Nickel Partitioning and Toxicity in Sediment during Aging: Variation in

Subscriber access provided by Northern Illinois University

Article

Nickel partitioning and toxicity in sediment during aging: Variation in toxicity related to stability of metal partitioning David M. Costello, Chad R. Hammerschmidt, and G. Allen Burton Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b04033 • Publication Date (Web): 16 Sep 2016 Downloaded from http://pubs.acs.org on September 18, 2016

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 32

Environmental Science & Technology

1 2 3

NICKEL PARTITIONING AND TOXICITY IN SEDIMENT DURING AGING: VARIATION IN

4

TOXICITY RELATED TO STABILITY OF METAL PARTITIONING

5

David M. Costello1,*, Chad R. Hammerschmidt2, and G. Allen Burton Jr.3,4

6 7

1. Department of Biological Sciences, Kent State University, Kent, OH, 44242, USA

8

2. Department of Earth & Environmental Sciences, Wright State University, Dayton, OH,

9 10 11 12

45435, USA 3. School of Natural Resources & Environment, University of Michigan, Ann Arbor, MI, 48109, USA 4. Earth & Environmental Sciences, University of Michigan, Ann Arbor, MI, 48109, USA

13 14

* Corresponding author

15 16 17 18 19 20 21

Department of Biological Sciences PO Box 5190 Kent, OH 44242 Phone: (330) 672-2035 Email: [email protected]

22

1 Table

23

4 Figures

1 ACS Paragon Plus Environment


24

Abstract

25

Metals in sediment can be complexed by minerals, partition between solid and aqueous

26

phases, and cause toxicity at high concentrations. We studied how the oxidation of surface

27

sediment that occurs during aging alters the partitioning and toxicity of Ni. Two sediments

28

(Burntwood and Raisin) were amended with Ni, equilibrated, incubated in a flow-through flume,

29

and examined for sediment physicochemistry and toxicity to Hyalella azteca (7-d growth).

30

Through time, the sediment surface (5 mm) was oxidized, acid-volatile sulfide concentrations

31

declined in Raisin sediment, and amorphous Fe oxides increased. Porewater Ni concentrations

32

declined through time but total Ni concentrations in sediment were unchanged, suggesting

33

changes in Ni partitioning through time. Both sediments elicited a toxic dose–response by H.

34

azteca early in the aging process; but only Burntwood, for which Ni was primarily partitioned to

35

Fe oxide minerals, exhibited a consistent dose–response during aging. Low total Ni

36

concentrations (20 mg kg-1) in Raisin sediment reduced H. azteca growth at initiation, but all Ni

37

treatments (up to 3000 mg kg-1) exhibited similar growth after 12 days of aging. The dynamic

38

toxicity observed in Raisin sediment was likely due to the instability of NiS in surface sediments

39

early in the aging process. These data suggest that short-term toxicity assays with

40

homogenized Ni-amended sediment (i.e., standard sediment toxicity tests) may be accurate for

41

sediments where Ni speciation is dominated by oxidized ligands; however, under high-AVS and

42

high-Fe conditions, calculated toxicity thresholds may be overly conservative (here by >100-

43

fold) with respect to natural sediment conditions.


Page 2 of 32

Page 3 of 32

44


TOC Art.

Non-toxic

Sediment toxicity

Raisin

Burntwood

Dynamic toxicity High AVS & moderate Fe Changing Ni partitioning

Stable toxicity Low AVS & high Fe Stable Ni partitioning

Highly toxic

45

Aging amended sediment



46 47

Introduction Partitioning and toxicity of metals (e.g., Cu, Ni, Zn) in sediment is strongly controlled by the

48

abundance and distribution of other elements and molecules that co-precipitate, adsorb, and

49

otherwise complex metals.1–3 A large and growing body of evidence demonstrates that, for most

50

organisms, only freely dissolved metal ions cause toxicity, and metals bound to solid-phase

51

ligands are non-toxic.1,4–7 Thus, the geochemical characteristics of sediment are key to

52

controlling toxicity, and widely used sediment bioavailability models account for metal binding by

53

reduced sulfur and organic carbon,1,8–10 which are purported to be the most important binding

54

ligands. Although such multi-parameter bioavailability models offer more accurate estimates of

55

toxicity than criteria derived from total metal concentrations, there are still limitations to this

56

approach. Primary limitations to the current bioavailability models include an assumption of

57

homogenous equilibrium conditions and an omission of metal binding to commonly occurring

58

Fe, Mn, and Al oxide minerals.

