Perchlorate in environmental waters of the Laurentian Great Lakes watershed: Evidence for uneven loading

Journal of Great Lakes Research 45 (2019) 240–251

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Perchlorate in environmental waters of the Laurentian Great Lakes watershed: Evidence for uneven loading D.R. Van Stempvoort ⁎, J. Struger, S.J. Brown Water Science and Technology Directorate, Environment and Climate Change Canada, 867 Lakeshore Road, Burlington, Ontario L7S 1A1, Canada

a r t i c l e

i n f o

Article history: Received 10 September 2018 Accepted 4 December 2018 Available online 28 January 2019 Communicated by Ron Hites Keywords: Perchlorate Laurentian Great Lakes Atmospheric deposition Anthropogenic

a b s t r a c t A database of nearly 500 analyses of perchlorate in water samples from the Laurentian Great Lakes (LGL) watershed is presented, including samples from streams, from the Great Lakes and their connecting waters, with a special emphasis on Lake Erie. These data were assessed to test an earlier hypothesis that loading of perchlorate to the LGL watershed is relatively uniform. Higher perchlorate concentrations in streams in more developed and urban areas appear to indicate higher rates of loading from anthropogenic sources in these areas. Variable perchlorate concentrations in samples from Lake Erie indicate transient (un-mixed) conditions, and suggest loss by microbial degradation, focused in the central basin of that lake. Interpretation of the data included estimation of annual loading by streams in various sub-watersheds, and simulations (steady state and transient state) of the mass balance of perchlorate in the Great Lakes. The results suggest uneven loading from atmospheric deposition and other sources. Crown Copyright © 2019 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research. All rights reserved.

Introduction Backus et al. (2005) were the first to document measurable concentrations of perchlorate in waters within the Laurentian Great Lakes (LGL) watershed of North America (Fig. 1). Recently Poghosyan et al. (2014) published perchlorate concentrations for all of the LGL and, based largely on isotope evidence, they concluded that the perchlorate in these lakes is dominantly of natural origin. Using mass balance calculations, they inferred that a relatively uniform atmospheric deposition of perchlorate could account for the majority of the perchlorate present in the LGL, and they noted evidence for some loss of perchlorate within Lake Erie (Poghosyan et al., 2014). In contrast to the above LGL-focused study (Poghosyan et al., 2014), other research, in the same watershed and elsewhere, has demonstrated the importance of localized anthropogenic sources, such as fireworks displays, to explain the occurrence of elevated perchlorate concentrations in environmental waters. For example, in the Ontario portion of the LGL watershed, immediately following fireworks displays in the vicinity, Backus et al. (2005) and Sabourin et al. (2006) reported concentrations of perchlorate in surface waters ranging up to 0.19 and 22 μg/L respectively. Similarly, Roy and Malenica (2013) and Robertson et al. (2014) reported that elevated perchlorate concentrations in shallow groundwater at sites in the Ontario portion of the LGL watershed, ranging in concentrations up to about 1 μg/L each, were likely influenced by fireworks. ⁎ Corresponding author. E-mail address: [email protected] (D.R. Van Stempvoort).

In this paper we introduce a database of nearly 500 analyses of perchlorate in water samples from the LGL watershed, collected from streams and from the Great Lakes and their connecting waters, with a special emphasis on Lake Erie. Then we assess these data by addressing two related questions: Does this large dataset support the earlier hypothesis that loading of perchlorate to the LGL watershed is relatively uniform? Alternatively, do these data indicate that localized anthropogenic inputs of perchlorate have a significant influence on loading throughout this watershed?

Background information Perchlorate is often detectable in environmental waters (Urbansky, 2002; Trumpolt et al., 2005; Kosaka et al., 2007; Quinones et al., 2007; Parker et al., 2008; Kannan et al., 2009; Rajagopalan et al., 2009; Wu et al., 2010; Fang and Chen, 2012). Due to concerns about the potential negative impacts of perchlorate on human health as a contaminant in drinking water, some jurisdictions have a regulation (2 μg/L: Massachusetts Department of Environmental Protection, 2018), a public health goal (1 μg/L: California Environmental Protection Agency, 2015), or have made a recommendation (6 μg/L: Health Canada, 2005) regarding maximum perchlorate concentrations. The United States Environmental Protection Agency had plans to develop a national primary drinking water regulation for perchlorate (USEPA, 2014), and has set a risk-based screening level of 14 μg/L in tap water (USEPA, 2015). There are concerns about the ecotoxicity of elevated concentrations of perchlorate in environmental waters (Kendall and Smith, 2006).

https://doi.org/10.1016/j.jglr.2018.12.007 0380-1330/Crown Copyright © 2019 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research. All rights reserved.

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water and/or groundwater in the vicinity (Sabourin et al., 2006; Wilkin et al., 2007; Munster et al., 2009; Scheytt et al., 2011; Wu et al., 2011). In a recent review, Sijimol and Mohan (2014) concluded that fireworks are one of the main sources of environmental perchlorate contamination globally, though many data gaps remain. Similarly, Yao et al. (2015) and Vella et al. (2015) reported that perchlorate analyzed in airborne particles in eastern Asia and in dust fall in Malta was largely derived from fireworks. Use of Chilean nitrate as fertilizer may produce zones of elevated perchlorate in soils and groundwater (Munster and Hanson, 2009b; Böhlke et al., 2009). Other anthropogenic sources that may release measurable quantities of perchlorate to the environment include explosives used for military applications, for blasting and mining, chlorate production, signal flares, airbags for vehicles, pulp mill effluent, sodium hypochlorite products used as disinfectants, and various other industrial and consumer products and wastes (Urbansky, 2002; Trumpolt et al., 2005; Massachusetts Department of Protection, 2006; Sabourin et al., 2006; Munster, 2008; Aziz and Hatzinger, 2009; Bickerton et al., 2009; Munster and Hanson, 2009a,b; Slaten et al., 2010; Isobe et al., 2013; Cao et al., 2018). Perchlorate is very mobile in the environment and often tends to persist (Urbansky, 2002; Jackson et al., 2005; Trumpolt et al., 2005). However, microorganisms that can degrade perchlorate appear to be widespread in the environment (Coates et al., 1999). In at least some environments, microbial degradation of perchlorate may require anaerobic conditions (Chaudhuri et al., 2002; Borden et al., 2014); it is

