ECOLOGICAL RISK ASSESSMENT FOR A MINE PIT LAKE, NEVADA,

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            Proceedings of the 20 Annual British Columbia Mine Reclamation Symposium in Kamloops, BC, 1996.
                                  The Technical and Research Committee on Reclamation
           ECOLOGICAL RISK ASSESSMENT FOR A MINE PIT LAKE, NEVADA, USA
                                               Jennifer R. Sampson
                                                  Ron S. Mellott
                                             Robert A. Pastorok, Ph.D.

                                            PTI Environmental Services
                                          15375 SE 30th Place, Suite 250
                                              Bellevue,WA 98007


ABSTRACT
Closure of an open pit gold mine in central Nevada, USA, will result in cessation of dewatering at the mine and
formation of a pit lake. The future pit lake will occur in a desert shrub community and have no surface water
inflows or outflows. An ecological risk assessment far the pit lake was conducted as part of an environmental
impact statement required for expansion of mine facilities. Because the pit lake does not yet exist, ecological risks
were estimated from the results of predictive water quality models and measurement of chemical concentrations in
the rock wall of the pit. The exposure of birds and mammals to individual metals through food and water
ingestion was estimated on the basis of concentrations of metals in water and bioconcentration factors and
through sediment ingestion was estimated from concentrations of metals in wall rock. Exposure estimates, which
were expressed as daily rates of intake of individual metals, were compared to no-effects and lowest-effects doses
reported in the literature for those metals. Results of the risk assessment demonstrated minimal risks to dabbling
ducks from exposure to zinc and no risk to other wildlife from chemical exposures.


INTRODUCTION
Expansion of gold mining activities that may result in impacts to U.S. public resources such as wildlife or
groundwater is subject to the requirements of an environmental impact statement (EIS). The purpose of
preparing an EIS is to determine whether proposed activities will result in adverse impacts on associated fish,
wildlife, and habitats in the vicinity of the proposed action and to determine the magnitude of those impacts. This
paper documents the successful implementation of ecological risk assessment (ERA) to meet the requirements for
permitting the expansion of a gold mine in Nevada. TID our knowledge, this is the first application of a predictive
ERA to a mine pit lake. This experience demonstrates the value of ERA in characterizing potential ecological
impacts and reducing uncertainties in the permitting process.


The proposed action includes cessation of mining activities within a gold quarry and discontinuation of pit
dewatering, resulting in the formation of a pit lake. Because the pit lacks surface water inflows and outflows and
is located in an arid region where annual evaporation significantly exceeds precipitation, naturally occurring
chemicals in the groundwater as well as chemicals brought into solution by the breakdown of wall rock will
concentrate over time. To the extent that formation of a lake in an arid desert environment creates an attractive
habitat for waterfowl and passerine birds, as well as a drinking water source for large mammals and raptors,




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increasing concentrations of metals may lead to relatively high exposures of wildlife to potential toxicants. The
ERA was used to estimate exposures of representative species expected to use the pit lake (receptors) to metals in
the pit lake and to compare predicted exposures to toxicity reference values (TRVs) for ecological receptors.


Hydrological and water chemistry models were used to predict groundwater inflow rates and chemical
concentrations, respectively. However, this paper presents only the results of those models as they relate to the
ERA and is focused on the risk assessment approach, models, and results. Methods and assumptions of the
hydrological models (HSI 1994) and the water quality models (PTI 1995a) are documented elsewhere. A more
complete discussion of the ERA methods, assumption!!, and uncertainties is provided by PTI (1995b).


STUDY SITE
The pit lake is located in the Great Basin, within a subunit of the Basin and Range Physiographic Province
(Ryser 1985). The rim of the mine pit is 6,500 ft above mean sea level. The vegetation community at the mine
site is dominated by grass species, big sagebrush (Artemesia tridentata), and open stands of single-leaf pinyon
pine (Pinus monophylld) and Utah juniper (Juniperus osteosperma) (Ryser 1985). The pit lake is expected to fill
with water from underground sources and precipitation to a maximum depth of 325 ft by the end of 159 years, at
which time the pit lake will be considered to have reached hydraulic equilibrium (HSI 1994; PTI 1995a). The
lake surface is predicted to rise another 3 ft during the ensuing 170 years. Thus, the surface of the pit lake is
predicted to rise at a rate of 8.8 ft/year during the first 20 years following closure of the mine, 2 ft/year for the
following 56 years, and 0.3 ft/year for the subsequent 83 years (HSI 1994). At equilibrium, the surface of the pit
lake is predicted to be 700-1,000 ft below the surrounding land surface (HSI 1994) and to encompass a surface
area of approximately 155 acres.


