Copper Sediment Toxicity and Partitioning during Oxidation in a Flow

May 12, 2015 - Department of Earth & Environmental Sciences, Wright State University, Dayton, Ohio 45435, United States. § School of Natural ... We e...
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Copper Sediment Toxicity and Partitioning during Oxidation in a Flow-Through Flume David M. Costello,*,† Chad R. Hammerschmidt,‡ and G. Allen Burton§,∥ †

Department of Biological Sciences, Kent State University, Kent, Ohio 44242, United States Department of Earth & Environmental Sciences, Wright State University, Dayton, Ohio 45435, United States § School of Natural Resources & Environment, University of Michigan, Ann Arbor, Michigan 48109, United States ∥ Earth & Environmental Sciences, University of Michigan, Ann Arbor, Michigan 48109, United States ‡

S Supporting Information *

ABSTRACT: The bioavailability of transition metals in sediments often depends on redox conditions in the sediment. We explored how the physicochemistry and toxicity of anoxic Cuamended sediments changed as they aged (i.e., naturally oxidized) in a flow-through flume. We amended two sediments (Dow and Ocoee) with Cu, incubated the sediments in a flowthrough flume, and measured sediment physicochemistry and toxicity over 213 days. As sediments aged, oxygen penetrated sediment to a greater depth, the relative abundance of Fe oxides increased in surface and deep sediments, and the concentration of acid volatile sulfide declined in Ocoee surface sediments. The total pool of Cu in sediments did not change during aging, but porewater Cu, and Cu bound to amorphous Fe oxides decreased while Cu associated with crystalline Fe oxides increased. The dose−response of the epibenthic amphipod Hyalella azteca to sediment total Cu changed over time, with older sediments being less toxic than freshly spiked sediments. We observed a strong dose−response relationship between porewater Cu and H. azteca growth across all sampling periods, and measurable declines in relative growth rates were observed at concentrations below interstitial water criteria established by the U.S. EPA. Further, solid-phase bioavailability models based on AVS and organic carbon were overprotective and poorly predicted toxicity in aged sediments. We suggest that sediment quality criteria for Cu is best established from measurement of Cu in pore water rather than estimating bioavailable Cu from the various solid-phase ligands, which vary temporally and spatially.

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INTRODUCTION

overlying anoxic sediment. Although the oxic layer is often very thin, it is relevant to metal bioavailability because epibenthic organisms primarily interact with oxic sediments.4 In contrast, sediments used for standard toxicity assays are often anoxic and homogenized, which destroys vertical redox gradients and dilutes any surface sediment and associated metal-binding ligands. Current models of metal bioavailability in sediment focus primarily on acid volatile sulfide (AVS), which is stable only under anoxic conditions, as the main contributor to metal complexation.2 However, Fe and Mn oxides, which are present in both oxic and anoxic sediments, also can complex metals5−7 and may be underappreciated in metal bioavailability models and risk assessment.8 For this study, we used a sediment-aging experiment to explore the role of Fe and Mn oxides on Cu bioavailability and

The toxicity of metals (e.g., Cu, Ni, Zn) in sediments is modified by the presence and cycling of solid-phase ligands that limit metal availability to biota.1,2 Metals can be complexed and coprecipitated by reduced sulfur, chelated by functional groups on organic molecules, and adsorbed to Fe and Mn oxide minerals; all of these reactions can render a fraction of the total pool of metal nontoxic to biota. Importantly, the speciation of metals among these metal-complexing agents is modified by physicochemical conditions (e.g., pH, redox potential).1 Natural sediments vary temporally and spatially in physicochemical conditions, and the diverse metal-complexing agents present in sediments may be more or less important for metal binding dependent on conditions at fine (e.g., near the sediment-water interface) and broad scales (e.g., seasonal and geographic variability). One of the most important physicochemical gradients in sediments is the decline of redox potential with increasing sediment depth.3 High oxygen demand in sediments and slow diffusion of oxygen results in a thin (often 1−10 mm) oxic layer © 2015 American Chemical Society

Received: Revised: Accepted: Published: 6926

January 12, 2015 May 11, 2015 May 12, 2015 May 12, 2015 DOI: 10.1021/acs.est.5b00147 Environ. Sci. Technol. 2015, 49, 6926−6933

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Environmental Science & Technology Table 1. Initial Sediment Physicochemistry Prior to Spiking with Cu and Aging in a Flow-Through Flume sediment

acid volatile sulfide (μmol g−1 dw)

organic matter (%)

total carbon (%)

total Fe (mg kg−1 dw)

amorphous Fe oxides (mg kg−1 dw)

crystalline Fe oxides (mg kg−1 dw)

porewater DOC (mg L−1)

total Cu (mg kg−1 dw)