59

Natural sediments and their chemical constituents are rarely homogenous and at

60

equilibrium; spatial and temporal variation in physicochemical conditions can occur at fine (e.g.,

61

sediment–water interface, diel) and broad (e.g., within a watershed, seasonal) scales.11,12

62

Hyporheic exchange of well-oxygenated surface water into stream sediments coupled with high

63

biological oxygen demand establishes strong redox gradients near the sediment–water

64

interface.13 Thus, stream sediment is often characterized by a shallow (1–10 mm) oxic surface

65

layer overlying reduced material. This spatial redox gradient is important for metal bioavailability

66

because biota primarily interact with the oxidized surface layer and some metal-binding ligands

67

are not thermodynamically stable under either oxidizing or reducing conditions. Amending

68

sediment with metals, which is a common experimental approach for establishing dose–

69

response thresholds, requires homogenization that perturbs sediment physicochemical

70

conditions and may impact the realism of experimental scenarios when compared to naturally

71

contaminated sediments.14,15 Furthermore, the timespan of most sediment dose–response 4 ACS Paragon Plus Environment

Page 4 of 32

Page 5 of 32


72

experiments (3000 µg L-1. Our regression analysis showed no relationship between the deep

405

porewater Ni concentration and the reduction in H. azteca growth. The mismatch between 17 ACS Paragon Plus Environment


406

porewater Ni concentrations at depth and H. azteca growth rates emphasizes the point that

407

conditions at the sediment surface, where organism exposure occurs, cannot be estimated from

408

deep sediment chemistry.34 The dynamic H. azteca dose–response is most likely related to

409

oxidation of AVS and release of sulfide-bound Ni. Additional support for this is found in the

410

inability of sulfur-based bioavailability models to predict non-toxic conditions in freshly amended

411

sediment. The first toxicity assay was completed when AVS concentrations were changing most

412

rapidly (2 days of aging, Figure 1), and at that time sediment with AVS in excess of NiSEM

413

resulted in H. azteca RGR that were 30% lower than control conditions. When Raisin sediment

414

was fully aged and AVS concentrations had stabilized (>20 days of aging, Figure 1), there were

415

no longer any treatments with observed toxicity when AVS exceeded NiSEM, but there were

416

many sediments that exceeded non-toxic thresholds8,31 and no reduction in growth rates was

417

observed. The treatments that exceeded the non-toxic threshold (i.e., 130 µmol Ni g-1 OC) fell

418

into the range of ‘uncertain toxicity’ (130–3000 µmol Ni g-1 OC),1 so it is not unprecedented that

419

no toxicity was observed. However, Besser and colleagues22 demonstrated that Raisin sediment

420

is potentially toxic above the non-toxic threshold; the same Raisin sediment (RR3) caused

421

significant mortality of H. azteca over a 28-d assay (i.e., LC20) when bioavailable Ni

422

concentrations exceeded 108 µmol Ni g-1 OC.22 This study adds to the growing body of

423

evidence demonstrating that AVS-based bioavailability models are inadequate for making

424

predictions in sediment under non-equilibrium conditions with distinct vertical redox gradients

425

and these models are not sufficiently resolved to predict toxic conditions.17,19

426

Consequences for sediment risk assessment. Comparing between our sediments at

427

different sampling periods allows us to draw critical conclusions about making risk assessment

428

decisions about Ni in sediment. Early in the experiment, Raisin sediment was toxic at a lower Ni

429

concentration than Burntwood sediment (EC10: 20 and 410 mg kg-1, respectively), whereas

430

aged sediment provided opposite conclusions (EC10: >3000 and 410 mg kg-1, respectively).

