Article pubs.acs.org/JAFC
Spatial and Temporal Variability in Pesticide Exposure Downstream of a Heavily Irrigated Cropping Area: Application of Different Monitoring Techniques Dominique O’Brien,*,† Stephen Lewis,† Aaron Davis,† Christie Gallen,§ Rachael Smith,# Ryan Turner,# Michael Warne,# Scott Turner,⊥ Stewart Caswell,⊥ Jochen F. Mueller,§ and Jon Brodie† †
Catchment to Reef Research Group, TropWATER, ATSIP, DB145, James Cook University, Townsville, Queensland 4811, Australia The University of Queensland, Entox, 39 Kessels Road, Coopers Plains, Queensland 4108, Australia # Water Quality and Investigations, Environmental Monitoring and Assessment Science, Science Delivery, Queensland Department of ScienceInformation Technology and Innovation (DSITI), Dutton Park, Queensland 4102, Australia ⊥ Organic Chemistry, Forensic and Scientific Services, Health Support, Queensland Department of Health, Queensland Government, 39 Kessels Road, Coopers Plains, Queensland 4108, Australia §
S Supporting Information *
ABSTRACT: Pesticide exposure threatens many freshwater and estuarine ecosystems around the world. This study examined the temporal and spatial trends of pesticide concentrations in a waterway within an agriculturally developed dry-tropics catchment using a combination of grab and passive sampling methods over a continuous two-year monitoring program. A total of 43 pesticide residues were detected with 7 pesticides exceeding ecologically relevant water quality guidelines/trigger values during the study period and 4 (ametryn, atrazine, diuron, and metolachlor) of these exceeding guidelines for several months. The presence and concentration of the pesticides in the stream coincided with seasonal variability in rainfall, harvest timing/cropping cycle, and management changes. The sampling approach used demonstrates that the application of these complementary sampling techniques (both grab and passive sampling methods) was effective in establishing pesticide usage patterns in upstream locations where application data are unavailable. KEYWORDS: Great Barrier Reef, pesticides, herbicides, passive sampling, sugar cane, irrigation
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INTRODUCTION Pesticide residues are now ubiquitous in many streams that drain agricultural, urban, and industrial lands around the globe, and concerns regarding their environmental risks have led to the implementation of numerous management regulations and assessment programs.1−5 However, many monitoring programs are limited by costs associated with sampling and laboratory methods; depending on the monitoring aims, a trade-off is often made between sampling frequency, spatial coverage, and analytical cost.6 Sampling within tropical areas is further complicated by the variable local weather profiles (i.e., raindriven ephemeral flows), extreme weather events, and remote locations, that, when combined with monitoring limitations, have resulted in limited data available on pesticide concentrations in tropical areas compared to the data available from temperate areas. The application of both grab and passive sampling methods allows for more pesticide residues (and degradation products) to be examined in a cost-effective manner and to assess how those concentrations vary in space and time.7 Such monitoring programs are particularly useful for the examination of the spatial and temporal variability of pesticide concentrations in streams in response to factors such as timing of application, seasonal variability in rainfall/runoff, and management change. However, application of such approaches is rare in tropical catchments. © XXXX American Chemical Society
Pesticides, along with nutrients and sediments, transported to the Great Barrier Reef (GBR) have been identified as a key issue for management under the Reef Water Quality Protection Plan.8−10 In response, the Queensland State and Australian Federal Governments implemented the Paddock to Reef Integrated Monitoring Modeling and Reporting program (Paddock to Reef), which encourages the agricultural industry to adopt best management practices to improve water quality in the GBR.11 Five herbicides, including diuron, atrazine, ametryn, hexazinone, and tebuthiuron, have been identified as priority herbicides to be targeted for reduction in their offsite transport. Among these five herbicides, diuron has been widely recognized as one that consistently poses the highest ecological risk,12,13 which is manifested through regulation on its use introduced by the Australian Pesticides and Veterinary Medicines Authority (APVMA) in 2011 and 2012. As a result, farmers have sought out a range of alternative pesticides as replacements,12 and many of these alternatives are now detectable in several rivers or tributaries that flow into the sea along the GBR coastline.14 Unfortunately, pesticide sales or usage data in the GBR are not Special Issue: Pesticide Fate and Effects in the Tropics Received: September 27, 2015 Revised: December 9, 2015 Accepted: January 11, 2016
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DOI: 10.1021/acs.jafc.5b04710 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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Figure 1. Sampling sites in the Barratta Creek complex. (Left) Map of the location of the sampling sites (red triangles) in relation to the surrounding land use in the area supplied with irrigation water from the Burdekin Haughton Water Supply Scheme (BHWSS; red lines). Land use classifications are based on the 2004 Queensland Land Use Mapping shape files obtained from the Queensland Department of Natural Resources and Mines (DNRM). (Right) Satellite image showing the locations of the four sampling sites in relation to the sugar cane croplands surrounding the wetlands supported by the Barratta Creek (catchment boundary indicated by the blue line59), the Ramsar wetland (green-shaded area), the GBRMP, and conservation zone.
