Risk-Based Screening of Selected Contaminants in the Great Lakes Basin

Journal of Great Lakes Research 41 (2015) 238–245

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Journal of Great Lakes Research

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Risk-based screening of selected contaminants in the Great Lakes Basin

Ruth N. Hull a,⁎, Sonya Kleywegt b,1, Julie Schroeder b,2 a Intrinsik Environmental Sciences Inc., 6605 Hurontario Street, Suite 500, Mississauga ONL5T 0A3, Canada b Ontario Ministry of the Environment and Climate Change, 40 St. Clair Ave West, 7th ﬂoor, Toronto, ON M4V 1M2, Canada article info abstract

Article history: A risk-based screening exercise was carried out to evaluate the significance of chemicals of emerging concern Received 19 March 2014 measured in water and sediment of the Great Lakes Basin. Chemical classes included pesticides, pharmaceuticals, Accepted 26 September 2014 organic wastewater constituents, nonylphenol ethoxylates, perfluorinated surfactants, chlorinated paraffins, Available online 17 December 2014 synthetic musks and flame retardants. Maximum measured concentrations were compared to benchmarks selected or developed to reflect a conservative no-effect level and/or the lowest-effect level. These benchmarks Communicated by Paul Helm reflected traditional effect information such as survival, growth and reproduction. From this analysis, several fi Keywords: pesticides, pharmaceuticals, polycyclic aromatic hydrocarbons and nonylphenol ethoxylates were identi ed as Aquatic toxicity potential concerns and needs for further work were identified. Five of these chemicals (all pesticides) were iden- Contaminant of emerging concern tified in waters of both the US and Canada (azinphos-methyl, chlorpyrifos, diazinon, malathion and metolachlor). Great Lakes Chlopyrifos, malathion and metolachlor are still registered for use in both jurisdictions; diazinon is registered for Risk-based screening use only in the US and azinphos-methyl is not registered for use in either jurisdiction, reflecting the persistence of these chemicals. The results of this screening exercise also were compared to those of several other studies, revealing some common chemicals. Although there are several uncertainties and data gaps in the benchmarks and monitoring data used in the current screening exercise, the results of this risk-based screening can be used by agencies for priority setting, program development, and to support ongoing collaborative research and monitoring programs. © 2014 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.

Introduction environmental risks. These contaminants may be previously unknown (based on new synthesis), unrecognized (never monitored for in the The Great Lakes Basin is one of the most biologically diverse regions Basin) or unregulated (no standards or guidelines). Under the newly- in Canada and the United States (US). The lakes (Superior, Michigan, ratified Great Lakes Water Quality Agreement (2012), Canada and the Huron, Erie and Ontario) support thousands of wetlands and diverse US have a mandate to prioritize chemicals, known as “chemicals of plants, fish and wildlife. The Basin is surrounded by lands of the States mutual concern”, for bi-national cooperative action. Identification of of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania emerging chemicals may help to inform priority setting and selection and Wisconsin in the US and the Province of Ontario in Canada. of chemicals of mutual concern. Targeted actions, by both the Canadian and US governments over Different methods and approaches have been used by governments the last two decades to control industrial, municipal and agricultural and research organizations to identify potential priority chemicals in sources of chemicals in the Basin, have resulted in significant improve- surface water. In 2009, Muir et al. completed the “Identification of ments in water quality. However, the Basin continues to be affected by New, Possible Persistent, Bioaccumulative and Toxic (PB&T) Chemicals both direct and indirect sources of chemicals that can enter the environ- in the Great Lakes Region” by screening chemicals in commerce. The ment every day due to residential, commercial and industrial activities approach was to combine the Canadian Domestic Substances List as well as by the continued presence of legacy chemicals. More recently, (DSL) with the US high production volume (HPV) chemicals on the with the enhancement of analytical techniques, scientists have begun to Toxic Substances Control Act (TSCA). To reduce the list of 429 com- identify new chemical threats to the Basin, identified as ‘contaminants pounds to a manageable size, the authors selected 10 priority chemicals of emerging concern’ based on their unknown human health and/or from 5 chemical groupings (brominated, chlorinated, fluoridated, non- halogenated or silicone related). Although quantitative structure activity relationships (QSARs) were used to assess aquatic toxicity and cancer ⁎ Corresponding author. Tel.: +1 905 364 7800. potential, they were not used to prioritize chemicals. E-mail addresses: [email protected] (R.N. Hull), [email protected] In 2011, the Water Environment Research Foundation funded a (S. Kleywegt), [email protected] (J. Schroeder). 1 Tel.:+14162121525. project to develop a diagnostic tool to evaluate and prioritize trace 2 Tel.:+14163253475. organic compounds (TOrCs) according to three approaches: 1) risk,

http://dx.doi.org/10.1016/j.jglr.2014.11.013 0380-1330/© 2014 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved. R.N. Hull et al. / Journal of Great Lakes Research 41 (2015) 238–245 239