Perchlorate is generated naturally in the atmosphere (Dasgupta et al., 2005; Furdui and Tomassini, 2010). Deposition of atmospheric perchlorate can result in its accumulation in the unsaturated zone in arid regions (Rao et al., 2007), including perchlorate found in sodium nitrate deposits in Chile (Trumpolt et al., 2005). Atmospheric deposition accounts for the low levels of perchlorate detected in ice samples from the High Arctic (1–50 ng/L: Furdui and Tomassini, 2010; Furdui et al., 2018; Cole-Dai et al., 2018), and in soil and ice in dry regions of the Antarctic (31 to 630 μg/kg: Kounaves et al., 2010). Atmospheric deposition may also explain the widespread occurrence of perchlorate in groundwater in the southwestern United States (Fram and Belitz, 2011). Furdui et al. (2018) reported evidence for an increase in atmospheric deposition of perchlorate in the high Arctic in recent decades, which they attributed to anthropogenic sources. But little is known about the variations in fluxes from the atmosphere to the earth's surface globally, and how they are influenced locally or regionally by natural and/or anthropogenic sources. Elevated (e.g., N1000 ng/L) concentrations of perchlorate in environmental waters have generally been attributed to anthropogenic sources. Perchlorate contamination of groundwater was first documented in California at rocket fuel manufacturing sites (California Department of Water Resources, 1964). The first commercial use of anthropogenic perchlorate was for fireworks, and this use has continued since the early 1900s (Stroo et al., 2009). Fireworks displays produce episodic releases of perchlorate to the atmosphere, followed by localized fallout (both wet and dry) leading to high concentrations of perchlorate in surface

EDU 2

EDU 1

1

Lake Superior

2

EDU 4

EDU 5

St. Marys River

4

Legend for pie charts

Lake Huron

Georgian Bay

5

EDU 6

6

Wetlands and open water Lake St. Clair

Lake Michigan

Forest Disturbance

Detroit River

9

Lake Ontario

7 Lake Erie

Community/infrastructure

EDU 9

Agriculture Bedrock Sand/gravel/mine

100

0

Kilometers 200 100

300

EDU 7

Fig. 1. Map of the Laurentian Great Lakes and connecting waters, and selected ecological drainage units (EDUs), shown as numbered areas on the Canadian side of the Great Lakes watershed, as defined by Wichert et al. (2004). Pie charts show land use distribution in selected catchments in each EDU (see ESM Table S1).

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reported to occur in the absence of nitrate, a preferred electron acceptor (Chaudhuri et al., 2002; Robertson et al., 2014). There is evidence that microbial communities living in lake sediments (Wilkin et al., 2007; Jackson et al., 2012), in anoxic bottom waters of lakes (Jackson et al., 2012) and in groundwater (Robertson et al., 2014; Mastrocicco et al., 2017) are capable of reducing perchlorate. In contrast, Smith et al. (2015) found that perchlorate in a well-mixed, well-oxygenated lake in Arctic Canada was likely not biodegraded, consistent with earlier evidence that perchlorate tends to persist under oxic conditions (e.g., Trumpolt et al., 2005; Borden et al., 2014). How pervasive and effective is the microbially-mediated natural attenuation of perchlorate in environmental waters? This remains an open question.

Methods Collection of water samples Over the period 2005–2011, stream samples were collected from various locations in the LGL watershed. Methods for collecting the stream samples are described by Struger et al. (2015). The stream samples were grouped geographically by ecological drainage units (“EDUs”), as defined by Wichert et al. (2004) (Fig. 1). This provided a way to compare results from areas that had differences in hydrology and land use (Fig. 1). For each ecological drainage unit, a reference catchment was selected to provide representative hydrological information and land use in as summarized in Electronic Supplementary Material (ESM) Table S1. Waters of the Great Lakes and their connecting channels were sampled (2005–2010) using standard procedures during scheduled water quality monitoring cruises of the Canadian Coast Guard vessels CCGS Limnos and CCGS Samuel Risley. The samples were obtained with Van Dorn, Rosette, or vertical water quality profiler samplers, or a hull pump (a few 1 m depth samples from the Detroit River). Most (101 of 124) samples were collected at 1 m below water surface; some Lake Erie samples were collected from either 1 or 2 m above the lake bottom (21 samples at −2 m, 2 samples at −1 m). Samples from river mouths along Lake Erie were sampled during some cruises by small boat.

Sample filtration and storage All water samples were filtered, generally within 24 h of collection, the final step being filtration through 0.2 μm pore-size PTFE membranes immediately prior to analysis. Surface water samples collected in 2005 and 2006 (Great Lakes and their connecting channels, some streams) were refrigerated for up to 49 days prior to analysis. This is consistent with Stetson et al. (2006) who determined that perchlorate is stable in environmental water samples, allowing holding times of at least 90 days for surface water (and at least 300 days for ground water). The other samples, collected from 2009 to 2011, were either refrigerated for up to 9 days, or frozen for up to 300 days prior to analysis.

Laboratory analyses All perchlorate analyses were conducted at the Canada Centre for Inland Waters, Burlington, ON, using ion chromatography coupled with tandem mass spectrometry. Samples collected in 2005 and 2006 were analyzed using the method described by Robertson et al. (2009), with a perchlorate detection limit of 11 ng/L. Samples collected between 2009 and 2011 were analyzed using the method described by Robertson et al. (2014) with a detection limit of 5 ng/L (September–December 2009) or 2 ng/L (December 2009–2011). For all statistical tests and calculations, including mean concentrations, non-detections were assigned values of 0 ng/L.

Estimating rates of loading of perchlorate using stream data We inferred loading of perchlorate (from atmospheric deposition and other sources) indirectly for individual EDUs (Fig. 1) by using stream data, along with relevant information about the water balance in each EDU based on a reference catchment that was selected using the Ontario Flow Assessment Tool (OFAT, Ontario Ministry of Natural Resources, 2018). The following Eq. (1) is based on two conservative assumptions: i. all of the perchlorate deposited to the terrestrial portion of each EDU eventually ends up as dissolved perchlorate in runoff in the streams; ii. no loss of perchlorate in the catchments by degradation or by retention processes (e.g., sorption) in vegetation, soils, groundwater or streams.