The initial rapid rise of water (8.8 ft/year or greater) arid variation in water level is likely to preclude development
of significant shallow-water habitats and associated aquatic communities (i.e., rooted aquatic macrophytes and
benthic macroinvertebrates) that would attract wildlife. As hydrologie conditions approach equilibrium, aquatic
plant and invertebrate communities may become established along the perimeter of the pit lake. After 76 years,
the shallowest submerged bench could create a shallow-water zone lake of approximately 9 acres around the pit,
which could sustain rooted macrophytes and provide !habitat for aquatic invertebrates, shorebirds, and dabbling
ducks. Small patches of vegetation may inhabit the lake perimeter at any point after mine closure.




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METHODS
Ecological Risk Assessment
ERA consists of a problem formulation phase (including description of the site and habitats, listing of chemicals
of potential concern, identification of measurement and assessment endpoints, and selection of receptors),
exposure assessment, effects assessment, and risk characterization (U.S. EPA 1992). Both a screening-level risk
assessment (to identify the chemicals expected to occur in pit lake water that will be significantly below
concentrations that are hazardous to wildlife) and a food-web exposure model were used in the ERA for the pit
lake. The principal difference between the two approaches is that the screening-level risk assessment uses highly
conservative assumptions and readily available screening values so that those metals posing no risk to wildlife can
be identified and dismissed from further analysis with confidence. A food-web model incorporating more realistic
exposure assumptions was used to evaluate metals predicted to occur at concentrations greater than screening
values.


Chemicals of Potential Concern
The chemicals selected for evaluation in the risk assessment were those measured in the water from developed
wells after the beginning of 1993. The analyte list corresponded to the Nevada Division of Environmental
Protection (NDEP) Profile I analyte list used for mining water pollution control permits.


Assessment and Measurement Endpoints
The assessment endpoint for this risk assessment was the reproductive potential of the population of each receptor
species. The indicator of effects was the reproductive toxicity of each chemical to each receptor species. Ingested
doses, or TRVs, associated with reduced viability of embryos, reduced viability or survivorship of young, or
reduced fecundity were the measurement endpoints for this evaluation.


Selection of Receptors
Modeling the exposure for all species that may use the pit lake as breeding or foraging habitat or for drinking is
impractical and unnecessary. A subset of species expected to use the pit lake was selected to represent species
protected by federal or state laws and species with societal value. Receptors also reflect all relevant exposure
pathways, including ingestion of water, aquatic vegetation, aquatic invertebrates, and sediments. Exposures to
wildlife could be elevated if fish were present in the pit lake because fish bioaccumulate some of the more toxic
metals (e.g., mercury). It was assumed for this risk assessment that no fish would be present in the pit lake




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because an 8-ft security fence topped with barbed wire surrounded by a rock berm would be installed to prevent
stocking of the pit lake with fish. Therefore, fish-eating wildlife were not included in the list of selected receptors.


Screening-Level Risk Assessment
Two sets of screening criteria were applied: one for mammals and one for birds. To screen the list of constituents
for mammals, highest median concentrations of pit lake constituents predicted for each time period were
compared to drinking water standards for the protection of human health. Drinking water standards are based on
a 70-kg mammal (human) consuming 2 L/day every day for 70 years. Chemicals that are known to be
carcinogenic are regulated to a risk level of 10-5. Human health drinking water standards represent a conservative
benchmark for the protection of large mammals.


To screen the list of constituents for birds, toxicological benchmarks were derived from the specific exposure
parameters and no-observed-adverse-effects levels (NOAELw) for mallard ducks. Because mallards could
consume both plants and insects from the pit lake, they are likely to be the avian receptor with the greatest
exposure potential. Benchmark values for mallards were derived with the following equation:




It was assumed that mallards obtain 92 percent of their diet from plante (41 percent) and insecte (51 percent)
inhabiting the pit lake (with the remaining fraction of the diet from upland sources) and that chemicals are




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absorbed as efficiently by wild mallards from wild foods and water as they are by laboratory animals given
laboratory foods.