2) chemical PB&T, and 3) a hybrid approach based on risk, persistence, toxicity guidelines and screening benchmarks. As an initial screening, and bioaccumulation potential (Diamond et al., 2011). The approach the maximum measured concentration was used and compared to envi- was similar to that of Muir et al. (2009) with a focus on persistence ronmental guidelines from a number of sources. When guidelines were and bioaccumulation of the individual chemicals. Unlike Muir et al., not available, a literature search was conducted to develop a screening the authors considered only unregulated chemicals (517), which benchmark. To be consistent with current guidelines, the screening were then grouped into several classes: pharmaceuticals and personal benchmarks were developed based on standard toxicity endpoints of care products (PPCPs), natural and synthetic hormones, surfactants, survival, growth and reproduction. deodorizers/fragrances, industrial chemicals, current use pesticides, polycyclic aromatic hydrocarbons (PAHs), flame retardants and plasti- cizers. Chemicals in all categories were identified as high priority Monitoring information using at least one of the three approaches, although more pesticides were identified than any other category of chemical, and fewer personal Monitoring data were obtained from the IJC report (Klecka et al., care products, PAHs and flame retardants were identified than the other 2009), which reported concentrations of approximately 320 chemicals categories. This diagnostic tool used predicted chronic toxicity thresh- in water and sediment (Table 1). For this study, 245 chemicals were olds using a QSAR model instead of using empirical toxicity data. selected from the IJC list, based on preliminary screening and sorting More recently, Blair et al. (2013) completed a review and prioritiza- to remove duplicates (e.g., synonyms of the same substance) and classi- tion of PPCPs that are of environmental concern in Lake Michigan. The fication of some chemicals into groups. For some of the chemicals select- authors compared measured concentrations of selected chemicals ed (pharmaceuticals and polybrominated diphenyl ethers), additional with reported predicted no-effect concentrations (PNECs) that were monitoring data provided by Ontario Ministry of the Environment reported using the review paper from Verlicchi et al. (2012) and were used to supplement the IJC data (personal communication, ECOSAR v.1.11 from the US EPA (USEPA, 2012). The authors determined S. Kleywegt of Ontario Ministry of the Environment and Climate Change, that 14 PPCPs were of ecological concern to this Great Lake. Toronto, ON). In 2009, the International Joint Commission (IJC) compiled a decade's worth of environmental data to understand chemical presence in the Great Lakes Basin (Klecka et al., 2009). Data for approximately Environmental guidelines 320 chemicals (pesticides, pharmaceuticals, organic wastewater constituents, nonylphenol ethoxylates, perfluorinated surfactants, chlori- Environmental guidelines were compiled from a number of sources. nated paraffins, synthetic musks and flame retardants) measured in The sources were chosen based on their relevance to the Great Lakes water and sediment were compiled and summarized in the report. and jurisdiction (Canadian/American), and date of publication; others These data were then compared to Canadian, American and European were chosen based on having established criteria for the particular sub- guidelines. However, many of the chemicals did not have guidelines stance. The sources included: Canadian Water or Sediment Quality and hence the significance of the measured concentrations could not Guidelines (CCME, 2010); Ontario Provincial Water Quality Objectives be determined. and Sediment Guidelines (MOEE, 1994a,b; MOE, 2008); Environment Detection of a chemical in a particular environmental matrix does Canada Ideal Performance Standards for pesticides (Sabo et al., 2008; not necessarily mean that it is of concern or may cause harm. Thus, Stantec, 2008); Environment Canada and Health Canada Screening the objective of the following risk-based screening exercise was to iden- Assessment Probable No Effect Concentrations (PNEC) (EC/HC, 2008, tify chemicals detected in the Great Lakes Basin that may be of concern 2009a,b); Environment Canada Estimated No-effect Values (ENEVs) to aquatic life through the development of benchmarks based on avail- (EC, 2006, 2008); European Union Environmental Quality Stan- able toxicity information. We present the approach, selected or devel- dards (EU, 2005a,b); European Union Risk Assessment reports (EU, oped benchmarks and results of our screening exercise and compare 2005c,d, 2008a,b,c,d,e,f); Australia and New Zealand Environment and the results of the chemicals that had hazard quotients (HQ) suggesting Conservation Council Water Quality Guidelines (ANZECC, 2000); Oak possible toxic effects (HQ N 1) to those identified in other studies. Ridge National Laboratory Screening Benchmarks for water (Suter and Tsao, 1996)andsediment(Jones et al., 1997); Office of Pesticide Programs benchmarks (US EPA OPP, 2007a,b,c,d, 2011); Dutch NC (neg- Methods ligible concentration) and MPC (maximum permissible concentration) values from Crommentuijn et al. (1997) and United Kingdom Environ- The significance of the chemicals measured in water and sediment mental Quality Standards (UK, 2007). Electronic supplemental Material from both Canadian and American sample sites of the Great Lakes (ESM) Table S1 gives the guidelines which were used for each substance Basin was evaluated by comparing measured concentrations to aquatic in water and while ESM Table S2 gives the guidelines for sediment.

