Hydroelectric Power and Indigenous Health in the Canadian North

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Citation Calder, Ryan Spencer Dyas. 2017. Hydroelectric Power and Indigenous Health in the Canadian North. Doctoral dissertation, Harvard T.H. Chan School of Public Health.

Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:42066834

Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Dissertation advisor: Dr. Elsie Sunderland Ryan S.D. Calder

Hydroelectric Power and Indigenous Health in the Canadian North

Abstract

Hydroelectric reservoir creation accelerates microbial conversion of inorganic mercury

(Hg) to bioaccumulative, neurotoxic methylmercury (MeHg). This thesis forecasts MeHg production in flooded reservoirs based on soil organic carbon content and probabilistically models the exposure impacts on local human populations by considering as a case study the Inuit settled downstream from hydroelectric development on the Churchill River, Labrador, Canada.

Expected riverine MeHg levels there are approximately ten times present-day average values.

Mean MeHg exposures are forecasted to double following flooding and over half of the women of childbearing age and young children in the most northern community are projected to exceed the U.S. EPA’s reference dose. Equal or greater impacts on aqueous MeHg are expected at 11 sites across Canada, suggesting the need for remediation measures prior to flooding or screening of potential sites for human health impacts. Coupled hydrodynamic and biogeochemical simulation of the downstream estuary suggests that estuarine MeHg concentrations increase by

1.2–2.2 times seasonal baseline average. High trophic-level species that contribute most to

MeHg exposures are also the basis of indigenous peoples’ traditional diets, contributing disproportionately to intake of polyunsaturated fatty acids and vitamins B12 and D. This analysis supplements traditional food consumption data for Labrador Inuit with publicly available food subsidy records and nutritional databases. While traditional foods account for < 10% of overall calories consumed, they are the main source of MeHg (70%), PCBs (>90%) and a disproportionate source of omega-3 fatty acids (36%) and vitamin D (39%). This analysis calculates the nutritional impacts of substituting higher-MeHg traditional foods with store-

ii bought foods and forecasts health impacts using dose-response functions. Substitution reduces but does not eliminate neurodevelopmental impacts. The relative risk (RR) of cardiovascular mortality is greater for substitution scenarios (population mean RR up to 1.5) than for a baseline diet with MeHg content up to eight times current levels. Substitution generally increase population-wide cancer risks (mean RR up to 1.02) relative to baseline and are associated with a decline in sufficiency of key nutrients (e.g., iron, phosphorus). Dietary advisories alone therefore cannot be used to mitigate risks associated with increased exposures to MeHg.

iii Contents Abstract ...... ii
Supplementary tables ...... vi
Figures...... vii
Supplementary figures ...... vii
Acknowledgments ...... viii
1
Introduction ...... 1
1.1
Methylmercury sources and toxicity ...... 2
1.2
Reservoir creation and methylmercury production, fate and transport ...... 3
1.3
Hydroelectric power expansion and indigenous populations ...... 4
1.4
Methylmercury exposures and food advisories ...... 5
1.5
The Lower Churchill Project and the Lake Melville Inuit ...... 5
1.6
Thesis structure ...... 7
2
Future impacts of hydroelectric power development on methylmercury exposures of Canadian indigenous communities ...... 9
Abstract ...... 9
2.1
Introduction ...... 10
2.2
Methods...... 12
2.3
Results and discussion ...... 17
2.3.1
Methylmercury increases in flooded reservoirs ...... 17
2.3.2
Impacts on downstream environment ...... 20
2.3.3
Methylmercury increases in biota ...... 21
2.3.4
Inuit exposures and risks ...... 23
2.3.5
Pan-Canada implications ...... 25
Acknowledgments ...... 26
Supporting information ...... 27
3
Attenuation of freshwater mercury inputs to an estuarine fjord due to lateral and vertical mixing ...... 49
Abstract ...... 49
3.1
Introduction ...... 50
3.2
Methods...... 51
3.2.1
Boundary conditions ...... 53
3.2.2
Solids budget ...... 56
3.2.3
Chemical transformations ...... 57
3.3
Results and discussion ...... 58
Supporting information ...... 63
4
Dietary advisories increase health risks for indigenous populations facing increasing methylmercury exposures ...... 70
Abstract ...... 70
4.1
Introduction ...... 71
4.2
Methods...... 73
4.2.1
Baseline food intake ...... 73
4.2.2
Nutrients in foods ...... 74
4.2.3
Health impacts model ...... 75
4.3
Results and discussion ...... 78
4.4
Discussion ...... 82

iv Supplemental materials ...... 84
5
Conclusions ...... 98
5.1
Key findings ...... 98
5.2
Future work ...... 99
6
References ...... 101

v Supplementary tables

Table S2-1: Methods used to calculate sediment-water exchange of MeHg ...... 27
Table S2-2: Distributions of uncertain parameters used to simulate MeHg enrichment in water and biota in flooded reservoirs ...... 28
Table S2-3: Characteristics of planned hydroelectric power projects across Canada ...... 29
Table S2-4: Measured MeHg concentrations in the Churchill River between 2012-2015 ...... 32
Table S2-5: Community-based monitoring of fish species from the Lake Melville region between 2014-2015 ...... 33
Table S2-6: MeHg concentrations in aquatic species harvested from the Lake Melville region . 34
Table S2-7: Bioaccumulation factors (BAFs) between aquatic MeHg concentrations and measured concentrations in biota and estimated lifetime habitat fractions ...... 37
Table S2-8: Hair mercury sampling from Inuit individuals in the communities downstream of the Muskrat Falls reservoir ...... 40
Table S2-9: Food frequency questionnaire (FFQ) data collected from Inuit individuals from the communities downstream from the Muskrat Falls reservoir ...... 41
Table S2-10: MeHg concentrations in aquatic foods harvested outside the Lake Melville region ...... 42
Table S2-11: Modeled MeHg concentrations in country foods after flooding of the Muskrat Falls reservoir ...... 44
Table S3-1: Model compartment dimensions ...... 63
Table S3-2: Monthly average values for freshwater discharges ...... 63
Table S3-3: Flows between pairs of model cells ...... 63
Table S3-4: River and ocean Hg and solids concentrations for baseline simulations ...... 64
Table S3-5: Atmospheric deposition and exchange of Hg species ...... 64
Table S3-6: Parameterization of solids concentrations in freshwater inputs ...... 65
Table S3-7: Solid particle characteristics ...... 65
Table S3-8: Parameterization of solids settling velocity ...... 65
Table S3-9: Burial rates determined from 210Pb core dating ...... 65
Table S3-10: Parameterization of physical properties ...... 66
Table S3-11: Parameterization of chemical transformations ...... 67
Table S3-12: Temperature and salinity in water column model cells ...... 69
Table S3-13: Total photosynthetically active radiation (PAR) at the surface of Earth and chlorophyll concentrations in the Lake Melville region ...... 69
Table S4-1: Nutritional and PCB data for locally caught seafood ...... 84
Table S4-2: Nutritional and PCB data for other local foods ...... 87
Table S4-3: Nutritional and PCB data for store-bought seafood ...... 89
Table S4-4: Nutritional and PCB data for food subsidized under Nutrition North ...... 91
Table S4-5: Foods used for junk food substitution scenario ...... 95
Table S4-6: Dose-response relationships for neurodevelopmental (IQ) endpoint ...... 95
Table S4-7: Dose-response relationships for cardiovascular endpoint ...... 96
Table S4-8: Dose-response relationships for cancer ...... 97

vi Figures

Figure 1-1: Three communities (Inuit population) around Lake Melville, downstream from active hydroelectric development on the Churchill River, Labrador, Canada ...... 6
Figure 2-1: Relationship between soil organic carbon content and MeHg concentrations ...... 18
Figure 2-2: Planned locations for hydroelectric power expansion in Canada and indigenous populations with reserves or communities within 100 km of development regions ...... 19
Figure 2-3: Probabilistically modeled scenarios for MeHg increases in downstream river and estuary of the Muskrat Falls hydroelectric facility ...... 20
Figure 2-4: Top 20 MeHg exposure sources for Inuit downstream of the Muskrat Falls hydroelectric reservoir ...... 22
Figure 2-5: Modeled changes in Inuit MeHg exposures following flooding of the Muskrat Falls reservoir ...... 24
Figure 3-1: Schematic of laterally averaged 2D model ...... 53
Figure 3-2: Evaluation of total suspended solids – discharge rating curve for the Churchill River ...... 56
Figure 3-3: Modeled Hg0 concentrations in Lake Melville at baseline ...... 58
Figure 3-4: Modeled HgII concentrations in Lake Melville at baseline ...... 59
Figure 3-5: Modeled MeHg concentrations in Lake Melville at baseline ...... 60
Figure 3-6: Modeled MeHg concentrations in Lake Melville showing the effect of a pulse from the Churchill River equal to an eight-fold enrichment relative to baseline inputs...... 61
Figure 4-1: Total calories per capita for different demographic groups ...... 78
Figure 4-2: Contribution of traditional foods to overall consumption of select nutrients, calories, MeHg and PCBs ...... 79
Figure 4-3: IQ decrement in children ...... 80
Figure 4-4: Relative risk (RR) of cardiovascular death for persons over 25 ...... 81
Figure 4-5: Relative risk (RR) of cancer death for persons over 25 ...... 82
Figure 4-6: Change in nutrient intake for four isocaloric local food replacement scenarios ...... 83

Supplementary figures

Figure S2-1: Schematic of model for mercury cycling the Lake Melville estuary ...... 31
Figure S2-2: Map of the Labrador Inuit Settlement Area, existing and future hydroelectric developments on the Churchill River, and locations of indigenous communities ...... 39
Figure S2-3: Number of planned hydroelectric power sites with forecasted reservoir MeHg concentrations above and below the Muskrat Falls reservoir and corresponding indigenous populations potentially impacted ...... 43
Figure S2-4: Measured concentrations of total Hg in hair samples from individuals in three Inuit communities downstream from the Muskrat Falls hydroelectric facility ...... 46
Figure S2-5: Fraction of population exceeding exposure thresholds in 2014 (measured) and post- flooding (modeled) by community ...... 47
Figure S2-6: Baseline (measured) and post-flooding (modeled) MeHg intake ...... 48

vii Acknowledgments

My advisor, Dr. Elsie Sunderland, has invested significant time and energy into my training. Through her frank feedback and advice, I have learned many conventions, norms and other unwritten rules about the scientific writing process that have surely saved me many years of trial and error. She entrusted me with a great deal of responsibility that has made me strive to perform at the very best of my abilities to produce impactful, rigorous work. Drs. John Evans,

Jim Shine and Marcia Testa have supported my research with their active participation on my research committee. I thank them for their constructive suggestions about my analysis and presentation of results and for their enthusiasm for the work as it has unfolded.

Our entire research group, Biogeochemistry of Global Contaminants, has been supportive of my work throughout. Dr. Amina Schartup has been my guide through the world of mercury chemistry served as principal sanity checker of my analysis. Her work characterizing uptake of methylmercury into subarctic food webs was a foundational component of my own work. She and Prentiss Balcom generated a large amount of soil and water mercury data that is used here.

The analysis also benefited from Dr. Miling Li’s work using stable mercury isotopes to infer habitat utilization patterns of aquatic species. Thanks to Amelia Valberg for measuring mercury content in the hundreds of hair samples we received from Labrador (and for keeping me informed of my own exposures) and to the Harvard College students I supervised, Angela Jiang and Harry Stone, who assisted with data analysis and interpretation. I owe the timely completion of my dissertation to my compulsion to outshine Clifton Dassuncao at every opportunity – a colleague who nevertheless has been a source of support throughout the odyssey of doctoral training.

viii The staff at the Harvard T.H. Chan School of Public Health and the Harvard John A.

Paulson School of Engineering & Applied Sciences have provided moral and practical support throughout my time as a doctoral student. Rose West and Barbara Zuckerman have tracked my progress and helped me ensure I meet all relevant milestones and stay in the registrar’s good graces. Thanks to Brenda Mathieu for help with the office miscellany: expense reports, duct tape, faxes and countless others.

The Nunatsiavut Government helped enormously with this research by ensuring that our dietary survey anticipated all relevant aspects of the local Inuit diet. In particular, I thank Marina

Biasutti-Brown and Tom Sheldon for their help recruiting study participants, managing research, assistants, anonymizing survey data and sending us samples.

I thank Brad deYoung and Zhaoshi Lu of the Memorial University of Newfoundland for sharing their hydrodynamic modeling tools and data for Lake Melville. This was essential for modeling mercury transport in the downstream environment.

Sincere thanks to the friends and family who have, in their own ways, supported my work. I owe my sense of self-worth and dignity to my mother, Holly McEwen, whom I credit for my will to achieve all outcomes to date. This dissertation adds to the Calder legacy of graduate studies in earth and environmental sciences, and so I thank (or blame) my aunts Lynn and Lorna for their influence in this direction. Finally, Daniel Sylvia’s usually positive attitude and low-worry outlook has helped me stay focused and happy over the past several years (even if I had to type the manuscript myself).

ix 1
Introduction

Hydroelectric capacity is expanding around the world as societies strive to meet growing energy demands with renewable resources. Ecosystem-scale artificial reservoirs are required to control electrical output of high-capacity hydroelectric facilities by regulating river discharge and hydraulic gradient. Flooding enhances the supply of labile organic carbon for microbes and results in geochemical conditions that facilitate their conversion of inorganic mercury to bioaccumulative methylmercury (MeHg). In Canada, many ecosystems impacted by hydroelectric development are occupied and utilized by indigenous people whose traditional diets include large quantities of locally caught fish, birds and mammals. Hydroelectric development has been linked to elevated MeHg exposures among indigenous populations, but the magnitude of the exposure impact has not previously been quantified. Utilities, governments and other stakeholders have so far lacked tools to forecast the magnitude and distribution of

MeHg in the aquatic environment following flooding and to characterize the related population exposure impacts and the health impacts of policy responses such as dietary advisories.

This thesis, divided into five chapters, quantifies human health and environmental impacts of MeHg production following hydroelectric development and the relative impacts of food consumption advisories issued in indigenous communities. This chapter reviews current science on Hg sources and cycling and MeHg toxicity and the link with reservoir creation. It describes the factors that are driving expansion of hydroelectric capacity in Canada and the risks posed to indigenous populations and introduces the case of the Lake Melville Inuit, around which this thesis is structured. This chapter closes with an overview of the research questions addressed by subsequent sections of the thesis. Chapter 2 presents a prospective risk assessment of hydroelectric development based on a multi-year geochemical and human exposures study.

1 Chapter 3 expands this analysis to quantify temporal and spatial variability of MeHg impacts in a downstream estuarine fjord. Chapter 4 quantifies the net health impacts of food consumption advisories in comparison to the risks posed by increased MeHg exposures from local foods.

1.1
Methylmercury sources and toxicity

Inorganic mercury (Hg) is released into the environment from both anthropogenic and natural sources and distributed globally through atmospheric deposition to terrestrial and aquatic ecosystems (Smith-Downey et al. 2010, Amos et al. 2013). Inorganic Hg is converted to the organic species methylated in aquatic environments by microorganisms, predominantly anaerobic sulfate- and iron-reducing bacteria, as a byproduct of metabolic function (Compeau and Bartha 1984). MeHg is the only form of Hg that biomagnifies through the food web, reaching concentrations in phytoplankton more than five orders of magnitude higher than in the ambient water column and increasing by a factor of two to three for every subsequent trophic level (Chen et al. 2008). High-trophic-level marine species can therefore have biotic MeHg burdens ten million times greater than concentrations in the ambient water, making consumption of fish and other marine life responsible for the vast majority of population-wide MeHg exposures (Clarkson 1993, Sunderland 2007). Indigenous populations, who consume large amounts of local seafood, are therefore particularly vulnerable to increases in MeHg content in local environments (Wheatley et al. 1997).

Elevated prenatal exposures to MeHg have been associated with irreversible damage to the developing nervous system ranging from attention and IQ deficits to mental retardation and cerebral palsy in proportion to the magnitude of prenatal exposures (NRC 2000). High MeHg exposures have also been associated with cardiovascular risk factors, notably oxidative stress, atherosclerosis and decreased heart rate variability, and outcomes, notably myocardial infarction

2 (Roman et al. 2011). While past research has produced inconsistent results, new studies support a causal relationship between elevated MeHg exposures and hypertension (Wells et al. 2017).

1.2
Reservoir creation and methylmercury production, fate and transport

The flooding associated with reservoir construction leads to decomposition of organic matter, increasing the supply of substrate for sulfate-reducing bacteria that methylate Hg present in soils. Schartup et al. (2015a) experimentally flooded soil cores and measured a 14-fold enrichment of MeHg in the overlying water column within five days. In flooded ecosystems, this causes fish MeHg burdens to increase, reaching a peak within five to ten years and returning to baseline over a period of roughly 30 years (Bodaly et al. 2007). The magnitude of the increase relative to baseline varies considerably, ranging from two- to eleven-fold across sites where measurements are available (Harris and Hutchinson 2008, Anderson 2011). Carbon content of flooded soils, size of flooded area and amplitude of reservoir drawdown have been positively associated with the magnitude of the post-flooding peak in upland boreal environments (Jackson

1991, Hall et al. 2005). This work integrates readily available site data (e.g., soil organic carbon content) into a mechanistic model that allows sites to be screened for relative impacts.

There has been comparatively little study on the fate and transport of MeHg downstream from reservoirs. MeHg complexed to terrestrial DOC is comparatively resistant to degradation and may therefore be transported long distances downstream from an impoundment (Jonsson et al. 2014). Limited available measurements suggest that reservoirs disproportionately export

MeHg-rich bottom waters, resulting in concentrations in the downstream environment higher than in the reservoir on average, and that MeHg impacts on fish persist at distances of at least

250–300 km downstream (Anderson 2011, Kasper et al. 2014). Schartup et al. (2015a) demonstrated that stratified subarctic coastal environments concentrate freshwater inputs of

3 MeHg into the surface layer that controls uptake by phytoplankton, suggesting that perturbations to riverine MeHg levels are likely to have measurable effects in downstream estuarine food webs. This work structures biogeochemical and mixing characteristics of a northern coastal environment into a predictive model to quantify the effect of perturbations in freshwater MeHg inputs to MeHg concentrations in the upper regions of a northern coastal environment.

1.3
Hydroelectric power expansion and indigenous populations

Canada is the world’s second largest producer of hydroelectric power, which accounts for

59% of its total electrical production (NRCAN 2016a). The United States export market is a driving force behind expansion of Canadian hydroelectric capacity, exports having increased six- fold since 1990 (Aarons and Vine 2015). Roughly 10% of electricity produced in Canada is exported, accounting for up to 16% of the electricity portfolio in New York and New England and 12% in Minnesota and North Dakota (US EIA 2015).

The vast majority of Canada’s current and projected future hydroelectric capacity is located in northern boreal ecosystems, far from urban centers and often in close proximity to indigenous populations. Across Canada, 131 facilities representing nearly 50% of current installed capacity are located within indigenous treaty or settled land claim areas (Lee et al.

2012), not counting facilities with downstream or indirect impacts on nearby indigenous communities. Inuit and other indigenous populations consume large amounts of fish, marine mammals and other local foods, leading to MeHg exposures higher than the general population and making them vulnerable to changes in the levels of MeHg in local foods. The Inuit of

Labrador and Quebec were found to have blood Hg levels five and 15 times greater than the general Canadian population respectively, with local aquatic foods being the dominant exposure source (Chan 2011). Hydroelectric development has therefore been implicated in MeHg

4 exposures among nearby indigenous communities at levels exceeding the threshold for acute

effects and well beyond reference doses for subchronic developmental risks (Clarkson et al.

1976, Dumont et al. 1998, Health Canada 2004). However, the extent to which hydroelectric

development has contributed to increased exposures has so far been unclear due to changing

diets, a lack of environmental monitoring and incomplete baseline exposure data (Schoen and

Robinson 2005).

1.4
Methylmercury exposures and food advisories

Dietary advice restricting consumption of local foods is the predominant policy tool for

limiting exposures of indigenous people to elevated levels of contaminants such as MeHg in

local foods (Furgal et al. 2005, Passos and Mergler 2008). However, traditional indigenous diets

are disproportionate sources of protein, iron (Fe), zinc (Zn), polyunsaturated fatty acids (PUFAs)

and vitamins A, B2, B3, B6, B12 and D, meaning that MeHg exposures must be controlled

within the overall context of maintaining nutritional sufficiency among indigenous people

(Wheatley 1995, Nakano et al. 2005, Kuhnlein and Receveur 2007, Beaumier and Ford 2010,

Gagné et al. 2012, Sheehy et al. 2015). It therefore remains unclear whether and under what

circumstances food consumption advisories are health-protective. This thesis quantifies net

health impacts of replacing local foods with lower-MeHg alternatives in comparison to the risks

of increased MeHg exposures.

1.5
The Lower Churchill Project and the Lake Melville Inuit

The Churchill River is the largest in Atlantic Canada, running 856 km from the Labrador

interior and draining an area of 79,800 km2 (Marsh 2006). It drains into the Labrador Sea via

Lake Melville, a large (3,000 km2) estuarine fjord that extends 180 km into the Canadian taiga

5 shield. Roughly 2,500 Labrador Inuit are settled in three communities around Lake Melville

(Statistics Canada 2013).

