al. (2007) who
measured responses of TBARS in stickleback (Gasterosteus aculeatus L.) liver at sites
contaminated with urban pollutants (i.e. MWWE) and sites that were relatively pristine.
Sanchez et al. (2007) reported TBARS ranges of 44-55 nmol/g for fish in the non-
52
contaminated sites, and 120-205 nmol/g for fish sampled from contaminated sites. By
comparison, rainbow darters exhibited TBARS within the lower range (i.e. pristine sites)
in the upper rural watershed, and exhibited TBARS within the higher range at the urban
sites, particularly downstream of the WWTP. Relative to the stickleback data, fantail
darters exhibited responses in the higher range at the most upstream and most
downstream rural sites, while falling within the lower range for the second most upstream
rural site.
Oakes and Van der Kraak (2003) measured TBARS in white sucker (Catostomus
commersoni) exposed to pulp mill effluent. The study reported that TBARS in the livers
of white suckers ranged from 250-350 nmol/g tissue, and 15-23 nmol/g tissue in the
gonad. The range in response reported in the present study is comparable. A comparison
between the results in the present study and those presented by Oakes and Van der Kraak
(2003) suggests that sampling the fish liver may result in higher TBARS concentrations
than gonad or gill tissue. The difference in response between TBARS in the liver and gill
must be considered when comparing the data from the present study to the values
reported by Sanchez et al. (2007) and by Oakes and Van der Kraak et al. (2003).
Studies have shown that the presence of certain PPCPs may elevate TBARS in
fish populations. Azole fungicides, carbamazepine, and atrazine have all been shown to
induce TBARS in fish (Ferreria et al. 2010; Nwani et al. 2010). In the present study, the
sites with the highest concentrations of these compounds detected in POCIS also
exhibited higher TBARS concentrations in the darters. Therefore, these compounds may
be influencing oxidative stress in rainbow and fantail darters.
53
0
50
100
150
200
250
300
350
Gordonville Petherton FMCDS
TBA
RS
(nm
ol/
g ti
ssu
e)
Site
RBD
FTD
0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
Gordonville Petherton FMCDS Horse Ranch Pioneer Tower
TBA
RS
(nm
ol/
g ti
ssu
e)
Site
Figure 5: Mean levels of TBARS ± S.E. (nmol per g) in gill tissue collected from
rainbow darters sampled from each of the five sites. Significance is noted by
different letters (p<0.05).
Figure 6: Comparison of mean levels of TBARS ± S.E. (nmol per g) in gill tissue
collected from rainbow (RBD) and fantail (FTD) darters sampled from each of the
three rural sites.
a
a
a
a
a
a
b
a
a
b
a
a
c
a
a
54
Non-steroidal anti-inflammatory drugs (NSAIDs) have been shown to influence
TBARS in two different ways. Naproxen has been shown to act as a strong inducer of
TBARS within fish (Nunes et al. 2015; Gagne et al. 2006). Increases in naproxen
concentrations align with TBARS responses between sites, suggesting possible influence
on the oxidative stress response in the darters. On the contrary, ibuprofen has been
shown to reduce the impacts of reactive oxygen species as it acts as a cellular protection
mechanism (Bartoskova et al. 2013). The presence of ibuprofen at the urban sites may be
counteracting the TBARS induction caused by exposure to other contaminants at these
sites.
3.7. AChE
As shown in Figure 7, AChE activity in the brain tissue of rainbow darters
decreased in rainbow darters with distance downstream (p≤0.0002). Significant
differences in AChE activity were observed between fish collected at Petherton and
Horse Ranch (p≤0.038), and between fish collected at Petherton and Pioneer Tower
(p≤0.007). A significant species-site interaction (p≤0.0006) was observed in AChE
responses, but no significant differences between species collected at the three rural sites
were observed (Fig 8). It is possible that differences in individual health related to age,
nutrition and habitat may be responsible for variability that obscures the significance of
differences between species. The fantail darters sampled at the agriculturally impacted
sites experienced a trend of increasing AChE activity between Petherton and FMCDS
(p≤0.002).
The AChE activity in brain tissue from both species of fish observed in this study
are generally within the ranges reported for the brain tissue of fish in several other
55
studies. Sumith et al. (2012) reported AChE activity in the brain tissue of G. ceyonensis,
D. malabaricus, and R. daniconius collected from agriculturally impacted sites to be
within the ranges of 0.6-1.4 µmol/min/mg protein, which is similar to the range of 0.4-
2.75 µmol/min/mg protein reported in this study. There is no obvious explanation for
why AChE activity is different between rainbow and fantail darters. While activity in the
brains of the rainbow darters gradually decreases downstream, there is an increase for the
fantail darters. It is possible that there are differences in the rates of metabolism of
pesticides between species, but this requires further study.
The significant decrease in AChE activity in rainbow darters from the
agriculturally impacted watershed into the urban watershed is consistent with the
presence of 2,4-D and dicamba at both urban sites. Both of these herbicides have been
shown to inhibit AChE in fish when present at concentrations similar to those mentioned
in the present study (da Fonseca et al. 2008; Cattaneo et al. 2008). Atrazine has also been
shown to inhibit AChE over extended periods of exposure similar to those measured in
this study (Santos and Martinez 2012). Therefore it is possible that AChE activity in
darters collected at both agriculturally impacted and urban impacted sites is being
influenced by the presence of these herbicides. The presence of other contaminants
including neonicotinoids, and organophosphate pesticides that were not measured in this
study may also be influencing AChE in darters as these insecticides are commonly used
across agriculture in southern Ontario (Cutler and Scott-Dupree 2014).
56
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Gordonville Petherton FMCDS
AC
hE
Act
ivit
y (u
mo
l/m
in/m
g p
rote
in)
Site
RBD
FTD
0.0
0.5
1.0
1.5
2.0
2.5
Gordonville Petherton FMCDS Horse Ranch Pioneer Tower
AC
hE
Act
ivit
y (u
mo
l/m
in/m
g p
rote
in)
Site
Figure 7: Mean AChE activity ± S.E. (µmol/min/mg protein) in brain tissue of
rainbow darters at all five sites. Significance noted by different letter (p<0.05).
Figure 8: A comparison of the mean AChE activity ± S.E. (µmol/min/mg protein) in
brain tissue of rainbow darters and fantail darters collected at the rural sites.
a
a
a
a
a
a
a
ab
a
a
b
a
a
b
a
a
57
4.0 Conclusions
The use of in situ biomarkers to determine biological impacts from CECs,
including PPCPs and CUPs is a powerful tool for environmental assessment when used in
combination with contaminant monitoring. Biomarkers altered in rainbow and fantail
darters included elevated levels of oxidative stress (TBARS), an induction of EROD
metabolism, which is associated with CYP1A activity, and the inhibition of the
neurotransmitter AChE. Fantail darters exhibited elevated concentrations of TBARS
compared to rainbow darters, as well as greater inhibition of AChE at the most
downstream agriculturally impacted site. Rainbow darters exhibited higher EROD
activity compared to fantail darters at the most upstream agricultural site only.
This study found that in some instances, the intensity of biomarker responses
reflected the presence of specific chemical contaminants. Biomarker responses in the
fantail darters sampled at the most downstream agricultural site were variable from one
biomarker to the next and did not fit the trends observed with biomarkers at the other two
agricultural sites. Only AChE inhibition exhibited a significant species-site interaction,
but a species-site trend that was close to significance was also observed with the TBARS
assay. Significant site and species effects were observed with the TBARS assay. There
was a trend for differences between species for AChE inhibition that was close to
significance. Further investigation is required to determine the mechanisms for the
differences in species responses, as these data are insufficient to identify the origin of
these differences.
58
Chapter 3: Conclusions and Future Steps
1.0. Major Findings
The primary goal of this study was to evaluate and compare biological responses
in darter species collected in sections of the Grand River watershed that are primarily
impacted by agricultural or urban activities. The first major finding of this study was that
there is a trend of increasing biological responses in darters collected from the Grand
River with distance downstream from areas dominated by agricultural land uses to urban
sites. Secondly, there was evidence of differences in biological response between the two
species of darters that were collected.