Table 1 Summary of chemical groups selected, reviewed and identiﬁed for follow up in this study.

Chemical group Chemicals selected Chemicals with Chemicals N Chemical without Chemicals with insufﬁcient analytical Chemicals for HQ from IJC data (#) water data (#) benchmark (#) benchmarks (#) or toxicity data for HQ (#) calculation (#)

Pesticides 101 101 24 6 0 30 Pharmaceuticals 58 54 0 54 23a 31 Organic wastewater chemicals 56 39 7 12 1b 18 Alkyl phenol ethoxylates 6 1 1 0 0 1 Synthetic musks 8 8 0 4 1c 3 Perﬂuorinated compounds 2 2 1 1 0 2 Chlorinated parafﬁns 2 2 0 0 0 0 Flame retardants 12 9 0 4 0 4 Total 245 216 33 81 25 89

a 1,7-Dimethylxanthine, albuterol, azithromycin, carbadox, ciprofloxacin, codeine, dehydronifedepine, digoxigenin, digoxin, doxycycline, dyphrenhydramine, enalprilat, enrofloxacin, norfloxacin, oxytetracycline, paroxetine metabolite, pentoxifylline, ranitidine, sarafloxacin, sulfamethizole, tetracycline, virginiamycin, and warfarin. b Coprostanol. c DPMI. 240 R.N. Hull et al. / Journal of Great Lakes Research 41 (2015) 238–245