Table 1. Site Coordinates and Percent Land Use Contribution above Each Sampling Site Barratta sampling sites Upper 19°41′23.15″ S 147°10′13.69″ E percent land use contribution above site (%) grazing 84 cropping 15 conservation/other 1
West
East
Lower
19°32′9.94″ S 147°13′3.07″ E
19°33′42.37″ S 147°13′16.71″ E
19°28′41.55″ S 147°13′57.66″ E
72 25 3
publicly available, and, with the exception of “anecdotal evidence” (i.e., farmer/industry stakeholder communications on usage within the region), changes in pesticide use cannot be quantified. Barratta Creek, located in the dry tropics of northeastern Australia (Figure 1) and with a large proportion of sugar cane cropping in the catchment, has been identified as a high-risk area compared to other GBR catchments as pesticide concentrations15−20 exceed both Australian and New Zealand21 water quality guideline trigger values and international22 guideline values.15−20,23,24 Although previous studies have examined the concentrations and loads of pesticide residues at various sites along Barratta Creek, no systematic and continuous monitoring approach to examine spatial and temporal variations within Barratta Creek has been undertaken. This study has undertaken continuous monitoring of pesticide concentrations over two years (July 2011−July 2013) at four
60 31 9
sites within Barratta Creek with an aim to assess pesticide presence and the temporal and spatial variability of pesticide residues in this intensely developed tropical catchment.
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MATERIALS AND METHODS
Study Site. Barratta Creek drains a large area of the Burdekin− Haughton floodplain and has a total catchment area of 1167 km2, which covers 0.9% of the Burdekin Dry Tropics Natural Resource Management region.25 Land use within the Barratta Creek catchment includes grazing on native pastures (60% of area) and irrigated sugar cane production (approximately 31%), with the remaining catchment area consisting of wetland/conservation, minimal use, and other crops;25 other crops include legumes (i.e., chickpeas, soybeans, etc.) grown in fallow sugar cane paddocks as well as mango orchards, mixed horticulture, cotton, and rice. Sugar cane within the Barratta catchment accounts for approximately one-fourth of the total land area cultivated for sugar cane production across the whole Burdekin region. The creek network drains into nationally (Australian Nature Conservation B
DOI: 10.1021/acs.jafc.5b04710 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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Table 2. Frequency (Percent) at Which a Contaminant Was Detected per Sampling Period (∼1 Month Intervals) Irrespective of Sampling Method (That Is, Grab or Passive Sampling)
Herbicide. bInsecticide. cFungicide. dFuel and oil additive. eFlame retardant and pesticide. fPolycyclic musks. #Breakdown product; BHT, 2,6-ditert-butyl-p-cresol; ND, not detected; N/A, not analyzed; SC, sugar; H, horticulture; L, legume; C, cotton; R, rice; S, sunflower; M/L, mango/lychee; U/I, urban/industrial; G, grazing; F, forestry. Shaded cells indicate chemicals that have been reported previously in the GBR catchment area.13,16,18−20,44−46
a
and raised local water tables.23 The sampling sites monitored as part of this study (Figure 1) were all located within the area identified by the directory of important wetlands in Australia.26 The three freshwater sites (Upper Barratta Creek, West Barratta Creek, and East Barratta Creek) have been subjected to previous monitoring efforts16−19 but
Agency; ANCA) and internationally (Ramsar) recognized wetlands and ultimately the World Heritage listed GBR.18,19 The Barratta Creek catchment has been extensively developed for sugar cane supported by furrow irrigation, the introduction of which has altered the previously intermittent flow regimen of Barratta Creek to one of constant flow17 C