Ocoee Dow

6.3 0.54

8.2 2.1

3.6 0.68

46 000 6800

1700 840

17 000 1700

4 21

27 5.9

rapid exchange rate maintained an oxic water column and kept aqueous Cu concentrations below toxic levels. Water velocity at the surface of the sediment was 10 cm s−1, which minimized sediment resuspension and transport. Rectangular plastic cups (4.4 cm width × 8.3 length × 7.6 height) were completely filled with Cu-amended sediment and placed in the flume. While adding sediment, a small peeper (2.9 mL) was placed horizontally 1 cm from the bottom of the cup and completely covered by sediment.13 Peepers consisted of polyethylene vials filled with Chelex-cleaned deoxygenated ultrapure water and capped at a single opening with polyether sulfone (PES) filters (0.45 μm). Dissolved ions in pore waters equilibrated with peeper fluid within 7 days and provide timeintegrated concentrations; the 7-day window is shorter than the time scale of Cu toxicity dynamics observed in this experiment (described below), thus we believe these measurements give an accurate representation of porewater dynamics. Sediment from each treatment was divided into 14 cups and arranged in the flume so that sediments with lower Cu concentrations were upstream of higher concentrations. Filtered Cu concentrations in overlying water, which were measured above reference sediments, were 7 days needed for equilibration between pore waters and peepers.13 Peeper fluid was diluted 10×, acidified with HNO3 to 1%, and refrigerated prior to analysis of dissolved organic carbon (DOC) with an infrared combustion analyzer and dissolved metals (Cu, Fe, and Mn) by inductively coupled plasma mass spectrometry (ICP−MS). Frozen sediments were thawed for measurement of AVS and simultaneously extracted Cu (CuSEM) according to standard procedures.14,15 Sulfide was determined colorimetrically14 and CuSEM was measured by ICP−MS. Oxidized Fe (amorphous and crystalline) and associated Cu was measured with selective extractions.16 Briefly, amorphous Fe oxides (FeHFO) and associated Cu (CuHFO) were extracted by reacting wet sediment with a buffered (pH = 8) ascorbate solution for 24 h at 25 °C. The total pool of reactive oxidized Fe (amorphous and

toxicity. Using homogenized anoxic sediments as a starting point, we aged sediments in a flow-through flume and measured changes in sediment geochemistry and metal toxicity through time. We predicted that aging sediments under these conditions would result in a well-developed oxic surface layer overlying anoxic sediments, greater complexation of sediment Cu with Fe and Mn oxides, and reduced porewater Cu. Consequently, we hypothesized that observed changes in sediment chemistry will result in decreased Cu bioavailability, and aged sediments would be less toxic than freshly amended sediments having the same Cu concentration. Ultimately, we posit that aged sediments are most representative of natural field conditions and a better model for making predictions about Cu bioavailability.

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EXPERIMENTAL SECTION Sediment preparation. Fine-grained sediments were collected from Madden Branch of the Ocoee River (Benton, TN, U.S.A.) and Dow Creek (Midland, MI, U.S.A.). Sediments were stored at room temperature in sealed buckets under N2 headspace until amending with Cu. Prior to any manipulation, sediments were gently stirred to maintain water content and bulk density. Ocoee and Dow sediments differed in physicochemical characteristics that are important for metal bioavailability (Table 1). Most significantly, Ocoee sediments had AVS, organic matter (OM), and total Fe concentrations that were about 10-fold greater than those in Dow sediments. Sediments were amended with Cu by an indirect spiking procedure9 with pH adjustment.10 Briefly, a small volume of sediment was amended with CuCl2·2H2O, sealed under a N2 headspace, and shaken for 1 h to mix. After 24 h, NaOH was added to adjust sediment pH to within 0.5 units of the initial pH.10 After 7 d, amended sediments were diluted with reference sediment to create five treatment concentrations for each sediment type (Ocoee: 27−2300 mg Cu kg−1 dw, Dow: 2−670 mg kg−1), and total Cu concentrations were stable through time (Supporting Information (SI), Table S1). Target Cu concentrations were selected based on reported toxicity of sediment Cu to H. azteca,11 and appropriate adjustments were made to account for nontoxic CuS expected in Ocoee sediments.2 Sediments were incubated for an additional 28 days under N2 (rolled 1 h, twice per week) to allow adequate time for equilibration of Cu between solid-phase fractions and pore water.12 At initiation of the experiment, all treatments had sediment pH within 0.2 units of reference sediments. Aging of Sediments. Sediments were aged in a recirculating flume with continuous renewal of water that drained from the flume through an overflow standpipe (SI Figure S1). City water (Ann Arbor, MI) was passed through activated carbon, a biofiltration tank, and ultraviolet sterilizer before entering the flume. Water chemistry was relatively stable throughout the exposure period; water was 23 °C (standard deviation (SD) ± 2 °C), saturated with oxygen (8.2 ± 0.4 mg L−1), alkaline (pH = 7.8 ± 0.4), and hard (126 ± 28 mg CaCO3 L−1). Water was exchanged at a rate of 6.6 L min−1, and the entire volume of the flume (∼400 L) was replaced hourly. This 6927