The mean stream concentration in each EDU was used to infer a rate of total annual direct loading (“dl”) of perchlorate (ψdl-a, while applying a unit conversion: μg/(m2·year) = 10 mg/(ha·year)) in that EDU, using Eq. (1): ψdl−a ¼ ðcs  roa−rc Þ=arc

ð1Þ

where cs is the mean perchlorate concentration in streams for each EDU (ng/L = μg/m3), roa-rc is the annual runoff (m3/year) in the reference catchment for each EDU (modeled by OFAT, see ESM Table S1, and arc is the area of the same reference catchment (m2). In this approach, we assume that our stream perchlorate data (ESM Table S2), which are the only such data available, are representative for each EDU. These stream data should be augmented in future, especially in EDUs where only one stream was sampled (EDUs 4 and 7), and/or where each stream was only sampled once (EDUs 1 and 2). Because Eq. (1) assumes no degradation or other loss of perchlorate, it may underestimate the actual perchlorate loading. Some previous studies have indicated that perchlorate may undergo microbial degradation in waters with low oxygen or anoxic conditions (Jackson et al., 2012; Robertson et al., 2014; Mastrocicco et al., 2017). Estimating perchlorate mass balance in the Great Lakes Similar to the approach of Poghosyan et al. (2014), we also used our measured perchlorate concentrations in the Laurentian Great Lakes to infer perchlorate loading in the LGL watershed. However, in contrast to Poghosyan et al. (2014), the modeling outlined below assumed that the loading could vary for each lake subwatershed. There are uncertainties associated with water balances in the LGL watershed (e.g., Neff and Nicholas, 2005) and, as described in this study, much larger uncertainties with respect to both perchlorate loading to the watershed (including possible spatial variations and changes over time) and potential perchlorate losses (e.g., biodegradation). Given these uncertainties, current modeling can only provide very rudimentary approximations of perchlorate mass balances in the LGL watershed (cf. Poghosyan et al., 2014). The method for our initial steady state, mass balance approach is outlined here. Our subsequent transient state simulation is explained below. Assuming steady state, complete mixing for each Great Lake, the following mass (m) flux and removal processes are applicable: inflow (if) and outflow (of) of water via connecting channels between the Great Lakes, runoff to the lake from the surrounding catchment (ro), direct atmospheric deposition by wet and dry processes (ad), direct groundwater discharge to the lakes (gd) focused in nearshore areas, direct discharge of wastewater (treated or untreated) to the lake (wwd),

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The perchlorate transported in runoff and as groundwater discharge may be derived from either atmospheric deposition to the land portion of the lake catchment or from land-based sources (e.g., wastewater). Without a very thorough and detailed investigation, the influxes associated with direct atmospheric deposition, runoff, groundwater discharge and wastewater discharge cannot be distinguished. In our simulations these influxes were considered collectively as direct loading (“dl”), which was assumed to be uniform within each lake watershed, but could vary between lake watersheds (i.e., uneven loading):

infer outflow and inflow concentrations (cof, cif). For each lake, the outflow concentration (cof) was set equal to the mean concentration in that lake, and the inflow concentration (cif) was equal to the concentration of the lake that feeds into it. The loading ψdl-a was determined for each lake watershed individually. Given the evidence (2009 data) for a drop-off in perchlorate concentrations between the western and central-eastern basins of Lake Erie (see results below), this lake was modeled as a non-conservative (but steady-state) system. The mean concentration measured in 2009 samples from the western basin was used (as cof) to determine the loading (ψdl-a) for this lake, and then an internal loss (~37%) was assumed to occur in the central and/or eastern basins, to match the mean 2009 concentration in these basins (ESM Table S2), and to provide an inflow (cif) concentration to Lake Ontario. The lake watershed ψdl-a estimates provided a useful comparison to the ψdl-a estimates that were calculated for each EDU based on stream data.

mdl−a ¼ mad−a þ mro−a þ mgd−a þ mwwd−a

Statistical analysis

and internal loss by bio/geochemical reactions in the lake (ir). The annual (a) change in mass storage in the lake, Δmlk-a, can be calculated as follows: Δmlk−a ¼ mif−a þ mad−a þ mro−a þ mgd−a þ mwwd−a −mof−a −mir−a

ð2Þ

ð3Þ

For the annual fluxes through connecting channels, volumes (v) for each lake/system (Table 1, based on Neff and Nicholas, 2005) and concentration data were included, and Eqs. (2) and (3) could be combined: Δmlk−a ¼ ðvif−a  cif Þ þ mdl−a −ðvof−a  cof Þ−mir−a

The statistical program Minitab® 16 was used to perform twosample t-tests (t -values, significance p-values), for comparing different datasets of perchlorate concentrations.

ð4Þ

Results and discussion

where cof is the measured concentration of perchlorate in the lake and/ or its outflow, and cif is its measured concentration in the influent channel or in the immediately upstream lake. For most lakes (exception was Lake Erie, see below), it was assumed that there were no changes in mass storage or internal losses (Δmlk-a = 0; mir-a = 0), such that Eq. (4) could be rearranged to yield the annual loading (ψdl-a) for the entire lake catchment (acat): ψdl−a ¼ mdl−a =acat ¼ ðvof−a cof −vif−a  cif Þ=acat

Perchlorate concentrations in streams The medians and ranges of concentrations of perchlorate in streams in the various EDUs in the LGL watershed are shown in Fig. 2 (means, other details in ESM Table S2). Collectively the concentrations in streams in the three relatively undeveloped EDUs (1, 2, 4) were significantly lower than in the four more developed EDUs (5, 6, 7, 9) at confidence levels N 97% (Table 2). More specifically, the median and mean concentrations in the three relatively undeveloped EDUs were lower than the median and mean concentrations in the four more developed EDUs (Fig. 2, ESM Table S2). These observations suggest that influx of perchlorate to environmental waters within the LGL watershed is uneven, and that influx of anthropogenic perchlorate is greatest in the developed portions of the watershed. Samples from river mouths along Lake Erie also had higher mean and median perchlorate concentrations than in the undeveloped EDUs (ESM Table S2), though this was not statistically significant (at the

ð5Þ

For this simulation, the lake catchment areas (i.e., acat) provided in the Great Lakes Atlas (Fuller et al., 1995) were used, along with the water cycle flux components for each lake/system (i.e., vof-a, vif-a) provided by Neff and Nicholas (2005) (Table 1). The Lake Michigan – Lake Huron watersheds were modeled as a single sub-watershed, following Neff and Nicholas (2005). The Lake Superior and Lake Michigan diversions (see Neff and Nicholas, 2005) were ignored. The mean lake concentrations obtained in this study (ESM Table S2) were used to

Table 1 Hydrologic data related to the water balance of the Great Lakes, and estimated perchlorate mass balances for these lakes, based on the steady state and transient state simulations (see text). Lake