Benchmark development In each case, the AF accounted for differences in species (intra and interspecies), exposure conditions (laboratory versus field, varying Aquatic toxicity benchmarks were needed to evaluate the signifi- environmental conditions), paucity of toxicological data, etc. (CCME, cance of the measured environmental concentrations for chemicals 2007). without guidelines. For those chemicals without environmental guide- The benchmark protection goal (NOEC benchmark) is typically the lines, a literature search was conducted and screening aquatic toxicity protection of 100% of exposed species; however, significant uncertainty benchmarks were developed. Benchmarks were developed generally exists given the often limited datasets used and the use of application following the Canadian Council of Ministers of the Environment factors. The benchmarks derived in this study have been used as an ini- (CCME) water quality guideline development process (CCME, 2007). tial screening tool, to identify potential issues in the monitoring data. For this exercise, both a no-observed-effect concentration (NOEC) and Therefore, benchmarks were only derived for chemicals and media for the lowest-observed-effect concentration (LOEC) benchmark were de- which monitoring data were available (e.g., if a substance was moni- veloped, where data were available. The LOEC benchmark was intended tored only in water, no benchmark for the substance in sediment was as a concentration that may cause an adverse effect and the NOEC derived). benchmark was intended as a concentration estimated not to cause an adverse effect. Most benchmarks were developed based on available Grouping of chemicals toxicity information up to and including 2012 (see ESM Tables S1 and S2 for complete lists of benchmarks). Subsets of the chemicals (congeners) were grouped based on their Existing databases (e.g., ECOTOX, 2011; Wiki Pharma, 2011) were chemical classifications. These included perfluorinated compounds, chlo- consulted before the literature search was conducted. Scientific litera- rinated paraffins, nonylphenol ethoxylates (NPE) and polybrominated ture collected for each substance was reviewed and the appropriate ef- diphenyl ethers (PBDEs). fect data was collated for use in benchmark development. The quality of All of the perfluorinated surfactants that are sulfonates were the studies was not investigated (e.g., static vs. flow-through conditions, assessed by Perfluorooctane Sulfonic Acid (PFOS) and all those that nominal vs. measured concentrations, appropriate statistical analysis). are carboxylic acids were assessed using Perfluorooctanoic Acid However, when information on study quality was available, it was con- (PFOA). The short-chain chlorinated paraffins (C10 to C13) were sidered in the benchmark development process. In addition, the original assessed using “Total SCCP” (Total Short-Chain Chlorinated Paraffins), paper was reviewed for each study that formed the basis of a bench- and the medium-chain chlorinated paraffins (C14 to C17) were mark to ensure that data and study details (e.g., concentration, units, assessed using “Total MCCP” (Total Medium-Chain Chlorinated acute vs. chronic) were correct. Consistent with the CCME water quality Paraffins). Nonylphenol and its ethoxylates were assessed using toxic guideline development process (CCME, 2007), benchmarks were based equivalency factors (TEFs) related to nonylphenol (CCME, 2002a,b). on survival, growth and reproduction endpoints. Non-traditional end- The PBDEs were grouped according to the number of bromine atoms points (e.g., behavior) were considered where there was a potential (i.e., all the triBDEs considered together, all the tetraBDEs considered to- link to whole organism effects (e.g., survival, growth or reproduction) gether, etc. for these plus the pentaBDEs, hexaBDEs, heptaBDEs and based on professional judgment and comments made by authors of decaBDE). The number of congeners within a group varies. Deca-BDE the studies reviewed. For example, a decrease in predator avoidance has only one congener, also known as BDE-209, while the pentaBDEs or swimming ability was considered to have a potential link to include 46 individual congeners (BDE-082 to BDE-127) (Health decreased survival. The lowest chronic NOEC or Effect Concentration/ Canada, 2006). Lethal Concentration (EC/LC) ≤ 10 value was used to derive the NOEC benchmark, and the lowest chronic LOEC or EC/LC N 10 value was Hazard quotient derivation used to derive the LOEC benchmark. The general approach used to identify or develop the benchmarks is illustrated in Fig. 1.Twobenchmarks Hazard quotients (HQs) were calculated as the ratio of the maxi- were developed for data rich chemicals. In data poor instances, only one mum reported concentration of a contaminant measured in the Great benchmark could be developed (Table 2). Also, if only acute data were Lakes Basin and either the corresponding available environmental available, an acute benchmark was developed; these were generally guideline or a benchmark derived from the available toxicity literature. based on LC50 or EC50 data. For HQs based on an older existing guideline, a review was carried out to To derive a benchmark, the critical toxicity value was divided by an determine whether a more stringent benchmark should be considered. application factor (AF). Application or safety factors (hereafter referred If so, the new benchmark was adopted/set and used for the HQ calcula- to as application factors) were applied to account for uncertainties in tion. the data (e.g., extrapolation between species), and have been used in both human health and ecological risk assessments and guideline devel- HazardQuotientðÞ HQ opment (Solomon et al., 2007). Similar to the approach used to derive ¼ maximumreportedconcentrationinwaterandorsediment : water quality guidelines (CCME, 2007), the AF differed based on the environmentalguidelineorderivedbenchmark available dataset. An AF of 10 was applied to the critical study (i.e., the lowest acceptable and appropriate toxicity endpoint) to derive the For those chemicals with a HQ N 1, a more detailed analysis of the benchmark when the available data generally met the species require- number and location of exceedances, and sources of the chemicals ments for a CCME Type B1 guideline (CCME, 2007): three species of was carried out. freshwater fish, three species of freshwater invertebrate, and one species of freshwater plant. The requirements for particular types of species Results (e.g., the need for a salmonid species to be included) were not considered because few of the chemicals had datasets that met the rigorous re- Water quirements of a CCME water quality guideline. Consistent with the approach to derive a CCME Type B2 guideline (CCME, 2007), an AF of Of the 245 chemicals identified, 216 had water data and were 20 or 100 was applied to the critical study to derive the benchmark selected for the screening. Of these, 102 could be screened out (below when the available data did not meet the requirements for a Type B1 existing benchmarks) and 114 chemicals were identified for follow up guideline. The AF of 20 was used if the substance was not persistent including 33 chemicals that exceeded an existing benchmark and 81 (i.e., the half-life in water was less than 8 weeks; CCME, 2007), and chemicals that did not have a benchmark (Table 1). However, HQs the AF of 100 was used if the substance was persistent (CCME, 2007). could not be calculated for 25 chemicals due to limitations in the R.N. Hull et al. / Journal of Great Lakes Research 41 (2015) 238–245 241

Is there an existing guideline?

Yes No

Is there recent Yes Derive New literature to suggest Benchmark a lower benchmark?

Use WQG or Is there at least 1 US EPA OPP chronic data point? benchmark No Yes

Develop Acute benchmark Develop Chronic benchmark

Select lowest acute effect Are there data for at least 3 value and divide by 10 fish, 3 invertebrate, and 1 plant species?

No Yes

Acute Select lowest no- Is the substance Select lowest Benchmark effect value and persistent? effect value and apply an AF of 10. apply an AF of 10.