The Lower Churchill Project aims to develop 3,000 MW of generating potential at

Muskrat Falls and Gull Island roughly 45 and 100 km upstream from Lake Melville, respectively

(Nalcor Energy 2009b). The Muskrat Falls hydroelectric facility is nearly complete and will saturate 41 km2 of the existing watershed presently covered mainly by spruce trees and podzolic soils (Stobbe and Nowosad 1957, Woodrow 1995). The date for completion of the Gull Island facility that would flood an additional 85 km2 has not yet been determined (Nalcor Energy

2009b). Figure 1-1 shows the Lower Churchill Project vis-à-vis the Lake Melville Inuit communities.

The developer of the Lower

Churchill Project has claimed that

“the influence of the Project does not extend beyond the mouth of the Churchill River and, consequently, there is no reasonable possibility that the

Project would have an adverse environmental effect on the Figure 1-1: Three communities (Inuit population) around Lake Melville, downstream from active hydroelectric development on the Labrador Inuit Settlement Area” Churchill River, Labrador, Canada

(Nalcor Energy 2009b) and

“[does] not predict that that creation of the Muskrat Falls reservoir will heighten risk to people in

Lake Melville” (Fitzpatrick 2016). There is currently limited scientific basis to evaluate the

6 plausibility of such statements, resulting in a pattern where governments and developers respond post hoc to health and environmental impacts of hydroelectric development, often through litigation (Notzke 1994, Palmer and Tehan 2006).

1.6
Thesis structure

Chapter 2 of this thesis (published in Environmental Science & Technology) describes the link between organic carbon and MeHg concentrations in flooded soils of reservoirs, characterizes baseline exposures of the Lake Melville Inuit and forecasts the range and distribution of exposure impacts from upstream reservoir creation. This work includes a baseline

MeHg exposure assessment and dietary survey enrolling 1,145 Inuit over three assessment periods, analysis of 656 hair samples and the development of a probabilistic model to forecast

MeHg production, transport, uptake through the food web and impacts on human exposure.

Chapter 3 quantifies how increases in freshwater MeHg inputs from anticipated hydroelectric development and exacerbated by climate change will be transported through an estuarine environment and describes the spatial attenuation and magnitude of the response in comparison to interseasonal variability. This work introduces a mechanistic, spatially resolved model of Hg cycling in Lake Melville, explicitly modeling physical transport (e.g., sediment inputs, freshwater inputs, hydraulic circulation) and chemical reactions as a function of physical parameters (e.g., temperature, light penetration, ice cover) to describe the magnitude of impacts of hydroelectric development on estuarine food webs.

Chapter 4 calculates the health benefits among Labrador Inuit of avoiding MeHg exposure increases, for instance from hydroelectric development and climate change, and compares these risks to those posed by reduced intake of nutrients from local foods. A population-wide nutritional model is assembled from government databases and the dietary survey presented in

7 Chapter 2 to calculate the significance of local foods in overall exposure to MeHg and polychlorinated biphenyls (PCBs). Dose-response models from the literature are used to calculate the distribution of cardiovascular, cancer and neurodevelopmental risks for dietary scenarios based on 1) increased exposures to MeHg from local foods vs. 2) substitution of local foods with store-bought alternatives in order to limit MeHg exposure increases.

8 2
Future impacts of hydroelectric power development on methylmercury exposures of

Canadian indigenous communities*

Abstract

Developing Canadian hydroelectric resources is a key component of North American plans for meeting future energy demands. Microbial production of the bioaccumulative neurotoxin methylmercury (MeHg) is stimulated in newly flooded soils by degradation of labile organic carbon and associated changes in geochemical conditions. We find all 22 Canadian hydroelectric facilities being considered for near-term development are located within 100 km of indigenous communities. For a facility in Labrador, Canada (Muskrat Falls) with planned completion in 2017, we probabilistically modeled peak MeHg enrichment relative to measured baseline conditions in the river to be impounded, downstream estuary, locally harvested fish, birds and seals, and three Inuit communities. Results show a projected 10-fold increase in riverine MeHg levels and a 2.6-fold increase in estuarine surface waters. MeHg concentrations in locally caught species increase 1.3 to 10-fold depending on time spent foraging in different environments. Mean Inuit MeHg exposure is forecasted to double following flooding and over half of the women of childbearing age and young children in the most northern community are projected to exceed the U.S. EPA’s reference dose. Equal or greater aqueous MeHg concentrations relative to Muskrat Falls are forecasted for 11 sites across Canada, suggesting the need for remediation measures prior to flooding.

* Calder, R. S. D., A. T. Schartup, M. Li, A. P. Valberg, P. H. Balcom and E. M. Sunderland (2016). "Future impacts of hydroelectric power development on methylmercury exposures of Canadian indigenous communities." Environ Sci Technol 50 (23): 13115-22.

9 2.1
Introduction

Hydroelectric power accounts for 16.2% of global electricity generation and plans to greatly expand capacity are underway as countries seek to develop carbon neutral energy sources

(International Energy Agency (IEA) 2010, Barros et al. 2011). In Canada, 59% of the electricity supply is from hydroelectric power and expansion is a key component of meeting international agreements on carbon dioxide (CO2) reductions (Natural Resources Canada (NRCAN) 2015).

Enhanced releases of CO2, methane (CH4), and methylmercury (MeHg) that are sustained for one to three decades following flooding are widely acknowledged (Rudd et al. 1993, St. Louis et al. 2004, Barros et al. 2011). Impacts of CO2 and CH4 releases are global but MeHg is a neurotoxin that bioaccumulates in food webs and adversely affects individuals who rely on local ecosystems for food (Rosenberg et al. 1997). Previous studies show reservoir characteristics can be used to project MeHg levels in water (Hall et al. 2005, Rolfhus et al. 2015) and fish (Johnston et al. 1991) following flooding but a prospective analysis of risks to human health from hydroelectric power expansion is lacking.

Traditional diets of indigenous people in the Arctic and Subarctic are rich in fish, birds, seal, and whale that provide many nutritional and cultural benefits (Receveur et al. 1997,

Kuhnlein and Receveur 2007) but also biomagnify environmental contaminants (Donaldson et al.

2010, Stow et al. 2011). Negative impacts of MeHg exposure on neurodevelopment (IQ) are well-established and widely used as the basis for regulatory thresholds (National Research

Council (NRC) 2000). In northern indigenous populations, increased MeHg exposure has been significantly associated with cardiovascular risk factors for adults such as increased resting heart rate and heart rate variability (Valera et al. 2011, Valera et al. 2013), as well as increased incidence of attention deficit/hyperactivity disorder (ADHD) among children with high prenatal

10 exposures (Boucher et al. 2012). Acute MeHg toxicity is associated with widespread neurological abnormalities, paresthesia and ataxia (Clarkson et al. 1976). In Canadian indigenous communities previously impacted by hydroelectric flooding (Methylmercury Study Group 1980,

Dumont et al. 1998), measured MeHg exposures have surpassed the lowest observed effects levels for acute MeHg toxicity (Clarkson et al. 1976).

Inorganic mercury (Hg) is a natural component of soils and has been enriched globally by anthropogenic sources (Smith-Downey et al. 2010, Amos et al. 2013). MeHg is the only Hg species that biomagnifies in aquatic food webs (Lavoie et al. 2013). Previously, we simulated flooding using soil cores from a planned hydroelectric reservoir in Labrador, Canada and found a

14-fold MeHg enrichment in overlying water within three days that was increasing exponentially at the end of the five-day experimental period (Schartup et al. 2015a). These results suggest enhanced MeHg availability to fish, birds and seals occurs almost immediately after reservoir flooding (Schartup et al. 2015a). Similarly, whole ecosystem experiments in Northern Ontario show MeHg production peaks within the first 1–3 years following impoundment (St. Louis et al.

2004, Hall et al. 2005). Elevated MeHg levels in previously flooded reservoirs have gradually declined back to baseline over several decades (Anderson 2011).

Here we quantify expected increases in MeHg exposures for three Inuit communities in

Labrador, Canada surrounding a hydroelectric facility to be flooded in 2016–17 (Muskrat Falls).

Our analysis considers: (a) potential MeHg enrichment in the flooded reservoir, (b) MeHg accumulation in the downstream environment (an estuary known as Lake Melville), (c) MeHg biomagnification in country foods, and (d) shifts in MeHg exposures for Inuit individuals. We use information from the Muskrat Falls site to forecast MeHg concentrations for planned

11 hydroelectric reservoir expansion areas across Canada and discuss potential impacts on human

health and mitigation strategies.

2.2
Methods

Data from nine sites across three ecosystems were used to derive a relationship between

soil organic carbon and peak methylmercury (MeHg) content of flooded soils (Mucci et al. 1995,

Hall et al. 2005, Rolfhus et al. 2015, Meng et al. 2016). We excluded data from sites inundated

more than three decades prior to MeHg measurements because MeHg production diminishes

over time and smaller increases are observed in periodically flooded environments (Rosenberg et

al. 1997, Schetagne and Verdon 1999, Schartup et al. 2015a). For data from the Experimental

Lakes Area (ELA) of Canada (boreal inceptisol), we used the highest MeHg concentrations

following flooding for each site (Hall et al. 2005). Soil organic matter was converted to organic

carbon using a conversion factor of 0.58, where needed (Qian and Follett 2012).

Methods used to calculate peak MeHg fluxes from flooded soils into overlying reservoir

waters for the Muskrat Falls, Labrador site are shown in Table S2-1. Satellite data were used to derive the organic carbon content (%) of the upper 30 cm of soil in each planned reservoir (Périé and Ouimet 2008, European Soil Data Centre (ESDAC) 2015). Flux of MeHg across the sediment-water interface was simulated probabilistically using the distributions described in

Table S2-2, including: 1) the 90th percentile solids diameter, 2) the sediment-water partition

coefficient (Kd, L kg-1) for MeHg, and 3) the MeHg fraction photochemically degraded during downstream transport.

We repeated this analysis for hydroelectric power development sites currently in the planning phase or under construction across Canada. All planned reservoirs are within 100 km of indigenous population reserves, settlements or communities, which is the approximate distance

12 of treaty negotiated Inuit hunting and fishing territory from the Muskrat Falls facility. For all

facilities, we modeled peak water column MeHg concentrations expected following flooding based on site-specific data for water discharge, flooded area, reservoir soil organic carbon, and the Muskrat Falls diffusive boundary layer estimate (Table S2-3).

For the Muskrat Falls site, downstream impacts of peak reservoir MeHg concentrations on the Lake Melville estuary were quantified using the model developed by Schartup et al.

(2015a) (Figure S2-1). The estuary is permanently stratified and our previous work shows biological productivity is concentrated in the low-salinity surface layer (upper 10 m), which is the focus of this analysis. The estuarine model is based on extensive field measurements collected between 2012-2014 (Table S2-4). It is externally forced with probabilistically modeled freshwater MeHg inputs from the impounded river (Churchill River) from this work, and previously characterized atmospheric deposition, and tidal inputs (Schartup et al. 2015a). Depth- specific tidal inflows and outflows to the Lake Melville estuary are based on buoy measurements and detailed hydrodynamic modeling (Lu et al. 2014). The annual mean flux of seawater from the subsurface to the surface layer (2.83×108 m3 d-1) was calculated from the hydraulic budget

for each vertical layer. We updated redox reactions for inorganic Hg species following the

parameterization by Soerensen et al. (2016).

Baseline MeHg concentrations in locally harvested foods from the Lake Melville region

were derived with the assistance of a community-led harvesting program (Table S2-5). Local

foods were selected for MeHg analysis in 2014-15 after consulting the Inuit Tribal Council. Fish

MeHg concentrations often exhibit a relationship with length (Anderson 2011). For this study,

we separated juvenile and adult size ranges and retained those most frequently consumed by

Inuit community members. All fish and shellfish samples were analyzed for total Hg/MeHg and

13 stables isotopes of carbon, nitrogen and Hg (Table S2-6) (Li et al. 2016a). Locally consumed seal

(Phoca hispida hispida) muscle, liver and kidney were obtained from Inuit hunters in the spring of 2015 and analyzed for total Hg and MeHg at Environment Canada in Burlington, Ontario (see

SI for details). Data for other birds and wildlife were obtained from Environment Canada and literature values, where applicable.

Site-specific bioaccumulation factors (BAFs) for 65 locally harvested foods including fish, birds, eggs and seal (Table S2-5) were used to link modeled MeHg increases in the

Churchill River and Lake Melville estuary following flooding to changes in locally harvested food concentrations (Table S2-7). This analysis assumes steady state biological MeHg concentrations with peak MeHg fluxes from the reservoir. Data from previously flooded environments indicates up to ten years are required for biota to reach maximum MeHg levels

(Verdon et al. 1991, Schetagne and Verdon 1999).

We calculated BAFs from measured MeHg concentrations in each locally consumed species and annual mean concentrations measured in the river, estuary and outer marine regions

(i.e., BAF = MeHg biota/water MeHg). Exposure to aqueous MeHg for each species was calculated from the fraction of their lifespan spent in each environment (i.e., the sum product of aqueous MeHg concentration multiplied by the lifespan in each region). We estimated the predominant habitat/foraging regions of each species using δ13C, δ15N, Δ199Hg, and 202Hg as tracers (Li et al. 2016a) and literature information on their habitat preferences. We accounted for uncertainty in the time spent in each foraging region using uniform distributions that envelope the likely ranges for each species (Table S2-2) and probabilistically simulating MeHg increases.

At previously flooded hydroelectric reservoirs, some typically herbivorous fish have been observed to eat fish stunned or killed by passage through hydroelectric turbines, effectively

14 raising their trophic level and magnifying MeHg concentrations (Brouard et al. 1994). We do not include such potential effects in our enrichment calculations.

We collected hair samples from the occipital region of the scalp as a biomarker for MeHg exposures in three Inuit communities (Happy Valley–Goose Bay, North West River, Rigolet) downstream from the Muskrat Falls development area with the assistance of 26 Inuit research assistants (Figure S2-2). Participants were recruited by the Nunatsiavut Government using membership rolls, which is limited to persons with demonstrated Inuit identity/ancestry. Samples were collected in both the June/July 2014 and September/October 2014 to account for any seasonal variability in MeHg intake and ensure overlap with the peak harvest season for seals in the spring. 656 hair samples were analyzed across these two periods, representing 571 unique

Inuit individuals and 19% of the total Inuit population in the region (Table S2-8). Total Hg was analyzed in the two-centimeter proximal end of hair using thermal decomposition, amalgamation, and atomic absorption spectrophotometry (EPA method 7473) with a Nippon

MA-3000 or Milestone DMA-80 at Harvard University. Most of the Hg in hair is present as

MeHg (>90%) and potential demethylation in the hair follicle means that total Hg is the best indicator of internal MeHg exposure (Berglund et al. 2005). At least one method blank and one certified hair reference materials (GBW-07601 and ERM-DB001) were tested every 10 samples and all recoveries were within certified ranges. Precision, calculated by replicate analysis of the duplicate hair samples (RSD) was better than 8.6%.

Food frequency questionnaire (FFQ) data using overlapping 24-hour, 1-month and 3- month recall periods were collected in March/April 2014 concurrently with hair sampling in

June/July and September/October 2014. The final FFQ survey population included 38% of Inuit individuals in the region (Table S2-9) and 1145 unique individuals. The survey included

15 information on height, weight, sex, age. Focus group sessions were conducted with Community

Research Advisory Committees to ensure comprehensiveness of country foods listed, local names and preparation methods. Interviews were conducted in-person with the use of visual aids for identification of fish meal sizes and species. Research protocols, consent procedures and the survey instrument were reviewed and approved by the Harvard Office of Human Research

Administration, the Newfoundland and Labrador Health Research Ethics Authority, and the

Nunatsiavut Government Research Advisory Committee prior to recruitment.

Three-month FFQ recall data from September 2014 (highest-enrollment sampling period) and the one-compartment pharmacokinetic model developed by the U.S. Environmental

Protection Agency (WHO 1990, WHO 2002) were used to probabilistically model baseline

MeHg exposures in the three Inuit communities prior to flooding. We chose the 3-month survey period because it most closely matches the exposure period recorded by hair samples. Variability in pharmacokinetic parameters for MeHg in the human body was probabilistically simulated following the methods outlined in Li et al. (2016b). We scaled individual fish servings to match the total meal number reported over the recall period because recall data on species-specific fish consumption tends to overestimate total consumption (Lincoln et al. 2011, Dong et al. 2015, Li et al. 2016b). Lognormal or gamma distributions were developed from measured MeHg concentrations in country foods (Table S2-6) and used in probabilistic exposure simulations

(Carrington and Bolger 2002). MeHg variability in store-bought foods (Table S2-10) was simulated following Carrington and Bolger (2002).

Modeled MeHg exposures were scaled by the ratio between measured and modeled hair

Hg to ensure agreement with actual exposure levels. For individuals who did not provide hair samples, we adjusted modeled exposures by the median of these correction factors (0.92).

16 Gender and age from 2011 census data were used to match the demographic distribution of the

Inuit population in each of the three communities (Statistics Canada 2012, Statistics Canada

2013). Shifts in exposure resulting from flooding of the Muskrat Falls reservoir were propagated

from probabilistically simulated increases in MeHg concentrations in country foods in each

individual’s diet.

2.3
Results and discussion

2.3.1
Methylmercury increases in flooded reservoirs

We find a strong linear relationship across multiple ecosystems between MeHg

concentrations in soils inundated within approximately three decades and their organic carbon

content (Figure 2-1). This relationship is consistent with site-specific results from prior work

(Rosenberg et al. 1997, Hall et al. 2005, Rolfhus et al. 2015). Labile organic carbon stimulates

the activity of methylating microbes by providing substrate for respiration (St. Louis et al. 2004).

Oxygen consumed during organic carbon degradation creates optimal geochemical conditions for

anaerobic microbes (mainly sulfate reducers in flooded soils) (Rosenberg et al. 1997, St. Louis et

al. 2004), thereby increasing MeHg production.

Our analysis indicates indigenous lands are located within 100 km of all potential

hydroelectric sites across Canada planned for near-term development (Figure 2-2). Modeled

sediment-to-water MeHg fluxes across reservoirs range from 11–977 ng m-2 day-1. When

normalized to soil organic carbon content, modeled fluxes (19–52 ng m-2 day-1) are consistent with those calculated from peak water column MeHg concentrations for a whole-ecosystem flooding experiment in the Experimental Lakes Area (ELA), Canada (24–115 ng m-2 day-1). For

17 Figure 2-1: Relationship between soil organic carbon content and MeHg concentrations (ng g-1 dry weight) of flooded soils. Each data point represents an individual sampling location. Hatched lines indicate standard errors around the mean. Soil cores are from the Wujiangu reservoir, China (subtropical terra rossa)(Meng et al. 2016), the Experimental Lakes Area (ELA, boreal inceptisol) in Northern Ontario, Canada (Hall et al. 2005, Rolfhus et al. 2015), and La Grande-2 (Robert Bourassa) Reservoir in Quebec, Canada (Mucci et al. 1995). ELA data indicate the site-wide peak in MeHg (1-2 years post-flood) except for the filled circle, which represents 9-years post flooding.

the Muskrat Falls reservoir, the expected mean flux (664 ng m-2 day-1) is within the range reported for other natural systems (2–830 ng m-2 day-1) (Gill et al. 1999).

Across Canada, MeHg concentrations in hydroelectric reservoirs following flooding range from negligible for generating stations and run of the river facilities to greater than 0.5 ng

L-1. Forecasted MeHg concentrations in reservoir water for the Muskrat Falls site (0.19 ng L-1) are moderate compared to other facilities across Canada due to its relatively smaller planned flooded area (41 km2). Highest forecasted concentrations are for a planned facility in Quebec

with a relatively large flooded area (144 km2) (Table S2-3). Ten of the planned sites across

Canada are expected to have post-flooding MeHg concentrations lower than Muskrat Falls, and

eleven are expected to be higher (Figure S2-3). The four sites with highest projected MeHg

18 Figure 2-2: Planned locations for hydroelectric power expansion in Canada and indigenous populations with reserves or communities within 100 km of development regions (Table S2-3). The inset map shows the Muskrat Falls facility in Labrador and the three Inuit communities studied here. Reservoir MeHg concentrations are modeled for each site using the relationship shown in Figure 2-1 and site specific data on soil organic carbon content (upper 30 cm) of flooded reservoirs derived from satellite data, and the sediment-water flux parametrization shown in Table S2-1.

concentrations (>0.35 ng L-1) have relatively large flooded areas (85–144 km2). Cumulatively, sites with projected MeHg concentrations higher than Muskrat Falls account for greater than

50% of proposed new energy generation (Figure S2-3).

After flooding of the Muskrat Falls reservoir, the annual flow-weighted mean MeHg concentration in the Churchill River is projected to increase approximately 10-fold from a measured baseline value of 17.5±11.5 pg L-1 (Table S2-4) to an expected mean of 180 pg L-1.

The 5th and 95th percentile scenarios represent 5.5 to 17-fold enrichment (90–300 pg L-1) relative

19 to baseline concentrations (Figure 2-3). These changes represent substantial increases in MeHg concentrations in the freshwater environment that will be magnified in local food webs.

2.3.2
Impacts on downstream environment

Few studies have considered the downstream impacts of enhanced MeHg concentrations in hydroelectric reservoirs.