Superior

Michigan-Huron

Erie

Ontario

acat vlk vif-a vof-a

209,800 12,000 0 −69.0 175

369,500 8460 69.0 −168 51

103,700 484 168 −184 2.6

82,990 1640 184 −220 7.5

mlk mif-a mdl-a mdl-a mir-a mof-a

691 0 3.8 7.6 0 −3.8

847 3.8 13.0 19.8 0 −16.8

68 16.8 8.4 9.0 −9.3 −15.9

148 15.9 3.9 4.9 0 19.8

Symbol in this paper Hydrologic dataa Entire catchment area (km2) (lake plus land portion) Lake water volume (km3) Gain by inflow (connecting channel) (km3/year) Loss by outflow (connecting channel) (km3/year) Residence time in lake (years)b Perchlorate mass balance data (present-day) Mass in lake (tonnes)c Mass gain by inflow (connecting channel) (tonnes/year)c Mass gain direct loading to lake basin (tonnes/year), assuming steady statec Mass gain direct loading to lake basin (tonnes/year), assuming transient stated Mass loss by microbial degradation (tonnes/year)c Mass loss by outflow (connecting channel) (tonnes/year)c

a From Neff and Nicholas (2005), with small adjustments to match outflow and inflow volumes between Lake Superior and Lakes Michigan-Huron, and between Lakes Michigan-Huron and Lake Erie. b Calculated as the ratio vlk/vof-a. c From steady state simulation. d From transient state simulation.

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a)

streams by EDU

9 1000

2 5

perchlorate ng/L

1

6

7

4

100

10

b) 1000

Perchlorate concentrations in the Great Lakes

perchlorate ng/L

Lake Erie: western basin Lake Erie: central & eastern basins

Lake St. Clair Lake Huron

100

known to occur at elevated levels in wastewater released from pulp mills as byproduct of the use of sodium chlorate for the bleaching process (Bickerton et al., 2009). Thus, it seems likely that the elevated perchlorate concentration in this creek is the direct result of the release of wastewater from the pulp mill to this stream. Similarly, the highest concentration in EDU 1 (370 ng/L) was probably also affected by effluent from a pulp mill located along this stream (1 of 5 streams sampled in EDU 1). These samples that were apparently impacted by pulp mill effluent illustrate the fact that some of the perchlorate loading to the LGL watershed may be from localized land-based anthropogenic sources, rather than atmospheric deposition. In Fig. 4 the concentrations of perchlorate in streams selected from two end-member categories, urban and remote/forest sites are shown. The stream samples collected at urban sites tend to have much higher perchlorate concentrations (mean 213 ng/L; range from 20 to 500 ng/L) than streams sampled at forested sites that are remote from urban and agricultural developments (mean 30 ng/L, range from nondetectable to 60 ng/L). A two-sample t-test indicated that the urban samples had significantly higher concentrations (t-value = 3.08; pvalue = 0.018). This is strong evidence that urban areas appear to be significant sources of anthropogenic perchlorate.

Lake Superior Detroit River St. Marys River

10 Fig. 2. Box-whisker plots of perchlorate concentrations: (a) streams in the seven selected ecological drainage units (EDUs) defined for the LGL watershed (Fig. 1); (b) three of the Laurentian Great Lakes and their connecting waters. From left to right, each plot shows data first from upstream sites and then those further downstream within the LGL watershed. Each box indicates the range for the second and third quartiles of the data, the median for each shown as a solid black line. The whiskers indicate the full range of data, which in the case of some streams samples (EDU 1 and 2) extends below the applicable detection limit (11 ng/L, see methods). Pairs of data with the same black symbol (e.g., triangle), one solid and one open, are statistically different based on twosample t-tests (see Table 2).

95% confidence interval: Table 2). Perhaps these samples were affected by mixing with water from Lake Erie; for example, seiches can drive lake water into rivers (Trebitz, 2006). Our estimated perchlorate loading rates in the individual EDUs based on stream data are shown in Table 3. The inferred loading rate in the relatively undeveloped EDUs (1, 2, 4) (231–446 mg/(ha·year)) are lower than the inferred loading rate in the more developed EDUs (5, 6, 7, 9) (677–1071 mg/(ha·year)) (Fig. 3). The perchlorate loading rates in the four most highly developed EDUs are also much higher than the deposition rate inferred by Poghosyan et al. (2014) for the entire LGL watershed (approximately 240 mg/(ha·year)). A few of the stream samples in the relatively undeveloped EDU 1 and EDU 2 areas have probably been impacted by localized anthropogenic perchlorate sources. For example, one of the 14 streams sampled in EDU 2 had a perchlorate concentration of 690 ng/L, much higher than any other stream sample from the same region. This creek is known to be directly impacted by wastewater from a pulp mill. Perchlorate is

The concentrations of perchlorate observed in our samples from the Great Lakes (Fig. 2, ESM Table S2) were generally similar to those reported by Poghosyan et al. (2014) (Fig. 5). The concentrations in the St. Marys River, which is the outlet channel from Lake Superior (Fig. 1), were similar to those in that lake (ESM Table S2). Downstream of this river, in Lake Huron, Lake St. Clair, the Detroit River and Lake Erie (Figs. 1 and 2, ESM Table S2), the concentrations increased significantly (at 99% or greater confidence level: Table 2). Compared to ranges of perchlorate concentrations in the streams, the ranges in the Great Lakes are much smaller (Fig. 2 and ESM Table S2). The Great Lakes have much larger volumes of water and longer residence times, compared to the streams, which results in more extensive mixing of runoff-derived water from different areas, and mixing of waters of different “ages” (i.e., the time that has elapsed since precipitation or influx by runoff), and a more even distribution of perchlorate throughout the lake. Spatial and temporal variations in Lake Erie Our large dataset for Lake Erie (n = 127; ESM Table S2) had much greater variation (standard deviation σ = 125 ng/L, range 53 to 1100 ng/L) compared to Poghosyan et al. (2014, see their Table S1 in their Supporting Information) (n = 7, σ = 10 ng/L, range 80 to 100 ng/L). In detail, our samples from Lake Erie over several years showed heterogeneity (Fig. 6). A two-sample t-test indicated that for the samples taken from Lake Erie in 2009, the concentrations in the western basin (μ ± σ: 137 ± 156 ng/L) were significantly higher than those in the central and eastern basins (combined μ ± σ: 86 ± 31 ng/L) at the 95% confidence interval (Table 2, cf. Fig. 2). However for the full dataset for 2005, 2009 and 2010, there was no significant difference in the concentrations between samples from the western basin versus the central and eastern basins combined (Table 2). In May 2009, pairs of samples were simultaneously collected from both near surface (1 m below surface) and near bottom (2 m above bottom) points at 23 sampling sites in Lake Erie (locations shown in ESM Fig. S2). These samples indicate a N50% variation in the concentrations of perchlorate collected at different sites in Lake Erie (Fig. 6). However, these paired samples generally had similar concentrations at both depths (Fig. 6). This appears to indicate relatively effective vertical mixing of perchlorate within the water column, which is not surprising, given that extensive mixing occurs during annual turnovers of the lake, usually in both spring and autumn (Schneider et al., 1993).