While biomarkers in fish collected at each site did not always show significant
differences, there were several significant differences in biomarker responses observed
across the study area. The changes in biological responses between the study sites
indicate that there are cumulative effects from contaminants as they are carried
downstream. Some of the biological responses observed in the present study indicate that
fish sampled in the urban watershed may be experiencing higher levels of stress due to
exposure to contaminants from urban sources (i.e. municipal wastewater effluent, runoff)
in combination with upstream agricultural contaminants. The rural watershed does
experience inputs from several small WWTPs and potentially from septic leakage, but it
is expected that fish will be primarily affected by chemicals of agricultural origin, such as
pesticides and runoff from land amended with biosolids. In this case, exposures will be
influenced by the timing of applications, and meteorological events that affect runoff, as
59
well as Best Management Practices, such as the size and location of buffer strips and
riparian zones.
Fantail darters were collected simultaneously with rainbow darters at the three
rural study sites. Differences in biomarker responses were observed between the two
species at all sites. However, the trend was not always consistent. The fantail darters did
not seem to always follow similar patterns of response. AChE activity measured in the
fantail darters was particularly interesting as they showed a significant increase in AChE
activity at the most downstream rural site compared to the other two upstream sites.
Rainbow darters showed a trend of greater AChE inhibition at downstream sites, which
would be expected from cumulative exposure to contaminants of agricultural origin. No
obvious relationship in responses between the species of darter and the study sites were
observed. Only AChE was found to have a significant species-site interaction. A more
detailed study is required to validate the differences in response between the two species
of darters and to determine the mechanisms for these responses.
2.0.Project Objectives and Hypotheses
This study aimed to achieve three objectives: 1) to monitor for the presence and
estimated TWA concentrations of targeted pharmaceuticals and personal care products
(PPCPs) and current use pesticides (CUPs) at the five study sites, 2) to monitor for
differences in the biological responses between rainbow darters between the five study
sites, and 3) to monitor for differences in biological responses between two species of
darters at each of the three rural sites. Using POCIS at each of the five study sites,
several PPCPs and CUPs were detected and successfully analyzed. Although some
60
compounds were not detected or quantifiable at all sites, many were quantified at either
all of the sites, or at all sites within either the rural or urban watershed.
The hypothesis H1 set out for this study predicted that biological responses
indicative of exposure to chemical contaminants would be observed in both darter species
at each of the study sites. This hypothesis was accepted as there was typically a
significant increase in the response of TBARS, EROD, and AChE trending downstream,
with some of the most intense responses at the urban study sites. As discussed in Section
1.0 of this chapter, biological responses were observed in darters collected at the five
study sites. The differences in responses observed in darters between several of the sites
were found to be statistically significant. However, for reasons that are difficult to
explain at this time, the AChE response in the fantail darters followed an inverse trend
compared to what was observed in the rainbow darters. When compared to the literature,
the observed responses in rainbow darters are similar to those found in fish collected at
sites impacted by chemical contaminants. The trends of response noticed in fantail
darters were comparable to the literature in terms of induction of TBARS and EROD, but
followed an inverse trend for AChE. The observed trends indicate that the changes in
biological response between darters collected in the Grand River may be due to
contaminants discharged through point and non-point sources that are specific to the rural
and urban study sites.
Hypothesis H2 was rejected, as there were significantly different responses in
TBARS, EROD, and AChE between rainbow and fantail darters collected at the three
rural study sites. There was no obvious trend for which species exhibited more intense
responses, as the fantail darters exhibited significantly higher TBARS compared to
61
rainbow darters, but typically exhibited less EROD activity and a reverse trend in AChE
inhibition. Reasons for differences in biomarker responses may be due to differences in
health and condition (e.g. exhaustion post-spawning, nutrition) or age. Fish in poor
health or with poor nutritional status may have been more susceptible to exhibiting
biomarker responses. Differences in tolerance to water temperature, pH, dissolved
oxygen concentrations, and ammonia concentrations (not measured in this study) may
have also influenced biological response. A more intensive study is required to
investigate the origins of the differences in biological response between rainbow and
fantail darters.
Typically, compounds of urban wastewater origin were found at the urban sites
and those of agricultural origin were found at the rural sites. However, there were some
exceptions. Atrazine, was found at between 70-140 ng/L at the urban sites, indicating
that there may have been urban inputs. Discharges of atrazine from WWTPs have been
observed before and attributed to the deposition of contaminated septic waste or
contaminated storm water overflow (Kolpin et al. 2006), but it is possible that this
herbicide originates from agricultural applications at upstream locations in the watershed.
The herbicides 2,4-D and dicamba, and the fungicide, carbendazim were also detected at
the site downstream of the Doon WWTP, indicating that the WWTP or another point
source (e.g. golf course) may be the origin of these compounds. Some pharmaceuticals
were detected in the rural watershed, which may have been from biosolids runoff, septic
leakage or through discharges from small, rural WWTPs. There are insufficient data to
accept or reject hypothesis H3 which focused on the distribution of contaminants between
the study sites. Some of target compounds were detected throughout the watershed (e.g.
62
atrazine, carbamazepine), but others were only detected in the rural section of the
watershed (e.g. tebuconazole, propiconazole, iprodione), or in the urban areas (e.g.
carbendazim, ibuprofen, trimethoprim, sucralose). The presence of some chemical
contaminants could be related to specific biomarker responses in the darters (e.g.
naproxen and TBARS), but other biological responses, such as induction of EROD could
be caused by a whole range of contaminants that were not monitored in this study.
In the future it may be beneficial to select a greater number of sample sites within
rural and urban sections of the watershed. This would allow for a more robust data set in
terms of differences in biomarker responses across a gradient of rural and urban sites. It
would also be beneficial to include proper reference sites for both rural and urban study
areas to have an appropriate baseline for the different somatic indices and biomarker
responses.
When sampling at both rural and urban sites there is a potential for biological
responses induced by confounding chemical and physical factors such as changes in
water temperature, flow, pH, nutrient levels, and dissolved oxygen. For future work it
would be beneficial to find reference sites of similar habitat to control for these
influences. This study would have also benefited from sampling species of darters that
are present at all of the sampling sites to create a more complete data set. The darters
collected may have been at different points in their reproductive cycle, which may have
influenced biomarker responses due to post-spawning exhaustion. Sampling fish at
different trophic levels instead of similar species may have offered more instructive
results as to how different fish species respond to the chemical stressors.
63
3.0. Future Work
Several observations in this study open up potential for future research. Female
darters were targeting in this study to maintain consistency and to reduce variability in
the ability of each sex to metabolize contaminants. The trends observed in the present
study indicates that a more extensive project may be beneficial. Five study sites were
used in this study, and only polar contaminants were considered. Future work may look
at expanding the total number of study sites to monitor across an exposure gradient, while
monitoring for both polar and non-polar organic contaminants.
An investigation into why fantail darters exhibited significantly different
responses compared to rainbow darters may also be of value. Both species share a
similar life history, making mechanistic studies of interest. It may be beneficial to
explore potential differences in responses to known inducers of targeted biomarkers (i.e.
β-napthoflavone for EROD induction) in a controlled setting. Laboratory trials may
indicate whether the species has an intrinsic buffering capacity for xenobiotic exposure,
or if the reasons for differences in their responses are more closely linked to differences
in habitat selection and life history.
Sucralose was detected at high concentrations downstream of the Doon WWTP.
However, this persistent compound was not detected at any of the rural sites. It may be
beneficial to investigate the removal of artificial sweeteners, including sucralose, at
several different WWTPs utilizing different treatment technologies and with services for
different population sizes. Sucralose is primarily discharged through WWTP effluent and
is persistent, only showing signs of degradation in water at pH 10 (Tollefsen et al. 2012).