Kasper et al. (2014) noted elevated fish

MeHg concentrations up to 250 km downstream of the impoundment. However, the Muskrat Falls environmental impact assessment posited there would be no impact on a large fjord (Lake Melville) approximately 40 Figure 2-3: Probabilistically modeled scenarios for MeHg increases in downstream river and km downstream that contains treaty-negotiated estuary of the Muskrat Falls hydroelectric facility. Photochemical MeHg demethylation is hunting and fishing territory for Labrador Inuit assumed to occur continuously down the reach of the Churchill River into Lake Melville thus the river concentration reflects the average of due to potential dilution throughout the water reservoir concentrations and downstream inputs to Lake Melville. column (Nalcor Energy 2009a). By contrast, our previous research indicates the estuary is permanently stratified and freshwater inputs from the

Churchill River are concentrated in the upper 10 m of the water column with limited mixing.

This concentrates riverine inputs within a relatively small volume of the estuary (the photic zone) that is most important for biological productivity, facilitating uptake at the base of estuarine food webs (Schartup et al. 2015a).

20 Modeling conducted here indicates expected mean MeHg concentrations in Lake

Melville surface waters will increase 2.6-fold following flooding of the Muskrat Falls reservoir

from 17 pg L-1 to a peak level of 44 pg L-1 (Figure 2-3). The 5th percentile scenario suggests a lower bound increase of 1.6-fold (28 pg L-1) and the 95th percentile scenario represents a 4-fold increase (69 pg L-1). These results suggest substantial increases in MeHg concentrations in the downstream estuary will result from flooding of the Muskrat Falls reservoir, contrasting the results of the initial Environmental Impact Assessment (Nalcor Energy 2009a).

2.3.3
Methylmercury increases in biota

Impacts of enhanced aqueous MeHg concentrations in the river and estuary surrounding

the Muskrat Falls site depend on the extent of bioaccumulation in local food webs. Site-specific

BAFs for fish, birds, eggs and seal range from 106 to 108 (Table S2-7). Highest baseline MeHg

concentrations are found in loon eggs, tern eggs, seal liver, and porpoise (literature value). Only

porpoise presently exceeds the 0.5 μg MeHg g-1 Canadian retail limit (Health Canada 2016) for

most fish (Figure 2-4, Table S2-6).

Modeled MeHg concentrations in the top 20 local foods contributing to Inuit MeHg

exposure after flooding range from 1.3 to 10 times measured baseline concentrations (Figure

2-4). This is consistent with two- to nine-fold increases in fish MeHg concentrations previously

reported for other Canadian reservoirs (Verdon et al. 1991, Harris and Hutchinson 2008).

Variable impacts of flooding across species downstream of Muskrat Falls mainly reflects

differences in foraging activity (i.e., time spent in the river, estuary and outer marine regions,

Table S2-7). For example, brook trout are highly enriched in MeHg following flooding due to

the large fraction of their lifespan spent in the freshwater environment (Table S2-11).

21 Figure 2-4: Top 20 MeHg exposure sources for Inuit downstream of the Muskrat Falls hydroelectric reservoir before (measured in 2014) and after flooding (modeled peak concentration) planned for 2016-17 (Table S1). Commercial species unaffected by local conditions are denoted by ‘*’. Panel (A) shows MeHg concentrations in country foods relative to Health Canada retail limits for fish other than tuna (0.5 μg g-1) (Health Canada 2007). Error bars indicate ±1 standard deviation for baseline and post-flooding (simulated) mean. Panel (B) shows relative changes in per-capita exposures based on the expected mean exposures from probabilistic simulations. Error bars indicate 5th–95th percentiles simulated for each species. Pie charts show population-wide MeHg exposure from country foods before (measured) and after (modeled) flooding, where white space corresponds to MeHg exposure from commercial foods. A complete list of MeHg concentrations in aquatic foods are available in TablesTable S2-6 and Table S2-11.

After flooding, expected mean MeHg concentrations in lake trout, seal, tern eggs, brook trout and char liver are all projected to be at or above the Canadian retail limit for MeHg (Figure

2-4A). Black duck, Atlantic cod and rock cod also exceed this level under the 95th percentile environmental increase scenario. After flooding, almost 90% of population-wide MeHg exposure is projected to be from locally caught foods (Figure 2-4B). Increasing MeHg burdens of traditional country foods consumed by Inuit will elevate their MeHg exposures and may also

22 adversely affect local wildlife that are also sensitive to high levels of MeHg exposure (Depew et al. 2012).

2.3.4
Inuit exposures and risks

Measured hair Hg concentrations in 474 individuals from the three Inuit communities downstream of Muskrat Falls show over 90% of baseline MeHg exposures are below regulatory guidelines for MeHg in the U.S. and Canada (Figure S2-4). Highest exposures are found in the most northern community of Rigolet, where 24% of individuals presently exceed the U.S.

Environmental Protection Agency’s (U.S. EPA) Reference Dose for MeHg (RfD, 0.1 μg kg-1 body weight day-1), and 3% are above Health Canada’s (HC) provisional tolerable daily intake

(pTDI, 0.20-0.47 μg kg-1 body weight day-1). Mean exposure levels in Rigolet in 2014 were similar to those reported in the 2007-2008 Inuit Health Survey for other communities along the

Labrador coastline (Chan 2011). All three Inuit communities downstream of Muskrat Falls have higher MeHg exposure levels than the general Canadian population due to greater consumption of aquatic foods (Lye et al. 2013).

Following flooding of the Muskrat Falls reservoir, median MeHg exposures are expected to at least double for the majority of the downstream Inuit population (Figure 2-5A). Projected increases are greatest in the community of Rigolet, where the median exposure increase is projected to be almost 200% relative to baseline values. Disproportionate increases in MeHg exposures occur for individuals who are already the most highly exposed and consume the greatest quantities of country foods. For example, mean MeHg intake increases from 0.15 to

0.50 µg kg-1 day-1 for individuals at the 90th percentile of post-flooding exposures and this demographic accounts for nearly 60% of the total additional MeHg intake (µg day-1) following flooding.

23 Average MeHg exposure levels

for women of childbearing age (16-49)

and young children (age <12) in the

community of Rigolet exceed the U.S.

EPA’s RfD (Figure 2-5B) and are within

15% of Health Canada’s provisional

tolerable daily intake (pTDI) level

(Health Canada 2004). This demographic

is most sensitive to the

neurodevelopmental impacts of MeHg

exposure (Mahaffey et al. 2011). Beyond

the 75th percentile of this population, all

Figure 2-5: Modeled changes in Inuit MeHg exposures individuals are above both regulatory following flooding of the Muskrat Falls reservoir. Panel (A) shows exposure increases relative to measured baseline intake in 2014. Error bars indicate the 5th-95th guidelines for MeHg (Figure 2-5B). percentile scenarios for MeHg increases in the flooded reservoir and biota based on probabilistic simulations. Grandjean and Budtz-Jorgensen (2007) Panel (B) shows baseline and post-flooding MeHg intake in women of childbearing age (16-49) and children (age found imprecision in the Faroe Islands <12) in the community of Rigolet. HVGB = Happy Valley – Goose Bay, NWR = North West River. a Health b biomonitoring data used to formulate the Canada (HC) provisional tolerable daily intake (pTDI); U.S. EPA reference dose (RfD) for MeHg. U.S. EPA’s RfD led to an overestimate of

50% and proposed that a revised RfD of 0.05 μg kg-1 day-1 (0.58 μg Hg g-1 hair) would be more appropriate. In Rigolet, 77% of individuals exceed this level (Figure S2-5). Exposures are lower in the other two communities due to more limited consumption of country foods (Figure S2-6).

Across the three communities, 41% of the total population and 28% of women of childbearing age (Figure S2-5) exceed the level proposed by Grandjean and Budtz-Jorgensen (2007).

24 Regulatory thresholds such as a RfD imply the existence of a safe level of chronic exposure. However, when formulating the RfD, the U.S. EPA itself acknowledged that “no evidence of a threshold arose for methylmercury-related neurotoxicity” (United States

Environmental Protection Agency (US EPA) 2002). Recent data from prospective birth cohorts support this conclusion (58-60). For adults, the Health Canada pTDI is the least conservative across international regulatory agencies (0.47 μg kg-1 day-1). Therefore, all consumers of local foods are likely to face decreased net health benefits as a result of increased MeHg in local foods.

2.3.5
Pan-Canada implications

Modeled reservoir MeHg levels at eleven of the proposed 21 hydroelectric sites across

Canada are comparable or greater than the Muskrat Falls reservoir (Figure 2-2). The communities of Happy Valley-Goose Bay and Northwest River consume fewer country foods than typical of most indigenous populations in Canada (Chan 2011), suggesting greater exposures of other indigenous communities with moderate and high projected reservoir MeHg levels.

Country foods are known to confer a wide-range of nutritional and social health benefits to indigenous communities and nutritious alternative food choices are limited in the Canadian

North (Receveur et al. 1997, Kuhnlein and Receveur 2007). Past studies suggest reducing or avoiding consumption of country foods may also result in substantial adverse impacts in individual health (Wheatley and Paradis 1996, Furgal et al. 2005). Reducing environmental

MeHg concentrations associated with hydroelectric flooding should thus be prioritized as a mitigation measure. For example, soil organic carbon content could be used as a screening criterion for site selection or reservoirs could be designed to minimize flooded area. Mailman et

25 al. (2006) review a number of other interventions, such as the removal of organic carbon from the planned reservoir regions prior to flooding. Without such mitigation strategies, our analysis shows hydroelectric development will have a disproportionate impact on indigenous communities, affecting long-term neurocognitive function in children and with potential population level impacts on endocrine and cardiovascular health (Tan et al. 2009, Rice et al.

2010, Roman et al. 2011, Karagas et al. 2012).

Acknowledgments

This work was supported by the U.S. National Science Foundation (OCE 1260464 and

1130549), the Canadian Northern Contaminants Program, ArcticNet Inc., Tides Canada Oak

Arctic Marine Fund Program, and the Nunatsiavut Government (NG). We thank research assistants employed by the NG for collection of dietary survey data, and Marina Biasutti-Brown,

Tom Sheldon, Rodd Laing, and Trevor Bell for assistance with sample collection and human health survey work. We thank Nil Basu (McGill U.), Jane Kirk and Derek Muir (Env. Canada) for assistance with seal sample shipping and analysis and Neil Burgess (Env. Canada) for information on egg and bird Hg data and foraging behavior.

26 Supporting information

Table S2-1.1: Methods used to calculate sediment-water exchange of MeHg Flux of MeHg into the water column based on the mass transfer &' ) ' J (ng m-2 s-1) * formulation of Steinberger and # Hondzo (1999) 2x10-10 (macromolecular organic D (m2 s-1) Molecular diffusivity for MeHg complexes) (Sunderland et al. 2010) Rate of change of MeHg ) dCw/dt concentration in the water column  &' ' -1 -1 $ )( '"  (ng L s ) determined by flux from flooded soil  #  and outflow from river

Steady state (dCw/dt = 0) &'   $ C (ng L-1) concentrations of MeHg in reservoir ( w  (  '" water $ #

-1 Concentration of MeHg in interstitial Derived from empirical relationship Cpw (ng L ) waters in Figure 1-1 and Kd -1 Cwb (ng L ) Pre-impoundment riverine MeHg 0.0175 (Schartup et al. 2015a) log K Sediment-water partition coefficient d 2.93±0.16 (Schartup et al. 2015a) [L kg-1] based on measurements 2 Af (m ) Land area flooded Table S2-2 Q (m3 s-1) River flow Table S2-2

Thickness of the diffusive sublayer    !  ! δ (m) controlled by turbulent action based  %

 %  % d  on Peterson (1999) ν (m2 s-1) Kinematic viscosity of water 1.3x10-6 ρ (kg m-3) Density of water 103 C (unitless) Coefficient 0.000463 n (unitless) Coefficient 3.38 Post-impoundment shear stress at the   τ (N m-2) sediment-water interface based on       Wilcock (1996)  Average flow velocity based on U (m s-1) 0.1 (AMEC 2013) Muskrat Falls facility κ (unitless) von Karman constant 0.41

27 Table S2-1.2: Methods used to calculate sediment-water exchange of MeHg (cont’d) 90th percentile solids diameter based on the predominant d90 (mm) soil type in the Muskrat Falls reservoir area (SLCWG 0.2 Chan and Govindaraju 2004, 2011) a (unitless) Constant 2.85 h (m) Height of the channel based on Muskrat Falls facility 16.8 e (unitless) Base of the natural logarithm 2.718

Table S2-2: Distributions of uncertain parameters used to simulate MeHg enrichment in water and biota in flooded reservoirs. Table S2-1 contains the complete parameterization for sediment- to-water fluxes of MeHg Parameter Distribution th a 90 percentile solids diameter in reservoir (d90, mm) Triangular: min = 0.005, max = 1, mode = 0.2 -1 b Sediment-water partition coefficient (log Kd, L kg ) Normal: µ = 2.96, σ = 2.54 Degradation of MeHg during downstream transport to Uniform: min = 0.3, estuary (fraction lost)c max = 0.5 Fraction of excess riverine MeHg demethylatable in Uniform: min = 0, max = 1 Lake Melville d Estuarine fraction of lifespan for key marine speciese Uniform: min = 0, max = 0.5 Estuarine fraction of lifespan for key bird speciesf Uniform: min = 0.5, max = 1 Riverine fraction of lifespan for sealsg Uniform: min = 0, max = 0.25 a Mode based on the dominant soil type (podzol) in the Muskrat Falls region (Soil Landscapes of Canada Working Group (SLCWG) 2011); minimum and maximum values represent ranges across a variety of soil types (Chan and Govindaraju 2004). b Probability distribution for site-wide mean derived from measurements (Wilcock 1996). c Maximum degradation is based on upper limit suggested by Schartup et al. (2015a); minimum is based on degradation rate measured by Jonsson et al. (2014). d MeHg complexed to terrestrial organic ligands may be resistant to degradation (Jonsson et al. 2014). e Fraction of MeHg obtained from the estuarine environment during foraging and/or spawning is uncertain for Atlantic cod, Atlantic salmon, and rock cod. f Seabirds (eider, tern, guillemot and gull) are found in both the marine and estuarine environments. Some birds consumed by Inuit may spend their entire life history foraging in the estuary (maximum) or in outer marine areas (minimum). g Inuit hunters report seasonal seal foraging in the freshwater environment.

28 Table S2-3.1: Characteristics of planned hydroelectric power projects across Canada Post- Flood Indigenous Hydroelectric Project (River, Flow flood Capacity area populations within Province/Territory) (m3 s-1) MeHg (MW) (km2) 100 kma (ng L-1) False Canyon (Liard, YT)b 151 160 0.24 58 Liard Middle Canyon (Liard, YT)b 160 90 0.21 38 Liard, Dease Detour Canyon (Pelly, YT)b 257 135 0.22 65 Selkirk, Little Salmon Granite Canyon (Pelly, YT)b 362 170 0.21 254 Hoole Canyon (Pelly, YT)b 97 25 0.13 13 Ross River Slate Rapids (Pelly, YT)b 53 136 0.35 42 Nacho Nyak Dun, Fraser Falls (Stewart, YT)b 359 570 0.29 300 Selkirk Two Mile Canyon (Stewart, 166 105 0.18 53 Nacho Nyak Dun YT)b La Martre (La Martre, NT)c 31 0 • 13 Whati Lutselk'e (Snowdrift, NT)c 42 0 • 1 Lutsel K'e Dene West Moberly, Saulteau, Doig River, Site C (Peace, BC)d 1251 53 0.04 1100 Halfway River Blueberry River Duncan's, Horse Lake, Amisk (Peace, AB)e 1600 8 • 330 Peavine Metis Black Lake, Fond du Tazi Twé (Fond du Lac, SK)f 304 0 • 50 Lac • Negligible increase from baseline. a First Nations unless otherwise specified. Locations on Figure 2-2 are centroids of traditional lands (Metis Settlements General Council 2016, NRCAN 2016b). First Nations populations are those living on their respective reserves and unceded lands (AANDC 2016b). b Comparative feasibility assessment ongoing (Midgard Consulting Inc 2015). c Under review (Government of the Northwest Territories 2011). d Construction began in 2015 and will continue through 2024 (Klohn Crippen Berger et al. 2011, BC Hydro 2015). e Permitting process ongoing. Peavine settlement is 169 km from project but traditional lands review is ongoing (AHP Development Corporation 2015). f Permitting process ongoing (Canadian Environmental Assessment Agency 2015)

29 Table S2-3.2: Characteristics of planned hydroelectric power projects across Canada (cont’d) Flood Post-flood Indigenous Hydroelectric Project (River, Flow Capacity area MeHg populations Province/Territory) (m3 s-1) (MW) (km2) (ng L-1) within 100 kma Fox Lake, War Lake, York Keeyask (Nelson, MB)b 3100 45 0.06 695 Factory, Tataskweyak, Bunibonibee Conawapa (Nelson, MB)c 3100 5 0.04 500 Fox Lake New Post Creek (Abitibi, ON)d 42 2 0.04 25 Taykwa Tagamou Romaine 1 (La Romaine, QC)e 291 12 0.35 270 Quebec Innu Romaine 2 (La Romaine, QC)e 291 85 0.38 640 (Ekuanitshit, Romaine 3 (La Romaine, QC)e 291 37 0.20 395 Nutashkuan) Romaine 4 (La Romaine, QC)e 291 144 0.55 245 Muskrat Falls (Churchill, NL)f 1829 41 0.19 824 Labrador Inuit, Gull Island (Churchill, NL)f 1829 85 0.37 2250 Innu and Metis a First Nations unless otherwise specified. Locations on Figure 2-2 are centroids of traditional lands (Metis Settlements General Council 2016, NRCAN 2016b). First Nations populations are those living on their respective reserves and unceded lands (AANDC 2016b). b Construction began in 2014 and will continue through 2021 (Manitoba Hydro-Electric Board et al. 2009, Keeyask Hydropower LP 2015). c Planning activities suspended pending results of resources planning review (Manitoba Hydro 2014). d Construction began in 2015 and will continue through 2018 (Northern Ontario Business Staff 2015). e Construction began in 2009 and will continue through 2017 (Romaine 3) – 2020 (Romaine 4). Construction complete on Romaine 1 and 2. Nutashkuan (132 km from Romaine 1) and Ekuanitshit and are the indigenous communities found to use the land impacted by the development (MDDEP 2009). f Construction of Muskrat Falls began in 2013 and will continue through 2017 (Ernst & Young LLP 2016). A construction timetable for Gull Island has not been released. Labrador Metis (NunatuKavut) is not plotted on Figure 2-2 because it does not have a recognized land claim.

30

Figure S2-1: Schematic of model for mercury cycling the Lake Melville estuary, Labrador, adapted from Schartup et al. (2015a) for this analysis. Hydrodynamic data used to calculate mixing are from Lu et al. (2014).

31 Table S2-4: Measured MeHg concentrations in the Churchill River between 2012-2015. Analytical procedures are described in Schartup et al. (2015a). Weighted Month - Churchill River MeHg - Weighted Season 3 -1 -1 n mean (pg L -1 Year discharge (m day ) (pg L ) SD (pg L ) 1) Winter 26.53 1.66 Dec 1.56E+08 27.49a – Jan-15 1.56E+08 27.49 1 Feb-15 1.57E+08 24.62 1

Spring 26.36 12.76 Mar-15 1.47E+08 23.21 1 Apr-14 1.35E+08 11.83 1 May-14 2.31E+08 36.91 1

Summer 4.99 1.15 Jun-13/14 2.03E+08 5.91 2 Jul-14 1.45E+08 5.01 1 Aug-14 1.36E+08 3.61 1

Fall 11.22 – Sep-12/14 1.32E+08 11.20 2

Oct 1.45E+08 11.20a – Nov 1.53E+08 11.20a –

Annual 17.94 11.46 a No data were available for this month so MeHg concentrations are based on a month with similar water discharges.