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Table 2 Selected results of two-sample t-tests which were used to compare perchlorate concentrations (ng/L) in different sets of stream and lake samples. Results are shown as: t-value (p-value). EDU refers to ecological drainage unit (see Fig. 1 and text). Perchlorate concentrations in streams EDU 2 EDU 1, 2 and 4 (grouped) EDU 1 EDU 2 EDU 4 EDU 5 EDU 6 EDU 7

EDU 4

0.05 (0.963)

0.73 (0.503) 0.96 (0.353)

EDU 5

EDU 6

EDU 7

EDU 9

−2.45 (0.022)⁎⁎

−2.29 (0.029)⁎⁎

−4.46 (0.000)⁎⁎⁎

−2.71 (0.012)⁎⁎

−1.40 (0.234) −2.04 (0.059) −9.48 (0.000)⁎⁎⁎

−1.40 (0.220) −1.97 (0.063) −5.97 (0.000)⁎⁎⁎

−2.61 (0.059) −3.72 (0.002)⁎⁎⁎ −13.71 (0.000)⁎⁎⁎ −3.96 (0.000)⁎⁎⁎ −2.76 (0.008)⁎⁎⁎

−1.58 (0.188) −2.28 (0.037)⁎ −8.83 (0.000)⁎⁎⁎

−0.14 (0.886)

River mouths along Lake Erie −1.69 (0.103)

−0.62 (0.539) −0.32 (0.747) 3.03 (0.004)⁎⁎⁎

Perchlorate concentrations in Great Lakes

Lake Superior

St. Marys River

Lake Huron

−1.08 (0.342)

−8.57 (0.000)⁎⁎⁎ −6.52 (0.001)⁎⁎⁎

St Marys River Lake Huron

Lake St. Clair

Detroit River

−4.12 (0.009)⁎⁎⁎ −3.84 (0.012)⁎⁎ −2.32 (0.068)

Lake St. Clair Detroit River western basin, Lake Erie 2009 western basin Lake Erie

−9.75 (0.000)⁎⁎⁎ −7.13 (0.006)⁎⁎⁎ 0.20 (0.842)

western basin Lake Erie (2005-2010)

central and eastern basin, Lake Erie 2009 central and eastern (2005-2010) basin, Lake Erie

−3.90 (0.000)⁎⁎⁎

−3.08 (0.003)⁎⁎⁎

−3.53 (0.001)⁎⁎⁎

−2.61 (0.011)⁎⁎

−1.50 (0.138)

−0.02 (0.987)

0.96 (0.355) −1.57 (0.122)

2.02 (0.078) −0.08 (0.937) 1.13 (0.260)

2.37 (0.064)

2.06 (0.046)⁎

⁎ Means of the two datasets are significantly different at the 95% or greater confidence interval. ⁎⁎ Means of the two datasets are significantly different at the 97% or greater confidence interval. ⁎⁎⁎ Means of the two datasets are significantly different at the 99% confidence interval or greater.

higher influx of perchlorate to the lake could occur by either direct atmospheric deposition, by runoff from developed catchments, or by direct discharge of treated (or untreated) wastewater. Certainly these high concentrations cannot be accounted for by relatively uniform atmospheric deposition of “indigenous perchlorate”, which is suggested by Poghosyan et al. (2014) to be the main source of perchlorate in the Great Lakes. The observed drop-off in concentrations in 2009 between the western and central basins of Lake Erie (Table 2, Fig. 2) suggests loss of perchlorate in the lake, possibly focused in the central basin. This loss may be due to microbial degradation (cf. Poghosyan et al., 2014) under low oxygen events (hypoxia), which are known to occur annually in the central basin of Lake Erie (Zhou et al., 2015). A few studies have examined the fate and behavior of perchlorate in other lakes. Wilkin et al. (2007) observed declines in concentrations in the water column of a lake in Oklahoma USA following a peak associated with fallout from fireworks. In parallel microcosm experiments, they found that microbial communities living in the sediments of this lake were capable of reducing perchlorate (Wilkin et al., 2007). In a study of perchlorate in ice-covered lakes in Antarctica, Jackson et al. (2012) found evidence for biological reduction of perchlorate in anoxic bottom

The spatial variations in perchlorate concentrations in near surface water (1 m depth) in Lake Erie for five different periods in 2005, 2009 (3 periods) and 2010 are shown in Fig. 7. For each period in 2009 and 2010, the highest concentrations tended to be clustered in the westernmost part of the lake. The strong lateral and temporal variations in perchlorate concentrations that we observed in Lake Erie (Fig. 7) indicate transient, un-mixed conditions that persist at least seasonally in some parts of the lake, notably in shallow (1 m) and nearshore samples. These observations suggest that there are both lateral (geographic) differences and temporal fluctuations in the flux of perchlorate to this lake. These variations may tend to persist in nearshore areas, because, for much of the year, influxes of water from streams and other shoreline discharges to the Great Lakes tend to become entrapped in nearshore, shallow areas along the coast (Csanady, 1970; Rao and Schwab, 2007), which can result in very distinct differences in water quality between nearshore and offshore areas of the lakes (Malkin et al., 2010; Yurista et al., 2015). We suspect that the highest concentrations of perchlorate observed in Lake Erie (Fig. 7) were affected by localized influx from anthropogenic sources, such as fireworks displays (cf. Backus et al., 2005) or plumes of wastewater, perhaps concentrated in urban areas. Localized

Table 3 Estimated loading (ψdl-a) of perchlorate in the seven selected ecological drainage units in the Laurentian Great Lakes watershed based on stream data. Ecological drainage unit (cf. Fig. 1) EDU 1

EDU 2

EDU 4

EDU 5

% of land developed as community/infrastructure or agriculture (reference catchment)a 1.5 1.0 24 65.9 Mean stream perchlorate concentration (ng/L) 98 94

b c

EDU 7

EDU 9

81.9

87.4

68.6

197

201

283

211

677

1071

902

721

b

47

Estimated mean annual loading based on stream data (mg/(ha·year)) 298 446 231 a

EDU 6

c

See Table S1 in Electronic supplementary material (ESM) (cf. Fig. 3). Cf. ESM Table S2. Based on Eq. (1) (Estimating rates of loading of perchlorate using stream data).