64
References
Ahmed, M., Latif, N., Khan, R. A., & Ahmad, A. (2012). Toxicological effect of
herbicides (diuron and bentazon) on snake venom and electric eel
acetylcholinesterase. Bulletin of Environmental Contamination and Toxicology,89(2),
229-233.
Anderson, J. C., Dubetz, C., & Palace, V. P. (2015). Neonicotinoids in the Canadian
aquatic environment: A literature review on current use products with a focus on fate,
exposure, and biological effects. Science of the Total Environment, 505, 409-422.
Arellano-Aguilar, O., Montoya, R. M., & Garcia, C. M. (2009). Endogenous functions
and expression of cytochrome P450 enzymes in teleost fish: a review. Reviews in
Fisheries Science, 17(4), 541-556.
Arlos, M. J., Bragg, L. M., Servos, M. R., & Parker, W. J. (2014). Simulation of the fate
of selected pharmaceuticals and personal care products in a highly impacted reach of a
Canadian watershed. Science of the Total Environment, 485, 193-204.
Bahamonde, P. A., Fuzzen, M. L., Bennett, C. J., Tetreault, G. R., McMaster, M. E.,
Servos, M. R., Martyniuk,C.J., & Munkittrick, K. R. (2015). Whole organism responses
and intersex severity in rainbow darter (Etheostoma caeruleum) following exposures to
municipal wastewater in the Grand River basin, ON, Canada. Part A. Aquatic
Toxicology, 159, 290-301.
Bartelt-Hunt, S., Snow, D. D., Damon-Powell, T., & Miesbach, D. (2011). Occurrence of
steroid hormones and antibiotics in shallow groundwater impacted by livestock waste
control facilities. Journal of Contaminant Hydrology, 123(3), 94-103.
Bartoskova, M., Dobsikova, R., Stancova, V., Zivna, D., Blahova, J., Marsalek, P.,
Zelnickova, L. Bartos, M., Casuscelli, F., & Faggio, C. (2013). Evaluation of ibuprofen
toxicity for zebrafish (Danio rerio) targeting on selected biomarkers of oxidative stress.
Neuroendocrinology Letters, 34, 102-108.
Bereswill, R., Golla, B., Streloke, M., & Schulz, R. (2012). Entry and toxicity of organic
pesticides and copper in vineyard streams: erosion rills jeopardise the efficiency of
riparian buffer strips. Agriculture, Ecosystems & Environment,146(1), 81-92.
Bisson, M., & Hontela, A. (2002). Cytotoxic and endocrine-disrupting potential of
atrazine, diazinon, endosulfan, and mancozeb in adrenocortical steroidogenic cells of
rainbow trout exposed in vitro. Toxicology and Applied Pharmacology,180(2), 110-117.
Bolger, T., & Connolly, P. L. (1989). The selection of suitable indices for the
measurement and analysis of fish condition. Journal of Fish Biology, 34(2), 171-182.
65
Bollmann, U. E., Tang, C., Eriksson, E., Jönsson, K., Vollertsen, J., & Bester, K. (2014).
Biocides in urban wastewater treatment plant influent at dry and wet weather:
Concentrations, mass flows and possible sources. Water Research, 60, 64-74.
Bravo, C. F., Curtis, L. R., Myers, M. S., Meador, J. P., Johnson, L. L., Buzitis, J.,
Collier,T.K., Morrow, J.D., Laetz,C.A., Loge, F.J., & Arkoosh, M. R. (2011). Biomarker
responses and disease susceptibility in juvenile rainbow trout Oncorhynchus mykiss fed a
high molecular weight PAH mixture. Environmental Toxicology and Chemistry, 30(3),
704-714.
Bretaud, S., Toutant, J. P., & Saglio, P. (2000). Effects of carbofuran, diuron, and
nicosulfuron on acetylcholinesterase activity in goldfish (Carassius
auratus). Ecotoxicology and Environmental Safety, 47(2), 117-124.
Brown, C. J., Knight, B. W., McMaster, M. E., Munkittrick, K. R., Oakes, K. D.,
Tetreault, G. R., & Servos, M. R. (2011). The effects of tertiary treated municipal
wastewater on fish communities of a small river tributary in Southern Ontario,
Canada. Environmental Pollution, 159(7), 1923-1931.
Buerge, I. J., Buser, H. R., Kahle, M., Muller, M. D., & Poiger, T. (2009). Ubiquitous
occurrence of the artificial sweetener acesulfame in the aquatic environment: an ideal
chemical marker of domestic wastewater in groundwater. .Environmental Science &
Technology, 43(12), 4381-4385.
Bundschuh, M., Goedkoop, W., & Kreuger, J. (2014). Evaluation of pesticide monitoring
strategies in agricultural streams based on the toxic-unit concept—Experiences from
long-term measurements. Science of the Total Environment, 484, 84-91.
Byer, J. D., Struger, J., Sverko, E., Klawunn, P., & Todd, A. (2011). Spatial and seasonal
variations in atrazine and metolachlor surface water concentrations in Ontario (Canada)
using ELISA. Chemosphere, 82(8), 1155-1160.
Cattaneo, R., Loro, V. L., Spanevello, R., Silveira, F. A., Luz, L., Miron, D. S., Fonseca,
M.B., Moraes, B.S., & Clasen, B. (2008). Metabolic and histological parameters of silver
catfish (Rhamdia quelen) exposed to commercial formulation of 2, 4-
dichlorophenoxiacetic acid (2, 4-D) herbicide. Pesticide Biochemistry and
Physiology, 92(3), 133-137.
Charlestra, L., A. Amirbahman, D.L. Courtemanch, D.A. Alvarez, H. Patterson. 2012.
Estimating pesticide sampling rates by the polar organic chemical integrative sampler
(POCIS) in the presence of natural organic matter and varying hydrodynamic conditions.
Environmental Pollution169:98-104.
Chaves, A., D. Shea, D. Danchower. 2008. Analysis of chlorothalonil and degradation
products in soil and water by GC/MS and LC/MS. Chemosphere 71:629-638.
66
Chen, Z. F., Ying, G. G., Jiang, Y. X., Yang, B., Lai, H. J., Liu, Y. S., Pan, C.G., & Peng,
F. Q. (2014). Photodegradation of the azole fungicide fluconazole in aqueous solution
under UV-254: Kinetics, mechanistic investigations and toxicity evaluation. Water
Research, 52, 83-91.
Cutler, G. C., & Scott-Dupree, C. D. (2014). A field study examining the effects of
exposure to neonicotinoid seed-treated corn on commercial bumble bee
colonies. Ecotoxicology, 23(9), 1755-1763.
Codi, S., Humphrey, C., Klumpp, D., & Delean, S. (2004). Barramundi as an indicator
species for environmental monitoring in north Queensland, Australia: laboratory versus
field studies. Environmental Toxicology and Chemistry,23(11), 2737-2744.
Countway, R. E., Dickhut, R. M., & Canuel, E. A. (2003). Polycyclic aromatic
hydrocarbon (PAH) distributions and associations with organic matter in surface waters
of the York River, VA Estuary. Organic Geochemistry, 34(2), 209-224.
Dalton, R.L., F.R. Pick, C. Boutin, A. Saleem. 2014. Atrazine contamination at the
watershed scale and environmental factors affecting sampling rates of the polar organic
chemical integrative sampler (POCIS). Environmental Pollution 189:13-142.
da Fonseca, M. B., Glusczak, L., Moraes, B. S., de Menezes, C. C., Pretto, A., Tierno, M.
A., Zanella,R., Goncalves,F.F., & Loro, V. L. (2008). The 2, 4-D herbicide effects on
acetylcholinesterase activity and metabolic parameters of piava freshwater fish
(Leporinus obtusidens). Ecotoxicology and Environmental Safety, 69(3), 416-420.
Da Rocha, A. M., de Freitas, D. S., Burns, M., Vieira, J. P., de La Torre, F. R., &
Monserrat, J. M. (2009). Seasonal and organ variations in antioxidant capacity,
detoxifying competence and oxidative damage in freshwater and estuarine fishes from
Southern Brazil. Comparative Biochemistry and Physiology Part C: Toxicology &
Pharmacology, 150(4), 512-520.