32 Table S2-5: Community-based monitoring of fish species from the Lake Melville region between 2014-2015. Analytical methods for total Hg and MeHg analysis are provided in Li et al. (2016a) Sample Location Date n Sampled By September Inuit residents of North West Smelt Churchill River 7 2014 River and Rigolet Inuit residents of North West Brook trout Lake Melville 20 River and Rigolet June-July Lake trout Churchill River 13 Field research coordinator 2014 Churchill River and July-Sept Stickleback 30 Field research coordinator Lake Melville 2014 Lake Melville Salmon July 2014 3 Rigolet fishers (Rigolet area) Lake Melville Long nose July-Aug Inuit fishers, North West River (between 20 sucker 2014 and Rigolet NWR/Rigolet Lake Melville July-Aug Inuit fishers, North West River Whitefish (between 20 2014 and Rigolet NWR/Rigolet Lake Melville July-Aug Inuit fishers, North West River Flatfish (between 20 2014 and Rigolet NWR/Rigolet July-Aug Pike Churchill River 2014 13 Inuit fishers (HVGB) August 2015 20 miles East of Arctic char August 2015 10 Inuit fisher (Rigolet) Rigolet September Atlantic cod St. Lewis Bay 5 Labrador fisher 2014 Rigolet and NWR Mussels June 2015 10 Inuit hunter areas Misc. river Churchill River August 2015 10 Inuit fishers fish above Muskrat Falls

33 Table S2-6.1: MeHg concentrations in aquatic species harvested from the Lake Melville region. Fish and bird concentrations are for fillets/muscle unless noted MeHg (μg g-1) Species n Data Source Mean ± SD Seal (Phoca hispida) <1 year (80%) a Muscle 0.11 ± 0.09 34 This study Liver 0.13 ± 0.16 50 This study Kidney 0.24 ± 0.12 14 This studyb Seal 1-4 years (10%) a Muscle 0.21 ± 0.17 18 This study, Brown et al. (2016) Liver 0.28 ± 0.29 n/a Mean of ages < 1 & >4 yr Kidney 0.31 ± 0.15 n/a Seal > 4 years (10%) a Muscle 0.39 ± 0.51 68 This study, Brown et al. (2016) Liver 0.43 ± 0.37 3 This study Kidney 0.38 ± 0.17 3 This studyb Atlantic Salmon (Salmo salar) Fillet 0.07 ± 0.02 12 Li et al. (2016a) Roe 0.01 ± 0.004 n/a This studyc Liver 0.09 ± 0.02 n/a This studyd Atlantic cod (Gadus morhua) 0.19 ± 0.06 5 Li et al. (2016a) Arctic char (Salvelinus alpinus) Fillet 0.06 ± 0.04 4 Li et al. (2016a) Roe 0.01 n/a This studyc Liver 0.08 n/a This studyd Sculpin (Myoxocephalus scorpius) Fillet 0.23 ± 0.09 10 Li et al. (2016a) Liver 0.11 ± 0.11 10 This studye Brook trout (Salvelinus fontinalis) Fillet 0.10 ± 0.03 48 Li et al. (2016a) Liver 0.10 ± 0.03 18 This studyf Roe 0.05 ± 0.02 17 This study Ouananiche (Salmo salar m. 0.15 ± 0.11 18 Jacques Whitford Environment sebago) Ltd (2006) Lake trout (Salvelinus namaycush) 0.99 ± 0.46 28 Jacques Whitford Environment Ltd (2006) a Fraction of total seal harvest in each age class estimated by Inuit seal hunters in 2015. b Fraction of total Hg as methylmercury in kidney estimated as 26% from Northern Quebec ringed seals; moisture content estimated as 29% (Lemire et al. 2015). c Estimated from salmon fillet:roe ratio (Zhang et al. 2001). d Estimated from salmon fillet:liver ratio (Zhang et al. 2001). e Estimated as 50% MeHg as a fraction of total Hg from literature values (Harley et al. 2015). f Estimated 62% MeHg as a fraction of total Hg based on salmon liver (Zhang et al. 2001). d Estimated from salmon fillet:liver ratio (Zhang et al. 2001). e Based on 44% MeHg as a fraction of total Hg as for molluscs (Claisse et al. 2001). f Converted from dry weight using moisture content from gull samples.

34 Table S2-6.2: MeHg concentrations in aquatic species harvested from the Lake Melville region (cont’d). Fish and bird concentrations are for fillets/muscle unless noted. MeHg (μg g-1) Species n Data Source Mean ± SD Flatfish (Pleuronectoide sp.) 0.07 ± 0.04 20 Li et al. (2016a) Capelin (Mallotus villosus) Fillet 0.02 ± 0.002 6 Li et al. (2016a) Roe 0.002a Rainbow smelt (Osmerus mordax) 0.11 ± 0.05 18 Li et al. (2016a) Mussels (Mytilus edulis) 0.004 ± 0.0005 6 Li et al. (2016a) Porpoise (Phocoena phocoena) Muscle 20 Das et al. (2004) (Atl. Norway) Liver 0.60 ± 0.06b 21 Das et al. (2004) (Atl. Norway) 1.22 ± 0.87b,c Rock cod (Gadus ogac) Fillet 0.19 ± 0.06 Assumed equal to cod Liver 0.23d Green sea urchin 0.04 8 Noël et al. (2011) (Strongylocentrotus droebachiensis) Periwinkle (Littorina littorea) 0.04 40 Noël et al. (2011) Clams (Arctica islandica) 0.01 ± 0.01 15 US FDA (2014) Scallops (Amusium laurenti) 0.01e 200 Karimi et al. (2012) Gull (Rissa tridactyla) Muscle 0.23 ± 0.27 7 Lavoie et al. (2010b) Eggs 0.06 ± 0.01 20 Lavoie et al. (2010a) Tern (Sterna paradisaea) Muscle 0.23 ± 0.25f 12 Clayden et al. (2015) Eggs 0.42 ± 0.25f 17 Clayden et al. (2015) Guillemot (Cepphus grylle) Muscle 0.27 ± 0.07 3 Braune et al. (1999) (Nfld.) Eggs 0.21 ± 0.01 20 Lavoie et al. (2010a) Black duck (Anas rubripes) Muscle 0.11 ± 0.08 12 Braune et al. (1999) (NL) Eggs 0.03 ± 0.003 Schwarzbach and Adelsbach (2003) – mallards, CA. Eider (Somateria mollissima) Muscle 0.11 ± 0.03 8 Braune et al. (1999) (NL) Loon (Gavia immer) Eggs 0.90 ± 1.88 29 Evers et al. (2005) (Maritimes) Sandpiper (Calidris pusilla) 0.07 ± 0.01 19 Burger et al. (2014) a Estimated from salmon fillet:roe ratio (Zhang et al. 2001). b Converted from dry weight using moisture content from seal. c Based on 29% MeHg as a fraction of total Hg (Joiris et al. 2001). d Estimated from salmon fillet:liver ratio (Zhang et al. 2001). e Based on 44% MeHg as a fraction of total Hg as for molluscs (Claisse et al. 2001). f Converted from dry weight using moisture content from gull samples.

35 Supporting information on seal mercury analyses

MeHg concentrations in seal liver and muscle were measured at the Environment Canada laboratory in Burlington, Ontario. Samples were freeze dried and homogenized, then digested with 5N HNO3 solution at 55 °C overnight. Digested samples were buffered with acetate and ethylated using sodium tetraethylborate (NaTEB). Ethylated MeHg was purged onto a Tenax packed column, separated by gas chromatography, and detected by cold vapor atomic fluorescence spectroscopy using a Brooks Rand MERX automated MeHg analyzer following established methods (Hintelmann and Nguyen 2005, Lehnherr et al. 2012). The average recovery for the DOLT 5 Certified Reference Material (CRM) included in each digestion cycle was

96.8±5.6% (SD; n = 8). Precision, estimated by replicate analysis of duplicate samples was on average 6% (n = 6).

36 Table S2-7.1: Bioaccumulation factors (BAFs) between aquatic MeHg concentrations and measured concentrations in biota and estimated lifetime habitat fractions for each species in the freshwater environment (river), Lake Melville (estuary) and outer marine regions (marine) Species log BAF River Estuary Marine References Arctic char 0.5 0.5 0 Dunbar (1965), Muscle 6.6 Bradbury et al. Liver 6.6 (1999)a,b Roe 5.6 Atlantic cod 7.7 0 0–0.50 0–0.50 Li et al. (2016a)c,d Atlantic salmon 0 0–0.50 0–0.50 Li et al. (2016a)c,d Muscle 7.3 Liver 7.4 Roe 6.4 Brook trout 0.5 0.5 0 Backus (1957), Muscle 6.8 Pilgrim et al. Liver 6.7 (2012)a,e Roe 6.5 Capelin 0 0.25 0.75 Li et al. (2016a)c Muscle 6.0 Roe 5.1 Clams 5.8 0 1 0 Harvest locationf Black duck 0.5 0.5 0 Longcore et al. Muscle 6.8 (2000)g Eggs 6.2 Eider 0 0.5–1 0.5–1 BirdLife International Muscle 6.9 (2015)d,g Flatfish 6.6 0 1 0 Armstrong and Starr (1994)a Green sea urchin 6.4 0 1 0 Harvest locationf Guillemot 0 0.5–1 0.5–1 Butler et al. (2002)d Muscle 7.4 Eggs 7.2 Gull 0 0.5–1 0.5–1 Baird et al. (1994)g Muscle 7.3 Eggs 6.7 a Stable Hg isotopes suggest mixed habitat (Li et al. 2016a). b Time spent in open ocean is short (several weeks per year) (Dunbar 1965, Bradbury et al. 1999). c Habitat is predominantly offshore and fish migrate into the estuary to feed and/or spawn. d Habitats modeled probabilistically (see Table S2-2). Reported BAF is expected value. e Habitat is predominantly freshwater. Radiotelemetry monitoring in the Churchill River revealed short (90% < 10 km) seasonal displacements (Nalcor Energy 2009a). f Sessile and low-motility species are based on predominant fishing location. g Increased MeHg following flooding is scaled by time spent in region (0.5) for migratory species.

37 Table S2-7.2: Bioaccumulation factors (BAFs) between aquatic MeHg concentrations and measured concentrations in biota and estimated lifetime habitat fractions for each species in the freshwater environment (river), Lake Melville (estuary) and outer marine regions (marine) (cont’d). Species log BAF River Estuary Marine Reference Lake trout 6.8 1 0 0 Black et al. (1986) Loon 0.5 0.5 0 McIntyre et al. (1997)a Eggs 7.7 Mussels 5.3 0 1 0 Harvest locationb Ouananiche 6.9 1 0 0 Bradbury et al. (1999) Periwinkles 6.4 0 1 0 Harvest locationb Porpoise 0 0.25 0.75 Read and Westgate Muscle 8.1 (1997)c Liver 8.4 Rainbow smelt 6.8 0 1 0 FishBase (d Rock cod 0 0–0.50 0–0.50 Ferguson et al. Muscle 7.7 (2010)e,f Liver 7.5 Sandpiper 6.6 0.5 0.5 0 Gratto-Trevor et al. (1992)a Scallops 6.1 0 1 0 Harvest locationb Sculpin 0 0.25 0.75 Li et al. (submitted)c Muscle 7.7 Liver 7.2 Seal 0–0.25 0.5–0.75 0.25 Sikumiut Muscle 7.1 Environmental Liver 7.1 Management Ltd. Kidney 7.3 (2007)f,g Tern 0 0.5–1 0.5–1 Hatch et al. (2002)a,f Muscle 7.3 Eggs 7.5 a Increased MeHg following flooding is scaled by time spent in region (0.5) for migratory species. b Sessile and low-motility species are based on predominant fishing location. c Habitat is predominantly offshore and fish migrate into the estuary to feed and/or spawn. Habitat fraction is modeled probabilistically (see Table S2-2). Reported BAF is expected mean. d Hg isotope signature in adults indicates mixed habitat (Li et al. submitted). e Same δ13C and δ15N stable isotope signature as Atlantic cod. f Habitat fraction modeled probabilistically (see Table S2-2). Reported BAF is expected mean. g Pups are found in sea ice in estuarine environment.

38

Figure S2-2: Map of the Labrador Inuit Settlement Area, existing and future hydroelectric developments on the Churchill River, and locations of indigenous communities. Source: Durkalec et al. (2016). Reprinted with permission from Nunatsiavut Government.

39 Table S2-8: Hair mercury sampling from Inuit individuals in the communities downstream of the Muskrat Falls reservoir in June/July (spring/summer) and September/October (fall) 2014 Unique Spring/ Total Individuals Demographic Group Fall (n) Summer (n) (n) (Percent Inuit Populationa) All individuals 157 499b 656b 571b Non-Inuit household membersc 21 84 105 94 Inuit individuals 136 412 548 474 (19%) Communities Happy Valley–Goose Bayd 96 265 361 325 (13%) North West River 37 133 170 139 (37%) Rigolet 24 101 125 107 (40%) Demographic Groupe Women of childbearing age (16-49)f 52 149 201 173 Children ≤ 12 years 15 29 44 40 Women of childbearing age (16-49 & 12 36 48 39 children ≤ 12 in Rigolet All male >12 years 56 174 230 200 All female >49 years 27 140 167 147 a Hair was collected for some individuals during both sampling periods. Total Inuit population is based on the 2011 Census and National Household Survey (Statistics Canada 2012, Statistics Canada 2013). b Including three individuals who did not report Inuit status c Hair samples were collected from non-Inuit individuals if they shared a residence with registered Inuit beneficiary identified by the Nunatsiavut Government. d Includes the nearby community of Mud Lake (n=22). e Combined data for all three communities. f As defined by the U.S. National Health and Nutrition Examination Survey (McDowell et al. 2004).

40 Table S2-9: Food frequency questionnaire (FFQ) data collected from Inuit individuals from the communities downstream from the Muskrat Falls reservoir in March/April (winter), June/July (spring/summer) and September/October (fall) 2014. Dietary survey data collection overlapped with hair sampling (Table S2-8) in the spring and fall. Unique Winter Spring/ Fall Total Individuals Demographic Group (n) Summer (n) (n) (n) (Percent Inuit Populationa) All individuals 231 294 1054b 1579b 1145b Non-Inuit householdc 34 49 167 250 188 members Inuit individuals 197 245 882 1324 952 (38%) Communities Happy Valley-Goose Bayd 170 217 667 1054 745 (31%) North West River 30 34 158 222 167 (43%) Rigolet 31 43 229 303 233 (87%) Demographic Groupe Women of childbearing age 59 77 278 414 306 (16-49) Children ≤12 years 55 59 166 280 179 Women of childbearing age (16-49 & children ≤ 12 in 15 19 100 134 101 Rigolet All male >12 years 74 108 387 569 406 All female > 49 yearsf 28 37 191 256 200 a Data from some individuals are for multiple survey periods. Total Inuit population is based on the 2011 Census and National Household Survey (Statistics Canada 2012, Statistics Canada 2013). b Total includes three individuals who did not report Inuit status. c Non-Inuit individuals who share a household with a registered Inuit beneficiary identified by the Nunatsiavut Government were included in the survey. d Includes the nearby community of Mud Lake (n=22). e Combined data for all three communities. f As defined by the U.S. National Health and Nutrition Examination Survey (McDowell et al. 2004).

41 Table S2-10: MeHg concentrations in aquatic foods harvested outside the Lake Melville region. Commercial market categories rather than species names are listed for store-bought seafood. MeHg (μg g-1) Species n Data Source Mean ± SD Minke whale (Balaenoptera 0.075 + 0.021 4 Riget et al. (2007) acutorostrata)a Polar bear (Ursus maritimus) 0.07 ± 0.05 23 Woshner et al. (2001) Cod 0.11 ± 0.07 115 US FDA (2014) Clams 0.01 ± 0.002 15 US FDA (2014) Scallops 0.02 ± 0.01b 200 Karimi et al. (2012) Mussels 0.02 ± 0.01b 134 Karimi et al. (2012) Catfish 0.04 ± 0.02b 103 Karimi et al. (2012) Crab 0.06 ± 0.03b 151 Karimi et al. (2012) Haddock 0.06 ± 0.03b 78 Karimi et al. (2012) Herring 0.02 ± 0.01b 115 Karimi et al. (2012) Lobster 0.04 ± 0.02b 149 Karimi et al. (2012) Oysters (canned) 0.003 ± 0.003b,c 361 Karimi et al. (2012) Pollock (fish sticks) 0.02 ± 0.01b 131 Karimi et al. (2012) Brook trout 0.09 ± 0.04b,d 44 Karimi et al. (2012) Rainbow trout 0.03 ± 0.02b 71 Karimi et al. (2012) Sardines 0.03 ± 0.02b 246 Karimi et al. (2012) Shrimp 0.03 ± 0.02b 361 Karimi et al. (2012) Skate 0.12 ± 0.05b 13 Karimi et al. (2012) Sole 0.10 ± 0.04b 51 Karimi et al. (2012) Tilapia 0.02 ± 0.01b 114 Karimi et al. (2012) d Fresh Tuna 0.44 ± 0.25 295 US FDA (2014) Canned tuna 0.16 ± 0.13e 1002 US FDA (2014) Fresh salmon 0.04 ± 0.02b 504 Karimi et al. (2012) Canned salmon 0.04 ± 0.04f 61 Karimi et al. (2012)e a Converted from dry weight using moisture content from seal muscle. b Standard deviation of distribution modeled following Carrington and Bolger (2002). c Based on all market oysters. d Based on all unspecified freshwater. e Yellowfin, bigeye and albacore weighted according to relative landings reported by Sunderland (2007). f Relative consumption of light and white canned tuna calculated from Sunderland (2007).

42

Figure S2-3: Number of planned hydroelectric power sites with forecasted reservoir MeHg concentrations above and below the Muskrat Falls reservoir and corresponding indigenous populations potentially impacted (circles). * Inuit population downstream from Muskrat Falls is included in the >0.35 bin because it is also potentially impacted by planned Gull Island facility.

43 Table S2-11.1: Modeled MeHg concentrations in country foods after flooding of the Muskrat Falls reservoir Post-flooding distribution of values Species Expected mean 75th percentile 90th percentile 95th percentile Arctic char Muscle 0.41 0.51 0.78 1.0 Liver 0.49 0.58 0.70 0.80 Roe 0.05 0.06 0.07 0.08 Atlantic cod 0.41 0.50 0.65 0.76 Atlantic salmon Muscle 0.16 0.20 0.25 0.29 Liver 0.20 0.23 0.28 0.31 Roe 0.020 0.023 0.027 0.031 Black duck Muscle 0.44 0.55 0.83 1.1 Eggs 0.11 0.13 0.16 0.18 Brook trout Muscle 0.68 0.84 1.1 1.3 Liver 0.62 0.76 1.0 1.2 Roe 0.34 0.42 0.58 0.70 Capelin Muscle 0.04 0.05 0.06 0.07 Roe 0.01 0.01 0.01 0.01 Clams 0.03 0.03 0.04 0.04 Eider Muscle 0.20 0.24 0.30 0.34 Flatfish 0.17 0.22 0.32 0.40 Green sea urchin 0.10 0.12 0.14 0.16 Guillemot Muscle 0.68 0.82 1.0 1.2 Eggs 0.53 0.61 0.74 0.84 Gull Muscle 0.41 0.46 0.54 0.59 Eggs 0.15 0.18 0.21 0.24 Lake trout 1.0 1.3 1.8 2.2 Loon Eggs 5.6 5.7 13.3 20.9 Minke whale 0.07 0.09 0.10 0.11 Mussels 0.01 0.01 0.01 0.01 Ouananiche 1.5 1.9 3.0 3.9 Periwinkles 0.10 0.12 0.14 0.16

44 Table S2-11.2: Modeled MeHg concentrations in country foods after flooding of the Muskrat Falls reservoir (cont’d) Post-flooding distribution of values Species Expected mean 75th percentile 90th percentile 95th percentile Porpoise Muscle 1.4 1.8 2.7 3.5 Liver 2.8 3.6 5.2 6.8 Rock cod Muscle 0.42 0.50 0.65 0.77 Liver 0.50 0.58 0.70 0.79 Sandpiper 0.26 0.30 0.37 0.42 Scallops 0.06 0.07 0.08 0.09 Sculpin Muscle 0.54 0.66 0.88 1.0 Liver 0.20 0.24 0.42 0.58 Seala Muscle 0.66 0.82 1.3 1.6 Liver 0.67 0.84 1.3 1.7 Kidney 1.0 1.2 1.6 1.9 Smelt 0.29 0.36 0.48 0.58 Tern 0.41 0.50 0.86 1.2 a Weighted by age range (Table S2-6).

45

Figure S2-4: Measured concentrations of total Hg in hair samples from individuals in three Inuit communities downstream from the Muskrat Falls hydroelectric facility (HVGB = Happy Valley – Goose Bay; NWR = North West River) and among demographic groups (all communities together). Canadian median (6–79 years old) (Lye et al. 2013) and Nunatsiavut mean (Chan 2011) are estimated using a mean blood-to-hair partition coefficient of 250 L g-1 (World Health Organization (WHO) 1990). Most of the Hg in hair is present as MeHg (>90%) and potential demethylation in the hair follicle means that total Hg is the best indicator of internal MeHg exposure (Berglund et al. 2005). At least one method blank and one certified hair reference materials (GBW-07601 and ERM-DB001) were tested every 10 samples and all recoveries were within certified ranges. Precision, calculated by replicate analysis of the duplicate hair samples (RSD) was better than 8.6%.

46 Figure S2-5: Fraction of population exceeding exposure thresholds in 2014 (measured) and post- flooding (modeled) by community (HVGB = Happy Valley – Goose Bay, NWR = North West River) and age/gender. anel (A) shows the population that exceeds Health Canada provisional tolerable daily intake (pTDI) guidelines for MeHg of 0.20 µg kg-1 day-1 for women of childbearing age and children 12 years and under and 0.47 µg kg-1 day-1 for others (Health Canada 2007). Panel (B) shows the population that exceeds the U.S. Environmental Protection Agency’s Reference Dose (RfD) (United States Environmental Protection Agency (US EPA) 2000), and panel (C) indicates the proportion of the population exceeding the RfD calculated based on more recent epidemiological research on neurotoxicity (Grandjean and Budtz- Jorgensen 2007, Bellanger et al. 2013).