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EDU 6

1000

1000 EDU 7

EDU 9

800 R² = 0.787

600

perchlorate (ng/L)

estimated perchlorate loading (mg/(ha•year))

1200

EDU 5

EDU 2

400

EDU 1

200

Lake Huron

100

9 sites 18 samples

EDU 4

Lake Erie

Lake Superior

2 sites 10 sites 20 samples 10 samples

15 sites 15 samples

1 site 7 samples 47 sites 124 samples

0 0

20 40 60 80 % developed land in reference catchment (community/infrastructure and agriculture)

100

Fig. 3. Plot showing relationship of estimated perchlorate loading (ψdl-a) in each ecological drainage unit (EDU) to the extent (percentage) of development in that EDU. Estimated loading is based on stream data (see Table 2); percentage development is based on a reference catchment in each EDU using the Ontario Flow Assessment Tool (see ESM Table S1).

waters or sediments of most of the lakes. In contrast, Smith et al. (2015) concluded that perchlorate concentrations in a well-mixed, welloxygenated lake in Arctic Canada were not likely affected by “[biogeo]-chemical attenuation.” In general, given that perchlorate tends to persist in the environment under oxic conditions (e.g., Trumpolt et al., 2005; Borden et al., 2014), microbial reduction of perchlorate is not expected to be important in oxic water columns of lakes.

10 Fig. 5. Comparison of the concentrations of perchlorate in three of the Great Lakes reported by Poghosyan et al. (2014), plotted in red, and those measured in this study, shown in blue.

metropolitan Detroit. Three samples from one site (160) had perchlorate concentrations ranging from 101 to 105 ng/L, very similar to those of Lake Huron. In contrast, three samples from the other site (161) had concentrations ranging from 205 to 212 ng/L. The latter samples with elevated perchlorate also had much higher concentrations of a chemical tracer of wastewater, the artificial sweetener acesulfame, (1640–1880 ng/L versus 360–396 ng/L) (Van Stempvoort et al., 2011a, b, 2013). We suspect that the site with higher perchlorate and acesulfame had been strongly impacted by a nearshore municipal wastewater plume, leading to localized, transient, elevated concentrations of both of these chemicals.

Perchlorate concentrations in Lake St. Clair Steady state simulation of perchlorate mass balances in the Great Lakes Within the sequential chain of Great Lakes and connecting waters that were sampled in this study, Lake St. Clair had the highest median concentration (Fig. 2). This lake is a connecting water body between Lake Huron and Lake Erie which receives most of its water as influx from Lake Huron. Accordingly, one would expect the perchlorate concentration in Lake St. Clair to be similar to that of Lake Huron, i.e. about 100 ng/L (Fig. 2). In September 2010, samples were collected at two sites in Lake St. Clair, both in nearshore areas adjacent to

500

perchlorate (ng/L)

400

300

200

100

0

urban areas

remote undeveloped areas

Fig. 4. Box whisker plot illustrating large contrast between perchlorate concentrations in streams samples collected at urban sites (n = 8) versus other stream samples collected at sites in forested areas remote from any major developed areas/communities (n = 9). Samples were from 12 streams (4 urban) in northern Ontario sampled in early October 2005, and from 5 streams (4 urban) sampled in southern Ontario from mid-September to early October 2011.

Based on our simulated steady-state mass balance for the Great Lakes (Tables 1and 4), perchlorate loading to the Lake Superior watershed (181 mg/(ha·year)) is lower than that to the Michigan-Huron and Ontario watersheds (352 to 472 mg/(ha·year)) and is much lower than that to the Erie watershed (813 mg/(ha·year)) (Fig. 8). These results support our other evidence, based on stream data, as discussed above, that perchlorate loading in the LGL watershed is uneven, and is higher in the more developed areas of the watershed. In contrast to our results, Poghosyan et al. (2014) suggested that total atmospheric deposition in the LGL watershed is relatively uniform and about twice that of their estimated wet deposition (14.1 ng/L which is equivalent to 28.2 ng/L in precipitation). Assuming a mean annual precipitation amount over the LGL watershed of 820–900 mm (Kutzbach et al., 2005), Poghosyan et al. (2014) implied that the perchlorate loading for the entire LGLW is approximately 240 ± 10 mg/(ha·year). Poghosyan et al. (2014) also provided a steady-state model of perchlorate fluxes and exchanges between lakes in the LGL watershed. The largest imbalance in their modeled fluxes was for Lake Huron, where the modeled annual outflow of perchlorate was 42% higher (based on their Supporting Information Fig. S4) than the annual influx (by atmospheric influx and inflows from Michigan and Superior). Poghosyan et al. (2014) stated that such imbalances in their model indicated a “possible perchlorate contribution from other sources not accounted for by the atmospheric deposition”, more specifically possible minor perchlorate contributions from the watersheds of Lakes Huron and Ontario. Thus, in spite of the differences in the approaches and overall conclusions of Poghosyan et al. (2014) and our study, both studies suggest that the loading of perchlorate to the lakes increases downstream of Lake Superior. If there has been a significant increase in loading of anthropogenic perchlorate in the LGL watershed in recent decades, then the above steady-state estimates (i.e., our Table 4, Fig. 8; also Poghosyan et al., 2014) have underestimated the current loading of perchlorate in the

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247

160 y = 0.843x + 14.98 R² = 0.832

140 120 perchlorate 100 (ng/L), bottom - 2 m 80 60 40 40

60

80

100

120

140

160

perchlorate (ng/L), 1 m depth Fig. 6. Plot showing vertical consistency of perchlorate concentrations at sites in Lake Erie. Each symbol is the plot of the analyses of samples collected at two different depths (1 m below surface; 2 m above lake bottom) at same site, May 25–28, 2009.