Yes No

LOEC NOEC Benchmark Benchmark

Select lowest Select lowest Select lowest effect value no-effect value effect value and Select lowest no- and apply an and apply an apply an AF effect value and AF of 100. AF of 100. of 20. apply an AF of 20.

LOEC NOEC LOEC NOEC Benchmark Benchmark Benchmark Benchmark

Fig. 1. Benchmark development process. analytical and/or toxicological data (Table 1). Most of these chemicals bisphenol A and PFOS exceeded NOEC benchmarks but not LOEC bench- were pharmaceuticals. For many of these emerging contaminants, marks. Chemicals that exceeded LOEC benchmarks were: acetochlor, there are no analytical standards or licensed methods. The analytical de- atrazine, chlorothalonil, chlorpyrifos, cis-permethrin, cyanazine, diazinon, tection limits are sometimes in the parts per billion range, and based on dieldrin, dinoseb, fonofos, malathion, (4-chloro-2-methylphenoxy) acetic potential toxicity of some chemicals, detection limits may be required in acid (MCPA), metolachlor, metribuzin, neburon, parathion, benzo(a) the parts per trillion range or lower, for both water and sediments. Ad- pyrene, bis(2-ethylhexyl) phthalate, ﬂuoranthene, pyrene and triclosan ditionally, many pharmaceuticals were anti-microbial agents and only (Table 2). limited data were available on their effects on natural microbial com- From the Canadian data, there were 13 chemicals with HQs greater munities (e.g., Brosche and Backhaus, 2010). There were endocrine dis- than 1 based on a NOEC and/or LOEC. Concentrations of azinphos- ruption data available for several organic wastewater constituents; methyl, carbamazepine, cloﬁbric acid, methoprene and naproxen however, to maintain consistency with the water quality guideline exceeded NOEC benchmarks but not LOEC benchmarks. Concentrations development process, these data were not included in the benchmark of carbaryl, chlorpyrifos, cypermethrin, diazinon, ibuprofen, malathion, development. In future, should toxicity data with endocrine disruption metolachlor and nonylphenol-TEQ exceeded LOEC benchmarks (Table 2). endpoints be directly linked to a whole organism effect, then these There were only 5 common chemicals with HQs greater than 1 based endpoints and data could be considered in the risk-based screening. on data for US and Canadian waters. These chemicals were all pesticides Of the 89 remaining chemicals, HQs were calculated based on an (azinphos-methyl, chlorpyrifos, diazinon, malathion and metolachlor). LOEC and/or NOEC benchmark. Of these, 52 chemicals had HQs below Concentrations of 2,3,6-trichlorobenzoic acid (2,3,6-TBA), 2,4,5- 1. The remaining 37 chemicals had at least one HQ above 1 and are sum- trichlorophenoxy propionic acid (2,4,5-TP; Fenoprop), indomethacin, marized in Table 2. acetophenone, 2,6-di-tert-butyl-phenol and the synthetic musks were From the US data, there were 29 chemicals with HQs greater than 1 compared only to acute toxicity benchmarks, as chronic toxicity data based on a NOEC and/or LOEC (Table 2). Concentrations of azinphos- were not available for benchmark development. All maximum concen- methyl, disulfoton, methiocarb, methyl parathion, phorate, anthracene, trations were at least 500 times below the acute benchmark suggesting 242 R.N. Hull et al. / Journal of Great Lakes Research 41 (2015) 238–245

Table 2 Maximum reported concentrations of chemicals in United States (US) and Canadian waters that exceeded a hazard quotient (HQ) of 1 based on a No-observed-effect-concentration (NOEC) and/or the Lowest-observed-effect-concentration (LOEC), All concentrations in μg/L. NA indicates substance not analyzed in this medium, or guideline or benchmark not available.

Substance Concentration in US waters Concentration in Canadian waters Water quality guidelineb LOEC HQ NOEC HQ