47

Figure S2-6: Baseline (measured) and post-flooding (modeled) MeHg intake relative to the Health Canada (HC) provisional tolerable daily intake (pTDI) and the U.S. EPA reference dose (RfD) for the communities of (A) Rigolet, the largest per-capita consumer of country foods, (B) North West River and (C) Happy Valley – Goose Bay

48 3
Attenuation of freshwater mercury inputs to an estuarine fjord due to lateral and vertical

mixing

Abstract

Flooding of hydroelectric reservoirs enhances the supply of labile organic carbon for microbes and results in geochemical conditions that facilitate their conversion of inorganic mercury to bioaccumulative methylmercury (MeHg). Northern estuarine environments are strongly stratified, which concentrates freshwater inputs of MeHg in the surface layer and facilitates water column MeHg production. This is exacerbated by increased freshwater inputs caused by hydroelectric development and climate change. Our prior work shows this causes enhanced MeHg uptake into the base of the estuarine food web. Understanding the influence of mixing dynamics on the MeHg concentrations in the surface waters of northern coastal environments is essential for predicting the response of biological MeHg levels to perturbations in freshwater inputs. Here we develop a mechanistic mercury cycling model coupled to a hydrodynamic simulation to forecast the impact of enhanced freshwater MeHg inputs on concentrations in Lake Melville, a northern estuarine fjord. This work simulates an eight-fold increase in MeHg inputs from Churchill River, corresponding to the peak increase expected from hydroelectric development. Results show that estuarine MeHg concentrations increase by 1.2–

2.2 times seasonal baseline average, with lowest increases in the bottom mixed water near the interface with the ocean roughly 170 km downstream from the river outfall and the highest increases in the inland upper reaches of the estuary within 13 km of the river outfall. Major loss processes from the surface layer include particle scavenging and vertical mixing, which reduces the overall impact of the freshwater pulse. In all zones, the response from the freshwater pulse exceeds the baseline interseasonal variability of 5–40%.

49 3.1
Introduction

Flooding associated with hydroelectric power development creates a pulse of methylmercury (MeHg), a bioaccumulative neurotoxin. Elevated MeHg concentrations in biota persist for decades following impoundment (Schetagne and Verdon 1999, Anderson 2011), posing risks to indigenous communities who rely on aquatic foods (Wheatley and Paradis 1995,

Dumont et al. 1998). As demand for renewable energy grows, many regions are poised to expand their hydroelectric power capacity (NRTEE 2009, IEA 2012). Recent work demonstrated that near-term expansion of hydroelectric capacity in Canada may have widespread impacts on

MeHg exposures among indigenous communities, of which the most significant are located upstream near coastal environments (Calder et al. 2016). However, the spatial extent of the penetration of a terrestrial MeHg source into estuarine environments and the impact of freshwater perturbations relative to overall interseasonal variability have not been evaluated.

This work models the spatial distribution of a MeHg pulse caused by hydroelectric power development in a subarctic estuarine fjord that provides hunting and fishing territory for indigenous Inuit and evaluates the relative importance of hydroelectric development within overall interseasonal variability.

Reservoir impoundment mobilizes organic matter from submerged vegetation and eroded soils (Louchouarn et al. 1993). Decomposing vegetation and increased hydraulic residence time create geochemical conditions that enhance the activity of microbial communities responsible for MeHg production in flooded soils (Jackson 1991). Reservoirs thus export bottom waters rich in particulate and dissolved MeHg (Canavan et al. 2000, Schetagne et al. 2000).

Biological availability of this MeHg downstream depends on the extent of removal by photodegradation and particulate deposition to benthic sediments. Strong binding of MeHg to

50 terrestrial dissolved organic carbon may enhance its stability, reducing photochemical

degradation (Poste et al. 2015). Direct measurements suggest increased MeHg concentrations in

fish suggest are still apparent 300 km downstream from the flooded area (Schetagne and Verdon

1999, Anderson 2011). The stratification and salinity gradients in northern estuarine

environments promote the uptake of freshwater methylmercury inputs into local food webs,

suggesting that perturbations in freshwater inputs are likely to result in impacts far into the

downstream environment (Schartup et al. 2015a). However, vertical mixing and dilution with

other freshwater and marine inputs are likely to dilute the MeHg pulse in the downstream

direction, while strong interseasonal variability may result in an impaired ability to detect

changes relative to baseline.

Here, we implement a mechanistic, spatially and temporally resolved Hg cycling model

to forecast the impacts of hydroelectric development on the MeHg levels in Lake Melville, a

subarctic estuarine fjord. We combine direct measurements of Hg concentrations and rate

constants with a geophysical model of the estuarine environment to forecast how seasonally and

spatially variable temperature, solids inputs, light penetration, Hg inputs, gas exchange and

advective forces combine to influence the response of MeHg levels to perturbations in

freshwater inputs resulting from hydroelectric development.

3.2
Methods

We develop a two-dimensional, laterally averaged biogeochemical model consisting of

ten water column cells and five active sediment cells for chemical transformations and transport

of three main Hg species (divalent Hg: HgII, elemental Hg: Hg0, and MeHg) in the Lake Melville

ecosystem. A fourth Hg species (dimethylmercury) is present in many offshore marine systems

but is generally negligible here (Schartup et al. 2015a). The model includes five horizontal layers

51 and three vertical layers. Model compartments were chosen to represent major features of the

ecosystem including: (1) the immediate downstream estuarine environment from the flooded

freshwater tributary (Goose Bay); (2 and 3) the central regions of Lake Melville; (4) the

vertically well-mixed area of Lake Melville; and (5) the outlet to the Labrador Sea known as the

Narrows. The three vertical layers of the model include: (1) the stratified upper 10 m of the

water column characterized by low-salinity characterized in previous work (Lu et al. 2014,

Schartup et al. 2015a); (2) the well-mixed high-salinity deeper waters of Lake Melville, and (3) a

3-cm active sediment layer corresponding to the site-wide average depth of the surface mixed

layer. The vertical depth of the water column ranges from 27 m in Goose Bay to 90 m in the

central region of Lake Melville. We refer to model cells using index notation [i,j] where i
[1..5]

refers to the longitudinal position with 1 being Goose Bay and 5 being the Narrows and j
[1..3]

refers to the vertical position with 1 being the surface layer, 2 being the mixed layer and 3 being

the active sediments.

We develop three coupled differential equations for tracking inputs and loss through reaction and transport of Hg species that are solved using Runge-Kutta numerical integration.

Processes represented in the model include redox transformations, methylation and demethylation, and horizontal and vertical advective transport associated with seawater circulation and settling particulate material. Losses from the system include sequestration in benthic sediment, tidal outflow and evasion of Hg0. The model is forced by external inputs of Hg

species from freshwater inputs, atmospheric deposition, and tidal inflow. Circulation in Lake

Melville is based on flow fields from the finite-volume coastal ocean model (FVCOM)

simulation (Chen et al. 2006). Figure 3-1 shows the discretization of the Lake Melville model

52 Figure 3-1: Schematic of laterally averaged 2D model with 15 cells divided longitudinally (four internal boundaries) and vertically (two water column layers and one active sediment layer) with primary transport processes illustrated. Model output evaluated against measurements from Schartup et al. (2015) taken at points indicated. and the intercompartmental transport processes, and compartmental dimensions are included in

Table S3-1.

3.2.1
Boundary conditions

Freshwater and marine inputs deliver Hg species and suspended solids to the Lake

Melville model domain. The Churchill and Goose rivers discharge to cell [1,1] (upper layer of

Goose Bay) while the Kenamu and North West rivers discharge to cell [2,1]. There is two-way exchange between the outer marine environment and cells [5,1] and [5,2].

53 Flow rates from the Churchill River, which accounts for about 80% of the freshwater

inputs into Lake Melville, are handled using real monthly average values from hydrograph data

for the years 1974-2012 (Environment Canada 2014). This period corresponds to flows after

damming at Churchill Falls, which significantly changed the river’s flow regime (Bobbit and

Akenhead 1982). The anticipated damming of Muskrat Falls and Gull Island is not expected to

have a significant effect on downstream flow rates due to the small live storage capacity (Nalcor

Energy 2009a), so these flow rates are not adjusted between model scenarios. Flow rates for

Goose, North West and Kenamu Rivers were approximated by interpolating between spring

highs and winter lows from the literature (Coachman 1953). Monthly average freshwater inputs

are summarized in Table S3-2. Longitudinal flows between model cells and tidal exchange

between the far-downstream cells and the ocean were calculated using flow-field data from an

FVCOM simulation of the Lake Melville system whose output was evaluated using available

mooring data (Lu et al. 2014). Net vertical flows were calculated to ensure conservation of mass

in every cell (Table S3-3). Flow rates between compartments are recalculated to preserve mass

for every monthly freshwater discharge value.

Notwithstanding strong stratification, transport of Hg species through the water column

across most of the model domain is dominated by advection (Péclet number >> 1). Net water

flows across the halocline in Goose Bay, however, are very small owing to the presence of a high

sill that limits the penetration of tidal inflows (Lu et al. 2014). Here we add a turbulent diffusion

term to capture Hg transport across the interface with mixing length equal to the elevation

difference between the centroids of the cells (  
) and a turbulent diffusion coefficient

  equal to   
 

, where  is the velocity gradient across the halocline  

54 and Ri is the Richardson number, calculated as a function of density and velocity gradients

(Munk and Anderson 1948, Martin and McCutcheon 1998).

Seasonal riverine and tidal Hg concentrations are derived from Schartup et al. (2015a)

(Table S3-4). Monthly average wet and dry deposition data is derived from the 2009 GEOS-

Chem model simulations (Amos et al. 2012) (Table S3-5). Air-sea exchange of dissolved

gaseous mercury (DGM) is modelled as a flux of elemental mercury (Hg0) driven by the

concentration gradient across the water surface and the water-side transfer velocity determined

by wind shear (Liss and Merlivat 1986) and uses the parameterization given by Sunderland et al.

(2010). Ice cover from December to May (Environment Canada 2015) impedes air-sea exchange

of Hg0 and deposition of HgII and MeHg.

We account for seasonally variable freshwater suspended solids inputs using the sediment discharge rating curve (Morehead et al. 2003) displayed in Table S3-6. For the Churchill River, we evaluate a model proposed by Northwest Hydraulic Consultants (2008) with respect to available data (Jacques Whitford Environment Ltd 1999, Minaskuat LP 2007, Murphy 2014) and find good agreement (Figure 3-2). We use this relationship also for Goose, Kenamu and North

West Rivers that together account for about 20% of yearly average freshwater inputs (Table

S3-2) because they, like the Churchill River, are all carved out of the high-grade metamorphic rock of Labrador’s Grenville Province (Greene 1974). Damming the Churchill River at Muskrat

Falls will result in lower sediment concentrations immediately downstream, but increased erosion is expected to result in a suspended solids concentration equal to pre-impoundment baseline within roughtly 10 km of the outfall to Goose Bay (Northwest Hydraulic Consultants

2008). Therefore, suspended solids inputs are held constant for post-flooding simulations.

55 #&"

#$"

#""

*"

 
 ("
-
)$+"& #%'


&" 

  

-
$"% #$"*) $"

" ""","" '"","$ #"","% #'","% $"","% $'","% %"","% %'","% &"","% &'","% 
%

Figure 3-2: Evaluation of total suspended solids – discharge rating curve for the Churchill River

Calder et al. (2016) suggest that upstream hydroelectric development may increase mean

MeHg inputs from the Churchill River into Goose Bay eight-fold (5–95% CI: 4–13 times). We therefore consider an eight-fold increase in MeHg inputs from the Churchill River to correspond to the post-flooding pulse, with exponential decline over 30 years, corresponding to the observed time course in fish (Bodaly et al. 2007, Anderson 2011).

3.2.2
Solids budget

We consider two solids size fractions for suspended solids: clay (diameter = 5 µm) and silt (diameter = 15 µm). Table S3-7 displays the particle size-specific Hg partition coefficients

(Babiarz et al. 2001) based on available site-specific measurements (Schartup et al. 2015a) and particle densities. Table S3-8 displays the parameterization of particle settling based on the parameterization of Cheng (1997) for Reynolds numbers greater than 1. Active sediments are permanently buried using area-specific rates calculated from 210Pb dating (Kamula 2015) (Table

56 S3-9), with the difference between settled and buried solids being resuspended. Hg species sorbed to settled solids reequilibrate with sediment concentrations before resuspension. Solids inputs from freshwater discharges and tidal sources are presumed to be 25 and 100% respectively, resulting in steady-state suspended solids concentrations consistent with field data presented in Schartup et al. (2015a).

3.2.3
Chemical transformations

Chemical transformations (methylation, demethylation, oxidation and reduction) are described using first-order rate constants derived from measurements in Lake Melville (Schartup et al. 2015a). Methylation and biotic demethylation rates are based on measurements in August and assumed to be zero in the winter months (Ullrich et al. 2001, Schartup et al. 2015a).

Photochemical demethylation is modeled using experimental data and the parameterization proposed by Black et al. (2012). We account for seasonal and spatial heterogeneity in certain environmental conditions known to affect reaction rates by using (1) monthly values for incident photosynthetically active radiation (PAR), ice cover status and surface chlorophyll concentrations and (2) compartment-specific values for temperature and salinity. Certain parameterizations were changed from those used by Schartup et al. (2015a) to account for seasonal and spatial differences: primary productivity in the surface layers is calculated as a function of incident PAR, salinity and concentrations of suspended solids and chlorophyll (Cole and Cloern 1987, Xu et al. 2005). Diffusivity is parameterized as a function of the variable temperature (Othmer and Thakar 1953, Kim and Fitzgerald 1986, Gill et al. 1999). Different

MeHg and HgII partition coefficients used for mineral solids and organic solids to account for the higher affinity of Hg species for organic particles (Sunderland et al. 2006). Equations of state for density and viscosity of water as well as temperature-dependent diffusivity of Hg are given in

57 Table S3-10. Table S3-11 summarizes the parameterization of chemical processes that differ from the budget developed by Schartup et al. (2015a). Table S3-12 (temperature and salinity) and Table S3-13 (photoactive radiation and surface chlorophyll concentrations) provide spatially and temporally resolved data that drive certain of these chemical reactions.

3.3
Results and discussion

Baseline simulations provide steady-state solutions consistent with field observations reported by Schartup et al. (2015a) and describe seasonal characteristics that could not be observed due to, for example, ice cover.

[1,1] [2,1] [3,1] [4,1] [5,1]

0.15

0.1

Hg0 [pM] 0.05

[1,2] [2,2] [3,2] [4,2] [5,2]

0.15

0.1

Hg0 [pM] 0.05

[1,3] [2,3] [3,3] [4,3] [5,3] 0.01

0.005 Hg0 [pmol/g] 0 246246246246246 Year

Figure 3-3: Modeled Hg0 concentrations in Lake Melville at baseline. Index i
[1..5] refers to longitudinal position where i = 1 is Goose Bay and i = 5 is the Narrows at the interface with the Atlantic Ocean. Index j
[1..3] refers to the vertical position, where j = 1 is the low-salinity surface layer, j = 2 is the mixed water and j = 3 is the active sediments.

58 Figure 3-3 shows seasonally and spatially varying Hg0 concentrations in Lake Melville

for a seven-year simulation, showing a winter peak in inland cells as ice impedes evasion from

the surface layer. This effect is less evident far downstream as efficient mixing with the open

ocean allows dissolved Hg0 to equilibrate with the atmosphere year-round. This seasonal effect is

also evident in HgII, which exists in dynamic equilibrium with Hg0. Deposition of particulate

HgII from freshwater inputs is also evident from the relatively higher sediment concentrations in

Goose Bay (i = 1). Figure 3-4 illustrates the model output for HgII at baseline. Seasonally

varying baseline MeHg concentrations are shown in Figure 3-5.

[1,1] [2,1] [3,1] [4,1] [5,1] 2.5 2 1.5 1 HgII [pM] 0.5

[1,2] [2,2] [3,2] [4,2] [5,2] 2.5 2 1.5 1 HgII [pM] 0.5

[1,3] [2,3] [3,3] [4,3] [5,3] 250

200

150

100 HgII [pmol/g] 50 246246246246246 Year

Figure 3-4: Modeled HgII concentrations in Lake Melville at baseline

59

[1,1] [2,1] [3,1] [4,1] [5,1] 0.08 0.07 0.06

MeHg [pM] 0.05 0.04 [1,2] [2,2] [3,2] [4,2] [5,2] 0.08 0.07 0.06

MeHg [pM] 0.05 0.04 [1,3] [2,3] [3,3] [4,3] [5,3]

2

1.5

1

MeHg [pmol/g] 0.5 246246246246246 Year

Figure 3-5: Modeled MeHg concentrations in Lake Melville at baseline

Upstream hydroelectric development will increase MeHg inputs into the upper layer of

Goose Bay by roughly eight-fold relative to baseline (95% CI: 4–13) (Calder et al. 2016). This simulation suggests that the response of MeHg concentrations in the downstream estuary will exceed interseasonal variability for the first several years of increased MeHg inputs from the

Churchill River (Figure 3-6), with increases in the upstream and surface zones exceeding increases in the downstream and bottom zones respectively. Increased freshwater inputs of

MeHg push concentrations out of the range of baseline interseasonal variability even in the bottom waters underlying the low-salinity surface region, owing to particulate scavenging of

MeHg from the surface zone.

60 [1,1] [2,1] [3,1] [4,1] [5,1]

0.15

0.1 MeHg [pM] 0.05 [1,2] [2,2] [3,2] [4,2] [5,2]

0.15

0.1 MeHg [pM] 0.05 [1,3] [2,3] [3,3] [4,3] [5,3] 2.5 2 1.5 1

MeHg [pmol/g] 0.5 10 20 30 40 50 10 20 30 40 50 10 20 30 40 50 10 20 30 40 50 10 20 30 40 50 Year

Figure 3-6: Modeled MeHg concentrations in Lake Melville showing the effect of a pulse from the Churchill River equal to an eight-fold enrichment relative to baseline inputs.

This analysis uses demethylation rates measured at baseline and so may underestimate post-flooding water column MeHg concentrations enriched by terrestrially complexed MeHg, which is relatively resistant to degradation (Poste et al. 2015). Schartup et al. (2015b) demonstrates that MeHg is taken up less readily by plankton when complexed to terrestrial DOC than marine DOC, while Wikner and Andersson (2012) show how terrestrial DOC may contribute to a longer food chain in the aquatic environment, increasing bioaccumulation in higher trophic level species relative to baseline. These competing phenomena may combine such that post-flooding peak biotic MeHg in the estuarine environment reflects the water column increases presented here.

61 Northern latitude ecosystems are warming more quickly than the global average, causing, among other things, reduced winter ice cover, higher productivity, enhanced freshwater and Hg inputs from thawing soils and increased stratification of aquatic environments (Kirk et al. 2011,

Stern et al. 2012). These changes may enhance MeHg production, uptake and human exposures.

Further study is needed to evaluate the importance of climate change relative to hydroelectric development on overall risks for increased human exposures.