watershed. Given that some of the Great Lakes have relatively long residence times (up to 175 years in Superior: Table 1), it seems likely that steady-state conditions are not applicable to the perchlorate budget in the Great Lakes. In contrast, our estimates of loading rates based on stream concentrations (Table 3, Fig. 8) may be closer to the actual current values, though there may also be lag effects for the stream data, associated with residence times along groundwater flow paths (Dunn et al., 2007) and in wetlands (Kadlec, 1994). Transient state simulation of perchlorate trends in the Great Lakes Given the above evidence that our initial assumption of steady state conditions may not be valid, we developed a transient state simulation to probe how, in a general way, perchlorate concentrations in the Great Lakes might have responded to increases in loading over time. Though many variations could be considered, we report here only one simulation, given the lack of available information to further constrain this modeling. In the selected simulation, we assumed that the initial “predevelopment” loading of perchlorate to the entire LGL watershed was uniform. We employed the same mass balance assumptions (Eqs. (2) to (5)) that we used in our steady state simulation, except that now the system was modeled as a transient one, in which loading (ψdl-a) increased from year to year, and the concentrations in the lakes responded to these changes, influenced by their different residence times (Table 1), and by changing influx concentration (cif) from upstream Great Lakes. This was accomplished by taking into account the hydrologic exchanges and mass fluxes affecting each lake, as summarized in Table 1. For this simulation, all lake volumes and annual water fluxes (Table 1) were assumed to be constant. For each Great Lake, the changing chemistry was calculated as yearly steps, assuming that the perchlorate supplied by direct loading, ψdl-a, to the land portion of the catchment of each Great Lake was transported within the same year to the lake (cf. Poghosyan et al., 2014), and that complete mixing occurred the same year within that lake. We developed our simulation in three phases: (i) We selected a general equation to simulate increasing perchlorate loading over the past century (1909–2009) in each Great Lake subwatershed as a relatively simple, logistic growth curve (sigmoid):   ψdl−a ¼ ψpredev þ ψextra = 1 þ e−kðy−ymidÞ

ð6Þ

where ψpredev is the predevelopment loading (mg/(ha·year)), ψextra is the additional loading at the theoretical endpoint

(maximum), y is the year, where start year = 0 (1909), the final year is 100 (2009), and the midpoint ymid = 50 (1949); k is the steepness coefficient, which was assumed to be 0.1 for all calculations. Our selections of values for ψpredev and ψextra are discussed below. The use of Eq. (6) allowed us to model increases in loading during the past century that have been most pronounced in recent decades (Furdui et al., 2018), and that have recently levelled off. However, we do not imply that the actual loading trends in these subwatersheds have been sigmoidal; the exact nature of these trends is unknown. (ii) In the next phase we developed a transient model of the changes in perchlorate concentrations in Lake Superior over the past century. We selected this lake first because it is not affected by changes in loading from upstream Great Lakes. To simulate the response of this lake to increased perchlorate loading, we accounted for annual increases in the mass of perchlorate in the lake (Δmlk-a), and in the concentration of perchlorate in the lake (clk) using Eqs. (7) and (8): Δmlk−a ¼ mdl−a −mof−a

ð7Þ

where mdl-a = ψdl-a · acat (see Eq. (5)), and the mass outflux by channel flow the same year, mof-a = vof-a · cof, assumed no loss by reactions in the lake (see Eq. (4)). clk ¼ mlk =vlk

ð8Þ

where mlk is the mass of perchlorate in the lake, vlk is the volume of water in the lake, and clk = cof. To constrain our simulated trend in perchlorate loading to the Superior subwatershed, we noted that Furdui et al. (2018) reported an approximately three-fold increase in perchlorate loading to the Canadian High Arctic during the past century (particularly since 1980), which they attributed to increased loading from anthropogenic sources. Thus, it seemed reasonable, as a first approximation, to assume that an increase in loading of perchlorate of similar magnitude has occurred in the Lake Superior subwatershed over the past century. Thus, for Lake Superior, the additional loading, ψextra, was assumed to be twice that of the predevelopment loading, ψpredev (i.e., ψextra = 2 · ψpredev), to provide an approximately three-fold increase in loading over time. A fit (by trial and error) for the current perchlorate concentration (clk) in Lake Superior (55 ng/L) was found: a predevelopment

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Legend Perchlorate (ng/L) in Lake Erie in river mouths

<50

50-99 75 54

41

100-149 150-200 120 173 133 156

>200 251 280

79

May 2005 71 84 116 122

128 134 123

133

May 2009 61

101 111 149 107 109 88 140 130 145 74 103

88

97 99

72 70

74 69

112

114

84

118

70 74

125

41

85

101

79

70 67 120

67 251 82 102 74 75 92

78

81

July 2009

109 94 141 107 164 87 89 110 134 87 77 610 77 112 104 80 85 116 481 215

61

69

153

71 72 74

78 124

84

103

August 2009

95

86

110

57

84

78 43

53 108

101

127

124

100 98 117 91 97 112

71

July 2010 95

76

Fig. 7. Variations of concentrations of perchlorate in Lake Erie (1 m depth) during five sampling excursions. The red dashes lines indicate boundaries between the western basin (left), central basin, and eastern basin (right). Each value plotted represents a single analysis, or an average, if more than one sample was collected, or if duplicate analyses were conducted.

(1909) loading (ψpredev) of 123 mg/(ha·year), yielding a final (2009) loading in the Superior watershed of 363 mg/(ha·year). (iii) In the third phase, changes in loading to the other Great Lake watersheds were simulated over the same period (1910–2009)

sequentially, from upstream (Michigan-Huron) to downstream (Ontario). Similar assumptions were applied to each: (a) the same predevelopment (1909) loading obtained in the Lake Superior step (phase ii); (b) Eq. (6) was again used to simulate the

D.R. Van Stempvoort et al. / Journal of Great Lakes Research 45 (2019) 240–251

1200

Erie subwatershed

900 800

Ontario subwatershed

EDU 7

800 EDU 5

perchlorate loading mg/(ha·year)

EDU 6

1000

perchlorate loading mg/(ha· year)

1000

Michigan-Huron subwatershed

EDU 9

Superior 600 subwatershed EDU 2

400 EDU 1 EDU 4

200 0

249

Lake Superior Lake Michigan and Huron Lake Erie Lake Ontario

700 600 500 400 300 200

Based on mean stream concentration

Based on steady state simulation

Based on transient state simulation

100 0 1910

Fig. 8. Comparison of estimated perchlorate loading in the LGL sub-watersheds based on (i) stream data, (ii) steady state simulation of perchlorate in the Great Lakes, (iii) transient state simulation of the same.

