Using the Biotic Ligand Model to Predict Metal Toxicity in Mineralized Systems

1. Using the Biotic Ligand Model to Predict Metal Toxicity in Mineralized Systems Kathleen S. Smith, Laurie S. Balistrieri, and Andrew S. Todd SEG Short Course on Environmental Geochemistry for Modern Mining October 29-30, 2010 in conjunction with the Geological Society of America Annual Meeting, Denver, CO U.S. Department of the Interior U.S. Geological Survey

2. Contact Information Kathleen S. Smith U.S. Geological Survey, Box 25046, Denver Federal Center, M.S. 964D, Denver, CO 80225-0046 ksmith@usgs.gov 303-236-5788 Laurie S. Balistrieri U.S. Geological Survey, University of Washington, Box 355351, Seattle, WA 98195 balistri@usgs.gov 206-543-8966 Andrew S. Todd U.S. Geological Survey, Box 25046, Denver Federal Center, M.S. 964D, Denver, CO 80225-0046 atodd@usgs.gov 303-236-1426

3. Acknowledgments This work was funded by the U.S. Geological Survey Mineral Resources Program

4. Outline • Relationship between metal speciation, bioavailability, and toxicity • How the biotic ligand model (BLM) fits into the EPA regulatory framework • Description of the BLM • Which parameters have the most influence on BLM computations? • Some challenges for implementation of the BLM • Case study

5. Fundamentals of Metal Speciation and Bioavailability • Chemical speciation is key to understanding metal mobility, bioavailability, and toxicity • Only the bioavailable metal fraction is important for metal toxicity • the free metal ion (e.g., Cu2+) is considered to be the most important bioavailable form (CuOH+ also important at higher pH) • Need to consider water-quality parameters that influence metal bioavailability • e.g., pH, hardness, DOC • presence of DOC decreases metal toxicity to aquatic biota by binding with dissolved metals • There is a relationship between water chemistry, metal speciation, and toxicological effects

6. Inorganic Copper Speciation Cu = 100 mg/L SO4 = 310 mg/L Data Source: Smith et al. (2007, Capulin leachate)

7. Regulatory Definitions Aquatic life criteria -estimates of concentrations of pollutants in ambient water that—if not exceeded—are expected to protect fish, invertebrates, and other aquatic life from adverse effects associated with exposure. Acute- exposure to a 1-hour average concentration of the chemical does not exceed the criterion more than once every 3 years on average. Chronic- exposure to a 4-day average concentration of the chemical does not exceed the criterion more than once every 3 years on average. Criterion Maximum Concentration (CMC)- estimate of the highest concentration of a material in ambient water to which an aquatic community can be exposed briefly without resulting in an unacceptable adverse effect. This is the acute criterion. Criterion Continuous Concentration (CCC)- estimate of the highest concentration of a material in ambient water to which an aquatic community can be exposed indefinitely without resulting in an unacceptable adverse effect. This is the chronic criterion.

8. EPA’s Numeric Aquatic Life Criteria for Metals: Hardness-Based Metal Criteria (acute criteria) (chronic criteria) Example (plug in numbers): CMC for Cu = exp{0.9422 [ln(hardness)]- 1.700} (0.960) from U.S. EPA (2009)

9. Evolution of EPA’s Numeric Aquatic Life Criteria for Metals One-size-fits-all national criteria Clean Water Act Total-recoverable metal concentrations Quality Criteria for Water (USEPA, 1976, Red Book) (total-recoverable concentrations) Hardness-based metal criteria CMC (acute) CCC (chronic) Quality Criteria for Water (USEPA, 1986, Gold Book) (hardness-adjusted criteria based on total-recoverable concentrations) Interim Guidance on Determination and Use of Water-Effect Ratios for Metals (USEPA, 1994) Water-Effect Ratio (WER) (adjustment to obtain site-specific value) Stay of Federal Water Quality Criteria for Metals (USEPA, 1995) (adopted dissolved metal concentrations) Dissolved metal concentrations Aquatic Life Ambient Freshwater Quality Criteria - Copper (USEPA, 2007) (incorporates use of the biotic ligand model in criteria derivation procedures) Biotic Ligand Model (BLM) prepared with information from Reiley (2007) Site-specific modification of criteria