62 Supporting information

Table S3-1: Model compartment dimensions Longitudinal zone Height (m) Surface Low-salinity Well-mixed Active area (m2) surface layer seawater sediments 1. Goose Bay 10 17 0.03 6.22E+08 2. Lake Melville 10 37 0.03 2.94E+09 3. Lake Melville 10 81 0.03 4.04E+09 4. High mixing zone 10 61 0.03 5.48E+08 5. The Narrows 10 26 0.03 1.36E+08

Table S3-2: Monthly average values for freshwater discharges. Churchill River values are from Environment Canada gauging stations (1974-2012). Goose, Kenamu and North West are from Coachman 1952, where * denotes interpolated values. River discharge (m3 day-1) Month Churchill Goose Kenamu North West January 1.56E+08 7.80E+06 * 1.75E+07 * 3.91E+07 * February 1.57E+08 4.11E+06 * 9.04E+06 * 3.54E+07 * March 1.47E+08 4.23E+05 5.68E+05 3.17E+07 April 1.35E+08 2.32E+07* 1.28E+07 * 9.36E+07 * May 2.31E+08 4.60E+07 2.51E+07 1.56E+08 June 2.03E+08 2.68E+07 * 1.99E+07 * 1.19E+08 * July 1.45E+08 7.66E+06 1.47E+07 8.16E+07 August 1.36E+08 2.62E+07 * 5.98E+07 * 5.79E+07 * September 1.32E+08 2.25E+07 * 5.14E+07 * 5.41E+07 * October 1.45E+08 1.89E+07 * 4.29E+07 * 5.04E+07 * November 1.53E+08 1.52E+07 * 3.44E+07 * 4.66E+07 * December 1.56E+08 1.15E+07 * 2.60E+07 * 4.29E+07 *

Table S3-3: Flows between pairs of model cells [i.j] where 

  and 

  refer to model index in the longitudinal and vertical directions respectively. Flows displayed are ×109 m3 day-1. Values for January shown. Downstream Upstream Net upward [1,1]/[2,1] 1.3 1.2 [1,1]/[1,2] 0 [2,1]/[3,1] 4.2 0.5 [3,1]/[4,1] 0.2 0.9 [2,1]/[2,2] 3.4 [4,1]/[5,1] 1.7 1.3 [5,1]/Sea 1.6 0.4 [3,1]/[3,2] -4.3 [1,2]/[2,2] 0 0 [2,2]/[3,2] 3.6 7.0 [4,1]/[4,2] 1.0 [3,2]/[4,2] 3.8 2.9 [4,2]/[5,2] 2.6 2.7 [5,1]/[5,2] 0.8 [5,2]/Sea 1.8 2.7

63

Table S3-4: River and ocean Hg and solids concentrations for baseline simulations . Values are from Schartup et al. 2015, and * denotes interpolated values. Churchill Goose Kenamu North West Ocean Month Hg0 (pmol L-1) Mar – May 0.022 0 0 0 0.06* Jun – Aug 0.04 0.19 0.19 0.19 0.07 Sept – Nov 0.14 0.14 0.14 0.14 0.04 Dec – Feb 0.14 0.14 0.14 0.14 0.05* Month HgII (pmol L-1) Mar – May 5.7 6.3 6.3 6.3 0.63* Jun – Aug 9.8 11.3 11.3 11.3 0.63 Sept – Nov 5.3 3.6 3.6 3.6 0.63 Dec – Feb 5.3 3.6 3.6 3.6 0.63* Month MeHg (pmol L-1) Mar – May 0.026 0.048 0.048 0.048 0.05* Jun – Aug 0.049 0.032 0.032 0.032 0.05 Sept – Nov 0.122 0.046 0.046 0.046 0.04 Dec – Feb 0 0.046 0.046 0.046 0.04*

Table S3-5: Atmospheric deposition and exchange of Hg species from 2009 Geos-CHEM simulation HgII deposition MeHg deposition Atmospheric Hg0 Month (µg m-2 yr-1) (µg m-2 yr-1) concentration (ng m-3) Dry Wet Dry Wet January 9.84E-04 3.38E-03 2.41E-02 NA 1.6 February 1.38E-03 4.56E-03 2.41E-02 NA 1.5 March 2.81E-03 8.65E-03 2.41E-02 NA 1.5 April 5.47E-03 1.32E-02 2.41E-02 NA 1.5 May 3.21E-02 1.37E-02 2.41E-02 NA 1.5 June 6.10E-02 1.39E-02 2.41E-02 NA 1.3 July 7.06E-02 1.57E-02 2.41E-02 NA 1.2 August 5.36E-02 1.81E-02 2.41E-02 NA 1.1 September 4.11E-02 1.61E-02 2.41E-02 NA 1.1 October 1.57E-02 8.49E-03 2.41E-02 NA 1.2 November 7.07E-03 3.61E-03 2.41E-02 NA 1.4 December 4.63E-04 3.87E-03 2.41E-02 NA 1.5

64 Table S3-6: Parameterization of solids concentrations in freshwater inputs Formulation Units Description Reference Sediment discharge  % ! mg L-1 Morehead et al. 2003  rating curve % $ Model fitted to data from Jacques Whitford Environment Ltd. 1999, Rating curve coefficients Minaskuat LLP 2007, Murphy 2014  %  for the Churchill River and compared to model from Northwest Hydraulic Consultants 2008

Table S3-7: Solid particle characteristics Clay Silt/sand Reference Spherical equivalent diameter (µm) 5 20 Chapra 2008 Density (g cm-3) 2.65 3.5 Suspended solids HgII partition coefficient (L kg-1) 5.6 5.8 MeHg partition coefficient (L kg-1) 5.0 4.0 Schartup et Active sediments al. (2015a) HgII partition coefficient (L kg-1) 4.0 4.0 MeHg partition coefficient (L kg-1) 3.0 2.4

Table S3-8: Parameterization of solids settling velocity, where &'and &' are cell-specific kinematic viscosity and density of water (Table S3-12) and is particle diameter (Table S3-7) Formulation Units Description Reference 
 Settling velocity for &'  m s-1 Reynolds numbers &' %  "  &' #
greater than 1  #
 Cheng &' 1997 
&' Particle parameter &' %  &'

Table S3-9: Burial rates determined from 210Pb core dating from Kamula (2015) where * denotes value interpolated using data from nearby Groswater Bay and the high mixing zone. Burial rate Longitudinal zone (cm yr-1) 1. Goose Bay 0.24 2. Lake Melville 0.17 3. Lake Melville 0.10 4. High mixing zone 0.15 5. The Narrows* 0.14

65 Table S3-10: Parameterization of physical properties to allow for variable temperature (T) and salinity (S) (Table S3-12) Formulation Units Description Reference Diffusivity dominated by #).. $(#) ! 2 -1  2 2 1  /    * 0
m s complexed organic Gill et al. 1999 molecules. -  #) 2 -1 0 Othmer and 3*+4 2 ," , #)   m s Molecular diffusivity of Hg  3*+4
 1
Thakar 1953

,  ! -1 -1 3*+4 2  0   *+ /  3*+4
 kg m s Dynamic viscosity of water AAWA 2008

, , 3*+4 2 -1 3*+4 2 ,

m s Kinematic viscosity of water 3*+4

#) 3 -1  2   cm mol Molar volume of Hg Clever et al. 1987 &$%' !  *+ 2   /   1 3*+4 Density of standard mean !  !  -3 0  1  *+ /   1  *+ kg m ocean water as a function of !  !  temperature 0   1  *+ /  1  *+ , &$%'  *+ 2*+ Schetz and Fuhs ! ! /   1 0 1  *+ Equation of state of seawater 1999 /  1! 0  1!  *+ *+ 3 producing density as a !  kg m /   1  *+  *+ function of temperature and ! ! salinity / 0  1 /  1  *+ !   !  0  1  *+  *+ /   1  *+

66 Table S3-11.1: Parameterization of chemical transformations, where 

 and 

Y Z refer to model index in the longitudinal and vertical directions respectively, z is the vertical depth of the surface of each compartment (Table S3-1), and 152 and 034 are the incident photosynthetically active radiation and surface chlorophyll concentration respectively ( Table S3-13). Formulation Units Description Reference V Black et al. "9:A:G=D=CGC T S /,7I< day-1 Photodemethylation in water column Y>?* +Z Y>?* +Z 2012 7I?* +Z T ! R! SW RJ>BG:E X
W m radiation over height of water (?.* R(? )Y>?Z column (adapted Beer-Lambert law) Albedo of snow-covered fast ice in Allison et al. T  the shortwave range 1993 Dummy variable to indicate winter,
W! R  'X Environment  T corresponding to the months when J>BG:E
%# R $&
Canada (2015) the system is covered by ice 6=@ FHE;V -2  Q   >*  >*  gC m Net primary productivity in the  T -1 Y>*Z day upper low-salinity zone Cole and  Cloern 1987  >* TR m Euphotic depth ) >* 6=@ FC@>9F -1 )Y>?Z T  R   >? Q  Y>?Z R Y>?Z m Extinction coefficient for an estuary Xu et al. 2005 Biotic demethylation in water 9:A:G=8>C -1 "Y>?* +Z U day column calibrated to respect available measurements Schartup et al. Biotic demethylation in the active "9:A:G=8>C T day-1 2015 Y>,Z sediments A:G= -1 "Y>,Z T  day Methylation in the active sediments CKD=CGC 7I< -1 "Y>?* +Z T Y>?Z day Photo-oxidation rate constant Sunderland et CK8>C -1 al. 2010 "Y>?Z T  day Biotic oxidation rate constant

67

Table S3-11.1: Parameterization of chemical transformations (cont’d) Formulation Units Description Reference 
  -1 
    
 day Photo-reduction rate constant 
  -1 Sunderland et al. 2010 
    
 day Biotic reduction rate constant

68 Table S3-12: Temperature and salinity in water column model cells [i.j] where 

  and 

  refer to model index in the longitudinal and vertical directions respectively based on Lu et al. (2014) [1,1] [1,2] [1,3] [1,4] [1,5] [2,1] [2,2] [2,3] [2,4] [2,5] Temperature (ºC) January 8.00 8.00 6.00 6.00 6.00 2.00 8.00 6.00 -2.00 1.00 February 7.00 7.00 5.00 5.00 8.00 2.00 7.00 5.00 -2.00 1.00 March 8.00 8.00 6.00 6.00 10.00 2.00 8.00 6.00 -2.00 1.00 April 9.00 9.00 7.00 7.00 12.00 2.00 9.00 7.00 0.00 1.00 May 10.00 10.00 8.00 8.00 14.00 2.00 10.00 8.00 2.00 1.00 June 12.00 12.00 9.00 9.00 12.00 2.50 12.00 9.00 4.00 1.00 July 13.00 13.00 10.00 10.00 10.00 2.50 13.00 10.00 2.00 1.00 August 14.00 14.00 11.00 11.00 8.00 2.50 14.00 11.00 0.00 1.00 September 12.00 12.00 10.00 10.00 6.00 2.00 12.00 10.00 -2.00 1.00 October 11.00 11.00 9.00 9.00 4.00 2.00 11.00 9.00 -2.00 1.00 November 10.00 10.00 8.00 8.00 2.00 2.00 10.00 8.00 -2.00 1.00 December 9.00 9.00 7.00 7.00 4.00 2.00 9.00 7.00 -2.00 1.00 Salinity (TSU) Year-round 0 5 5 15 22 20 22.5 25 30 35

Table S3-13: Total photosynthetically active radiation (PAR) at the surface of Earth and chlorophyll concentrations in the Lake Melville region from MODIS satellite data. Month Surface chlorophyll (mg m-3) PAR (W m-2) January 0 9.97 February 0 22.74 March 0 48.88 April 0 77.26 May 6.31 104.39 June 9.86 113.52 July 7.81 111.50 August 6.97 86.72 September 6.31 63.31 October 10.7 32.13 November 0 14.17 December 0 7.67

69 4
Dietary advisories increase health risks for indigenous populations facing increasing

methylmercury exposures

Abstract

Northern indigenous populations have diets rich in birds, fish and marine mammals, leading to high methylmercury (MeHg) and polychlorinated biphenyls (PCBs) exposures. MeHg exposures are increasing as a result of hydroelectric development and climate change, with food consumption advisories being the default risk mitigation strategy. However, traditional, locally caught foods contribute disproportionately to overall intakes of vitamin D, n-3 fatty acids and other nutrients, and the transition to market-based diets has been linked to increased risks of obesity, cardiovascular disease and diabetes. This analysis develops scenarios to forecast cardiovascular, neurodevelopmental, cancer and nutritional impacts of substituting store-bought foods for local foods and compares them to risks posed by rising levels of MeHg in local foods for indigenous Inuit in Labrador, Canada. Local foods account for less than 10% of total calories consumed but are the main source of MeHg (70%), PCBs (>90%) and are a disproportionate source of omega-3 fatty acids (70% of DHA and EPA) and vitamin D (39%). Substitution with store-bought foods avoids increases in neurodevelopmental risks from rising MeHg levels in local foods, but mean relative risk (RR) of cardiovascular and cancer mortality for substitution scenarios (up to 1.5 and 1.02 respectively) exceeds risks from the present-day diet for MeHg content of local foods up to approximately seven times current levels for cardiovascular risks and indefinitely for cancer risks. Substitution scenarios also result in reduced intake of key nutrients of up to 10% of daily targets. This analysis suggests dietary advisories alone cannot be used to mitigate risks associated with increased MeHg in traditionally harvested foods of indigenous populations.

70 4.1
Introduction

The diet of northern indigenous populations includes large quantities of predatory fish and marine mammals (Van Oostdam et al. 2005). This can lead to elevated exposures to bioaccumulative contaminants such as methylmercury (MeHg) and polychlorinated biphenyls

(PCBs) that have been associated with neurological, cardiovascular, immune and cancer risks in humans (Carpenter 2006, Karagas et al. 2012). Indigenous populations across the Arctic and

Subarctic rely on traditional, locally caught foods (hereafter “traditional foods”) for a disproportionate share of key nutrients, while rising consumption of less nutritious market-based foods has been linked to increased risks of adverse health outcomes such as diabetes and cardiovascular disease (Kuhnlein et al. 2004, Deutch et al. 2007, Kuhnlein and Receveur 2007,

Gagné et al. 2012, Johnson-Down and Egeland 2013, Luick et al. 2014). Consumption advisories for traditional foods are used to mitigate MeHg exposures, rising due to climate change and industrial development, but this goal must be balanced against nutritional targets and in consideration of the countervailing risks of dietary alternatives (Wheatley and Paradis 1996,

Furgal et al. 2005, McAuley and Knopper 2011, Bjerregaard and Mulvad 2012). This work quantifies health risks associated with increased MeHg exposures from traditional foods compared to risks posed by replacing traditional foods with store-bought alternatives using dietary data for Inuit of Labrador, Canada.

Traditional foods contain both contaminants and essential nutrients, including iron (Fe), zinc (Zn), polyunsaturated fatty acids (PUFAs) and vitamins A, B2, B3, B6, B12 and D, at levels higher than store-bought component of indigenous diets (Kuhnlein and Chan 2000, Nakano et al.

2005, Kuhnlein and Receveur 2007, Beaumier and Ford 2010, Gagné et al. 2012, Snodgrass

2013, Sheehy et al. 2015, Rosol et al. 2016). Evaluation of dietary interventions must therefore

71 account not only for contaminant-related risks that are avoided but also for risks associated with reduced intake of local foods and replacement by less nutritious alternatives. Such an approach has rarely been considered quantitatively during the development of food advisories beyond the tradeoffs associated with MeHg and PUFAs in seafood (Ginsberg and Toal 2009, Mahaffey et al.

2011).

MeHg levels in arctic marine food webs have increased by roughly ten-fold since pre- industrial times, and thawing permafrost, a warming water column and increased coastal stratification are likely to result in further MeHg increases in the future (Dietz et al. 2009, Stern et al. 2012). A ‘global boom’ in hydroelectric development (Zarfl et al. 2014) is resulting in widespread flooding of carbon-rich land, notably in the Canadian North, where over 90% of potential new capacity is expected to increase MeHg exposures to nearby indigenous populations

(Calder et al. 2016). While the nutritional importance of locally caught traditional foods is well documented, food consumption advisories focus solely on risks of elevated exposures to MeHg and are the only policy tool in practical use (Passos and Mergler 2008).

This work quantifies neurodevelopmental, cardiovascular and cancer risks to a northern indigenous population associated with 1) increasing MeHg levels in local foods and no dietary intervention vs. 2) substitution of local foods with store-bought alternatives. In prior work, we collected extensive dietary information and measured MeHg exposures for 1,145 indigenous

Inuit settled around Lake Melville, Labrador, Canada (Calder et al. 2016). This is supplemented here with data on store-bought foods from food subsidy records obtained through the Freedom of

Information Act (AANDC 2016a). We reviewed the Global Burden of Disease study (Wang et al. 2016) and latest meta-analyses to select dose-response functions for all relevant contaminants,

72 nutrients and foods. We use this analysis to discuss the efficacy of dietary advisories to protect the health of northern indigenous populations facing increased MeHg exposures.

4.2
Methods

4.2.1
Baseline food intake

We enrolled approximately 40% of the Inuit population in the Lake Melville region of

Labrador, Canada dietary survey and baseline MeHg exposure assessment (Calder et al. 2016).

We use consumption data for 64 local foods and 24 categories of store-bought seafood from this survey (Tables S4-1 to S4-5). We scaled seafood consumption data reported by the 499 individuals who provided hair samples to match MeHg intake calculated from hair Hg measurements. The median of this ratio (0.96) was applied to dietary data of the remaining 555 participants, as described in Calder et al. (2016).

Canada’s Nutrition North program subsidizes 42 nutritious, perishable store-bought foods or food categories (Table S4-4) in Rigolet, the northernmost community studied here. We combined latest available shipping data (AANDC 2016a) with retail and consumer spoilage fractions for perishable foods (Gustavsson et al. 2011) to calculate community-wide total consumption data for store-bought nutritious foods other than seafood, which is accounted for as described above. We assume the relative composition of these foods in Rigolet applies also to the two other communities studied. Because local food intake in the other two communities is smaller than in Rigolet (Calder et al. 2016), we assume consumption of store-bought foods is greater and scale per-capita data by the difference in mean local food consumption relative to

Rigolet. Total overall intake of these store-bought nutritious foods was apportioned to individuals proportionally to the difference between total calories consumed and known caloric intake from local foods and store-bought seafood. We calculated from Mifflin et al. (1990) total

73 calories consumed as 
 
  
  , where is weight (kg), is height

(cm),  is age (years), is 1 for males and 0 for females and is 1.7 for males and 1.6 for females (for moderately active individuals). Individual weights, heights and ages were collected in our survey (Calder et al., 2016). The difference between total caloric intake and calories from local foods, store-bought seafood and other store-bought nutritious foods is made up by other foods including nutrient-poor chips, snack foods and alcohol, hereafter referred to as “empty- calorie foods.” Table S4-5 describes the basket of empty-calorie foods retained for the purposes of nutrient analysis, with each food assumed to account for an equal proportion of per-capita intake. The analysis is not sensitive to the foods considered within this category or the relative composition of intake because all foods in this category are likely to be relatively nutrient-poor.

4.2.2
Nutrients in foods

We pair 96 foods with nutritional information for representative foods from the Canada

Nutrient File (CNF). Five foods with no data in the CNF were matched to foods in the United

States Department of Agriculture (USDA) Nutrient Database. Food-specific information on the nutrients considered in this analysis, described in the next section, was available for foods accounting for ≥ 90% of population-wide calorie intake. When nutritional information was missing for a food or a food group it was replaced by the average value for that nutrient from other foods in the same category, defined as: dairy, egg, fish liver, fish muscle, fish roe, fowl/poultry, fruit, grain, marine mammal, processed meat, red meat, shellfish, terrestrial mammal and vegetable. Total PCB content of all foods was derived from literature values and is included to ensure increases in cancer risks due to reduced local food consumption are not overestimated. Tables S4-1 to S4-5 summarize this information together with the per-capita caloric contribution of each food. Baseline MeHg values for local and store-bought foods are

74 modeled probabilistically using the values in Calder et al. (2016), and store-bought foods other than seafood are presumed to have negligible MeHg content.

Dietary scenarios consider 1) baseline diet with continuously increasing MeHg content in local foods and 2) transition diets, where local foods are replaced with store-bought foods preserving baseline caloric and MeHg intake. We consider transition scenarios where local foods are replaced with increased consumption of 1) the basket of nutritious store-bought foods proportionally to baseline consumption; 2) certain higher-risk foods from within this basket, e.g., processed meat; and 3) junk food.

4.2.3
Health impacts model

We calculate potential health impacts of dietary scenarios that consider: a) baseline diet with increasing MeHg content in local foods and b) transition diets, where local foods are replaced with store-bought foods preserving baseline caloric and MeHg intake. Food consumption advisories are implemented to limit increased MeHg exposures and preserve caloric intake, so we adopt this idealized modeling framework to compare outcomes across substation scenarios. We consider transition diet scenarios where local foods are replaced by: 1) the basket of nutritious store-bought foods consumed at baseline; 2) specific higher-risk foods such as processed meat; 3) specific lower-risk foods such as vegetables.

MeHg impairs neuronal homeostasis and causes oxidative stress, increased lipid peroxidation and ultimately cell death, making it a potent generalized neurotoxicant and cardiovascular stressor (Salonen et al. 1995, Virtanen et al. 2007, Farina et al. 2011). Meanwhile, n-3 fatty acids promote the development of cognitive function by mediating enzymatic activity and nutrient transport in the frontal cortex (Bourre 2004) and exert hypotriglyceridemic and hypotensive effects that reduce cardiovascular risks (Kris-Etherton 2002). Change in IQ is

75 retained as the endpoint representing the suite of neurotoxic (MeHg) and neuroprotective (n-3

fatty acids) impacts on developing fetuses (Table S4-6). For MeHg, we retain the

parameterization of Rice et al. (2010) based on Axelrad et al. (2007) and Cohen et al. (2005a)

(median estimate of 0.3 IQ points per µg Hg g-1 maternal hair, ages 16–49 used here), which may

be conservative given recent analyses suggesting an effect of 0.4–0.5 IQ points per µg g-1 at maternal hair concentrations exceeding 0.6 µg g-1 and >2 IQ points per ug g-1 at maternal hair

concentrations below 0.1 ug g-1 (Bellanger et al. 2013, Debes et al. 2016).

We reviewed the Global Burden of Disease Study to select relationships between food or

nutrient intake and cardiovascular (Table S4-7) and cancer (Table S4-8) risks that are most

robustly characterized (Forouzanfar et al. 2015). Continuous dose-response functions are

parameterized using latest available meta analyses for all individuals over 25 years old. We

restricted the analysis to relationships with evidence of a dose-response effect and significant

associations at intakes in the ranges calculated here. Red and processed meats trigger the

formation of carcinogenic N-nitrosos and proartherosclerotic trimethylamines in the

gastrointestinal tract, which has been linked to increased cardiovascular and colorectal cancer

risks (Chan et al. 2011a, Koeth et al. 2013). Excess sodium intake has been associated with

increased risk of cardiovascular disease, most notably via hypertension, and gastric cancer by

damaging gastric mucosa, promoting helicobacter pylori infection (Gancz et al. 2008, D'Elia et

al. 2012, Whelton et al. 2012). Trans fatty acids increase the ratio of LDL to HDL cholesterol,

trigger systemic inflammation and disrupt endothelial function and are therefore a strong

cardiovascular stressor (Mozaffarian et al. 2006). Meanwhile, fruits, vegetables and nuts are rich

in compounds thought to reduce cardiovascular risks via several pathways: inhibition of platelet

aggregation and oxidation of arterial cholesterol (antioxidants and polyphenols), mediation of

76 glucose homeostasis (fiber) and regulation of blood pressure (potassium and magnesium)

(Ludwig et al. 1999, Rissanen et al. 2003, Blomhoff et al. 2006, Kelly and Sabaté 2006, Wang et al. 2014). Fiber and calcium reduce colorectal cancer risks by binding stomach acids and mediating cellular differentiation, apoptosis and mutagenesis in the gastrointestinal tract (Slavin

2000, Aune et al. 2012).