DOI: 10.1021/acs.jafc.5b04710 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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study has been described previously.28,30 Analysis of the extracted samples employed liquid and gas chromatography−mass spectrometry (LC-MS/MS and GC-MS). All results have been reported as micrograms per liter (i.e., equivalent to ppb). Sample replicates were analyzed separately to ensure the reproducibility of the measurements obtained. Assessment of Ecosystem Risk. Guidelines have been established with respect to the percent of species theoretically protected when concentrations are maintained below a certain concentration (PC). Pesticide concentrations across the study sites were compared to the PC95 and PC99 (theoretically protect 95 or 99% of species in the ecosystem being considered) ecological threshold values proposed by Smith et al.40 and then to any existing ANZECC and ARMCANZ21 trigger values (TV). It is general practice that the PC95 values are applied for ecosystems already affected by anthropogenic activities. However, as the Barratta Creek system is of higher ecological significance as it lies within ANCA41 (East/West/ Upper Barratta sites) and Ramsar (Lower Barratta) listed wetlands, management of this site should aim to maintain pesticide concentrations at levels that protect 99% of species, and thus the PC99 values are more appropriate for the assessment of ecosystem risk of this system. Overall, ecosystem risk per site was assessed through the calculation of the 95th percentile concentration of individual pesticides per sampling year (i.e., the highest concentration that falls within 95% of all samples collected; when concentrations in samples were below the analytical reporting limit values, half the detection limits were used in the calculation) to compare to both the PC95 and PC99 guideline values (method described in Smith et al.20).
not at this level of sophistication. The end of the catchment estuarine site (Lower Barratta Creek) was within the Bowling Green Bay Ramsar wetland boundary. The percentage contributions of grazing, cropping, and conservation/other land uses above the monitored sampling sites are outlined in Table 1.25 Monitoring Methods. Water sampling across the four sites was undertaken through the combination of grab (point in time measurements), time/flow weighted sampling using an automated sampler (multiple point in time measurements; at Upper Barratta Creek only; data provided by Queensland Department of Science, Information Technology and Innovation (DSITI)), and passive sampling techniques (time-integrated measurement). Passive sampling devices facilitate the accumulation of chemicals from water into a sorbent. When calibrated correctly, the mass accumulated by a passive sampler can be used to provide a time-weighted average (TWA) measurement of a contaminant during the exposure period. Two passive sampling devices (PSDs) were employed: Chemcatcher and polydimethylsiloxane (PDMS) passive samplers. The Chemcatcher passive sampler configured with a styrenedivinylbenzene (SDB) Empore Disk (ED) and poly(ether sulfone) (PES) membranes in the original Teflon housing27−29 was used for sampling the polar chemicals. The PDMS passive samplers accumulate less polar chemicals and have been employed in assessing the concentrations of hydrophobic organic compounds.30−32 The PDMS strips (410 μm thick, 2.5 cm wide, 92 cm length; Purple Pig Australia) were deployed inside stainless steel cages. Passive sampling kinetics for each deployment were adjusted to the deployment specific flow conditions using the passive flow monitors (PFM) in replicate.33,34 Furthermore, water salinity/conductivity is known to influence the calibration method employed, so the water electrical conductivity (EC) was recorded during site visits using a Hydrolab Quanta (ECO Environmental) and the data were used to refine the calibration of the passive sampling devices.33 Passive samplers were deployed in replicate at each site attached to a length of chain on an overhanging tree branch such that the samplers were exposed to the main channel flow and remained submerged for the duration of the deployments. Previous studies show that PSDs can under- or overestimate the TWA concentrations of certain analytes when fluctuations in both concentration and flow occur during the deployment period.35−37 As such, each deployment period during this study lasted for approximately 4 weeks except when a runoff event occurred. When a runoff event occurred, samplers were exchanged within the next few