10. What is the Biotic Ligand Model? (BLM…not the agency)

11. The Biotic Ligand Model is incorporated into the U.S. Environmental Protection Agency 2007 Updated Aquatic Life Copper Criteria

12. Biotic Ligand Model (BLM) • Computational approach to predict acute metal toxicity • Considered to be an alternative to expensive and extensive Water-Effect Ratio (WER) toxicological testing to determine site-specific water-quality criteria • Acute metal toxicity is simulated as the accumulation of metal at a biologically sensitive receptor (the biotic ligand, BL) • Other aquatic BLMs in development: Ag, Cd, Pb, Ni, and Zn • Cu is currently the only metal that has the BLM incorporated into its Aquatic Life Criteria • BLM is being considered for regulatory and risk-assessment frameworks worldwide • US, Canada, Australia, New Zealand, European Union

13. Competing Cations H+ Ca2+ Na+ M-DOM Organic Complexes (WHAM V) Tipping (1994) Inorganic Complexes (CHESS) Santore and Driscoll (1995) M-OH+ M-CO3 M-Cl+ How Does the Biotic Ligand Model Work? Speciation/Bioavailability Uptake/Toxicity FREE METAL ION M+2 FREE METAL ION M2+ Metal Binding Site Metal Binding Site Gill/Biotic Ligand after Pagenkopf (1983) The BLM is an interface between the fields of aqueous geochemistry, physiology, and aquatic toxicology

14. The 3 Cs of the Biotic Ligand Model • Concentration • more metal in solution translates to more available to bind the biotic ligand • Competition • between inorganic ligands, organic ligand, and the biotic ligand for the metal • between cations (e.g., Ca, Mg, Na, H) and the metal at the biotic ligand site • Complexation • metal is not available to bind to the biotic ligand when it is bound to other ligands (organic or inorganic) All calculated within a chemical equilibrium framework

15. Research Biotic Ligand Model • Define one metal, one organism • Speciation mode • chemical speciation of metal between inorganic ligands, organic ligands, and the biotic ligand • Toxicity mode (acute toxicity) • predicts LC50 (metal concentration that is lethal to 50% of a group of test organisms)

16. Biotic Ligand Model Input Parameters Temperature pH Metal concentration (if running speciation mode) Dissolved organic carbon (DOC) Percent DOC as humic acid (HA; default=10%) Ca, Mg, Na, K (major cations) SO4, Cl (major anions) Alkalinity (or dissolved inorganic carbon) (Sulfide) Dissolved data only

17. Research Biotic Ligand Model • One metal, one organism • each pair linked to a metal-organism parameter file (within the BLM program) • NO metal mixtures • Able to consider user-selected metal/organism • requires parameter file • Cu Water Quality Criteria • gives FAV, CMC, CCC, and TU(acute) • currently available only for Cu

18. Influence of Input Parameters • Ca and Mg concentrations • hardness is known to mitigate metal toxicity • Alkalinity and pH • speciation and toxicity of most metals influenced by pH • complexation (metal hydroxides and carbonates) and competition (BL-H interactions) • Dissolved organic carbon (DOC) • can be very important for some metals • for Cu, DOC-bound fraction is often dominant • not much information at mined sites or in mineralized systems

19. Cu and Zn Binding to DOC as a Function of pH Cu Zn Data Source: Smith et al. (2007, Capulin leachate)

20. Which parameters have the most influence on biotic ligand model computations?

21. Predicted Cu Accumulation at the Biotic Ligand for 3 pH values pH 5.5 pH 7.5 pH 9.0 Data Source: BLM Standard Water

22. Predicted Zn Accumulation at the Biotic Ligand for 3 pH values pH 7.5 pH 5.5 pH 9.0 Data Source: BLM Standard Water

23. pH Influence on Predicted Cu and Zn Toxicity Zn Cu Data Source: BLM Standard Water