431

Considering most effects assessments are based on short-term (100-fold) when compared to field

468

contaminated sediment in lotic systems. Although the magnitude of change in dose–response

469

was large, the rate at which these sediments changed was quite fast. For the Raisin sediment,

470

the dose–response relationship that was not representative of field conditions was eliminated

471

after just 12 days of aging. However, we would caution that the very high amorphous Fe oxide

472

concentrations with abundant binding sites may have contributed to the rapid decline in toxicity.

473

It may be the case that reduced growth rates may have been sustained in a sediment with a

474

lower concentration of oxidized ligands. These results are consistent with those from a similar

475

study of Cu-amended sediment,6 which also demonstrated that sediment with reduced ligands

476

required aging to reestablish oxidized surface sediment for accurate predictions of toxicity in

477

field contaminated sediments.

478 479

Acknowledgments.

480

Jennifer Daley, Kyle Fetters, Maggie Grundler, Anna Harrison, Sara Nedrich, Olivia Rath, and

481

Larissa Sano assisted with experimental setup and sampling. Katelynn Alcorn, Nick Johnson,

482

Daniel Marsh, and Brendan Shields assisted with geochemical analyses. Chris Schlekat, Emily


Page 20 of 32

Page 21 of 32


483

Rogevich Garman and three anonymous reviewers provided comments that improved this

484

manuscript. Funding was provided by Rio Tinto, Nickel Producers Environmental Research

485

Association, Copper Alliance, International Lead Zinc Research Organization, Vanitec, and

486

Cobalt Development Institute.

487 488

Supporting Information Available. Available information includes additional sediment

489

chemistry results and a glossary of abbreviations. Also included are supporting tables of mean

490

NiTOT concentrations, QA/QC results, and statistical results and figures depicting sediment

491

physicochemistry (i.e., DOPEN, DOC, pH, Fe, Mn, NiSEM, and NiCFO) measured through time,

492

Ni:Fe ratios in sediment, plots of raw data from all toxicity tests, a summary plot of dose–

493

response statistical models, tissue Ni concentrations through time, and the relationship between

494

RGR and porewater Ni. This material is available free of charge via the Internet at

495

http://pubs.acs.org.

496



497

Figure 1. Raisin surface (A) and deep (B) sediment AVS measured through time as sediment

498

aged in a flow-through flume. Warmer colors (orange > yellow > green > blue > violet) indicate

499

higher sediment NiTOT (mean NiTOT reported in legend). Solid lines indicate best-fit lines for

500

specific NiTOT treatments as determined by multiple regression.

501

Figure 2. Ni in pore waters of Burntwood (A) and Raisin (B) deep sediments as they aged in a

502

flow-through flume. Warmer colors indicate higher sediment NiTOT. Solid lines indicate best-fit

503

lines for specific NiTOT treatments as determined by multiple regression. Note change in scale on

504

the y-axis between panels.

505

Figure 3. Relative growth rates (RGR) of Hyalella azteca exposed to Burntwood and Raisin

506

sediments from the first four of seven sampling dates (after 2, 9, 16, and 23 days of aging)

507

representing the time period when toxicity in Raisin sediment was most dynamic (data from all

508

sampling periods can be found in SI Figure S9). Data from all time periods was pooled for fitting

509

statistical models and calculating best-fit lines; RGR was negatively related to Ni in both

510

sediments (p < 0.01), but Raisin sediment became less toxic through time (NiTOT × time, p =

511

0.002) and Burntwood sediment dose–response was stable (p = 0.07). Dashed lines and slopes

512

represent best-fit lines for dose–response relationships on those particular days (e.g.,

513

Burntwood: RGRD2 = 0.11 – 0.14 × log(NiTOT)). Note the log scale on the x-axis and the change

514

in scale between Burntwood and Raisin sediment.

515

Figure 4. Hyalella azteca growth in response to solid-phase bioavailable Ni in Raisin surface

516

sediment of different ages. Each symbol represents the mean growth rate of replicate chambers

517

from a single treatment on a given sampling date (n = 5) normalized relative to the predicted

518

growth on reference sediment. Solid-phase bioavailable Ni is expressed as the concentration of

519

simultaneously extracted Ni (NiSEM) in excess of acid volatile sulfide (AVS) corrected for

520

sediment organic carbon (OC) content. Warmer colors indicate higher NiTOT treatments.