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differences between physicochemistry in deep and surface sediments. Changes to H. azteca RGR through time were assessed using multiple regression with aging time and log CuTOT concentration as continuous variables and an additional categorical variable to account for differences in initial H. azteca size at the start of testing. Similar to sediment physicochemistry, we analyzed growth rates from Dow and Ocoee sediments separately. A significant negative slope for the RGR and log CuTOT relationship indicated that sediment Cu elicited a toxic response, and a greater magnitude of slope (i.e., more negative) denoted that growth rates were significantly reduced at lower Cu concentrations. A significant interaction between time and CuTOT indicated that the toxicity of sediment Cu changes through time. In addition to comparing H. azteca growth rates to solid-phase Cu, we compared the H. azteca growth response to porewater Cu thresholds2 and organic carbon-normalized excess CuSEM (i.e., (CuSEM-AVS)/f OC) corrected for pH with the sediment biotic ligand model (sBLM).18 To normalize these comparisons across sampling dates, we calculated a mean growth index (mean RGR treatment/RGR reference ×100) for each CuTOT treatment for all sampling periods. For predictions of RGR from pore water Cu, we used only those data for which we made pore water Cu measurements (days 7, 21, 42, 86, and 213). Nonlinear least-squares regression with a logistic model was used to calculate an EC20 for each sediment, and these values were then compared to hardness-corrected water quality criteria established for the U.S., E.U., and Australia/New Zealand (16.4, 8.2, and 4.5 μg L−1, respectively).2,19,20 Organic carbon-normalized excess CuSEM was calculated for surface sediments and compared graphically to thresholds proposed by Di Toro and colleagues.18 Additional details on statistical analyses are provided in the SI.

crystalline), Mn, and associated Cu were extracted by shaking wet sediment in a solution of buffered (pH = 5) sodium hydrosulfite for 4 h at 60 °C. Supernatant from all extractions was filtered (0.45 μm, PES) prior to Cu, Fe, and Mn analysis by inductively coupled plasma optical emission spectrometry (ICP−OES). Crystalline Fe oxides (FeCFO, i.e., goethite, hematite, magnetite) and associated Cu (CuCFO) were calculated as the difference between total oxidized and amorphous Fe oxide extractions. No distinction was made between different crystal structures for Mn oxides and only the total reactive Mn oxide pool is reported. Dried sediments were digested for total metal analysis (CuTOT, FeTOT, and MnTOT) with a 3:1 solution of concentrated HNO3 and HCl and heating in a microwave according to U.S. EPA method 3051A. Diluted digestates were analyzed for CuTOT, FeTOT, and MnTOT by ICPOES. Gravimetric techniques were used to measure sediment water content (heating at 90 °C for 48 h; only samples from days 0, 1, and 213) and OM content by loss on ignition (550 °C for 4 h). Total carbon (TC) was measured on a subset of samples (initial and day 213 samples) with an elemental analyzer. Hyalella azteca Toxicity Tests. We initiated 7-d H. azteca toxicity tests during six of the sediment sampling periods (2, 7, 14, 21, 42, 86, 213 days). Ten H. azteca neonates (7−14 d old) were placed into plastic chambers with nylon mesh (120 μm) windows facing the sediment (SI Figure S1) and placed on five replicate cups of each sediment treatment. During initiation of each H. azteca test, five groups of 10 H. azteca neonates were dried for determination of average initial mass. After 7 days, chambers were removed from the sediment surface, and all remaining H. azteca (mean survival = 89 ± 13%) were recovered and counted. Recovered H. azteca evacuated their gut contents in clean water for 24 h prior to measuring dry mass.17 Surviving H. azteca from the same chamber were massed as a group on a microbalance (±0.001 mg) for calculation of relative growth rates (RGR in mg mg−1 d−1) RGR = (ln M 0 − ln MF)/t