Vitamin D metabolizes to 1,25(OH)2D, which exerts apoptotic, antiangiogenic and antimetastatic effects on many cell types and has therefore been shown to reduce risks for a wide variety of cancers (Giovannucci 2005, Giovannucci et al. 2006). We therefore also consider the cancer-protective effects of vitamin D given the strong evidence supporting a dose-response relationship and the significance of local foods for vitamin D sufficiency among indigenous populations at high latitudes (Giovannucci 2005, Giovannucci et al. 2006, Garland et al. 2007,

Grant 2010). To ensure a conservative calculation of the benefits of local foods, we further account for the cardiovascular risks associated with MeHg and the cancer risks associated with

PCBs, of which local foods are disproportionate sources among indigenous populations

(Kuhnlein and Chan 2000, Hoover et al. 2012). Certain foods (e.g., red meat, vegetables) are modeled on cancer and cardiovascular endpoints directly and not through their nutrient content, as described above. For these foods, we exclude from the health impacts model the effects of nutrients contained in such foods in order to avoid double-counting risks. We do not consider benefits related to increased whole grain consumption because we could not quantify the ratio of whole to processed grains in the baseline diet and because intake of whole grains is small in similar northern indigenous populations. To ensure calculated RRs for all individuals are plausible, we do not consider effects from changes in nutrients or foods greater than any identified saturation dose. For compounds with no identified saturation dose, RRs are confined to

77 the range identified in the epidemiological literature. An MeHg increase of 400% in traditional foods corresponds approximately to the location of the risk plateau in substitution scenarios and is roughly equal to the inter-species mean expected increase forecasted by in Calder et al. (2016), so the range 0–400% is considered in our risk figures.

4.3
Results and discussion

Figure 4-1 shows per-capita sources of calories across demographic groups. We find that local foods account for up to 42% of calories consumed on an individual level but a mean of only

1% (Happy Valley – Goose Bay) to 4% (Rigolet) across the three communities. Based on food subsidy records for Rigolet, nutritious, perishable foods account for 21% of population-wide calories. The largest contributor to population-wide caloric intake are store-bought foods not eligible for subsidy (77% of all calories), a category that includes empty-calorie snack foods and alcohol. While local foods account for less than 5% of population-wide caloric intake, Figure 4-1: Total calories per capita for different demographic groups calculated from Mifflin et al. they account for >95% and ~70% of PCB and (1990). Traditional, locally caught food is from dietary survey (Calder et al. 2016). Store-bought Hg exposures. Local foods are also a nutritious foods include market seafood reported in the dietary survey and nutritious perishable foods disproportionate contributor of several subsidized under the Nutrition North program (values reported for Rigolet used for all communities). “Other” is calculated to satisfy essential nutrients, notably n-3 fatty acids caloric intake and includes all other foods such as snack foods and alcohol. HVGB = Happy Valley DHA and EPA (70%), vitamin D (35%), – Goose Bay; NWR = North West River. vitamins B12 (19%), A (16%), B2, B3 and C

78 and iron (7%), vitamin B6 (6%) and zinc

(5%) (Figure 4-2). This is consistent with

other studies that have found traditional

diets to be richer in these nutrients than

store-bought diets (Nakano et al. 2005,

Kuhnlein and Receveur 2007, Beaumier

and Ford 2010, Gagné et al. 2012, Sheehy

et al. 2015). The present-day diet is

associated with neurodevelopmental and

cardiovascular risks that rise with MeHg

content. Figure 4-3 shows (a) the Figure 4-2: Contribution of traditional foods to overall consumption of select nutrients, calories, population-wide mean IQ deficit among MeHg and PCBs. Bars are overall per-capita intakes and lines represent 5–95% of individuals. children born to mothers aged 16–49 as a *Mean intake below recommended daily intake corresponding to daily values (DV) from US FDA 2013 where available and 500 mg day-1 for n-3 fatty function of increasing MeHg content in acids (DHA + EPA) (Kris-Etherton et al. 2009) local foods and (b) the value of higher percentiles at the 400% MeHg increase level, both with model confidence intervals based on variability in local food MeHg concentrations at baseline and dose-response model uncertainty

(Table S4-6). Transitioning to a market-based diet avoids excess MeHg risks but still presents risks relative to present-day levels owing to reduced intake of n-3 fatty acids. There is no appreciable difference between substitution scenarios.

Figure 4-4 illustrates that mean population-wide cardiovascular risks increase more quickly for dietary substitution scenarios owing to reduced intake of n-3 fatty acids and increased intake of red and processed meats and sodium. Increased intake of nuts, fruits and vegetables

79 does not offset this effect under the representative diet scenario. We show also the limiting case where local foods are replaced by processed meat, which presents the greatest RR per unit increase in consumption (Table S4-7). Therefore, market-food substitution increases cardiovascular risks relative to the baseline Figure 4-3: IQ decrement in children born to diet over a wide range of increases in the mothers with increasing Hg exposures from traditional foods (“Present-day diet”) or MeHg content of local foods and avoids substituting local foods with various market-based baskets that preserve baseline Hg exposures. (A) most, but not all, of the neurodevelopmental Population-wide mean and (B) population-wide mean and select population percentiles at 400% MeHg increase in local foods. Shaded region (A) risks of increased MeHg exposures. and error bars (B) represent model uncertainty around displayed mean value (5–95% CI). No Cancer risks for the baseline diet store-bought food scenario considered in this analysis presents results distinguishable from those scenario are assumed to be constant. presented here because of uniformly low levels of n-3 fatty acids and methylmercury.

Replacing local foods with store-bought foods can reduce per-capita PCB exposures by >95%, but this translates to reduced lifetime hepatic cancer risks of roughly 1% population-wide (simulated mean between 0% and 10% for

95% of population). Increased consumption of red and processed meat increases colorectal cancer risks by up to 2% population-wide (simulated mean between 0% and 10% for 95% of population), while decreased consumption of vitamin D increases risks for all cancers. The net result of dietary substitutions on overall risk of death from cancer of all types is an increase in lifetime risks relative to baseline, plateauing at < 2% (population-wide mean) and < 6% (95th percentile individuals). Figure 4-5 shows the increasing cancer risks for two limiting dietary

80 substitution scenarios, with processed meat

increasing cancer risks more quickly than the

basket of nutritious foods, due to its

relatively steep dose-response curve (Table

S4-8).

Figure 4-6 shows the population-wide

impacts of substitution of local foods on

intake of several key nutrients for which

mean intake is lower than the Figure 4-4: Relative risk (RR) of cardiovascular death for persons over 25 with increasing MeHg recommended daily value. As a fraction of exposures from local sources (“Baseline diet”) or substitution with store-bought alternatives preserving calorie intake and MeHg exposures from baseline. this daily value and across substitution (A) Population-wide mean and (B) population-wide mean and select population percentiles at 400% scenarios, nutrient intake would fall for n- MeHg increase in local foods. Shaded region (A) and error bars (B) represent model uncertainty around 3 fatty acids DHA and EPA (30%) and displayed mean value (5–95% CI). Baseline diet and processed meat substitution scenarios presented as bounding cases in (A) with vegetables and vitamins B12 (8–11%), D (7–8%) and A subsidized foods scenarios falling in between (omitted for clarity). (1–2%). Vitamin B2, iron and zinc intakes

are more sensitive to the substitution scenario assumed, with per-capita impacts on vitamin B2

ranging from a loss of 4% (empty-calorie snack foods scenario) to a gain of 2% (vegetables

scenario) as a fraction of recommended daily intake, with smaller inter-scenario variability for

zinc (0–2% loss) and iron (0–4% loss). There is substantial inter-individual variability, with the

95th percentile of losses of n-3 fatty acids (DHA and EPA) and vitamins B12 and D losses exceeding 100%, 43% and 30% of the recommended daily intake respectively in certain scenarios, although these losses are among individuals who were nutritionally sufficient at baseline.

81 4.4
Discussion

Increasing concentrations of MeHg fish and marine mammals present cardiovascular and neurodevelopmental risks to indigenous populations. Food consumption advisories aim to limit health risks of increased exposures to bioaccumulative contaminants but do not generally consider the risks represented Figure 4-5: Relative risk (RR) of cancer death for persons over 25 substituting local foods with store- by reduced consumption of local foods bought alternatives preserving calorie intake and MeHg exposures from baseline. (A) Population-wide mean and (B) population-wide mean and select (Wheatley 1997, Furgal et al. 2005). For population percentiles at 400% MeHg increase in local foods. Shaded region (A) and error bars (B) instance, many food advisories target represent model uncertainty around displayed mean value (5–95% CI). Subsidized food and processed whole populations and proposed limits on meat substitution scenarios presented as bounding cases in (A) with vegetables scenario falling in between (omitted for clarity). Increasing MeHg consumption of local foods without exposures in the baseline diet scenario are not considered to increase cancer risks. consideration of the health implications of dietary alternatives (Hydro-Québec 2014, Hydro-Québec Production 2014).

This analysis demonstrates that on cardiovascular and cancer risks and on nutritional status, plausible dietary substitution scenarios create risks greater than they avoid. Neurodevelopmental risks are largely but not completely avoided with store-bought substitution. This suggests that the most effective dietary intervention would encourage local food consumption and avoid excess

MeHg exposures by promoting intake of foods that are relatively low in MeHg at baseline, rich in n-3 fatty acids and vitamins B12 and D and forage predominantly in coastal and marine environments such as salmon.

82 Consumption of local, traditional foods

among Lake Melville Inuit is lower than

among other indigenous communities across

Canada. For example, British Columbia First

Nations consume roughly three times the

quantity of traditional foods as the Lake

Melville Inuit on a per-capita basis (Chan et

al. 2011b). Therefore, health and nutritional

impacts may be greater in other populations.

Finally, this analysis does not address the

psychosocial dimensions of hunting and

fishing and the preparation and consumption

Figure 4-6: Change in nutrient intake for four of traditional foods, loss of access to which isocaloric local food replacement scenarios. Nutrients shown are those for which mean intake is below dietary recommendations corresponding to has been linked to adverse mental health daily values (DV) from US FDA 2013 where available and 500 mg day-1 for n-3 fatty acids (DHA and social outcomes (King et al. 2009, + EPA) (Kris-Etherton et al. 2009). Overall-per capita averages represented by bars and 5th – 95th Kirmayer et al. 2009). Taken together, this percentiles among the population represented by lines. suggests that the promotion of select local alternative foods, particularly among women of childbearing age, is an overall more health- protective intervention than advisories on intake of local foods.

83 Supplemental materials

Table S4-1.1: Nutritional and PCB data for locally caught seafood Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Arctic char liver EFSA n/a 4.7 163 (FL) (2010) d Arctic char Fish, arctic char, Braune et al. 3230 4.9 30.8 muscle (FM) native, meat, raw (2005) e Arctic char roe Fish, roe, mixed 3045 0.1 84.1 (f) (FR) species, raw Fish, cod (scrod), Atlantic cod Braune et al. Atlantic, baked or 3195 5.1 3.7 muscle (FM) (2005) e broiled Fish, salmon, Atlantic salmon EFSA native, king or 5899 0.7 163 liver (FL) (2010) d chinook, liver Fish, salmon, Atlantic salmon Fromberg et al. Atlantic, wild, 3156 46.9 15.8 muscle (FM) (2011) baked or broiled Atlantic salmon Fish, salmon, 5928 1.9 43.2 (f) roe (FR) native, eggs, raw Brook trout liver EFSA n/a 0.8 163 (FL) (2010) d Brook trout Fish, trout, brook, Health Canada 7234 11.7 16.2 muscle (FM) raw (2001) g Brook trout roe Fish, roe, mixed 3045 0.6 44.3 (f) (FR) species, raw Fish, smelt, rainbow Capelin muscle Hording et al. (American, 3065 0.9 104 ± 33.2 (FM) (1997) capelin), baked or broiled Capelin roe Fish, roe, mixed 3045 0.04 283 (f) (FR) species, raw Mollusks, clam, Bocio et al. Clams (SF) mixed species, 3111 0.2 1.2 (2007) boiled or steamed a FL = fish liver; FM = fish muscle; FR = fish roe; SF = shellfish b From Canada Nutrient File c Fraction of total per-capita calories from all locally caught seafood d Value for fish liver e Value from Rigolet NL f Value for freshwater fish g Value for plaice n/a: Data not available and values are calculated as average of other foods in same nutritional category

84 Table S4-1.2: Nutritional and PCB data for locally caught seafood (cont’d) Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Fish, flatfish Flatfish (flounder or sole or Fromberg et al. 3007 0.03 3.5 (FM) plaice), baked or (2011) d broiled Health Canada Itiks (SF) n/a 0.03 0.3 (2001) e Lake trout Fish, trout, brook, 184.1 Guildford et al. 7234 0.9 (FM) raw ± 35.3 (2008) Mollusks, mussel, Bocio et al. Mussels (SF) blue, boiled or 3116 1.5 4.3 (2007) steamed Fish, salmon, Ouananiche Fromberg et al. Atlantic, wild, 3156 0.02 15.8 (FM) e (2011) baked or broiled Porpoise 65,400 ± Gaskin et al. n/a 0.02 blubber (MM) 50,700 (1983) Porpoise liver 1,030 ± Gaskin et al. n/a 0 (MM) 688 (1983) Porpoise meat Gaskin et al. n/a 0.02 929 ± 700 (MM) (1983) Rock cod liver Fish, lingcod, EFSA 5888 1.0 163 (FL) native, liver (2010) f Rock cod Fish, cod (scrod), Braune et al. muscle Atlantic, baked or 3195 1.5 0.9 (2005) g (FM) broiled Mollusks, scallop Scallops Kjølholt and (bay and sea), 5634 0.9 52.2 ± 7.4 (SF) Hansen (1986) h cooked, steamed Sculpin liver EFSA n/a 0 163 (FL) (2010) f Sculpin muscle Fish, sculpin, Muir et al. 5919 0.1 50 (FM) native, raw (1999) a FM = fish muscle; SF = shellfish; MM = marine mammal; FL = fish liver b From Canada Nutrient File c Fraction of total per-capita calories from all locally caught seafood d Value for plaice e Value for shellfish f Value for fish liver g Value for Nain NL h Pristine sites only n/a: Data not available and values are calculated as average of other foods in same nutritional category

85 Table S4-1.3: Nutritional and PCB data for locally caught seafood (cont’d) Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Game meat, native, Seal blubber Johansen et al. ringed seal, blubber, 5781 4.1 252 (MM) (2004) boiled Seal liver Game meat, native, Johansen et al. 5788 2.0 5.2 (MM) ringed seal, liver, raw (2004) Seal kidney Johansen et al. n/a 1.6 0.7 (MM) (2004) Game meat, native, Seal muscle Johansen et al. ringed seal, meat, 5783 5.1 4.1 (MM) (2004) boiled Fish, smelt, rainbow Smelt Hording et al. (American, capelin), 3065 2.7 286 ± 60.6 (FM) (1997) baked or broiled Whale, bowhead, Whale blubber skin and Johansen et al. 35086* 0.06 1,055 (MM) subcutaneous fat (2004) (muktuk) Whale muscle Game meat, whale, Johansen et al. 3648 0 5.5 (MM) raw (2004) Wrinkles Pacific surf, cooked Health Canada 45002474* 0.1 0.3 (SF) periwinkle meat (2001) d a MM = marine mammal; FM = fish muscle; SF = shellfish b Codes with * are from USDA Nutrient Database; other foods are from the Canada Nutrient File c Fraction of total per-capita calories from all locally caught seafood d Value for shellfish n/a: Data not available and values are calculated as average of other foods in same nutritional category

86 Table S4-2.1: Nutritional and PCB data for other local foods Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Cloudberry Bakeapples (FR) 5939 9.42 0 (d) (bakeapple), native Game meat, native, Black bear (TM) 3566 0.9 0 (e) bear, simmered Game meat, native, Caribou (TM) caribou (reindeer), 3578 7.7 0 (e) meat, cooked Egg, duck, whole, 8,531 Duck eggs (EG) 1138* 1.7 (f) fresh, raw ± 4,960 Duck, wild, native, 6,880 Johnstone et Duck muscle (FP) 5931 5.4 cooked ± 4,000 al. (1996) Mallory et Eider muscle (FP) n/a 2.3 1.84 al. (2004) g Goose, domesticated, Goose muscle (FP) 672 12.5 0 (h) meat only, roasted Guillemot eggs n/a 0 471 ± 161 (f) (EG) Guillemot muscle Johnstone et n/a 0.17 380 ± 130 (FP) al. (1996) Braune et al. Gull eggs (EG) n/a 3.6 502.3 (2007) i 1,890 ± Lindberg et Gull muscle (FP) n/a 0.01 1,760 al. (1985) j Labrador tea (FR) n/a 0.06 0 (d) 29,230 Frank et al. Loon eggs (EG) n/a 0.03 ± 39,000 (1983) Frank et al. Loon muscle (FP) n/a 0 4,430 (1983) k Game meat, native, Moose (TM) 3588 9.2 0 (e) moose, roasted a FR = fruit; TM = terrestrial mammal; EG = egg; FP = fowl/poultry b Codes with * are from USDA Nutrient Database; other foods are from the Canada Nutrient File c Fraction of total per-capita calories from all other locally caught food d Negligible levels in fruit e Negligible levels in terrestrial mammals (Johnstone et al. 1996, Johansen et al. 2004, Hassan et al. 2013) f Egg/muscle ratio for guillemot applied g Value from Rigolet NL h Negligible (Tsuji et al. 2008) i 2004 data j Values from Northern Sweden k Healthy males and females, pectoral muscle n/a: Data not available and values are calculated as average of other foods in same nutritional category

87 Table S4-2.2: Nutritional and PCB data for other local foods (cont’d) Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Game meat, native, Okalik/Hare (TM) 3596 0.4 0 (e) rabbit, wild, cooked Owl muscle (FP) 0.01 n/a Spruce grouse, Partridge muscle native, meat, 10.5 0 (d) (FP) cooked Game meat, native, Polar bear meat polar bear, meat, 5834 0.03 0 (e) (TM) boiled Game meat, native, Rabbit (TM) rabbit, wild, 3596 2.3 0 (e) cooked Red berries (FR) n/a 12 0 (f) Sandpiper (FP) n/a 0.4 0 (g) Johnstone et Snowbird (FP) n/a 0 3 ± 2.3 al. (1996) 5,200 Niemi et al. Tern eggs (EG) n/a 1.2 ± 1,425 (1986) Niemi et al. Tern muscle (FP) n/a 0.23 5,100 ± 825 (1986) h Wild blackberries Blackberry, raw 1.1 0 (f) (FR) Wild blueberries Blueberry, raw 10.2 0 (f) (FR) Wild raspberries Raspberry, wild, 5.6 0 (f) (FR) raw Other picked berries n/a 2.2 0 (f) (FR) Other wild plants n/a 0.6 0 (f) (FR) a FP = fowl/poultry; TM = terrestrial mammal; FR = fruit; EG = eggs b Codes with * are from USDA Nutrient Database; other foods are from the Canada Nutrient File c Fraction of total per-capita calories from all other locally caught food d Negligible (Lindberg et al. 1985) e Negligible levels in terrestrial mammals (Johnstone et al. 1996, Johansen et al. 2004, Hassan et al. 2013) f Negligible levels in fruit g Negligible (Johnstone et al. 1996) h Post-fledge values n/a: Data not available and values are calculated as average of other foods in same nutritional category

88 Table S4-3.1: Nutritional and PCB data for store-bought seafood Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Battered Sea Cuisine, breaded cod 4511– Health Canada 11.5 1.3 cod (FM) tender flaky fillets 9629* (2001) d Battered Gorton’s, haddock 4504– Health Canada haddock 0.9 1.3 breaded fish sticks 5406* (2001) d (FM) Brook trout Health Canada Fish, trout, brook, raw 7234 0.6 16.2 (FM) (2001) e Caned Mollusks, oyster, eastern Health Canada oysters (blue point), wild, canned, 3121 0.7 1.6 ± 1.9 (2007) f (SF) solids and liquid Canned Fish, salmon, chum (keta), Health Canada salmon canned, drained, solids 3218 3.7 0.9 (2001) g (FM) with bone, salted Canned Fish, tuna, light, canned in Health Canada 3131 13.1 0.9 tuna (FM) water, drained, unsalted (2001) g Catfish Fish, catfish (wolffish), Health Canada 3170 0 16.2 (FM) Atlantic, baked or broiled (2001) e Mollusks, clam, mixed Bocio et al. Clams (SF) 3111 1.5 1.2 species, boiled or steamed (2007) Crustaceans, crab, red, Health Canada Crab (SF) 3238 3.1 0.3 steamed (2001) h Fish sticks Fish, fish sticks, frozen, Health Canada (pollock) 3006 3.7 1.3 prepared (2001) d (FM) Fresh cod Fish, cod (scrod), Atlantic, Health Canada 3195 18.3 1.3 (FM) baked or broiled (2001) d Fresh Fish, pollock, Atlantic Health Canada pollock (Boston blue), baked or 3152 1.5 1.3 (2001) d (FM) broiled Fresh tuna Fish, tuna, skipjack (aku), Bocio et al. 3166 1.2 14.6 (FM) baked or broiled (2007) a FM = fish muscle; SF = shellfish b Codes with * are from USDA Nutrient Database. Other foods are from the Canada Nutrient File c Fraction of total per-capita calories from all store-bought seafood d Value for marine fish e Value for freshwater fish f Value for farmed g Value for canned fish h Value for shellfish