521

Numbers indicate sampling days on which the RGR for the nearest symbols were measured. 22 ACS Paragon Plus Environment

Page 22 of 32

Page 23 of 32


522

Samples identified with asterisks are samples where RGR was reduced below control rates

523

when bioavailable Ni concentrations were below the empirical non-toxic threshold (120 µmol

524

NiSEM g-1 OC).1,31 The arrow indicates the increase in H. azteca growth rate in the high Ni

525

sediment (3000 mg kg-1) as it aged (RGR after 2 and 100 days of aging are identified).



Page 24 of 32

526

Table 1. Initial physicochemical characteristics of test sediments prior to spiking with Ni and aging in a flow-through

527

mesocosm.

sediment

acid volatile sulfide (µmol g-1)

organic matter (%)

total carbon (%)

total Fe (mg kg-1)

amorphous Fe oxides (mg kg-1)

crystalline Fe oxides (mg kg-1)

total Ni (mg kg-1)

Burntwood Raisin

0.01 9.1

10 15

4.2 8.2

42000 13000

3200 5300

13000 2900

55 5


Page 25 of 32


528

References.

529 530 531 532

(1)

U.S. EPA. Procedures for the derivation of equilibrium partitioning sediment benchmarks (ESBs) for the protection of benthic organisms: metal mixtures (cadmium, copper, lead, nickel, silver and zinc); US Environmental Protection Agency: Washington, DC, 2005.

533 534 535

(2)

Chapman, P.; Wang, F. Ecotoxicology of metals in aquatic sediments: binding and release, bioavailability, risk assessment, and remediation. Can. J. Fish. Aquat. Sci. 1998, 55, 2221–2243. DOI: 10.1139/f98-145.

536 537

(3)

Burton, G. A. Metal bioavailability and toxicity in sediments. Crit. Rev. Environ. Sci. Technol. 2010, 40, 852–907. DOI: 10.1080/10643380802501567.

538 539 540 541

(4)

Besser, J. M.; Brumbaugh, W. G.; Ivey, C. D.; Ingersoll, C. G.; Moran, P. W. Biological and chemical characterization of metal bioavailability in sediments from Lake Roosevelt, Columbia River, Washington, USA. Arch. Environ. Contam. Toxicol. 2008, 54, 557–570. DOI: 10.1080/10643380802501567.

542 543 544

(5)

Ankley, G. T.; Di Toro, D. M.; Hansen, D. J.; Berry, W. J. Technical basis and proposal for deriving sediment quality criteria for metals. Environ. Toxicol. Chem. 1996, 15, 2056–2066. DOI: 10.1002/etc.5620151202.

545 546 547

(6)

Costello, D. M.; Hammerschmidt, C. R.; Burton, G. A. Copper sediment toxicity and partitioning during oxidation in a flow-through flume. Environ. Sci. Technol. 2015, 49, 6926–6933. DOI: 10.1021/acs.est.5b00147.

548 549 550

(7)

Costello, D. M.; Burton, G. A. Response of stream ecosystem function and structure to sediment metal: context dependency and variation among endpoints. Elem. Sci. Anthr. 2014, 2, 000030. DOI: 10.12952/journal.elementa.000030.

551 552 553 554

(8)

Di Toro, D. M.; McGrath, J. A.; Hansen, D. J.; Berry, W. J.; Paquin, P. R.; Mathew, R.; Wu, K. B.; Santore, R. C. Predicting sediment metal toxicity using a sediment biotic ligand model: Methodology and initial application. Environ. Toxicol. Chem. 2005, 24, 2410–2427. DOI: 10.1897/04-413R.1.

555 556 557 558

(9)

Campana, O.; Blasco, J.; Simpson, S. L. Demonstrating the appropriateness of developing sediment quality guidelines based on sediment geochemical properties. Environ. Sci. Technol. 2013, 47, 7483–7489. DOI: 10.1021/es4009272.