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RESULTS Sediment pH, Carbon, and Dissolved Oxygen. As sediments aged, pH and OM content did not change substantially in any of treatments (see SI). All Ocoee and Dow sediments had circumneutral pH (6−7.5), and, on average, Ocoee sediments were slightly more acidic than Dow sediments (SI Figure S3). Dow sediments contained on average 2% OM (∼0.7% TC) by mass, and Ocoee sediments contained on average 8% OM (∼4% TC); OM in both sediments did not change during aging. Although Ocoee sediment contained more particulate OM, Dow sediments contained more DOC in pore waters (mean DOC = 12 and 38 mg L−1, respectively). In both sediments, porewater DOC increased until day 42 and then declined to initial concentrations (SI Figure S4). In Dow sediments, DOPEN was ∼2.5 mm after 1 d of aging and increased to 4.5 mm by the end of the 213 d aging (SI Figure S5A). The linear increase in DOPEN through time was unrelated to CuTOT concentration in Dow sediment (SI Figure S4A, Table S2). In contrast, the linear increase of DOPEN through time in Ocoee sediments was greater in treatments with higher CuTOT (SI Figure S5B, Table S2). All Ocoee treatments had DOPEN ∼2.5 mm after 1 d of aging, and DOPEN increased to 4.5−7 mm by the end of the aging period (SI Figure S5B). Acid-Volatile Sulfide. Dow sediments contained less AVS than Ocoee sediments (Table 1), and the change in AVS through time differed between the two sediments. Across both sediments, depths, and all aging times, the concentration of AVS was strongly and inversely related to CuTOT (SI Table S2). This was expected because Cu sulfides are insoluble in the 1 M

(1)

where M0 and MF are the average masses of individual H. azteca at the beginning of the experiment and end of the experiment, respectively, and t is exposure time (d). A preliminary 7-d static renewal toxicity assay determined that placing neonates within a chamber produced an EC20 (growth) that was not significantly different than an EC20 for H. azteca directly exposed to the same sediment (data not shown). Data Analysis. The depth of DO penetration into sediment (DOPEN) was calculated as the difference between the sediment-water interface and suboxic-anoxic boundary; boundaries were determined by fitting a logistic curve using nonlinear least-squares regression (SI Figure S2). Multiple regression was used to determine the effect of Cu treatments and aging time on sediment physicochemistry and H. azteca growth. Results from Dow and Ocoee sediments were analyzed separately as these geochemically distinct sediments were anticipated to have different metal dynamics. Sediment physicochemistry changed more rapidly early in the aging process, and thus physicochemical variables were regressed against the log of aging time. In rare cases where physicochemical variables changed nonmonotonically through time (i.e., porewater DOC, surface Mn oxides) we considered time a discrete variable and used analysis of covariance rather than multiple regression. Paired t tests were used to determine 6928

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0.4%) sediments. Concentrations of CuHFO declined over time in the highest Cu treatments of Dow and Ocoee surface sediments and Ocoee deep sediments (Figure 2A,C; SI Table

HCl used to liberate reduced sulfur with the AVS extraction technique.2,21 AVS concentrations were stable through time in Dow surface and deep sediments (SI Table S2). However, AVS in Ocoee surface sediments decreased through time with a greater rate of decline in sediments with lower CuTOT (Figure 1). In deep Ocoee sediments, AVS did not change through time, with reference sediments maintaining relatively high AVS concentrations throughout the experiment (SI Table S2).

Figure 1. Ocoee surface sediment AVS measured through time as sediments aged in a flow-through flume. Warmer colors indicate higher sediment CuTOT (mean CuTOT surface reported in legend). Solid lines indicate best-fit lines for specific CuTOT treatments as determined by multiple regression.

Figure 2. Cu bound to amorphous (A,C) and crystalline (B,D) Fe oxides in Dow sediments as they aged in a flow-through flume. Warmer colors indicate higher sediment CuTOT (mean CuTOT reported in legend). Solid lines indicate best-fit lines for specific CuTOT treatments determined to be significant by multiple regression. Patterns for Ocoee sediment are similar (SI Figure S9).