Day, K. E., Kirby, R. S., & Reynoldson, T. B. (1994). Sexual dimorphism in Chironomus
riparius (meigen): Impact on interpretation of growth in whole‐sediment toxicity
tests. Environmental Toxicology and Chemistry, 13(1), 35-39.
Dorner, S. M., Huck, P. M., & Slawson, R. M. (2004). Estimating potential
environmental loadings of Cryptosporidium spp. and Campylobacter spp. from livestock
in the Grand River watershed, Ontario, Canada. Environmental Science &
Technology, 38(12), 3370-3380.
Edwards, M., Topp, E., Metcalfe, C. D., Li, H., Gottschall, N., Bolton, P., Curnoe, W.,
Payne, M., Beck, A., Kleywegt, S., & Lapen, D. R. (2009). Pharmaceutical and personal
care products in tile drainage following surface spreading and injection of dewatered
municipal biosolids to an agricultural field. Science of the Total Environment, 407(14),
4220-4230.
67
Ellman, G. L., Courtney, K. D., Andres, V., & Featherstone, R. M. (1961). A new and
rapid colorimetric determination of acetylcholinesteraseactivity. Biochemical
Pharmacology, 7(2), 88-95.
Farkas, A., Salanki, J., & Specziar, A. (2002). Relation between growth and the heavy
metal concentration in organs of bream Abramis brama L. populating Lake
Balaton. Archives of Environmental Contamination and Toxicology, 43(2), 236-243.
Ferreira, D., da Motta, A. C., Kreutz, L. C., Toni, C., Loro, V. L., & Barcellos, L. J. G.
(2010). Assessment of oxidative stress in Rhamdia quelen exposed to
agrichemicals. Chemosphere, 79(9), 914-921.
Fisher, T. C., Crane, M., & Callaghan, A. (2000). An optimized microtiterplate assay to
detect acetylcholinesterase activity in individual Chironomus riparius
Meigen. Environmental Toxicology and Chemistry, 19(7), 1749-1752.
Fonseca, V. F., França, S., Serafim, A., Company, R., Lopes, B., Bebianno, M. J., &
Cabral, H. N. (2011). Multi-biomarker responses to estuarine habitat contamination in
three fish species: Dicentrarchus labrax, Solea senegalensis and Pomatoschistus
microps. Aquatic Toxicology, 102(3), 216-227.
Frasco, M. F., & Guilhermino, L. (2002). Effects of dimethoate and beta-naphthoflavone
on selected biomarkers of Poecilia reticulata. Fish Physiology and Biochemistry, 26(2),
149-156.
Fuzzen, M. L., Bennett, C. J., Tetreault, G. R., McMaster, M. E., & Servos, M. R. (2015).
Severe intersex is predictive of poor fertilization success in populations of rainbow darter
(Etheostoma caeruleum). Aquatic Toxicology, 160, 106-116.
Gagné, F., Blaise, C., & André, C. (2006). Occurrence of pharmaceutical products in a
municipal effluent and toxicity to rainbow trout (Oncorhynchus mykiss)
hepatocytes. Ecotoxicology and Environmental Safety, 64(3), 329-336.
Garcia-Ac, A., Segura, P. A., Viglino, L., Fürtös, A., Gagnon, C., Prévost, M., & Sauvé,
S. (2009). On-line solid-phase extraction of large-volume injections coupled to liquid
chromatography-tandem mass spectrometry for the quantitation and confirmation of 14
selected trace organic contaminants in drinking and surface water. Journal of
Chromatography A, 1216(48), 8518-8527.
Gerecke, A. C., Schärer, M., Singer, H. P., Müller, S. R., Schwarzenbach, R. P., Sägesser,
M., Ochsenbein, U., & Popow, G. (2002). Sources of pesticides in surface waters in
Switzerland: pesticide load through waste water treatment plants––current situation and
reduction potential. Chemosphere, 48(3), 307-315.
Gillis, PL, F Gagné, R McInnis, TM Hooey, ES Choy, C André, ME Hoque, CD
Metcalfe. 2014. The impact of municipal wastewater effluents on field-deployed
freshwater mussels in the Grand River (ON). Environmental Toxicology and Chemistry,
33, 134-143.
68
Glusczak, L., Loro, V. L., Pretto, A., Moraes, B. S., Raabe, A., Duarte, M. F., da
Fonseca, M.B., de Menezes, C.C., & de Sousa Valladão, D. M. (2011). Acute exposure to
glyphosate herbicide affects oxidative parameters in piava (Leporinus
obtusidens). Archives of Environmental Contamination and Toxicology, 61(4), 624-630.
Gottschall, N., Topp, E., Metcalfe, C., Edwards, M., Payne, M., Kleywegt, S., Russel,
P., & Lapen, D. R. (2012). Pharmaceutical and personal care products in groundwater,
subsurface drainage, soil, and wheat grain, following a high single application of
municipal biosolids to a field. Chemosphere, 87(2), 194-203.
Gracia-Lor, E., Sancho, J. V., Serrano, R., & Hernández, F. (2012). Occurrence and
removal of pharmaceuticals in wastewater treatment plants at the Spanish Mediterranean
area of Valencia. Chemosphere, 87(5), 453-462.
Guillette, L. J., & Gunderson, M. P. (2001). Alterations in development of reproductive
and endocrine systems of wildlife populations exposed to endocrine-disrupting
contaminants. Reproduction, 122(6), 857-864.
Gurke, R., Rossmann, J., Schubert, S., Sandmann, T., Rößler, M., Oertel, R., & Fauler, J.
(2015a). Development of a SPE-HPLC–MS/MS method for the determination of most
prescribed pharmaceuticals and related metabolites in urban sewage samples. Journal of
Chromatography B, 990, 23-30.
Gurke, R., Rößler, M., Marx, C., Diamond, S., Schubert, S., Oertel, R., & Fauler, J.
(2015b). Occurrence and removal of frequently prescribed pharmaceuticals and
corresponding metabolites in wastewater of a sewage treatment plant. Science of the Total
Environment, 532, 762-770.
Hanson, N., & Larsson, Å. (2011). Biomarker analyses in caged and wild fish suggest
exposure to pollutants in an urban area with a landfill. Environmental Toxicology, 26(3),
315-324.
Harman, C., Bøyum, O., Thomas, K. V., & Grung, M. (2009). Small but different effect
of fouling on the uptake rates of semipermeable membrane devices and polar organic
chemical integrative samplers. Environmental Toxicology and Chemistry, 28(11), 2324-
2332.
Helm, P. A., Howell, E. T., Li, H., Metcalfe, T. L., Chomicki, K. M., & Metcalfe, C. D.
(2012). Influence of nearshore dynamics on the distribution of organic wastewater-
associated chemicals in Lake Ontario determined using passive samplers. Journal of
Great Lakes Research, 38, 105-115.
Hernandez-Moreno, D., Soler-Rodriguez, F., Míguez-Santiyán, M. P., & Perez-Lopez, M.
(2008). Hepatic monooxygenase (CYP1A and CYP3A) and UDPGT enzymatic activities
as biomarkers for long-term carbofuran exposure in tench (Tinca tinca L). Journal of
Environmental Science and Health Part B, 43(5), 395-404.
69
Hijosa-Valsero, M., Matamoros, V., Sidrach-Cardona, R., Martín-Villacorta, J., Becares,
E., & Bayona, J. M. (2010). Comprehensive assessment of the design configuration of
constructed wetlands for the removal of pharmaceuticals and personal care products from
urban wastewaters. Water research, 44(12), 3669-3678.
Hodson, P. V., Efler, S., Wilson, J. Y., El-Shaarawi, A., Maj, M., & Williams, T. G.
(1996). Measuring the potency of pulp mill effluents for induction of hepatic mixed-
function oxygenase activity in fish. Journal of Toxicology and Environmental
Health, 49(1), 83-110.