US CAN US CAN

Pesticides Acetochlor 10.6 NA 1.43 7.4 NA NA NA Atrazine 85.2 3.6 1.8, 13 6.6 0.28 NA NA Azinphos-methyl (Guthion) 0.124 0.0452 0.005, 0.036 NA NA 3.41.3 Carbaryl 0.03a 0.418 0.02 0.43 6 NA NA Chlorothalonil 0.24a NA 0.18 2.4 NA NA NA Chlorpyrifos 10 0.52 0.002 5000 260 NA NA cis-Permethrin 0.177 NA 0.004 44 NA NA NA Cyanazine 9.97 NA 2.0 20 NA 1000 NA Cypermethrin NA 0.38 0.069 NA 1.9 × 106 NA 1.9 × 107 Diazinon 22.5 1 0.08, 0.0016 14,000 625 NA NA Dieldrin 14.3 NA 0.001 7150 NA NA NA Dinoseb 0.21 NA 0.05 4.2 NA NA NA Disulfoton 0.21 0.00016 0.01 0.05 0.004 2.1 0.016 Fonofos 0.843 0.0028 0.008 105 0.35 NA NA Malathion 6.4 0.0208 0.1 6400 21 10,700 35 MCPA 37.3 0.0054 2.6 14 0.002 NA NA Methiocarb 2.57 NA 0.1 NA NA 26 NA Methoprene NA 0.308 0.09 NA 0.58 NA 3.4 Methyl parathion 0.33 NA 0.25 NA NA 1.3 NA Metolachlor 77.6 1.6 3, 7.8 155 3.2 210 4.3 Metribuzin 4.92 0.12 1 4.9 0.12 NA NA Neburon 0.24 NA NA 2.4 NA NA NA Parathion 0.08 0.0038 0.008, 0.013 10 0.48 NA NA Phorate 0.51 0.00015 0.21 NA NA 2.4 NA

Pharmaceuticals Carbamazepine NA 0.749 NA NA 0.75 NA 3.0 Cloﬁbric acid NA 0.175 NA NA 0.023 NA 1.8 Ibuprofen 0.018a 0.79 NA 0.36 16 NA NA Naproxen NA 0.551 NA NA 0.17 NA 1.7

Wastewater chemicals Anthracene 0.05 NA 0.012, 0.0008 0.83 NA 1.7 NA Benzo(a)pyrene 0.11 NA 0.015 7.3 NA NA NA Bis(2-eylhexyl) phthalate 20 NA 16 1.3 NA NA NA Bisphenol A 0.8 0.087 5, 0.175 NA NA 4.6 0.5 Fluoranthene 0.2 NA 0.04, 0.0008 13 NA 14 NA Pyrene 0.27 NA 0.025 11 NA NA NA Triclosan 0.3 0.01 0.115 2.6 0.09 NA NA

NPE Nonylphenol TEQ 3.85 5.5 1.0 0.99 1.4 NA NA

Perﬂuorinated surfactants PFOS 1.09 0.121 0.491 0.22 0.024 2.2 0.25

Bold HQ indicate a HQ N 1. NA Indicates substance not analyzed in this medium, or guideline or benchmark not available. a Estimated concentration based on ½ method detection limit (MDL) or sample detection limit. b See Supplemental material for complete details; multiple guidelines may be presented. a low likelihood of adverse effects to aquatic life from exposure to these The maximum concentration of p-p′-DDE also exceeded the LOEC chemicals, based on traditional aquatic toxicity endpoints. benchmark. From the Canadian data, the only HQ that could be calculated was for NPE, which exceeded the NOEC benchmark. Sediment

Out of the 245 chemicals identified for this study from the IJC data Discussion (Klecka et al., 2009), 64 had data for sediment. Of these, 45 were identified for follow up, including 10 that exceeded a benchmark and 35 that In this screening exercise, over half of the chemicals identified with had no benchmark. However, HQs could not be calculated for 34 HQs above 1 were pesticides. Many of these are no longer registered for chemicals due to limitations in the analytical and/or toxicological data use in Canada or the US. Those that are still used are mainly associated (Table 3). Most of these were pharmaceuticals and chemicals detected with the agricultural industry. Maps of pesticide use in the US show con- in municipal wastewater effluent. sistent, significant use in regions around the Great Lakes (USGS, 2002). For the 11 remaining chemicals, HQs were calculated based on an Interestingly, the five chemicals that exceeded a HQ of 1 in both US LOEC and/or NOEC benchmark. Of these, 2 chemicals had HQs below and Canadian waters were all pesticides. Chlopyrifos, malathion and 1. The remaining 9 chemicals had at least one HQ above 1 (Table 4). metolachlor are still registered for use in both jurisdictions; diazinon From the US data, the concentrations of dieldrin, p-p′-DDE, 2-meth- is registered for use only in the US and azinphos-methyl is not currently ylnaphthalene, anthracene, benzo(a)pyrene, fluoranthene, phenan- registered for use in either jurisdiction, reflecting the persistence of threne, pyrene and nonylphenol-TEQ exceeded NOEC benchmarks. these chemicals. R.N. Hull et al. / Journal of Great Lakes Research 41 (2015) 238–245 243

Table 3 Summary of sediment chemical groups selected, reviewed and identiﬁed for follow up in this study.