Sediment Fe and Mn. As sediments aged, total Fe and Mn concentrations changed in surface sediments, and the concentration of oxidized Fe and Mn exhibited the greatest change in deep sediments. Through time, FeTOT in Dow and Ocoee surface sediments changed slightly (SI Table S2), but these changes were small relative to the total pool of Fe. Total Mn concentrations increased through time in both Dow and Ocoee surface sediments (SI Table S2, Figure S6); the gain of MnTOT in surface sediments (∼30% increase) may have been from precipitation of Mn in overlying water (30 μg L−1 throughout the test). Ocoee sediments had substantially more Fe and Mn than Dow sediments, but Dow sediments had a greater fraction of Fe as amorphous Fe oxides (SI Figure S7). In deep Ocoee and Dow sediments, the fraction of Fe as FeHFO and Mn as Mn oxides increased rapidly during initial aging before stabilizing (SI Table S2, Figure S7). Fe and Mn in filtered pore water were greater in Ocoee than Dow sediments, decreased through time in Ocoee sediments, and did not change through time in Dow sediments (SI Table S2). Furthermore, mass balance estimates for both Fe and Mn suggest that the decline in porewater metals could not account for the increase in total (surface) and oxidized (deep) metal concentrations. Additional details on Fe and Mn chemistry are provided in the SI. Sediment Cu Speciation. Concentrations of CuTOT in sediment were static throughout the experiment, but the speciation of Cu within the sediments changed through time in both sediments. Concentrations of CuSEM either declined or remained stable as the sediments aged (SI Table S2). The fraction of total Cu recovered in the SEM fraction was greater from Dow than Ocoee sediments (80 and 50%, respectively), likely a result of a greater proportion of Cu as insoluble copper sulfides in the sulfur-rich Ocoee sediment. Copper associated with amorphous Fe oxides (CuHFO) accounted for a small proportion of CuTOT in both Dow (1−3%) and Ocoee (0.1−

S2, Figure S8A,C). The temporal decline of CuHFO was unexpected because the concentration of FeHFO increased during aging (SI Figure S7). Copper associated with crystalline Fe oxides (CuCFO) accounted for a larger portion of CuTOT than amorphous Fe-bound Cu in both Dow (5−13%) and Ocoee (2−8%) sediments. Similar to temporal changes in CuHFO, concentrations of CuCFO in both Dow and Ocoee surface sediments also declined with sediment age (Figure 2B; SI Figure S8B). In contrast, Dow deep sediments exhibited an increase of CuCFO through time (Figure 2D; SI Table S2). By the end of the aging period, the highest Cu treatment of Dow sediment had 12% of the CuTOT pool associated with crystalline Fe oxides. In Ocoee deep sediments, there was an increase in the concentration of CuCFO over time (SI Figure S8D), but high variability of CuCFO estimates led to a nonsignificant temporal change (SI Table S2). As expected, Cu in pore water was strongly correlated with CuTOT and declined through time as sediments aged (Figure 3; SI Table S2). Sediment-porewater partitioning coefficients (log KD, L kg−1) for Dow were on average 3.8 at the beginning of the experiment and increased to 4.2 after 213 days. The partitioning coefficient for Cu in Ocoee sediments was greater than Dow and also increased during aging (from 4.2 to 5.2). Removal of Cu from pore water was rapid, and porewater Cu concentrations declined 62−83% in all amended treatments after just 21 days of aging. Mass balance estimates suggest that the temporal decline of porewater Cu was not sufficient to explain the increase of Cu bound to crystalline Fe oxides (i.e., Dow deep sediment). Hyalella azteca Growth. Growth of H. azteca exposed to both Dow and Ocoee sediments was inversely related to sediment CuTOT early in the sediment aging test (Figure 4; SI 6929

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Figure 3. Copper in pore waters of Dow (A) and Ocoee (B) sediments aged in a flow-through flume. Warmer colors indicate higher sediment CuTOT. Solid lines indicate best-fit lines for specific CuTOT treatments as determined by multiple regression. Porewater Cu values from Dow reference sediments (black) were excluded from the multiple regression due to very low values. Note that the y-axis is on a log scale.

Figure 5. Summary of results from multiple regression describing the response of H. azteca relative growth rates (RGR) to sediment total Cu (CuTOT) and aging time. Points designate dose−response estimates on sampling dates and solid lines show the interpolated trend through time. Larger negative values indicate reduced growth at lower Cu concentrations and values close to zero indicate that all concentrations tested were nontoxic. Dashed lines indicate 95% confidence intervals of the slope estimates, and the point at which confidence intervals overlap 0 (solid horizontal line) indicate that all sediment concentrations tested were statistically nontoxic (Dow = 117 days and Ocoee = 220 days).