Hoeger, B., van den Heuvel, M. R., Hitzfeld, B. C., & Dietrich, D. R. (2004). Effects of
treated sewage effluent on immune function in rainbow trout (Oncorhynchus
mykiss). Aquatic Toxicology, 70(4), 345-355.
Holeton, C., Chambers, P. A., & Grace, L. (2011). Wastewater release and its impacts on
Canadian waters. Canadian journal of fisheries and aquatic sciences, 68(10), 1836-1859.
Hubbs, C. (1985). Darter reproductive seasons. Copeia, 56-68.
Ings, J. S., Servos, M. R., & Vijayan, M. M. (2011a). Hepatic transcriptomics and protein
expression in rainbow trout exposed to municipal wastewater effluent. Environmental
Science & Technology, 45(6), 2368-2376.
Ings, J. S., Servos, M. R., & Vijayan, M. M. (2011b). Exposure to municipal wastewater
effluent impacts stress performance in rainbow trout. Aquatic Toxicology, 103(1), 85-91.
Jasinska, E. J., Goss, G. G., Gillis, P. L., Van Der Kraak, G. J., Matsumoto, J., de Souza
Machado, A. A., ... & Metcalfe, C. D. (2015). Assessment of biomarkers for
contaminants of emerging concern on aquatic organisms downstream of a municipal
wastewater discharge. Science of the Total Environment, 530, 140-153.
Johnson, A. C., Keller, V., Dumont, E., & Sumpter, J. P. (2015). Assessing the
concentrations and risks of toxicity from the antibiotics ciprofloxacin, sulfamethoxazole,
trimethoprim and erythromycin in European rivers. Science of the Total
Environment, 511, 747-755.
Karaca, M., Varışlı, L., Korkmaz, K., Özaydın, O., Perçin, F., & Orhan, H. (2014).
Organochlorine pesticides and antioxidant enzymes are inversely correlated with liver
enzyme gene expression in Cyprinus carpio. Toxicology Letters, 230(2), 198-207.
Kaserzon, S. L., Hawker, D. W., Kennedy, K., Bartkow, M., Carter, S., Booij, K., &
Mueller, J. F. (2014). Characterisation and comparison of the uptake of ionizable and
polar pesticides, pharmaceuticals and personal care products by POCIS and
Chemcatchers. Environmental Science: Processes & Impacts, 16(11), 2517-2526.
Kelly, K. A., Havrilla, C. M., Brady, T. C., Abramo, K. H., & Levin, E. D. (1998).
Oxidative stress in toxicology: established mammalian and emerging piscine model
systems. Environmental Health Perspectives, 106(7), 375.
70
Kiparissis, Y., Balch, G. C., Metcalfe, T. L., & Metcalfe, C. D. (2003). Effects of the
isoflavones genistein and equol on the gonadal development of Japanese medaka, Oryzias
latipes. Environmental Health Perspectives, 111(9), 1158.
Koenig, S., Fernández, P., & Solé, M. (2012). Differences in cytochrome P450 enzyme
activities between fish and crustacea: relationship with the bioaccumulation patterns of
polychlorobiphenyls (PCBs). Aquatic Toxicology,108, 11-17.
Kolpin, D. W., Thurman, E. M., Lee, E. A., Meyer, M. T., Furlong, E. T., & Glassmeyer,
S. T. (2006). Urban contributions of glyphosate and its degradate AMPA to streams in
the United States. Science of the Total Environment, 354(2), 191-197.
Kurt‐Karakus, P. B., Teixeira, C., Small, J., Muir, D., & Bidleman, T. F. (2011). Current‐use pesticides in inland lake waters, precipitation, and air from Ontario,
Canada. Environmental Toxicology and Chemistry, 30(7), 1539-1548.
Lapen, D. R., Topp, E., Metcalfe, C. D., Li, H., Edwards, M., Gottschall, N., Bolton, P.,
Cunroe, W., Payne, M., & Beck, A. (2008). Pharmaceutical and personal care products in
tile drainage following land application of municipal biosolids. Science of the Total
Environment, 399(1), 50-65.
Larcher, S., Delbès, G., Robaire, B., & Yargeau, V. (2012). Degradation of 17α-
ethinylestradiol by ozonation—Identification of the by-products and assessment of their
estrogenicity and toxicity. Environment International, 39(1), 66-72.
Le Cren, E. D. (1951). The length-weight relationship and seasonal cycle in gonad weight
and condition in the perch (Perca fluviatilis). The Journal of Animal Ecology, 201-219.
Li, H., Vermeirssen, E. L., Helm, P. A., & Metcalfe, C. D. (2010a). Controlled field
evaluation of water flow rate effects on sampling polar organic compounds using polar
organic chemical integrative samplers. Environmental Toxicology and Chemistry, 29(11),
2461-2469.
Li, H., Helm, P. A., & Metcalfe, C. D. (2010b). Sampling in the Great Lakes for
pharmaceuticals, personal care products, and endocrine‐disrupting substances using the
passive polar organic chemical integrative sampler. Environmental Toxicology and
Chemistry, 29(4), 751-762.
Lissemore, L., Hao, C., Yang, P., Sibley, P. K., Mabury, S., & Solomon, K. R. (2006).
An exposure assessment for selected pharmaceuticals within a watershed in Southern
Ontario. Chemosphere, 64(5), 717-729.
MacLeod, S.L., E.L. McClure, C.S. Wong. (2007). Laboratory calibration and field
deployment of the polar organic chemical integrative sampler for pharmaceuticals and
personal care products in wastewater and surface water. Environmental Toxicology and
Chemistry 26:2517-2529.
71
Maier, D., Blaha, L., Giesy, J. P., Henneberg, A., Köhler, H. R., Kuch, B., Osterauer, R.,
Peschke, K., Richter, D., Scheurer, M., & Triebskorn, R. (2015). Biological plausibility
as a tool to associate analytical data for micropollutants and effect potentials in
wastewater, surface water, and sediments with effects in fishes. Water Research, 72, 127-
144.
Maillard, E., Payraudeau, S., Faivre, E., Grégoire, C., Gangloff, S., & Imfeld, G. (2011).
Removal of pesticide mixtures in a stormwater wetland collecting runoff from a vineyard
catchment. Science of the Total Environment, 409(11), 2317-2324.
Maqsood, S., & Benjakul, S. (2011). Comparative studies on molecular changes and pro-
oxidative activity of haemoglobin from different fish species as influenced by pH. Food
Chemistry, 124(3), 875-883.
Martin, J. D., Adams, J., Hollebone, B., King, T., Brown, R. S., & Hodson, P. V. (2014).
Chronic toxicity of heavy fuel oils to fish embryos using multiple exposure
scenarios. Environmental Toxicology and Chemistry, 33(3), 677-687.
Mawhinney, D. B., Young, R. B., Vanderford, B. J., Borch, T., & Snyder, S. A. (2011).
Artificial sweetener sucralose in US drinking water systems.Environmental science &
technology, 45(20), 8716-8722.
Mayer, T., Bennie, D., Rosa, F., Palabrica, V., Rekas, G., Schachtschneider, J., &
Marvin, C. (2008). Dispersal of contaminants from municipal discharges as evidenced
from sedimentary records in a Great Lakes coastal wetland, Cootes Paradise,
Ontario. Journal of Great Lakes Research, 34(3), 544-558.
Mazzella, N., Lissalde, S., Moreira, S., Delmas, F., Mazellier, P., & Huckins, J. N.
(2010). Evaluation of the use of performance reference compounds in an Oasis-HLB
adsorbent based passive sampler for improving water concentration estimates of polar
herbicides in freshwater. Environmental science & technology, 44(5), 1713-1719.
Mazzella, N., T. Debenest, F. Delmas. (2008). Comparison between the polar chemical
integrative sampler and the solid-phase extraction for estimating herbicide time-weighted
average concentrations during a microcosm experiment. Chemosphere 73:545-550.