Exposure Assessment
The exposure assessment was based on the results of the pit lake water quality model (PTI 1995a) and
concentrations of metals in wall rock, as well as assumptions concerning the behavior of receptors and their
expected uses of the pit lake. Described below are the methods used to determine concentrations of metals in each
medium and to calculate the daily dose to receptors of those metals that did not pass the screening criteria used in
the food-web model. Exposure assumptions are based on a review of the literature and conversations with
wildlife experts concerning the behavior and food requirements of each receptor species.


Metal Concentrations in Water
Water chemistry models (HSI 1994; PTI 1995a) were used to predict the concentrations of metals during the first
330 years following closure of the mine. Metals for which concentrations, were modeled were those on the NDEP
Profile I analyte list detected in groundwater samples and those associated with mine activities. The 330-year
postclosure period was subdivided into short-term (0-159 years) and long-term (160-33O years) modeling
periods. Exposure estimates presented here were derived from the highest value of the median predicted
concentration of each metal for 159 years and 330 years postclosure. The methods and assumptions used to
predict pit lake water chemistry are described by PTI (1995a).


Metal Concentrations in Sediment
Average concentrations of aluminum, mercury, selenium, silver, and zinc in wall rock were used as estimates of
concentrations of metals in sediment because it is probable that wall-rock erosion and bench decomposition will
contribute the majority of sediments to the pit lake, and contributions from atmospheric deposition of dust will be
negligible. In addition, the estimated concentrations of metals in sediment derived from the water column
(chemical precipitates and organic detritus) were within the range of concentrations observed in wall rock (PTI
1995b).


Metal Concentrations in Biota
Bioconcentration factors (BCFs) derived from the literature were used to predict the concentrations of each metal
in aquatic invertebrates and plants. The predicted conœntration of a metal in pit lake water was multiplied by its




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BCF, as described in Equations 3 and 4, to provide an estimate of the concentration of the metal in the aquatic
animal or plant. BCFs are reported in liters per kilogram (dry weight).


Food-Web Exposure Model
For those chemicals predicted to occur at concentrations greater than screening levels, the daily rate of ingestion
of each chemical by individual receptors was estimated using more realistic exposure parameters incorporated
into a food-web exposure model as follows:




For receptors expected to consume aquatic invertebrates and aquatic plants, C; values for these food sources were
estimated by multiplying the expected concentration of the metal in water (Cp in milligrams per liter) by the BCF
of the food organism (liters per kilogram of the food organism). The term Cplants in the food-web exposure
model then becomes:




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                                             CP x BCFinvertebrates                                             (4)




Absolute gastrointestinal absorption efficiency for a chemical varies depending on the form and the matrix in
which a chemical occurs. Absorption of metals from laboratory foods is expected to be different than absorption
of metals from wild foods or from sediments. The relative gastrointestinal absorption efficiency (A;) reflects the
difference between absorption of metals from wild food or sediment and absorption of chemicals from laboratory
foods. Site-specific data on the relative absorption efficiency of metals by the receptors consuming food from the
pit lake are not available. On the basis of PTI (1994), ATSDR (1994), and Pascoe et al. (1994), bioavailability
from dietary sources in the wild was assumed to be less than bioavailability in the laboratory because chemicals
in wild foods may be more tightly bound to cellulose, protein, and other substances than the soluble form of a
chemical spiked into laboratory food or water. The relative absorption efficiency of chemicals from both diet and
soil in the field is assumed to be one-half (0.5) the absorption efficiency in the laboratory. Relative absorption
efficiency from water is assumed to be 1 .0. Other key exposure assumptions made on the basis of natural history
of receptors are summarized in Table 1.


Effects Assessment
TRVs for metals were derived from the toxicological literature. Both NOAELs and lowest-observed-adverse-
effects levels (LOAELs) were used, depending on which values were available. TRVs reported in the literature
were extrapolated to derive species-specific TRVs for each receptor species using the method described by
Opresko et al. (1994). Species-specific TRVs (expressed as NOAELw or LOAELw) were either used to derive
the toxicological benchmarks or used directly as a basis for comparison for calculating hazard quotients as
described below.