Figure 4. Relative growth rates (RGR) of Hyalella azteca exposed to Dow sediment from sampling dates representing freshly spiked (Day 7) and aged (Day 213) sediments. Dashed lines (and reported slopes) represent best-fit lines for the dose−response relationship on that sampling day (e.g., RGRd7 = 0.063−0.021 × log(CuTOT)). Plots of RGR on all sampling dates from Dow and Ocoee sediments are presented elsewhere (SI Figure S9).

Figure 6. Hyalella azteca growth in response to porewater Cu (A) and solid phase Cu (B) measured in Dow (green) or Ocoee (blue) sediments of different ages. Solid-phase Cu concentrations are expressed as the concentration of simultaneously extracted Cu (CuSEM) in excess of acid volatile sulfide (AVS) corrected for sediment organic carbon (OC) content (B). Negative values (i.e., AVS in excess of CuSEM) are placed at 1 on the log x-axis. Dashed lines (A) indicate best-fit lines from nonlinear least-squares logistic regression. The vertical lines indicate toxicity thresholds discussed in the text, and the two points identified with sampling dates (B) indicate sediments that are predicted to be toxic but for which we observe no toxic response.

Table S2, Figure S9); however, the dose−response relationship changed with further sediment aging (time × Cu interaction, p < 0.01 for both Dow and Ocoee). This suggests that low concentrations of Cu impaired growth early in the experiment (i.e., large negative slope), but these same sediments became less toxic (i.e., slope = 0) as they aged. Slopes of the RGR versus CuTOT relationship for Dow sediment became less negative more quickly (and logarithmically) than those for Ocoee sediments (Figure 5). Our statistical models predicted that growth rates measured on all Dow sediments were similar after 117 days of aging (i.e., the dose−response slope was no different from 0) and all Cu treatments tested (up to 670 mg Cu kg−1 dw) were nontoxic. Additionally, our statistical models predicted that growth rates on all Ocoee sediment (up to 2300 mg Cu kg−1 dw) would be similar after 220 days of aging. We found that by combining sediments of all ages, H. azteca growth declined as a logistic function of increasing porewater Cu (Figure 6A). Given the same porewater Cu concentration, H. azteca exposed to Ocoee sediments exhibited a greater reduction in relative growth when compared to organisms exposed to Dow sediments. Porewater Cu concentrations that

elicited a 20% reduction in relative growth (EC20) were 3.3 and 7.8 μg L−1 in Ocoee and Dow sediments, respectively. Importantly, porewater DOC concentrations were greater in Dow sediments compared to Ocoee sediments and likely helped mitigate toxicity. These EC20 values are less than the hardness-corrected water quality criteria recommended by U.S. EPA (16.4 μg L−1),2 but within the range of the EU general PNEC for Cu and hardness-modified guideline value in Australia (8.2 and 4.5 μg L−1, respectively).19,20 Bioavailability models based on solid-phase concentrations of Cu and ligands (i.e., (CuSEM-AVS)/f OC) were unable to differentiate between toxic and nontoxic conditions for these sediments of different ages (Figure 6B). The pH-specific threshold criteria derived 6930

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Environmental Science & Technology from the sBLM18 accurately differentiated between toxic and nontoxic conditions for freshly spiked sediments, but could not account for declines in toxicity as sediments aged (Figure 6B).