Metcalfe, C. D., Metcalfe, T. L., Kiparissis, Y., Koenig, B. G., Khan, C., Hughes, R. J.,
Croley, T.R., March, R.E., & Potter, T. (2001). Estrogenic potency of chemicals detected
in sewage treatment plant effluents as determined by in vivo assays with Japanese
medaka (Oryzias latipes). Environmental Toxicology and Chemistry, 20(2), 297-308.
Metcalfe, C. D., Kleywegt, S., Letcher, R. J., Topp, E., Wagh, P., Trudeau, V. L., &
Moon, T. W. (2013). A multi-assay screening approach for assessment of endocrine-
active contaminants in wastewater effluent samples. Science of the Total
Environment, 454, 132-140.
72
Metcalfe, C. D., Chu, S., Judt, C., Li, H., Oakes, K. D., Servos, M. R., & Andrews, D. M.
(2010). Antidepressants and their metabolites in municipal wastewater, and downstream
exposure in an urban watershed. Environmental Toxicology and Chemistry, 29(1), 79-89.
Metcalfe, C., Hoque, M. E., Sultana, T., Murray, C., Helm, P., & Kleywegt, S. (2014).
Monitoring for contaminants of emerging concern in drinking water using POCIS passive
samplers. Environmental Science: Processes & Impacts, 16(3), 473-481.
Metcalfe, C.D., Sultana, T., Li, H., & Helm, P.A. Fungicides and current-use herbicides
in urban receiving waters in Ontario, Canada monitored using POCIS passive samplers,
Science of the Total Environment (submitted)..
Metcalfe, T. L., Metcalfe, C. D., Bennett, E. R., & Haffner, G. D. (2000). Distribution of
toxic organic contaminants in water and sediments in the Detroit River. Journal of Great
Lakes Research, 26(1), 55-64.
Metcalfe, T. L., Dillon, P. J., & Metcalfe, C. D. (2008). Detecting the transport of toxic
pesticides from golf courses into watersheds in the Precambrian shield region of Ontario,
Canada. Environmental Toxicology and Chemistry, 27(4), 811-818.
Miao, X. S., Yang, J. J., & Metcalfe, C. D. (2005). Carbamazepine and its metabolites in
wastewater and in biosolids in a municipal wastewater treatment plant. Environmental
Science & Technology, 39(19), 7469-7475.
Miège, C., Budzinski, H., Jacquet, R., Soulier, C., Pelte, T., & Coquery, M. (2012). Polar
organic chemical integrative sampler (POCIS): application for monitoring organic
micropollutants in wastewater effluent and surface water. Journal of Environmental
Monitoring, 14(2), 626-635.
Moore, M. T., Kröger, R., Locke, M. A., Lizotte Jr, R. E., Testa III, S., & Cooper, C. M.
(2014). Diazinon and permethrin mitigation across a grass–wetland buffer. Bulletin of
Environmental Contamination and Toxicology, 93(5), 574-579.
Moreau-Guigon, E., Motelay-Massei, A., Harner, T., Pozo, K., Diamond, M., Chevreuil,
M., & Blanchoud, H. (2007). Vertical and temporal distribution of persistent organic
pollutants in Toronto. 1. Organochlorine pesticides. Environmental Science &
Technology, 41(7), 2172-2177.
Mortensen, A. S., & Arukwe, A. (2007). Effects of 17α-ethynylestradiol on hormonal
responses and xenobiotic biotransformation system of Atlantic salmon (Salmo
salar). Aquatic Toxicology, 85(2), 113-123.
Nunes, B., Campos, J. C., Gomes, R., Braga, M. R., Ramos, A. S., Antunes, S. C., &
Correia, A. T. (2015). Ecotoxicological effects of salicylic acid in the freshwater fish
Salmo trutta fario: antioxidant mechanisms and histological alterations. Environmental
Science and Pollution Research, 22(1), 667-678.
73
Nwani, C. D., Lakra, W. S., Nagpure, N. S., Kumar, R., Kushwaha, B., & Srivastava, S.
K. (2010). Toxicity of the herbicide atrazine: effects on lipid peroxidation and activities
of antioxidant enzymes in the freshwater fish Channa punctatus (Bloch). International
Journal of Environmental Research and Public Health, 7(8), 3298-3312.
Oakes, K. D., & Van Der Kraak, G. J. (2003). Utility of the TBARS assay in detecting
oxidative stress in white sucker (Catostomus commersoni) populations exposed to pulp
mill effluent. Aquatic Toxicology, 63(4), 447-463.
Oakes, K. D., McMaster, M. E., & Van Der Kraak, G. J. (2004). Oxidative stress
responses in longnose sucker (Catostomus catostomus) exposed to pulp and paper mill
and municipal sewage effluents. Aquatic Toxicology, 67(3), 255-271.
Paine, M. D., Dodson, J. J., & Power, G. (1982). Habitat and food resource partitioning
among four species of darters (Percidae: Etheostoma) in a southern Ontario
stream. Canadian Journal of Zoology, 60(7), 1635-1641.
Palma, P., Köck-Schulmeyer, M., Alvarenga, P., Ledo, L., de Alda, M. L., & Barceló, D.
(2015). Occurrence and potential risk of currently used pesticides in sediments of the
Alqueva reservoir (Guadiana Basin). Environmental Science and Pollution
Research, 22(10), 7665-7675.
Pedrajas, J. R., Peinado, J., & Lopez-Barea, J. (1995). Oxidative stress in fish exposed to
model xenobiotics. Oxidatively modified forms of Cu, Zn-superoxide dismutase as
potential biomarkers. Chemico-Biological Interactions, 98(3), 267-282.
Poissant, L., Beauvais, C., Lafrance, P., & Deblois, C. (2008). Pesticides in fluvial
wetlands catchments under intensive agricultural activities. Science of the Total
Environment, 404(1), 182-195.
Rajakumar, A., Singh, R., Chakrabarty, S., Murugananthkumar, R., Laldinsangi, C.,
Prathibha, Y. & Senthilkumaran, B. (2012). Endosulfan and flutamide impair testicular
development in the juvenile Asian catfish, Clarias batrachus. Aquatic Toxicology, 110,
123-132.
Reichenberger, S., Bach, M., Skitschak, A., & Frede, H. G. (2007). Mitigation strategies
to reduce pesticide inputs into ground-and surface water and their effectiveness; A
review. Science of the Total Environment, 384(1), 1-35.
Reid, S. M. (2004). Age estimates and length distributions of Ontario channel darter
(Percina copelandi) populations. Journal of Freshwater Ecology, 19(3), 441-444.
Ribalta, C., Sanchez-Hernandez, J. C., & Sole, M. (2015). Hepatic biotransformation and
antioxidant enzyme activities in Mediterranean fish from different habitat depths. Science
of the Total Environment, 532, 176-183.
74
Rodayan, A., Segura, P. A., & Yargeau, V. (2014). Ozonation of wastewater: removal
and transformation products of drugs of abuse. Science of the Total Environment, 487,
763-770.
Rossi, S. C., Da Silva, M. D., Piancini, L. D. S., Ribeiro, C. A. O., Cestari, M. M., & de
Assis, H. C. S. (2011). Sublethal effects of waterborne herbicides in tropical freshwater
fish. Bulletin of Environmental Contamination and Toxicology, 87(6), 603-607.
Rujiralai, T., Bull, I. D., Llewellyn, N., & Evershed, R. P. (2011). In situ polar organic
chemical integrative sampling (POCIS) of steroidal estrogens in sewage treatment works
discharge and river water. Journal of Environmental Monitoring, 13(5), 1427-1434.
Ryan, C. C., Tan, D. T., & Arnold, W. A. (2011). Direct and indirect photolysis of
sulfamethoxazole and trimethoprim in wastewater treatment plant effluent. Water
Research, 45(3), 1280-1286.
Sabourin, L., Beck, A., Duenk, P. W., Kleywegt, S., Lapen, D. R., Li, H.,
Metcalfe,C.D., Payne, M., & Topp, E. (2009). Runoff of pharmaceuticals and personal
care products following application of dewatered municipal biosolids to an agricultural
field. Science of the Total Environment, 407(16), 4596-4604.