Chemical group Chemicals selected Chemicals with Chemicals N Chemical without Chemicals with insufﬁcient analytical Chemicals for HQ from IJC data (#) sediment data (#) benchmark (#) benchmarks (#) or toxicity data for HQ (#) calculation (#)

Pesticides 101 9 3 0 1a 2 Pharmaceuticals 58 12 0 12 12b 0 Wastewater chemicals 56 32 6 17 17c 6 Nonylphenol and ethoxylates 6 1 1 0 0 1 Synthetic musks 8 0 Perﬂuorinated compounds 2 2 0 2 2d 0 Chlorinated parafﬁns 2 1 0 0 0 0 Flame retardants 12 7 0 4 2e 2 Total 245 64 10 35 34 11

a Chlorpyrifos. b 1,7-Dimethylxanthine, albuterol, azithromycin, cimetidine, codeine, dehydronifedipine, diltiazem, diphenhydramine, miconazole, ranitidine, thiabendazole, and warfarin. c 2,6-Dimethylnaphthalene,3-methyl indole, 3-tert-butyl-4-hydroxy anisole, acetophenone, anthraquinone, carbazole, cholesterol, D-limonene, indole, isoborneol, isophorone, isopropylbenzene, isoquinoline, menthol, N,N-diethyltoluamide, triphenyl phosphate, and B-sitosterol. d PFOS, PFOA. e Dechlorane Plus, TBE.

Most of the organic wastewater constituents of concern were PAHs treatment plant at concentrations exceeding the PNEC (caffeine, which are released from non-point sources, such as wood burning, vehi- paraxanthine, sulfamethoxazole, ofloxacin, fluoxetine, triclocarban), cle emissions and forest fires, and from point sources, such as the iron none of which were identified in our current study. Diamond et al. and steel manufacturing industry in Ontario and the US. These (2011) used the median or mean environmental concentration and chemicals are also released from a variety of other sources in the compared to predicted toxicity (QSAR approach), and included endo- Great Lakes region, including the effluent from wastewater treatment crine disruption as an endpoint. Chemicals exceeding a HQ of 0.1 were plants (USGS, 2008). identified. The use of a HQ of 0.1 would have resulted in more chemicals NPEs were identified of potential concern in sediment of Canadian being identified under our approach in water (lindane, profam, atorva- and American areas of the Great Lakes Basin while water data for both statin, benzafibrate, chlorotetracycline, erythromycin, fluoxetine, areas produced HQs close to 1. NPEs are found in a variety of products, gemfibrozil, lincomycin, monensin, roxythromycin, sulfamethoxazile, and the primary pathway for release to the environment is through sulfadimethoxine, sulfamethazine, alpha estradiol, cis-androsterone wastewater treatment plants, as is the same for pharmaceuticals. Syn- and phthalic anhydride); these chemicals were not on the priority list thetic musks, chlorinated paraffins and PBDEs were not monitored at of Diamond et al. (2011). concentrations approaching water or sediment toxicity benchmarks. A shortcoming of using occurrence data is that such data are scarce Two pesticides and six PAHs were found at concentrations in sedi- for many chemicals and may be difficult to compare over time and ment exceeding benchmarks in American streams that feed into the across studies due to non-standardized analytical test methods and Great Lakes. Monitoring data for these chemicals in sediments within changing detection limits. Despite these limitations, several common the Great Lakes in Canada or the US were not included in the Klecka chemicals were identified by Diamond et al. and our study, including et al. (2009) report. Therefore, the analysis of sediment contamination pesticides (chlorpyrifos, cis-permethrin, dieldrin, DDE), triclosan, NPE within the Great Lakes may be considered incomplete. and bis(2-ethylhexyl)phthalate. Blair et al. (2013) and Diamond et al. (2011) also used a hazard quo- There were no chemicals in common between our study and the tient approach to screen chemicals. Blair et al. (2013) developed HQs by screening work completed by Muir et al. (2009), as their focus was on utilizing maximum reported water concentrations compared to the five chemical groupings (brominated, chlorinated, fluoridated, nonhalo- predicted-no-effect concentration (developed by using ECOSAR and genated or silicone related) and identified chemicals only on the basis of applying an assessment factor of 1000). Not considering concentrations persistence, bioaccumulation potential and production volume; con- in wastewater effluent itself, only six PPCPs were measured in the centrations in the environment and toxicity data were not used. Also, aquatic environment of Lake Michigan downstream of the wastewater many of these chemicals were not included in the original study by

Table 4 Maximum reported concentrations of chemicals in sediment that exceeded a hazard quotient (HQ) of 1 based on No-observed-effect-concentration (NOEC) and/or the Lowest-observed effect-concentration (LOEC). All concentrations in μg/kg. NA indicates substance not analyzed in this medium or guideline not available.