binding sites after aging when compared to freshly spiked sediments. Conversely, the relative abundance of FeCFO did not change through time but the amount of Cu associated with crystalline Fe oxides increased through time. In Dow deep sediment with the highest CuTOT, the molar ratio of CuCFO:FeCFO increased from 0.01 to 0.04, which suggests that crystalline Fe oxides had 4× more occupied binding sites in aged sediments than freshly spiked sediments. The shift in Cu affinity for Fe oxides through time indicates that the CuFe oxide binding is not strictly stoichiometric; the coarse mineral categories used here (i.e., amorphous, crystalline) are not refined sufficiently to distinguish between specific minerals (e.g., hematite and geothite) that may have different surface properties and Cu-binding affinities. However, our data do suggest that crystalline, as opposed to amorphous, Fe oxide minerals are more important for long-term complexation of Cu, and FeCFO is a potential sink of bioavailable porewater Cu and may be partly responsible for the decline in toxicity as sediments (and FeCFO) aged. Previous efforts to estimate bioavailable metal in sediments from measurement of solid phase fractions (e.g., SEM-AVS) have been modestly successful, and our study provides additional critical evidence about the utility of standard bioavailability models. Bioavailability models based on AVS and SEM can accurately identify nontoxic conditions when AVS is in excess of SEM, yet under conditions where CuSEM is in excess of AVS, there is limited power to differentiate between toxic and nontoxic conditions. Even in Ocoee sediments, where AVS was a major binding ligand, a standard measure of bioavailable Cu (i.e., CuSEM-AVS) predicted an increase through time of bioavailable Cu in surface sediments as AVS declined, which is contrary to the observed decrease in toxicity. For example, the lowest Ocoee treatment (220 mg kg−1 dw) had AVS in excess of CuSEM in surface sediments at the beginning of the experiment (CuSEM-AVS = −2.5 μmol g−1 dw) but, because of oxidation of AVS during aging, the older sediments exceeded the nontoxic threshold (CuSEM-AVS = 0.1 μmol g−1 dw). Advanced bioavailability models (i.e., sBLM), which attempt to predict toxic thresholds based on measurements of SEM, AVS, OC, and pH,18 also were unsuccessful at differentiating between toxic and nontoxic conditions of sediments through time. In particular, Dow sediments with elevated Cu aged >42 days were predicted to be toxic based on sediment chemistry, but we observed no reduction in H. azteca growth. The sBLM assumes that OC is the sole determinant for the equilibrium distribution of Cu in excess of AVS between particulate ligands and pore waters; however, it has been demonstrated that KD in sediments is best predicted by organic carbon only when sediments are freshly amended with metal and KD is better predicted by Fe and Mn as sediments age.8 We suggest that the successful application of the sBLM was a function of using only laboratory-amended sediments that were not sufficiently aged.18 Improvements to the SEM-AVS models by incorporating other ligands (e.g., OC, Fe oxides) is complicated by the nonstoichiometric binding between metals and other ligands (e.g., our observed change in CuCFO/FeCFO molar ratio during aging). However, we anticipate that analytical methods required for determining specific ligand chemistry (e.g., X-ray adsorption spectroscopy) may not be cost-effective for risk assessment. We suggest that because the current AVS-based bioavailability models ignore important metal binding ligands (e.g., Fe oxides), they are overly conservative for risk assessment and

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DISCUSSION As hypothesized, we observed a change in toxicity during sediment aging with “older” sediments eliciting less of a toxic response than freshly amended sediments containing the same total concentration of Cu. Further, we observed rapid removal of Cu from pore water through time as both sediments aged. The strong dose−response relationship between porewater Cu and H. azteca growth from both sediments is further support for the model that dissolved metals in sediments are the primary cause of toxicity.2 As expected, the relationship between CuTOT and porewater Cu (i.e., log KD) changed through time, likely as a result of a change in the type, abundance, and sorptive capacity of solid-phase ligands. Further, we suggest that the differences and temporal changes of the ligand pools (e.g., AVS, DOC) between Dow and Ocoee sediments explain the changes in Cu speciation and toxicity through time in these two sediments. The difference in AVS concentrations between Dow and Ocoee sediments likely was responsible for some of the temporal dynamics in Cu pools and toxicity. Greater concentrations of AVS in Ocoee compared to Dow sediments resulted in a greater fraction of Cu bound to sulfide ligands that could be oxidized. Our physicochemical measurements of DOPEN and porewater Fe and Mn indicated that oxidation reactions were favored in aged sediments. This was most apparent in Ocoee reference surface sediments where AVS declined through time as reduced sulfur was likely oxidized. Although we could not measure oxidation of insoluble CuS,21 we anticipate that, as others have observed,22,23 increasing the redox potential caused oxidation of CuS in Ocoee sediments. Measurements of CuTOT indicated that any Cu liberated during CuS oxidation was not lost from the sediment but instead retained by other solid-phase ligands, likely organic matter and Fe and Mn oxides.22 In Dow sediments that had a relatively small fraction of sulfide-bound Cu, increasing redox potential likely liberated minimal Cu due to the minor contribution to Cu binding by reduced ligands. Therefore, we suggest that the greater sustained toxicity in Ocoee (up to 220 d) compared to Dow (117 d) sediments was likely a result of the oxidation of reduced ligands, which contributed a larger and sustained fresh pool of liberated Cu in Ocoee sediments that needed to equilibrate between pore water and solid-phase oxidized ligands. We observed temporal and spatial changes in Fe and Mn oxides that influenced the solid-phase partitioning and toxicity of Cu. Importantly, increases in the abundance of oxidized Fe and Mn did not occur only in sediment containing molecular oxygen (0−0.7 cm depth), rather the relative abundance of Fe (i.e., FeHFO) and Mn oxides increased through time at depth (1−7 cm). This suggests that the increase in redox potential that occurs during aging can extend to depths below the oxic/ suboxic region in sediments. Unexpectedly, temporal patterns of Cu associated with Fe and Mn oxides did not match temporal patterns in Fe and Mn oxide pools. Most notably, the pool of FeHFO increased through time but the fraction of Cu associated with FeHFO declined through time. For example, in Ocoee deep sediment with the highest CuTOT, the molar ratio of CuHFO/FeHFO declined from 0.004 to 0.001 during aging, which suggests that FeHFO has a quarter as many occupied 6931