By trial and error, fits for this transient state simulation were found that matched the current concentrations in these lakes: the simulated final (2009) perchlorate loadings were 537, 864 and 593 mg/(ha·year) respectively in the Michigan-Huron, Erie and Ontario subwatersheds (Table 4, Fig. 9). The simulated trends in the loading in each subwatershed, and the changes in the perchlorate concentrations in each lake are shown in Fig. 9 which suggests that the concentrations of perchlorate have increased significantly in all Great Lakes over the past century, and that the increase may have been relatively small in Lake Superior, and strongest in Lake Erie. This figure also shows that, if ongoing loss of perchlorate has occurred in Lake Erie throughout the past century, as assumed in this simulation, then it is possible that the central and eastern portions of this lake, and Lake Ontario (downstream), may have had the lowest perchlorate concentrations early in the 20th century, before significant increases in the perchlorate loading, especially in the Erie subwatershed. Overall, the perchlorate loading estimated by our transient state simulation were similar to those based on our stream data and on our steady state simulation (Fig. 8). In all three approaches, the loadings obtained varied between the subwatersheds of the Great Lakes; they were higher downstream of Lake Superior, notably in the Erie subwatershed

Table 4 Estimated loading (ψdl-a) of perchlorate (mg/(ha·year)) to Great Lakes subwatersheds based on the simulations of perchlorate mass balances in the Great Lakes. Subwatershed Steady state simulation Transient state simulation

Superior

Michigan and Huron

Eriea

Ontariob

181 363

352 537

813 864

472 593

a Outflow (cof) value based on mean concentration in the western basin of Lake Erie (see Estimating perchlorate mass balance in the Great Lakes). b Inflow concentration (cif) based on mean concentration in the central and eastern basins of Lake Erie; (cof) based on the median value reported by Poghosyan et al. (2014).

1950

1970

1990

2010

Year

160 140 120

perchlorate ng/L

trend of perchlorate loading in each lake subwatershed over the past century, but this time ψextra was varied independently to obtain a unique fit for each lake. Similar to our steady state simulation of Lake Erie, in our transient state simulation for this lake, in every year the perchlorate concentration within the central basin of this lake (and in the outflow from this lake) was assumed to be lower by 37% compared to the western basin, due to ongoing loss within the central basin.

1930

Lake Superior Lakes Michigan and Huron western basin, Lake Erie central and eastern basins, Lake Erie Lake Ontario

100 80 60 40 20 0 1910

1930

1950

1970

1990

2010

Year Fig. 9. Results of the transient simulation of trends of perchlorate loading in the LGL subwatersheds over the past century, and of responding perchlorate concentrations in the Great Lakes.

(Table 4, Fig. 8). The loadings based on our transient state simulation were consistently higher than those based on our steady state simulation (Table 4, Fig. 8). If, in addition to losses in Lake Erie, there are other losses (e.g., microbial degradation) of perchlorate within the LGL watershed, then our calculations and simulations (Tables 3, 4) have likely underestimated the actual rates of perchlorate loading in the watershed. Summary and conclusions Our observations of perchlorate concentrations in streams in the LGL watershed do not support an earlier conceptual model (Poghosyan et al., 2014) that suggested perchlorate loading is dominantly by atmospheric deposition from natural sources and distributed relatively evenly over this watershed. Our observed perchlorate concentrations in streams and the Great Lakes are compatible with the hypothesis

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that perchlorate loading to the LGL watershed is spatially uneven, affected by local or regional variations in the influx of perchlorate. Based on observed perchlorate concentrations in the streams, we provide estimates of loading rates in seven ecological drainage units (EDUs) in the LGL watershed. We conclude that there is strong evidence for higher rates of perchlorate loading in the more developed EDUs downstream of Lake Superior. Higher perchlorate loading in more developed EDUs is likely influenced by localized anthropogenic sources. Simple modeling of mass balances of perchlorate concentrations in the Great Lakes, assuming steady state, produced results that were consistent with the above concept that perchlorate loading in the watershed is uneven. Variable concentrations observed in surface samples from Lake Erie are inferred to be indicative of transient (un-mixed) conditions. These results appear to indicate that variable, localized anthropogenic sources produce transient, higher perchlorate concentrations in shallow and nearshore areas of the lake, in the western basin for example. Give the above results, we also provided a simulation that assumed transient state behavior of perchlorate in the Great Lakes, based on earlier evidence that perchlorate loading has increased over time, due to increased input from anthropogenic sources. Our transient state simulation suggests that perchlorate concentrations may have increased significantly in all of the Great Lakes over the past century, ranging from an approximately 50% increase in Lake Superior (from 37 to 55 ng/L in our simulation) to an approximately three-fold increase in the western basin of Lake Erie in particular (from 46 to 137 ng/L in our simulation). Our data for Lake Erie, and some previous studies of lakes (Jackson et al., 2012) and groundwater (Robertson et al., 2014), indicate evidence for microbial degradation of perchlorate within anoxic or suboxic environmental waters. However, the current lack of details regarding the nature and magnitude of losses of perchlorate along flowpaths in the LGL watershed (e.g., in groundwater, wetlands, lakes) remains an important science gap. Acknowledgements This research was funded by Environment and Climate Change Canada. Samples of the Great Lakes and mouths of rivers flowing into Lake Erie were provided by Environment and Climate Change Canada staff and summer students on the CSS Limnos. Samples from Lake Superior streams and other streams in the study were collected by staff of the Water Quality Monitoring and Surveillance Division, Environment and Climate Change Canada, Burlington, Ontario. Greg Bickerton arranged for collection of the 2005 samples from the Great Lakes and streams in the watershed. We benefitted from the comments of three anonymous reviewers. Appendix A. Supplementary material Supplementary material for this article can be found online at https://doi.org/10.1016/j.jglr.2018.12.007. References Aziz, C.E., Hatzinger, P.B., 2009. Perchlorate sources, source identification and analytical methods. Chapter 4. In: Stroo, H.F., Ward, C.H. (Eds.), In Situ Bioremediation of Perchlorate in Groundwater. Springer, Dordrecht, Netherlands, pp. 55–78. Backus, S.M., Klawuun, P., Brown, S., D'sa, I., Sharp, S., Surette, C., Williams, D.J., 2005. Determination of perchlorate in selected surface waters in the Great Lakes Basin by HPLC/MS/MS. Chemosphere 61 (6), 834–843. Bickerton, G., Brown, S., Ptacek, C., 2009. National Assessment of Groundwater Quality in Canada: Perchlorate. Environment Canada, Canada Centre for Inland Waters, Burlington, Ontario (Unpublished report). Böhlke, J.K., Hatzinger, P.B., Sturchio, N.C., Gu, B., Abbene, I., Mroczkowski, S.J., 2009. Atacama perchlorate as an agricultural contaminant in groundwater: isotopic and chronologic evidence from Long Island, New York. Environ. Sci. Technol. 43 (15), 5619–5625.

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