559 560 561

(10)

Simpson, S. L.; Batley, G. E.; Hamilton, I. L.; Spadaro, D. A. Guidelines for copper in sediments with varying properties. Chemosphere 2011, 85, 1487–1495. DOI: 10.1016/j.chemosphere.2011.08.044.

562 563 564 565

(11)

Burton, G. A.; Green, A.; Baudo, R.; Forbes, V.; Nguyen, L. T. H.; Janssen, C. R.; Kukkonen, J.; Leppanen, M.; Maltby, L.; Soares, A.; et al. Characterizing sediment acid volatile sulfide concentrations in European streams. Environ. Toxicol. Chem. 2007, 26, 1–12. DOI: 10.1897/05-708R.1.

566 567 568 569

(12)

Nimick, D. A.; Gammons, C. H.; Cleasby, T. E.; Madison, J. P.; Skaar, D.; Brick, C. M. Diel cycles in dissolved metal concentrations in streams: Occurrence and possible causes. Water Resour. Res. 2003, 39, 1247. DOI: 10.1029/2002WR001571.

570 571

(13)

Jørgensen, B.; Revsbech, N. Diffusive boundary layers and the oxygen uptake of sediments and detritus. Limnol. Oceanogr. 1985, 30, 111–122. DOI: 25 ACS Paragon Plus Environment


572

10.4319/lo.1985.30.1.0111.

573 574 575 576 577

(14)

Brumbaugh, W. G.; Besser, J. M.; Ingersoll, C. G.; May, T. W.; Ivey, C. D.; Schlekat, C. E.; Rogevich Garman, E. Preparation and characterization of nickelspiked freshwater sediments for toxicity tests: Toward more environmentally realistic nickel partitioning. Environ. Toxicol. Chem. 2013, 32, 2482–2494. DOI: 10.1002/etc.2272.

578 579 580 581

(15)

Simpson, S. L.; Angel, B. M.; Jolley, D. F. Metal equilibration in laboratorycontaminated (spiked) sediments used for the development of whole-sediment toxicity tests. Chemosphere 2004, 54, 597–609. DOI: 10.1016/j.chemosphere.2003.08.007.

582 583 584 585

(16)

Hutchins, C. M.; Teasdale, P. R.; Lee, S. Y.; Simpson, S. L. Influence of sediment metal spiking procedures on copper bioavailability and toxicity in the estuarine bivalve Indoaustriella lamprelli. Environ. Toxicol. Chem. 2009, 28, 1885–1892. DOI: 10.1897/08-469.1.

586 587 588 589

(17)

Simpson, S. L.; Ward, D.; Strom, D.; Jolley, D. F. Oxidation of acid-volatile sulfide in surface sediments increases the release and toxicity of copper to the benthic amphipod Melita plumulosa. Chemosphere 2012, 88, 953–961. DOI: 10.1016/j.chemosphere.2012.03.026.

590 591 592 593

(18)

De Jonge, M.; Teuchies, J.; Meire, P.; Blust, R.; Bervoets, L. The impact of increased oxygen conditions on metal-contaminated sediments part I: effects on redox status, sediment geochemistry and metal bioavailability. Water Res. 2012, 46, 2205–2214. DOI: 10.1016/j.watres.2012.01.052.

594 595 596

(19)

Costello, D. M.; Burton, G. A.; Hammerschmidt, C. R.; Rogevich, E. C.; Schlekat, C. E. Nickel phase partitioning and toxicity in field-deployed sediments. Environ. Sci. Technol. 2011, 45, 5798–5805. DOI: 10.1021/es104373h.

597 598 599 600

(20)

Campbell, P. G. C.; Tessier, A. Ecotoxicology of metals in the aquatic environment: Geochemical aspects. In Ecotoxicology: A hierarchical treatment; Newman, M. C.; Jagoe, C. H., Eds.; CRC Press: New York, NY, USA, 1996; pp. 11–58.

601 602 603

(21)

U.S. EPA. Methods for collection, storage and manipulation of sediments for chemical and toxicological analyses: Technical manual; Washington, DC, USA, 2001.