Salaberria, I., Hansen, B. H., Asensio, V., Olsvik, P. A., Andersen, R. A., & Jenssen, B.
M. (2009). Effects of atrazine on hepatic metabolism and endocrine homeostasis in
rainbow trout (Oncorhynchus mykiss). Toxicology and Applied Pharmacology, 234(1),
98-106.
Sanchez, W., Ait-Aissa, S., Palluel, O., Ditche, J. M., & Porcher, J. M. (2007).
Preliminary investigation of multi-biomarker responses in three-spined stickleback
(Gasterosteus aculeatus L.) sampled in contaminated streams. Ecotoxicology, 16(2), 279-
287.
Sánchez-Muros, M. J., Villacreces, S., Miranda-de la Lama, G., de Haro, C., & García-
Barroso, F. (2013). Effects of chemical and handling exposure on fatty acids, oxidative
stress and morphological welfare indicators in gilt-head sea bream (Sparus aurata). Fish
Physiology and Biochemistry, 39(3), 581-591.
Sattler, C., Kächele, H., & Verch, G. (2007). Assessing the intensity of pesticide use in
agriculture. Agriculture, Ecosystems & Environment, 119(3), 299-304.
Scheurer, M., Brauch, H. J., & Lange, F. T. (2009). Analysis and occurrence of seven
artificial sweeteners in German waste water and surface water and in soil aquifer
treatment (SAT). Analytical and Bioanalytical Chemistry, 394(6), 1585-1594.
Scornaienchi, M. L., Thornton, C., Willett, K. L., & Wilson, J. Y. (2010). Cytochrome
P450-mediated 17β-estradiol metabolism in zebrafish (Danio rerio). .Journal of
Endocrinology, 206(3), 317-325.
75
Scribner, E.A., J.L. Orlando, W.A. Battaglin, M.W. Sandstrom, K.M. Kuivila, M.T.
Meyer. (2006). Results of analyses of the fungicide, chlorothalonil, its degradation
products, and other selected pesticides at 22 surface-water sites in five southern states,
2003-04. U.S. Geological Survey, Open File Report 2006-1207, 36 p.
Servos, M. R., Bennie, D. T., Burnison, B. K., Jurkovic, A., McInnis, R., Neheli, T.,
Schnell, A., Seto, P., Smyth, S.A., & Ternes, T. A. (2005). Distribution of estrogens, 17β-
estradiol and estrone, in Canadian municipal wastewater treatment plants. Science of the
Total Environment, 336(1), 155-170.
Shelley, L. K., Ross, P. S., Miller, K. M., Kaukinen, K. H., & Kennedy, C. J. (2012).
Toxicity of atrazine and nonylphenol in juvenile rainbow trout (Oncorhynchus mykiss):
effects on general health, disease susceptibility and gene expression. Aquatic
Toxicology, 124, 217-226.
Singer, H., Jaus, S., Hanke, I., Lück, A., Hollender, J., & Alder, A. C. (2010).
Determination of biocides and pesticides by on-line solid phase extraction coupled with
mass spectrometry and their behaviour in wastewater and surface water. Environmental
Pollution, 158(10), 3054-3064.
Smith, E. M., Iftikar, F. I., Higgins, S., Irshad, A., Jandoc, R., Lee, M., & Wilson, J. Y.
(2012). In vitro inhibition of cytochrome P450-mediated reactions by gemfibrozil,
erythromycin, ciprofloxacin and fluoxetine in fish liver microsomes. Aquatic
Toxicology, 109, 259-266.
Smith, E. M., & Wilson, J. Y. (2010). Assessment of cytochrome P450 fluorometric
substrates with rainbow trout and killifish exposed to dexamethasone, pregnenolone-16α-
carbonitrile, rifampicin, and β-naphthoflavone. Aquatic Toxicology, 97(4), 324-333.
Solé, M., Varó, I., González-Mira, A., & Torreblanca, A. (2015). Xenobiotic metabolism
modulation after long-term temperature acclimation in juveniles of Solea
senegalensis. Marine Biology, 162(2), 401-412.
Spoelstra, J., Schiff, S. L., & Brown, S. J. (2013). Artificial sweeteners in a large
canadian river reflect human consumption in the watershed. PLOS One 8(12),1-6.
Stamatis, N., Hela, D., & Konstantinou, I. (2010). Occurrence and removal of fungicides
in municipal sewage treatment plant. Journal of Hazardous Materials, 175(1), 829-835.
Struger, J., L’italien, S., & Sverko, E. (2004). In-use pesticide concentrations in surface
waters of the Laurentian Great Lakes, 1994–2000. Journal of Great Lakes
Research, 30(3), 435-450.
Sturve, J., Almroth, B. C., & Förlin, L. (2008). Oxidative stress in rainbow trout
(Oncorhynchus mykiss) exposed to sewage treatment plant effluent. Ecotoxicology and
Environmental Safety, 70(3), 446-452.
76
Sumith, J. A., Hansani, P. L., Weeraratne, T. C., & Munkittrick, K. R. (2012). Seasonal
exposure of fish to neurotoxic pesticides in an intensive agricultural catchment, Uma‐oya,
Sri Lanka: Linking contamination and acetylcholinesterase inhibition. Environmental
Toxicology and Chemistry, 31(7), 1501-1510.
Tanna, R. N., Tetreault, G. R., Bennett, C. J., Smith, B. M., Bragg, L. M., Oakes, K. D.,
McMaster, M.E., & Servos, M. R. (2013). Occurrence and degree of intersex (testis–ova)
in darters (Etheostoma sp.) across an urban gradient in the Grand River, Ontario,
Canada. Environmental Toxicology and Chemistry, 32(9), 1981-1991.
Ternes, T. A., Stumpf, M., Mueller, J., Haberer, K., Wilken, R. D., & Servos, M. (1999).
Behavior and occurrence of estrogens in municipal sewage treatment plants—I.
Investigations in Germany, Canada and Brazil. Science of the Total Environment, 225(1),
81-90.
Tetreault, G. R., Bennett, C. J., Shires, K., Knight, B., Servos, M. R., & McMaster, M. E.
(2011). Intersex and reproductive impairment of wild fish exposed to multiple municipal
wastewater discharges. Aquatic Toxicology, 104(3), 278-290.
Tetreault, G. R., Brown, C. J., Bennett, C. J., Oakes, K. D., McMaster, M. E., & Servos,
M. R. (2013). Fish community responses to multiple municipal wastewater inputs in a
watershed. Integrated Environmental Assessment and Management, 9(3), 456-468.
Tetreault, G. R. (2012). The Response of Wild Fish to Municipal Wastewater Effluent
Exposures at Sites in Canada (Doctoral dissertation, University of Waterloo).
Tixier, C., Singer, H. P., Oellers, S., & Müller, S. R. (2003). Occurrence and fate of
carbamazepine, clofibric acid, diclofenac, ibuprofen, ketoprofen, and naproxen in surface
waters. Environmental Science & Technology, 37(6), 1061-1068.
Togunde, O. P., Oakes, K. D., Servos, M. R., & Pawliszyn, J. (2012). Determination of
pharmaceutical residues in fish bile by solid-phase microextraction couple with liquid
chromatography-tandem mass spectrometry (LC/MS/MS). Environmental Science &
Technology, 46(10), 5302-5309.
Tollefsen, K. E., Nizzetto, L., & Huggett, D. B. (2012). Presence, fate and effects of the
intense sweetener sucralose in the aquatic environment. Science of the total
environment, 438, 510-516.
Topp, E., Monteiro, S. C., Beck, A., Coelho, B. B., Boxall, A. B., Duenk, P. W.,
Kleywegt, S., Lapen, D.R., Payne, M., Sabourin, L., Li, H., & Metcalfe, C. D. (2008).
Runoff of pharmaceuticals and personal care products following application of biosolids
to an agricultural field. Science of the Total Environment, 396(1), 52-59.