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Environmental Science & Technology

through time, Cu speciation in Ocoee sediments through time, and plots of raw data from all toxicity tests. The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.5b00147.

only appropriate, at best, for screening-level assessments. Alternatively, we suggest the direct measurement of metal concentrations in pore water for improved prediction of dose− response and estimation of sediment quality criteria thresholds.2 For our study, we were able to calculate porewater Cu effective concentrations (i.e., EC20) for H. azteca growth that are applicable to sediments of varying age and ligand structure. The water quality criteria for Cu we examined had variable success at predicting toxicity, and most strikingly we found that the hardness corrected sediment quality criteria for interstitial waters developed by U.S. EPA2 was under-protective. These water quality guidelines are derived from dose−response to Cu in overlying waters,2,19,20 which, as these data demonstrate, may not be equivalent to exposure to Cu in pore water. We suggest that studies relating toxic effects to porewater metal concentrations be used to update current sediment criteria. Finally, although it has been suggested that porewater DOC is not a necessary measurement needed for accurate prediction of pore water toxic effects,18 we found that there was variability in EC20 between Dow and Ocoee sediments that could be resolved by accounting for porewater DOC (i.e., higher EC20 with greater porewater DOC). DOC is a known ligand for metals and we suggest that, similar to surface waters, porewater DOC may reduce toxic response to metals, and development of a porewater-based BLM may be fruitful for risk assessment.24,25 We demonstrated that aging Cu-amended anoxic interstitial water in a flow-through flume alters redox conditions and geochemistry of sediment, which modifies Cu speciation and the toxicity of Cu to epibenthic amphipods. In surface sediments, metal sulfides declined as sediments aged due to a shift in redox conditions to favor oxidation reactions; however, we did not measure significant loss of Cu as oxidized ligands (e.g., Fe oxides) likely sorbed any Cu liberated from reduced ligands. As sediments aged and Cu was removed from pore water, they became less toxic to H. azteca, which supports observations in field studies of nickel-amended sediments of different age.8 Aged sediments, which were more heterogeneous and oxidized than freshly spiked sediments, are likely a more accurate representation of undisturbed field-contaminated sediments. Laboratory studies using metal-amended sediments that are not fully aged are likely overly conservative with higher relative porewater metal concentrations and greater toxicity than field-contaminated sediments at similar concentrations. Our study suggests that 200 days of aging is required for sediments with a large proportion of reduced metal ligands (i.e., AVS) and aging sediments for 100 days may be needed if most ligands are oxidized. Because sediments have a variety of solidphase ligands, we recommend that porewater Cu be directly measured for the most accurate assessment of risk to epibenthic organisms. Further, the pore water criteria for Cu that is based on water-only exposure2 does not adequately protect against risk to epibenthic organisms and likely needs to be updated with data from studies that directly measure porewater Cu exposure.

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AUTHOR INFORMATION

Corresponding Author

*Phone: (330) 672-2035; e-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS Anna Harrison, Raissa Mendonça, Maggie Grundler, Olivia Rath, Kyle Fetters, and Lauren Estes assisted with experimental setup and sampling. Alison Agather, Katelynn Alcorn, Daniel Marsh, Deepthi Nalluri, and Brendan Shields assisted with geochemical analyses. Funding was provided by Rio Tinto, Nickel Producers Environmental Research Association, Copper Alliance, International Lead Zinc Research Organization, Vanitec, and Cobalt Development Institute.

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REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

Available information includes additional experimental details, results, and a glossary of abbreviations. Also included are supporting tables of mean CuTOT concentrations and statistical results, photos of the experimental system, and figures depicting methods for calculation of DOPEN, sediment physicochemistry (i.e., DOPEN, pH, DOC, Fe, Mn) measured 6932

DOI: 10.1021/acs.est.5b00147 Environ. Sci. Technol. 2015, 49, 6926−6933

Article

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DOI: 10.1021/acs.est.5b00147 Environ. Sci. Technol. 2015, 49, 6926−6933