Effects of alkalinity, calcium carbonate, chloride, hydrogen ions, magnesium, potassium, sodium, sulfate, and
total dissolved solids on mammals were assumed to be negligible, because it was assumed that mammals would



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              TABLE 1. VALUES FOR BODY WEIGHT AND FOOD, WATER, AND
                      SEDIMENT INGESTION RATES OF RECEPTORS




find saline water unpalatable and would avoid drinking it. To evaluate the effects of these constituents on birds,
the total dissolved solids concentration was converted to conductivity and compared to no-effects levels (TRVs)
in ducks reported by Mitcham and Wobeser (1988a,b).


Risk Characterization
Hazard quotients were used for the risk estimate in both the screening-level risk assessment and the more detailed
food-web model and risk assessment. In general, a hazard quotient is calculated as the expected environmental
exposure divided by the TRV (e.g., NOAELw or LOAELw), or the benchmark value, and serves as the basis for
the risk characterization. Thus, the hazard quotient is an expression of the factor by which the estimated
exposure exceeds some exposure value associated with an adverse effect (benchmark or TRV). Interpretation of
the hazard quotient depends heavily on the assumptions used to derive the exposure estimate and the lexicological
endpoint represented by the NOAEL or LOAEL value. For the screening-level risk assessment, hazard quotients
were calculated as:




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RESULTS
Selection of Receptors
The receptors selected for the risk assessment were killdeer (Charadrius vociferus), cliff swallow (Hirundo
pyrrhonotd), mallard (Anas platyrhynchos), golden eagle (Aquila chrysaetos), mule deer (Odocoileus
hemionus), and bighorn sheep (Ovis canadensis). These receptors represent the diverse biota expected to use the
pit lake and a variety of exposure pathways.


Exposure Assessment
Exposure assumptions for each receptor are summarized in Table 1. The predicted concentration of each metal
in water in both the short-term and the long-term scenarios are reported by PTI (1995a) and summarized in
Table 2. Estimates of sediment chemistry are also presented in Table 2 (PTI 1995b). BCFs were obtained from
the literature and are summarized in Table 3. The basis for selection of BCF values used in this risk assessment
is provided in PTI (1995b). Résulte of the food-web model were incorporated directly into calculation of the
hazard quotients presented in the risk characterization.




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                      TABLE 2. MEDIAN CONCENTRATIONS OF CHEMICALS
                       OF POTENTIAL CONCERN IN WATER AND SEDIMENT
                                PREDICTED FOR THE PIT LAKE




Effects Assessment
The TRVs that were used for calculation of species-specific NOAELw and LOAELw values are presented in
Table 4. NOAELw and LOAELw values are not presented but are incorporated directly into calculation of
benchmarks (Cwater) or compared directly to doses estimated using the food-web model.




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        TABLE 3. BIOCONCEEIMTRATIOIM FACTORS USED TO ESTIMATE CHEMICAL
             CONCENTRATIONS IN AQUATIC FOODS OF WILDLIFE SPECIES




Risk Characterization
Screening-Level Risk Assessment
Results of the screening-level assessment (Table 5) indicate that, during the entire 330-year modeling period,
antimony, cadmium, chloride, chromium, copper, iron, lead, manganese., selenium, silver, thallium, and zinc are
unlikely to affect mammals adversely and that arsenic, copper, and lead are unlikely to adversely affect birds
using the pit lake. The cumulative concentration of alkalinity, calcium, carbonate, chloride (birds), hydrogen
ions, magnesium, potassium, sodium, and sulfate is expressed as conductivity, which is below levels that cause
adverse effects on juvenile ducks in laboratory experiments (Mitcham and Wobeser 1988a,b).


On the basis of the results of the screening-level risk assessment, the risk of exposure of mammals to aluminum,
arsenic, fluoride, mercury, and nickel was evaluated using a food-web exposure model and hazard quotient. In
addition, risk to all birds from exposure to mercury, selenium, and zinc and risk to killdeer and cliff swallow from
exposure to aluminum and silver were evaluated using the food-web exposure model and hazard quotient.


Food-Web Exposure Model
The results of the food-web exposure modeling and comparison to NOAELw and LOAELw values using hazard
quotients (Table 6) indicate that if water ingestion is the only exposure route, hazard quotients for all receptors



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                   TABLE 4. TOXICITY REFERENCE VALUES FOR CHEMICALS




and for all chemicals are less than 1.0 in both the short-term and long-terra modeling periods. Therefore, because
mule deer, bighorn sheep, and golden eagle are expected to only drink water from the pit lake, these species are
not at risk from chemical constituents of the pit lake. Any mallard ducks, cliff swallows, or killdeer that do not
obtain food from the pit lake also are not at risk.