days to ascertain that samplers remained in a linear uptake phase.36,38 During each site visit two 1 L grab samples were collected using a 3−5 m extendable sampling pole from ∼20 cm below the water surface in amber glass bottles. The passive and grab samples were kept on ice during transport and stored at 4 °C prior to analysis. Rainfall and streamwater level data were obtained from Queensland Department of Natural Resources and Mines39 Northcote gauging station (119101A) located ∼50 m downstream of the Upper Barratta Creek sampling site. During January 2013, the rain gauge failed and the rainfall associated with ex-Tropical Cyclone Ita was not recorded. To fill in the missing data the rainfall recorded at the nearest gauging site (119003A: Haughton River at Powerline, located ∼9 km to the northwest) was obtained. Sample Extraction and Analysis. Analysis of all grab water samples was undertaken by the Queensland Health Forensic and Scientific Services (QHFSS) by HPLC-MS/MS using an AB/Sciex API4000Q mass spectrometer equipped with an electrospray (TurboV) interface coupled to a Shimadzu Prominence HPLC system (Shimadzu Corp., Kyoto, Japan). Separation is achieved using a 3 μm, 150 × 2 mm, Luna(2) C18 column (Phenomenex, Torrance, CA, USA) run at 40°C and a flow rate of 1.1 mL min−1 with a linear gradient starting at 15% B for 0.5 min, ramped to 100% B in 10 min, held for 3 min, then ramped to 15% B in 0.2 min, and equilibrated for 3 min (A = 1% acetonitrile/99% HPLC grade water/0.1% formic acid; B = 95% acetonitrile/5% HPLC grade water/0.1% formic acid). The passive samplers were extracted for the quantification of pesticide concentration at the University of Queensland. A full description of the passive sampling extraction and analysis methods employed in this
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RESULTS Environmental Condition. Electrical conductivity (EC) and rainfall data were obtained to inform the environmental conditions during the study period relative to long-term averages. The study period captured one of the wettest years on record within the catchment with ∼1200 mm during 2011−2012, whereas average rainfall (∼700 mm) occurred during 2012−2013. The data obtained are presented in more detail in the Supporting Information. Pesticides Detected and Frequency of Detection. A total of 48 organic compound residues were detected over the two-year monitoring program including 32 herbicides (including 3 breakdown products), 10 insecticides (including 1 breakdown product and the insect repellent DEET), and 1 fungicide. Nonpesticide organic compound residues detected during the analysis included the fuel and oil additive 2,6-di-tertbutyl-p-cresol (BHT), a plasticizer (bisphenol A), and 2 polycyclic musks (galaxolide and tonalid). In addition to the known pesticide contaminants of concern, pesticide residues were detected that have not previously been reported within the GBR catchment area (see unshaded chemicals in Table 2). Grab sampling detected 17 residues (14 herbicides, 1 insecticide, 2 nonpesticides), and PSDs identified 45 residues (32 herbicides, 9 insecticides, 1 fungicide, 3 nonpesticides). Of the PSDs samplers, the Chemcatcher passive sampler detected 33 compounds in total including an additional 22 residues (18 herbicides, 2 insecticides, 1 fungicide, and 1 herbicide additive) not detected by the grab method. The PDMS passive samplers detected 10 residues (4 herbicides, 2 herbicide breakdown products, 2 insecticides, 1 fungicide, and 1 fuel/oil additive) that were not detected by either the grab or Chemcatcher sampling methods. Overall, grab samples detected 3 residues (bifenthrin, bisphenol A, and tris(dichloropropyl) phosphate) not detected by the PSDs. On a concentration and detection frequency basis, the nine key pesticides identified were diuron (0.01−12.8 μg L−1; 88% D
DOI: 10.1021/acs.jafc.5b04710 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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Table 3. Frequency (Percent) and Concentration (Micrograms per Liter) Range for the Nine Most Frequently Detected Pesticides during This Study across All Sampling Sites