604 605 606 607

(22)

Besser, J. M.; Brumbaugh, W. G.; Ingersoll, C. G.; Ivey, C. D.; Kunz, J. L.; Kemble, N. E.; Schlekat, C. E.; Garman, E. R. Chronic toxicity of nickel-spiked freshwater sediments: Variation in toxicity among eight invertebrate taxa and eight sediments. Environ. Toxicol. Chem. 2013, 32, 2495–2506. DOI: 10.1002/etc.2271.

608 609 610 611

(23)

Brumbaugh, W. G.; May, T.; Besser, J. M.; Allert, A.; Schmitt, C. Assessment of elemental concentrations in streams of the New Lead Belt in southeastern Missouri 2002-05. In U.S. Geological Survey Scientific Investigations Report 2007–5057; Reston, VA, 2007; pp. 1–57.

612 613 614 615

(24)

Allen, H. E.; Fu, G.; Deng, B. Analysis of acid-volatile sulfide (AVS) and simultaneously extracted metals (SEM) for the estimation of potential toxicity in aquatic sediments. Environ. Toxicol. Chem. 1993, 12, 1441–1453. DOI: 10.1002/etc.5620120812.

616 617

(25)

Hammerschmidt, C. R.; Burton, G. A. Measurements of acid volatile sulfide and simultaneously extracted metals are irreproducible among laboratories. Environ. 26 ACS Paragon Plus Environment

Page 26 of 32

Page 27 of 32


618

Toxicol. Chem. 2010, 29, 1453–1456. DOI: 10.1002/etc.173.

619 620 621

(26)

Kostka, J.; Luther, G. Partitioning and speciation of solid phase iron in saltmarsh sediments. Geochim. Cosmochim. Acta 1994, 58, 1701–1710. DOI: 10.1016/0016-7037(94)90531-2

622 623 624

(27)

Panov, V. E.; Mcqueen, D. J. Effects of temperature on individual growth rate and body size of a freshwater amphipod. Can. J. Zool. 1998, 76, 1107–1116. DOI: 10.1139/cjz-76-6-1107.

625 626 627

(28)

Norwood, W. P.; Borgmann, U.; Dixon, D. G. Saturation models of arsenic, cobalt, chromium and manganese bioaccumulation in Hyalella azteca. Environ. Pollut. 2006, 143, 519–528. DOI: 10.1016/j.envpol.2005.11.041.

628

(29)

R Core Team. R: A language and environment for statistical computing, 2015.

629 630 631

(30)

Simpson, S. L.; Apte, S. C.; Batley, G. E. Effect of short-term resuspension events on trace metal speciation in polluted anoxic sediments. Environ. Sci. Technol. 1998, 32, 620–625. DOI: 10.1021/es970568g.

632 633 634

(31)

Burton, G. A.; Nguyen, L. T. H.; Janssen, C.; Baudo, R.; McWilliam, R. A.; Bossuyt, B.; Beltrami, M.; Green, A. Field validation of sediment zinc toxicity. Environ. Toxicol. Chem. 2005, 24, 541–553. DOI: 10.1897/04-031R.1.

635 636 637 638

(32)

Adams, W. J.; Blust, R.; Borgmann, U.; Brix, K. V; DeForest, D. K.; Green, A. S.; Meyer, J. S.; McGeer, J. C.; Paquin, P. R.; Rainbow, P. S.; et al. Utility of tissue residues for predicting effects of metals onaquatic organisms. Integr. Environ. Assess. Manag. 2011, 7, 75–98. DOI: 10.1002/ieam.108.

639 640 641 642

(33)

Schlekat, C. E.; Van Genderen, E.; De Schamphelaere, K. A. C.; Antunes, P. M. C.; Rogevich, E. C.; Stubblefield, W. A. Cross-species extrapolation of chronic nickel Biotic Ligand Models. Sci. Total Environ. 2010, 408, 6148–6157. DOI: 10.1016/j.scitotenv.2010.09.012.