Assuming that killdeer, cliff swallows, and mallards obtain their food from the pit lake, risk to killdeer and cliff
swallows from exposure to aluminum, mercury, selenium, or silver is negligible because predicted exposures are
below NOAELw values (hazard quotient less than 1.0). Exposure of mallards to aluminum and silver could not



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      TABLE 5. RESULTS OF THE SCREENING-LEVEL ASSESSMENT




Note: --         - data gap; analyte could not be screened in the risk assess-
                   ment
           NA    - not analyzed; analyte not expected to affect wildlife
           NOAEL - no-observed-adverse-effects level
           S     - incorporated calculation of total dissolved solids (TDS) for
                   comparison with the toxicity reference value for TDS
a
  Hazard quotient equals highest median concentration predicted for any time
period by water quality model divided by human health drinking water
standard.
b
  Hazard quotient equals highest median concentration predicted for any time
period divided by the NOAEL-based toxicological benchmark for mallards.


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                    TABLE 6. RESULTS OF THE FOOD-WEB EXPOSURE MODEL AIMD
                                    RISK CHARACTERIZATION




Source: PTI(1995b)

Note:       NA                   not applicable
a
    Hazard quotient is based on wildlife lowest-observed-adverse-effects level.
b
    Food, water, and sediment.
c
    Hazard quotient in parentheses is based on wildlife lowest-observed-adverse-effects level.




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be evaluated because water-to-plant BCFs were not available for these chemicals. In addition, mallard popula-
tions are not at risk from exposure to mercury. The exposure of mallards to selenium in both the short-term and
the long-term scenarios exceeds the NOAELw but does not exceed the LOAELw, indicating that risk to mallards
from exposure to selenium is minimal.


Exposure of all bird receptors to zinc in the long-term scenario is greater than NOAELw values, but exposures of
killdeer and cliff swallows are less than LOAELw values, indicating that there is no risk to killdeer and cliff swal-
lows from exposure to zinc. Exposure of mallards to zinc could exceed the LOAELw value in the short-term
scenario by a factor of 1.2 and in the long-term scenario by a factor of 2.4. These estimates are driven by a rela-
tively high value for the water-to-plant BCF for zinc (Table 3). Uncertainty analysis indicates that water-to-plant
BCFs for zinc range from 10 to 4,875 L/kg. When calculated with the median BCF (440 L/kg), the zinc hazard
quotient for mallards is 0.35 in the short term and 0.69 in the long term. Therefore, the uncertainty associated
with the risk estimate for mallards is greater than an order of magnitude, and the hazard quotient of 2.4 approxi-
mates the upper bound risk estimate.


The risk of exposure of mammals to strontium and of birds to antimony, cadmium, chromium, fluoride, iron,
manganese, nickel, strontium, and thallium could not be analyzed because of data gaps (Table 4). In addition,
exposure of mallards to aluminum and silver could not be evaluated because water-to-plant BCFs were not avail-
able for these chemicals.


DISCUSSION
The results of this ERA indicate negligible risk to wildlife populations from aluminum, antimony (mammals
only), arsenic, copper, fluoride (mammals only), lead, manganese, mercury, nickel (mammals only), selenium,
silver, zinc (mammals only), or total dissolved solids. Results of the food-web exposure model indicate that the
average daily intake of zinc by mallards nesting and feeding at the pit lake for the long-term modeling period
could exceed both the NOAELw and LOAELw values. Sources of uncertainty in this ERA include 1) the
assumptions that form the basis for predictions of pit lake chemical concentrations, 2) data gaps for exposure
variables and NOAELw or LOAELw values, 3) the extent to which shallow water zones and shorelines will
develop into vegetated aquatic habitat, 4) the extent to which pit lake habitats will be used by wildlife, 5) vari-
ability in chemical toxicity related to species differences and chemical interactions (e.g., synergistic and antago-
nistic relationships between chemicals), and 6) variability in BCFs related to species differences and site-specific
environmental factors. To compensate for uncertainties and avoid underestimating risk, wildlife risk models were




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developed using conservative assumptions. As a result, the predicted exposures are probably higher than will
actually occur. Although data gaps remain, the results of this ERA indicate that pit lake water and sediments will
not pose a significant population-level risk to wildlife ibr up to 330 years after mine closure.


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