89 Table S4-3.2: Nutritional and PCB data for store-bought seafood (cont’d) Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Fish, herring, Fromberg et al. Herring (FM) Atlantic, baked or 3015 3.0 15.8 (2011) broiled Crustaceans, lobster, American Health Canada Lobster (SF) 3210 3.4 0.3 (northern), boiled or (2001) d steamed Mollusks, mussel, Bocio et al. Mussels (SF) blue, boiled or 3116 8.7 4.3 (2007) steamed Fish, trout, rainbow, Rainbow trout Fromberg et al. farmed, baked or 3187 0.9 10 (FM) (2011) broiled Fish, salmon, Fromberg et al. Salmon (FM) Atlantic, wild, baked 3156 8.7 15.8 (2011) or broiled Fish, sardine, Atlantic, canned in Bocio et al. Sardines (FM) 3203 5.0 24.3 oil, drained solids (2007) with bone Mollusks, scallop Kjølholt and Scallops (SF) (bay and sea), 5634 4.7 52.2 ± 7.4 Hansen (1986) cooked, steamed e Crustaceans, shrimp, Bocio et al. Shrimp (SF) mixed species, 3212 5.9 0.5 (2007) boiled or steamed Health Canada Skate (FM) n/a 0 1.3 (2001) f Fish, flatfish (flounder or sole or Health Canada Sole (FM) 3007 0.05 1.3 plaice), baked or (2001) f broiled Fish, tilapia, baked Health Canada Tilapia (FM) 5697 0.1 1.8 or broiled (2007) g a FM = fish muscle; SF = shellfish b Codes with * are from USDA Nutrient Database; other foods are from the Canada Nutrient File c Fraction of total per-capita calories from all store-bought seafood d Value for shellfish e Pristine sites only f Value for marine fish g Value for farmed n/a: Data not available and values are calculated as average of other foods in same nutritional category

90 Table S4-4.1: Nutritional and PCB data for food subsidized under Nutrition North Name in Baseline Total PCBs Food name Database nutritional calories Mean ± SD (nutritional category) a code b Reference database (%) c (ng g-1 ww) Apple, Gala, raw, All fresh fruits (FR) 7216 6.1 d 0 (e) with skin Blueberry, frozen, All frozen fruits (FR) 1706 0.04 0 (e) unsweetened All fresh vegetables, Brussels sprouts, except whole pumpkins 2379 4.8 d 0 (e) boiled, drained (VE) All frozen vegetables Broccoli, frozen, (excluding French fries, chopped, boiled, 2377 0.08 0 (e) etc.) (VE) drained All-purpose flour, whole- wheat flour, rye flour and Grains, wheat other semi-perishable flour, white, all 4501 0 0 (e) flours (except cake flour purpose, bleached and pastry flour) (GR) Health Pork, cured, back Bacon (PM) 7219 4.8 f 0.4 Canada bacon, pan-fried (2001) g Bread (except garlic Bread, white, 4066 8.3 0 (e) bread) (GR) commercial Bread products without English muffin, 3906 2.9 h 0 (e) filling or coating (GR) wheat Health Butter (DA) Butter, regular 118 1.4 i 1.5 Canada (2001) Cheese (including block Health cheese, shredded cheese Cheese, cheddar 119 1.2 i 0.5 Canada and cottage cheese) (DA) (2001) j Health Milk, fluid, Chocolate milk (DA) 69 1.7 0.1 Canada chocolate, whole (2001) k a Food name/category from the Nutrition North program; FM = FR = fruit; VE = vegetables; GR = grains; PM = processed meat; DA = dairy b From the Canada Nutrient File c Fraction of total per-capita calories from all foods subsidized under Nutrition North d Retail and consumer waste = 40% (Gustavsson et al. 2011) e Assumed negligible in fruit, vegetables, legumes and grains f Retail and consumer waste = 15% (Gustavsson et al. 2011) g Value for cured pork h Retail and consumer waste = 29% (Gustavsson et al. 2011) i Retail and consumer waste = 15.5% for all dairy based on value for milk (Gustavsson et al. 2011) j Value for cheddar cheese k Value for whole milk

91 Table S4-4.2: Nutritional and PCB data for food subsidized under Nutrition North (cont’d) Name in Baseline Total PCBs Food name Database nutritional calories Mean ± SD (nutritional category) a code b Reference database (%) c (ng g-1 ww) Lasagna with Health Combination foods (e.g., meat and 5870 0.5 0.08 Canada lasagna) sauce, frozen (2001) d Cook-type cereals (e.g., Cereal, hot, oatmeal and porridge) 1432 0.03 e 0 (f) oats, porridge (GR) Health Cooking oils (e.g., canola, Vegetable oil, 451 1.0 0.2 Canada peanut, olive and linseed) canola (2001) g Crackers, crisp bread, Snacks, rice hard bread, Pilot biscuits, cakes, Melba toast, arrow-root crackers 5493 1.1 e 0 (f) biscuits and Social Tea (include mini biscuits (GR) rice cakes) Cream, sour, Health Cream, sour cream, cream cultured, 18% 152 1.2 h 0.2 Canada cheese (DA) M.F. (2001) i Dried fruits (e.g., grapes, Apple, dried, dates, cranberries and sulphured, 1490 0.2 0 (f) apricots) (FR) uncooked Egg, chicken, Health Eggs and egg substitutes whole, fresh 125 4.4 j 0.2 Canada (EG) or frozen, raw (2001) Plant-based beverage, soy, Enriched soy milk 6720 0.2 h 0 (f) enriched, all flavours Fresh and frozen meat Health other than side bacon and Beef, ground, 2683 21.7 0.2 Canada products that are breaded, lean, raw (2001) k battered or in pastry (RM) a Food name/category from Nutr. North; GR = grains; DA = dairy; FR = fruit; EG = eggs; RM = red meat b From the Canada Nutrient File c Fraction of total per-capita calories from all foods subsidized under Nutrition North d Value for frozen entrees e Retail and consumer waste = 29% (Gustavsson et al. 2011) f Assumed negligible in fruit, vegetables, legumes and grains g Value for cooking fats and salad oils h Retail and consumer waste = 15.5% based on value for milk (Gustavsson et al. 2011) i Value for cream j Retail and consumer waste = 15% based on value for meat (Gustavsson et al. 2011) k Value for beef steak

92 Table S4-4.3: Nutritional and PCB data for food subsidized under Nutrition North (cont’d) Datab Baseline Total PCBs Food name Name in nutritional ase calories Mean ± SD (nutritional category) a database Reference code b (%) c (ng g-1 ww) Fresh and frozen pasta Pasta, fresh- (except combined foods refrigerated, plain, as 4502 0 0 (d) containing pasta) (GR) purchased Fast foods, pizza, Health cheese, meat and Fresh and frozen pizzas 5862 4.9 0.3 Canada vegetable, regular (2001) crust, frozen, cooked Fresh and frozen poultry Chicken, broiler, e.g., chicken, turkey, Health breast, skinless, goose) other than 7322 5.8 0.2 Canada boneless, meat, products that are breaded, (2001) grilled battered or in pastry (FP) Fresh and frozen seafood, Fish, tuna, white, Counted Health other than products that canned with water, 3084 in Table 1.3 Canada are breaded, battered or drained, salted S4-3 (2001) in a pie crust (FM) Health Milk, fluid, partly Fresh milk (DA) 61 2.6 e 0.1 Canada skimmed, 2% M.F. (2001) f Frozen French fries, Potato, french-fried, Health home fries and similar frozen, shoestring, 6517 5.3 0.1 Canada potato-based products heated in oven (2001) Health Ice cream, iced milk, iced Dessert, frozen, ice 4288 2.6 g 0.2 Canada yogourt and sorbet (DA) cream, chocolate (2001) Apple juice, canned Individually wrapped or bottled, unsweetened juice (all unsweetened, calcium 7419 0.8 0 (d) sizes) and Vitamin C and D added Shortening, Health household, Lard and shortening 539 1.5 0.2 Canada unspecified vegetable (2001) h and animal oils a Food name/category from the Nutrition North program; GR = grains; FP = fowl/poultry; FM = fish muscle; DA = dairy b From the Canada Nutrient File c Fraction of total per-capita calories from all foods subsidized under Nutrition North d Assumed negligible in fruit, vegetables, legumes and grains e Retail and consumer waste = 15.5% (Gustavsson et al. 2011) f Value for whole milk g Retail and consumer waste = 15.5% based on value for milk (Gustavsson et al. 2011) h Value for cooking fat and salad oils

93

Table S4-4.4: Nutritional and PCB data for food subsidized under Nutrition North (cont’d) Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Margarine, tub, Health Margarine hydrogenated, canola 7575 1.5 0.1 Canada oil (2001) Melted cheese Kraft Cheez Whiz Health spreads (e.g., Pasteurized Process 1188* 0.04 0.384 Canada Cheez Whiz) Cheese Sauce (2001) d Peanut butter and Peanut butter, natural 6289 0.7 0 (e) other nut butters Health Dip, cream cheese Perishable dips 6786 0.5 f 0.2 Canada base (2001) g Milk, evaporated, Health Powdered and whole, canned, 140 0.02 0.07 Canada evaporated milk undiluted, 7.8% M.F. (2001) Kraft Velveeta Health Processed cheese Pasteurized Process 1191* 1.8 0.4 Canada (e.g., Velveeta) Cheese Spread (2001) Ready-to-eat Cereal, ready to eat, breakfast cereals 1258 0.8 0 (e) Life, Quaker (GR) Salad dressing, Health Salad dressing and mayonnaise type, 527 1.3 0.1586 Canada mayonnaise commercial, regular (2001) g Tofu and other vegetable-based meat substitutes Tofu, silken, firm 4911 0 0 (e) (e.g., vegetable patties and nut burgers) Milk, fluid, whole, Health pasteurized, UHT milk (DA) 113 1.0 h 0.1 Canada homogenized, 3.25% (2001) i M.F. a Food name/category from the Nutrition North program; DA = dairy; GR = grains b Codes with * are from USDA Nutrient Database; other foods are from the Canada Nutrient File c Fraction of total per-capita calories from all foods subsidized under Nutrition North d Value for processed cheese e Assumed negligible in fruit, vegetables, legumes and grains f Retail and consumer waste = 15.5% based on value for milk (Gustavsson et al. 2011) g Value for cooking fat and salad oils h Retail and consumer waste = 15.5% (Gustavsson et al. 2011) i Value for whole milk

94 Table S4-4.5: Nutritional and PCB data for food subsidized under Nutrition North (cont’d) Food name Baseline Total PCBs Name in nutritional Database (nutritional calories Mean ± SD database code b Reference category) a (%) c (ng g-1 ww) Unsweetened nuts Nuts, mixed nuts, dry 2577 0.6 0 (e) and grains (GR) roasted with peanuts Yogourt and Health Yogourt, plain (2- yogourt drinks 6961 1.3 f 0.2 Canada 3.9% M.F.) (DA) (2001) a Food name/category from the Nutrition North program; DA = dairy; GR = grains b Codes with * are from USDA Nutrient Database; other foods are from the Canada Nutrient File c Fraction of total per-capita calories from all foods subsidized under Nutrition North

Table S4-5: Foods used for junk food substitution scenario Food name Database code a Snacks, potato chips, dried potatoes, plain 4360 Cake, snack cake, cream-filled, chocolate with icing (frosting) 3784 Alcohol, beer, regular, (5% alcohol by volume) 2943 a From the Canada Nutrient File

Table S4-6: Dose-response relationships for neurodevelopmental (IQ) endpoint Parameter and definition a Description Reference -1   Δ IQ in child per µg day Δ      maternal MeHg intake -1  –Δ IQ in child per µg g Δ Hg in Rice et al.  !   "  maternal hair (2010) Intake-to-hair conversion (day g-1, Calder et  participant-specific) al. (2016) Cohen et  !    
 Δ IQ in child per g day-1 Δ DHA  al. intake by mother

" (2005b) a LN = lognormal; T = triangular; RR = relative risk

95

Table S4-7: Dose-response relationships for cardiovascular endpoint Parameter and definition a Description Reference RR of cardiovascular death per 100 Engell et al. 7 5 :  6 :   mg day-1 Δ intake of n-3 fatty acids b,c (2013) RR of all cardiovascular death for 1 !, : 8 !, 9  % µg day-1 Δ MeHg intake d !, !,  %  RR of sudden cardiovascular death  :
-1 %  for a 1 µg day Δ MeHg intake

!, 5 6 RR of sudden cardiovascular death Virtanen et  ;
:  
:  < -1 b % per 0.5 µg g Δ hair Hg al. (2012) Zipes and Fraction of cardiovascular deaths that  :  Wellens are sudden (1998) $+*
.+'2 5 6  ; :    RR of cardiovascular death per 85 g Pan et al. :  < day-1 Δ red meat intake b,e (2012) #0/)

.+'2 5 6  ; :    RR of cardiovascular death per 29 g Pan et al. :  < day-1 Δ processed meat intake b,f (2012)  03-24+,;5 :  6 RR of cardiovascular death per 106 g Wang et al.  -1 b,g :  < day Δ fruit and vegetable intake (2014) RR of cardiovascular death per 28 g Grosso et "321;5 :   6 :  <  day-1 Δ nut intake b,h al. (2015) RR of cardiovascular death per 7 g Threapleton  -(+0;5 :   6 :  <  day-1 Δ fiber intake b,i,j et al. (2013) %/*-3. 5 6  ; :    RR of cardiovascular death per 100 Strazzullo :  < mmol (6 g) day-1 Δ sodium intake b,j,k et al. (2009) RR of cardiovascular death per 4.5 g Mozaffarian & ;5 :   6 : <  day-1 Δ trans fatty acid intake b,j,l et al. (2006) a LN = lognormal; T = triangular; RR = relative risk b Distribution calculated from reported mean and confidence intervals c RR confined to the interval [0.05, 20] based on the 95% confidence limit on the lowest relative risk identified in the literature for cardiovascular death associated with elevated n-3 fatty acid intake (Albert et al. 2002) d RR confined to the interval [0.2,5.4] (Salonen et al. 1995) e RR confined to the interval [0.5,2] f RR confined to the interval [0.28,3.5] (Whiteman et al. 2007) (ischemic heart disease); serving size calculated as average of processed foods g RR confined to the interval [0.65,1.54] h RR confined to the interval [0.25,4] (Guasch-Ferré et al. 2013) i RR confined to the interval [0.5,2] j RR of mortality ≈ RR of morbidity (Forouzanfar et al. 2015) k RR confined to the interval [0.2,4.9] l RR confined to the interval [0.34,2.9]; 4.5 g trans fatty acids ≈ 2% of daily energy intake for a 2,000 kcal day-1 diet.

96

Table S4-8: Dose-response relationships for cancer Parameter and definition a Description Reference %�' %�' Combined RR of death from all cancers,  5 7(8 ( where i = [CR; hep; tot]  %�' '&-  4 3#** RR of all cancer death from RR of 7'&-8 5
#**
hepatic cancer from PCBs ) RR of all cancer death from RR of %�' ! 
4 3#** 7!8 5 colorectal cancer, where j = [Red meat; ) #**
Proc. meat] 6"(0 %�'   
RR of death from total cancers for a 1 IU  5 -1 e 
70,08 day Δ vitamin D intake   3
 $#/&'&- RR of hepatic cancer death for a  5 -1 -1 d,f $#/&'&- 1 µg kg day Δ PCB intake Excess risk of developing hepatic cancer US EPA   5   for 1 µg day-1 Δ PCB intake (central (1996) estimate) !&%
+� 1 2  7 5    RR of colorectal cancer death per 100 g Chan et al. 5 8 day-1 Δ red meat intake b,c,d (2011a) .,$

+� 1 2  7 5    RR of colorectal cancer death per 50 g Chan et al. 5  8 day-1 Δ processed meat intake b,c,d (2011a)

6"(0 1 2 RR of death from all cancers per 25 nmol Giovannucci  57 5   5  8 L-1 Δ plasma 25(OH)D b et al. (2006) nmol L-1 plasma 25(OH)D per IU day-1 Giovannucci  5   vitamin D intake et al. (2006) Lifetime probability of death from cancer Howlader et  5   #** (all types) al. (2016) Lifetime probability of death from  5  Idem '&- colorectal cancer Lifetime probability of death from  5   Idem ! hepatic cancer Lifetime probability developing hepatic  5  Idem $#/&'&- cancer Calder et al.  Participant-reported body weight (kg) (2016) a LN = lognormal; T = triangular; RR = relative risk b Distribution calculated from reported mean and confidence intervals c Change in risk plateaus at change in consumption of 140 g day-1 (Chan et al. 2011a) d Assuming RR of case = RR of death e RR confined to interval [0.30, 3.33] based on 95% confidence limit of lowest relative risk identified in the literature for colorectal cancer associated with elevated intake of vitamin D (Garland et al. 2007), where RR = OR/(1–pcancer (CR) +pcancer (CR)×OR) (Grant 2014) f Unconstrained RR due to wide range in the magnitude of attributable risk (Ojajarvi 2001)

97 5
Conclusions

This thesis has integrated biogeochemical, fluid mechanics, human exposures and health impacts modeling into an integrated framework to forecast environmental and human health risks from artificial hydroelectric development. A ‘global boom’ (Zarfl et al. 2014) in demand for hydropower is increasing overall risks from MeHg exposures. This makes the development of tools to screen potential projects and forecast risks from development and subsequent dietary interventions increasingly critical.

5.1
Key findings

Chapter 2 demonstrates that increased demand for hydroelectric power poses widespread risks for indigenous populations in Canada, yet little has been done to forecast these risks or use them to inform development decisions. This work demonstrates that soil organic carbon can be used to forecast the magnitude of the post-impoundment MeHg pulse, and probabilistic fate-and- transport modeling can produce a forecast of biotic MeHg concentrations and human exposures.

This also implies that removal of carbon-rich topsoil may be an effective mitigation measure. In the case of the Lake Melville Inuit, mean population-wide exposures may show moderate increases, leaving many below regulatory thresholds. However, relatively highly exposed individuals at baseline are pushed well beyond regulatory thresholds for subacute effects. Risk assessments must therefore consider the full distribution of baseline exposures to quantify the range of human health risks.

Chapter 3 shows that perturbations in freshwater MeHg concentrations result in perturbations far into the downstream environment, raising levels in the stratified surface layer well beyond the range of seasonal variability. Therefore, water column MeHg increases in the estuarine environment should be detectable after the pulse, enabling evaluation of model

98 performance in the estuarine zone. Whereas Chapter 2 evaluated a homogeneous surface layer, this section demonstrates that effects will persist far downstream and into the portion of Lake

Melville more closely associated with traditional Inuit fishing activities. This work also describes

MeHg impacts using an exponential decay curve, whereas Chapter 2 considered only peak fluxes. Previous work demonstrates that this upper layer controls uptake of MeHg into local food webs, meaning upstream perturbations will have implications for MeHg accumulation for biota in downstream coastal environments.

Chapter 4 demonstrates that food consumption advisories may not be a health-protective intervention among populations with increasing exposures to MeHg. Food consumption advisories are a common policy response to increased exposures to bioaccumulative contaminants, yet few analyses examine the countervailing risks of dietary interventions. Local food consumption data collected in Chapter 2, supplemented with data for store-bought food intake, nutritional data for all foods were combined with dose-response models from the literature. The integrated analysis demonstrates that for a wide range of MeHg increases in local foods and for a number of plausible substitution scenarios, dietary interventions reduce neurodevelopmental risks (for children with high prenatal exposures) but increase cancer and cardiovascular risks relative to the baseline diet. Therefore, because food consumption advisories tend to be deployed across whole populations, they may not be health-protective on the whole.

5.2
Future work

Chapter 2 presents a forecast for MeHg levels in the water column that are probabilistically distributed to reflect uncertainty about the mean value of certain parameters in the environmental model. Experiments are currently underway to constrain model estimates for MeHg fluxes from flooded soils. These experiments will also evaluate the effect of removing carbon-rich topsoil

99 from the flooded environment and characterize the time course of the MeHg pulse over several weeks. This will therefore constrain the range of forecasts made in Chapter 2 and allow for the development of a soil-removal scenario that might imply lower post-flooding exposures.

Rising temperatures and increased productivity and water column stratification in northern coastal environments will amplify the uptake of MeHg into the food web relative to present day. However, reduced ice cover will enhance photodegradation of MeHg. The mechanistic model described in Chapter 3 can be expanded to model uptake of MeHg into the food web and to compare the effects of hydroelectric development with the effects of climate stressors. The net effect of these and other processes on net MeHg production and on uptake into the food web will allow for a quantitative forecast of the effects of climate change on MeHg exposures.

Chapter 4 found that there would likely be health benefits from reduced consumption of higher-MeHg local foods among women of childbearing age. However, dietary advisories have unpredictable effects and have resulted in generalized loss of confidence in local foods (Furgal et al. 2005). Because reduced local food intake results in elevated cardiovascular and cancer risks, even given higher MeHg exposures, dietary advisories may not be health-protective on the whole. Research is therefore needed on how public health messages may be targeted to promote health-protective local food choices among vulnerable populations without undermining overall confidence in the quality and nutritional value of the traditional diet within indigenous populations.

100 6
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