detection in grabs and 100% in PSDs), atrazine (0.017−11.5 μg L−1; 96% detection in grabs and 100% in PSDs), ametryn (0.001−1.99 μg L−1; 60% detection in grabs and 100% in PSDs), metolachlor (0.003−5.31 μg L−1; 48% detection in grabs and 100% in PSDs), hexazinone (0.001−0.327 μg L−1; 22% detection in grabs and 100% in PSDs), simazine (below detection limit (BDL)−0.543 μg L−1; 16% detection in grabs and 98% in PSDs), imidacloprid (BDL−0.504 μg L−1; 7% detection in grabs and 93% in PSDs), tebuthiuron (BDL−0.007 μg L−1; 0% detection in grabs and 100% in PSDs), and prometryn (BDL−0.03 μg L−1; 2% detection in grabs and 84% in PSDs). Chemical-specific detection frequencies are presented in Table 2 with site- and method-specific detection frequency and concentrations for the nine key pesticides presented in Table 3. Further analysis presented in this paper predominantly focuses on the nine key pesticides identified. The PSDs employed in this study measure a TWA concentration for the pesticide residues detected and cannot be directly compared to the point in time (PIT) concentration measurements made using grab sampling without recognizing the differences in the two different methods (Figure 2). However, the ranges of pesticide concentrations when detected by two or more sampling methods showed very good agreement (Table 3). Furthermore, there was a similar temporal rise and fall trend in the concentrations measured at each site when the TWA and PIT values were compared (Figures 3−5). Although the TWA and PIT values were generally “in range” when detected by both grab and passive sampling methods, the agreement became less clear when the
frequency of pesticide detection in the grab water samples fell below the analytical limit of reporting (e.g., ametryn and metolachlor); the PSDs were able to detect these herbicides at lower quantifiable limits for longer periods of time during the study period. The measured TWA and PIT pesticide concentrations have been plotted in Figures 3−5. Summary concentrations of atrazine, diuron, ametryn, metolachlor, hexazinone, and imidacloprid measured using the Chemcatcher PSD are shown in the box plots in Figure 6. The ranges and medians of atrazine, diuron, ametryn, and hexazinone concentrations over the two-year sampling period were comparable across the three freshwater sampling sites. Whereas the measured concentration ranges of metolachlor were comparable across the three freshwater sites, the median concentration measured at East Barratta was higher than those at the Upper Barratta and West Barratta sites. Furthermore, although the median concentrations of imidacloprid measured across the three freshwater sites were similar, a greater range was recorded at the Upper Barratta site. The concentrations of all pesticides measured at the Lower Barratta estuarine site were generally between one-third and one-half the concentrations measured within the freshwater reaches of the creek (Figure 6). Temporal Changes in Pesticide Concentration. In general, the highest pesticide concentrations detected during this study across all sampling sites (and recorded by the different techniques) occurred from August 2011 to January 2012 and from October 2012 to January 2013. Peak pesticide concentrations in Barratta Creek coincided with the end of the sugar cane harvest period (November−December) and with E
DOI: 10.1021/acs.jafc.5b04710 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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Figure 3. Temporal change in atrazine, diuron, and hexazinone concentrations at Upper Barratta Creek when measured in grab samples (dot points: point in time measurements of concentration) and the time-weighted average concentration measured using the passive sampling devices (lines) within the catchment during the sampling period and pesticide data obtained by DSITI (small dot points). The grab sample data are shown only when samples were above the analytical level of detection. Plots for concentrations obtained at the Lower Barratta estuarine site are available for comparison in the Supporting Information. Vertical spikes indicate daily rainfall (mm) (data obtained from DNRM39).
Figure 2. PIT (A) and TWA (B) concentrations of the nine key pesticides measured at Upper Barratta Creek between July 2011 and July 2013.