Uno, T., Kaji, S., Goto, T., Imaishi, H., Nakamura, M., Kanamaru, K., Yamagata, H.,
Kaminishi, Y., & Itakura, T. (2011). Metabolism of the herbicides chlorotoluron, diuron,
linuron, simazine, and atrazine by CYP1A9 and CYP1C1 from Japanese eel (Anguilla
japonica). Pesticide Biochemistry and Physiology, 101(2), 93-102.
77
U.S. Environmental Protection Agency. (2015). U.S. EPA Pesticides. Retrieved July 5,
2015.
Vajda, A. M., Barber, L. B., Gray, J. L., Lopez, E. M., Woodling, J. D., & Norris, D. O.
(2008). Reproductive disruption in fish downstream from an estrogenic wastewater
effluent. Environmental Science & Technology, 42(9), 3407-3414.
Verlicchi, P., Al Aukidy, M., & Zambello, E. (2012). Occurrence of pharmaceutical
compounds in urban wastewater: removal, mass load and environmental risk after a
secondary treatment—a review. Science of the Total Environment, 429, 123-155.
Wallace, C. B., Burton, M. G., Hefner, S. G., & DeWitt, T. A. (2013). Effect of preceding
rainfall on sediment, nutrients, and bacteria in runoff from biosolids and mineral fertilizer
applied to a hayfield in a mountainous region. Agricultural Water Management, 130,
113-118.
Wang, S., Oakes, K. D., Bragg, L. M., Pawliszyn, J., Dixon, G., & Servos, M. R. (2011).
Validation and use of in vivo solid phase micro-extraction (SPME) for the detection of
emerging contaminants in fish. Chemosphere, 85(9), 1472-1480.
Weissteiner, C. J., Pistocchi, A., Marinov, D., Bouraoui, F., & Sala, S. (2014). An
indicator to map diffuse chemical river pollution considering buffer capacity of riparian
vegetation—A pan-European case study on pesticides. Science of the Total
Environment, 484, 64-73.
Whitehead, A., Kuivila, K. M., Orlando, J. L., Kotelevtsev, S., & Anderson, S. L. (2004).
Genotoxicity in native fish associated with agricultural runoff events. Environmental
Toxicology and Chemistry, 23(12), 2868-2877.
Whyte, J. J., Jung, R. E., Schmitt, C. J., & Tillitt, D. E. (2000). Ethoxyresorufin-O-
deethylase (EROD) activity in fish as a biomarker of chemical exposure. Critical Reviews
in Toxicology, 30(4), 347-570.
Xing, H., Wu, H., Sun, G., Zhang, Z., Xu, S., & Li, S. (2013). Alterations in activity and
mRNA expression of acetylcholinesterase in the liver, kidney and gill of common carp
exposed to atrazine and chlorpyrifos. Environmental Toxicology and
Pharmacology, 35(1), 47-54.
Xuereb, B., Lefèvre, E., Garric, J., & Geffard, O. (2009). Acetylcholinesterase activity in
Gammarus fossarum (Crustacea Amphipoda): linking AChE inhibition and behavioural
alteration. Aquatic Toxicology, 94(2), 114-122.
78
Appendix 1: POCIS Sampling Rates for PPCPs
Table A1: Mean (±SD) sampling rates (Rs) in litres per day determined for the target
compounds in POCIS in static experiments at 15oC (n=3). Sampling rates were
determined by Li et al. (2010b).
1) Rs determined by Metcalfe et al. (2014).
COMPOUND Rs
Hormone
Estrone 0.636 ± 0.068
Androstenedione 0.410
Painkiller
Ibuprofen 0.254 ± 0.019
Acetominophen 0.111 ± 0.016
Anti-inflammatory
Naproxen 0.298 ± 0.016
Artificial Sweetener
Sucralose1 0.160
Antibiotic
Sulfamethoxazole 0.348 ± 0.049
Trimethoprim 0.411 ± 0.073
Cholesterol reducer
Gemfibrozil 0.306 ± 0.031
Anti-convulsant
Carbamazepine 0.397 ± 0.018
79
Appendix 2: POCIS Sampling Rates - CUPS
Table A2: Mean (±SD) sampling rates (Rs) in litres per day determined for the target
compounds in POCIS in static experiments at 20oC (n=3). Sampling rates were
determined by Metcalfe et al. (submitted).
1) Determined from amounts accumulated on POCIS sorbent
COMPOUND Rs
Fungicides
Propiconazole 0.469 ± 0.049
Tebuconazole 0.440 ± 0.047
Ketoconazole 0.474 ± 0.037
Climbazole Rs?
Fluconazole 0.379 ± 0.048
Clotrimazole 0.564 ± 0.065
Azoxystrobin 0.318 ± 0.008
Myclobutanil 0.293 ± 0.032
Carbendazim 0.341 ± 0.032
Iprodione 0.492 ± 0.013
Thiophanate-methyl1 0.092
Herbicides/Biocides
Atrazine 0.214 ± 0.069
Diuron 0.765 ± 0.066
Irgarol 1051 0.396 ± 0.019
Glyphosate Not determined
Terbutryn 0.461 ± 0.031
Dicamba1 0.0312
2,4-D1 0.0292
Mecoprop1 0.0672
80
Appendix 3: Fungicide LC-MS/MS Parameters
Table A3.1: Ionization parameters for the pesticides targeted in this study.
Analyte Q1 Q3 Polarity DP EP CE CXP
Azoxystrobin 404.145 85.5 + 146 10 33 18
Fluconazole 306.99 238 + 121 10 23 22
Irgarol
254.076 198 + 76 10 25 20
Climbazole 293.006 197 + 131 10 23 18
Myclobutanil 289.008 69.9 + 121 10 23 10
Propiconazole 342.122 158.9 + 136 10 37 18
Tebuconazole 308.117 69.9 + 126 10 45 8
Carbendazim 192.097 159.9 + 116 10 23 18
Atrazine
216.189 174 + 101 10 23 16
Ketoconazole 531.233 489 + 166 10 43 30
Terbutryn 242.133 186 + 121 10 25 22
Dicamba
218.867 160.8 - -55 -10 -18 -17
2,4-D
219.906 161.9 - -50 -10 -18 -13
Iprodione 328.007 140.8 - -80 -10 -16 -17
Mecoprop 212.948 140.9 - -90 -10 -20 -19
81
Table A3.2: Ionization parameters for all pesticide surrogates used in this study.
Internal Standard Q1 Q3 Polarity DP EP CE CXP
Ketoconazole-d4 535.041 81.1 + 211 10 107 10
Carbendazim-d4 196.05 164 + 56 10 7 18
Fluconazole-d4 311.021 70.1 + 131 10 51 12
Propiconazole-d5 347.023 279.1 + 66 10 13 28
Atrazine-d5 220.996 72.9 + 176 10 29 10
Terbutryn-d5 247.045 172.9 + 151 10 23 20
Tebuconazole-d6 313.3 91.2 + 14 10 28 4
2,4-D-d3
221.722 163.9 - -25 -10 -18 -19
2,4-C-d3
216 143.8 - -25 -10 -17 -10
3,6-D-d3
221.816 164 - -60 -10 -18 -7
Iprodione-d5 333.03 96.9 - -40 -10 -38 -11
82
Table A3.3: Pesticide analytes with their corresponding internal standards (IS) used in
the present study.
Analyte MW (g/mol) I.S.
Azoxystrobin 404.145 Atrazine-d5
Fluconazole 306.99 Fluconazole-d4
Irgarol 254.076 Atrazine-d5
Climbazole 293.006 Atrazine-d5
Myclobutanil 289.008 Atrazine-d5
Propiconazole 342.122 Propiconazole-d5
Tebuconazole 308.117 Tebuconazole-d6
Carbendazim 192.097 Carbendazim-d4
Atrazine 216.189 Atrazine-d5
Ketoconazole 531.233 Ketoconazole-d4
Terbutryn 242.133 Terbutryn-d5
Dicamba 218.867 3,6-D-d3
2,4-D 219.906 2,4-D-d3
Iprodione 328.007 Iprodione-d5
Mecoprop 212.948 2,4-C-d3