Substance Concentration in US sediment Concentration in Canadian sediment Sediment guidelinea LOEC HQ NOEC HQ

US CAN US CAN

Pesticides Dieldrin 4.6 NA 2, 2.85/6.67 0.69 NA 2.3 NA p-p′DDE 6.8 NA 5, 1.42/6.75 1.02 NA 4.7 NA

Wastewater chemicals 2-Methyl-naphthalene 50 NA 20.2/201 0.25 NA 2.5 NA Anthracene 110 NA 220, 46.9/245 0.13 NA 2.3 NA Benzo(a)pyrene 390 NA 370, 31.9/782 0.27 NA 12 NA Fluoranthene 1400 NA 750, 111/2355 NA NA 13 NA Phenanthrene 720 NA 560, 41.9/545 0.13 NA 17 NA Pyrene 1100 NA 490, 53/875 0.27 NA 21 NA

NPE Nonylphenol TEQ 64050 110000 1400 NA NA 46 79

Bold HQ indicate a HQ N 1. a See Supplemental material for complete details; multiple guidelines may be presented. 244 R.N. Hull et al. / Journal of Great Lakes Research 41 (2015) 238–245 the IJC, as the focus of the IJC study was on chemicals monitored in the than standard toxicity endpoints, including screening techniques that Great Lakes Basin. may be applied to a wide range of substances; 3) reviewing updated The results of this screening process are influenced by many factors, monitoring data as there has been an increase in the number of publica- including the availability of ecotoxicity data, the understanding of the tions on concentrations of emerging chemicals in the last five years; persistence of each substance in aquatic ecosystems, and the extent of 4) further analytical method development for chemicals with effects monitoring data. These factors all introduce uncertainty into the results of concern below current detection levels; and 5) consideration of pro- of the risk-based screening, and could influence the conclusions. The duction/emissions data and mass balance/fate models to complement supplemental data identify those substances where ecotoxicity data monitoring efforts in the risk-based screening of chemicals in the were unavailable, when application factors were applied to the toxicity Great Lakes Basin. data to account for persistence, and where monitoring data were un- fl available. New knowledge in any of these areas could in uence the re- Acknowledgments sults and conclusions of this screening, as discussed briefly below. fi There was a signi cant ecotoxicity data gap for many substances, The authors would like to thank the following individuals who pro- which precluded calculation of hazard quotients. That is, of the 216 sub- vided input and/or advice during various phases of this project: Gary stances in water and 64 substances in sediment, HQs could not be calcu- Klecka, Derek Muir, Mark Servos, Sean Backus, Paul Helm, Fe de Leon, lated for 25 (12%) and 34 (53%), respectively. These substances were Tim Fletcher, Natalie Feisthauer and Scott Teed. The authors also largely pharmaceuticals and organic wastewater constituents. In addi- thank the two anonymous reviewers for their helpful comments. This tion, several substances had to be evaluated using acute toxicity data be- project has received funding support from the Government of Ontario cause of the lack of chronic data. Chronic toxicity data are needed for all ENVSDB-092011. Such support does not indicate endorsement by the of these substances because some of these substances are used in signif- Government of Ontario of the contents of this contribution. icant quantities and are not destroyed by all wastewater treatment plant technologies. Appendix A. Supplementary data For substances with limited ecotoxicity data, an AF of 20 or 100 was applied depending on persistence. New information about persistence Supplementary data to this article can be found online at http://dx. could change the application factor applied, resulting in a different haz- doi.org/10.1016/j.jglr.2014.11.013. ard quotient. This may be the case for four substances in Canadian and/ or US waters with HQs based on non-persistent application factors (atorvastatin, sulfamethoxazole, propham, and androsterone). Howev- References er, the half-lives of atorvastatin and sulfamethoxazole (6.6 days and 19 ANZECC (Australia and New Zealand Environment and Conservation Council), 2000. days, respectively) were based on a microcosm study (Lam et al., 2004), Australia and New Zealand guidelines for fresh and marine water quality. Chapter 3 and were well below the half-life of 8 weeks needed to be considered a aquatic ecosystems. Available at:, http://www.mincos.gov.au/__data/assets/pdf_file/ persistent compound. This issue does not apply to data-rich substances. 0019/316126/wqg-ch3.pdf (Accessed January 29, 2010). Blair, B.D., Crago, J.P., Hedman, C.J., Klaper, R.D., 2013. Pharmaceuticals and personal care In the case of lack of monitoring data, there were more than 100 products found in the Great Lakes above concentrations of environmental concern. chemicals monitored in American portions of the Great Lakes Basin Chemosphere 93 (9), 2116–2123. that were not monitored in Canada. 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