643 644 645 646

(34)

Amato, E. D.; Simpson, S. L.; Belzunce-Segarra, M. J.; Jarolimek, C. V; Jolley, D. F. Metal fluxes from porewaters and labile sediment phases for predicting metal exposure and bioaccumulation in benthic invertebrates. Environ. Sci. Technol. 2015, 49, 14204–14212. DOI: 10.1021/acs.est.5b03655.

647 648 649

(35)

Danner, K. M.; Hammerschmidt, C. R.; Costello, D. M.; Burton, G. A. Copper and nickel partitioning with nanoscale goethite under variable aquatic conditions. Environ. Toxicol. Chem. 2015, 34, 1705–1710. DOI: 10.1002/etc.2977.

650 651 652

(36)

Limousin, G.; Gaudet, J. P.; Charlet, L.; Szenknect, S.; Barthès, V.; Krimissa, M. Sorption isotherms: A review on physical bases, modeling and measurement. Appl. Geochemistry 2007, 22, 249–275. DOI: 10.1016/j.apgeochem.2006.09.010.

653 654 655 656

(37)

Simpson, S. L.; Yverneau, H. H.; Cremazy, A.; Jarolimek, C. V; Price, H. L.; Jolley, D. F. DGT-induced copper flux predicts bioaccumulation and toxicity to bivalves in sediments with varying properties. Environ. Sci. Technol. 2012, 46, 9038–9046. DOI: 10.1021/es301225d.

657 658 659 660

(38)

Costello, D. M.; Burton, G. A.; Hammerschmidt, C. R.; Taulbee, W. K. Evaluating the performance of diffusive gradients in thin films for predicting Ni sediment toxicity. Environ. Sci. Technol. 2012, 46, 10239–10246. DOI: 10.1021/es302390m.



Figure 1

Acid volatile sulfide (µmol g−1)

Acid volatile sulfide (µmol g−1)

Raisin 15

A

7 260 620 1300 3000

surface

10

5

0 15

0

B

20

40

60

80

100

80

100

deep

Aging time (d) 10

5

0 0

20

40

60

Aging time (d)

ACS Paragon Plus Environment

Page 28 of 32

Page 29 of 32


Figure 2

Porewater Ni (µg L−1)

2500

A

Burntwood

2000

B

Raisin

10000 8000

1500

6000

1000

4000

500

2000

0

0 0

20

40

60

80

100

0

20

Aging time (d)


40

60

Aging time (d)

80

100


Page 30 of 32

Figure 3

BURNTWOOD 0.20

0.20

0.15

0.10

0.10

0.05

0.05

Relative growth rate (mg mg-1 d-1)

0.20

slope = -0.014 10

100

0.00 1000 0.20

d9

0.15

0.15

0.10

0.10

0.05

0.05

0.00

0.20

slope = -0.014 10

100

0.00 1000 0.20

d16

0.15

0.15

0.10

0.10

0.05

0.05

0.00

0.20

slope = -0.014 10

100

0.00 1000 0.20

d23

0.15

0.15

0.10

0.10

0.05

0.05

0.00

d2

d2

0.15

0.00

RAISIN

slope = -0.014 10

100

0.00 1000

slope = -0.020 1

10

100

1000

d9

slope = -0.008 1

10

100

1000

d16

slope = -0.004 1

10

100

1000

d23

slope = -0.001 1

10

100

Total Ni (mg kg-1 dw)


1000 10000

Page 31 of 32


Normalized RGR (% of ref)

Figure 4

140

100

120 100 80

*

60

2

*

40 -200

0

200

400

600

(NiSEM-AVS)/f OC (µmol NiSEM g−1 OC)


Dynamic toxicity

Non-toxic 0.01

Environmental Science Technology Page 32 of 32 AVS & moderate Fe Raisin &High Changing Ni partitioning

Slope estimate

Sediment toxicity

0.00

-0.01 -0.02 Burntwood

-0.03

Stable toxicity Low AVS & high Fe Stable Ni partitioning

ACS Paragon Plus Environment -0.04 Highly toxic 0

20 40 60 80 100 Aging amended sediment

Nickel Partitioning and Toxicity in Sediment during Aging: Variation in

Recommend Documents