the onset of the first wet-season rains in November 2011 and December 2012, respectively. Consistently, the nine key pesticides were detected at highest levels between July and December. Six of the nine pesticides (diuron, atrazine, ametryn, metolachlor, hexazinone, and imidacloprid) are registered for use in sugar cane, and the temporal change in concentrations reflected usage patterns within the industry; that is, the highest concentrations were measured during the sugar cane harvest period (July−December), with concentrations increasing as the harvest period progressed (for example, see Figure 2). Concentrations of the herbicides ametryn, atrazine, and diuron were highest between August 2011 and February 2012 and between September 2012 and February 2013. Concentrations of metolachlor followed a similar trend; however, there were additional fluctuations in the TWA concentrations recorded across the study period. Concentrations of hexazinone and imidacloprid increased in association with rainfall-runoff-driven discharge within the creek (Figure 4). The maximum TWA and PIT concentrations of atrazine and diuron recorded during our monitoring program were 11.5 and 12.3 μg atrazine L−1 and 9.2 and 12.8 μg diuron L−1, respectively. Peak concentrations of atrazine and diuron occurred during low-flow conditions during October 2011 and December 2012 (grab sampling) and during August 2011, November 2011, and December 2012 (passive sampling). Pesticide concentrations rapidly decreased following each subsequent rainfall event throughout the wet season and then
generally increased following the onset of either crop planting or the crop harvest period (June) when pesticides (predominant examples include pre-emergent herbicides atrazine, diuron, ametryn, metribuzin, and metolachlor; knockdown herbicides 2,4-D and MCPA; and insecticides imidacloprid and permethrin) are applied to cane blocks. Exceptions to this pattern included the herbicide terbuthylazine, which is registered for use in legume fallow crops but not in sugar cane, and the insecticide bifenthrin and herbicides imazapic and isoxaflutole, which are registered for use on sugar cane. The latter herbicides were predominantly detected during the nonharvest period from December through June. Reductions in pesticide concentrations as the wet season progressed were observed with each subsequent rainfall event. During the 2011/ 2012 water year, rainfall extended into the winter months, which led to a delay in the 2012 sugar harvest42 and coincided with an increase in the TWA concentrations of metolachlor, ametryn, and imidacloprid. Site-specific differences in the contaminant profiles included the detection of clomazone (herbicide) and imidacloprid urea (insecticide) only at West Barratta; fluometuron (herbicide) at Upper and East Barratta; mecoprop (herbicide) only at Upper Barratta; and the failure to detect bifenthrin (insecticide) at F
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Figure 5. Temporal change in simazine, prometryn, and tebuthiuron concentrations at Upper Barratta Creek when measured in grab samples (dot points: point in time measurements of concentration) and the time-weighted average concentration measured using the passive sampling devices (lines) within the catchment during the sampling period. The grab sample data are shown only when samples were above the analytical level of detection. Plots for concentrations obtained at the Lower Barratta estuarine site are available for comparison in the Supporting Information. Vertical spikes indicate daily rainfall (mm) (data obtained from DNRM39).
Figure 4. Temporal change in ametryn, imidacloprid, and metolachlor concentrations at Upper Barratta Creek when measured in grab samples (dot points: point in time measurements of concentration) and the time-weighted average concentration measured using the passive sampling devices (lines) within the catchment during the sampling period and pesticide data obtained by DSITI (small dot points). The grab sample data are shown only when samples were above the analytical level of detection. Plots for concentrations obtained at the Lower Barratta estuarine site are available for comparison in the Supporting Information. Vertical spikes indicate daily rainfall (mm) (data obtained from DNRM39).
those 12 pesticides, the guidelines for 2,4-D, imazethapyr, bromacil, MCPA, and tebuthiuron were not exceeded, whereas hexazinone, atrazine, simazine, diuron, ametryn, imidacloprid, and metolachlor concentrations exceeded at least one guideline value (TV or 99/95% species protection concentration (PC) values − PC99/PC95) in at least one sample collected across the fresh (Table 4) or estuarine sites (Table 5) using either grab or passive methods. Table 6 outlines the 95th percentile concentrations for each detected pesticide with an established or proposed guideline. Diuron 95th percentile concentrations exceeded both the existing TV and the proposed PC95 guidelines across all fresh and estuarine sites for both years of sampling. The atrazine 95th percentile concentrations did not exceed the existing TV but did exceed the proposed PC95 guideline at Upper and East Barratta sites over both sampling years and at West Barratta during 2012−2013. Atrazine and simazine use has been banned in most European countries.43 Ametryn 95th percentile concentrations exceeded the proposed PC95 guideline at Upper and West Barratta in 2012−2013, East Barratta over both sampling years, and the proposed marine PC95 guideline at the estuarine site during 2011−2012. Metolachlor 95th percentile concentrations exceeded the
Upper Barratta and bromacil (herbicide) at East Barratta (Table 2). Overall, both the grab and passive sampling techniques generally displayed similar concentration ranges and seasonal trends. The pesticide concentrations detected in the grab samples followed the same trend over time as the TWA measurements. Average concentrations of atrazine and diuron measured using both the grab and Chemcatcher sampling methods at the three freshwater sampling sites were higher during the June−November harvest period (i.e., when pesticides are being reapplied to plots postharvest) compared to the nonharvest period (December−May), with t test p values of