24. Predicted Cu Accumulation at the Biotic Ligand for 3 DOC values 1 ppm 5 ppm 10 ppm Data Source: BLM Standard Water

25. Predicted Zn Accumulation at the Biotic Ligand for 3 DOC values 1 ppm 5 ppm 10 ppm Data Source: BLM Standard Water

26. DOC Influence on Predicted Cu and Zn Toxicity In Rainbow Trout Zn Cu Data Source: BLM Standard Water

27. How do BLM-based criteria compare with hardness-based criteria? Cu Criteria (calculated using EPA moderately hard water; hardness = 65 mg/L) from USEPA (2007, p. 12)

28. Some Challenges in Implementation of the Biotic Ligand Model (BLM) • Complete set of BLM input parameters has not historically been measured at most sites • estimation techniques not well established • Dissolved organic carbon (DOC) • need standardized collection and measurement techniques for use with the BLM • different “qualities” of DOC (e.g., headwater vs. wastewater) • temporal and spatial site variability • DOC fractionation in presence of Fe and Al • Current BLMs do not consider all influences on metal bioavailability and toxicity • multiple metal toxicity • dietary metal toxicity

29. Variability in Measured Parameters Yields Variability in BLM Toxicity Predictions Data Source: Kansas River, BLM Example Input File

30. EXAMPLE: Chemical Fractionation of Dissolved Organic Matter in Mineralized and Mined Areas Smith, K.S., Ranville, J.F., Diedrich, D.J., McKnight, D.M., and Sofield, R.M., 2009, Consideration of iron-organic matter interactions when predicting aquatic toxicity of copper in mineralized areas, in Proceedings of Securing the Future and the 8th International Conference on Acid Rock Drainage (ICARD), Skellefteå, Sweden, June 22-26, 2009, 9 p.

31. Dissolved Organic Matter (DOM) Fractionation McKnight et al. (1992) demonstrated that DOM fractionates in the presence of precipitating Fe and Al oxides • Some DOM is removed from solution by sorption onto precipitating Fe and Al oxides • DOM sorption results in chemical fractionation • molecules with greater contents of aromatic moieties, carboxylic acid groups, and amino acid residues are preferentially sorbed • Remaining DOM is depleted in the constituents that are preferentially sorbed

32. Dissolved Organic Matter Sources Impacted Not Impacted Deer Cr. Dissolved Snake R. Dissolved Snake R. Sediment from McKnight et al. (1992)

33. Toxicity Results 6 mg/L DOM Ceriodaphnia dubia No DOM Deer Cr. DOM (unfractionated) Snake R. DOM Snake R. Sediment Fraction Mortality Suwannee R. FA Less Toxic Total Copper Concentration (mg/L)

34. Free Copper Measured with a Cu ISE 6 mg/L DOM No DOM Cu2+ Deer Cr. DOM Suwannee R. FA Snake R. DOM Snake R. Sediment Bound Cu

35. Toxicity and Specific UV Absorbance (SUVA) SUVA correlates with LC50 SRFA Deer Creek Snake R Sed Snake R Diss

36. Summary DOM with greater affinity for metal binding tends to be preferentially sorbed to sediment phases in iron- and aluminum-rich streams DOM isolated from an iron- and aluminum-rich stream was 3 times less effective at reducing copper toxicity Fractionation of organic matter between dissolved and sediment phases in iron- and aluminum-rich streams can result in more bioavailable dissolved copper and greater potential for copper toxicity to aquatic biota Stream ecosystems downstream of iron- and aluminum-rich streams may be more vulnerable to adverse effects from metal toxicity

37. What does this mean for the Biotic Ligand Model?

38. Use of the Biotic Ligand Model in Mineralized Areas It is likely that a modified version of the BLM that incorporates the effects of Fe and Al will need to be used to compute site-specific water-quality criteria and potential metal toxicity in many mineralized areas

39. CASE STUDY Application of the BLM: Examining toxicity of Cd, Cu, & Zn in a river affected by acid mine drainage* • Study area • Geochemistry • Surface water toxicity tests • Predicted toxicity for water fleas & fathead minnows • Lessons learned *Balistrieri, L.S., Seal, R.R., Piatak, N.M., Paul, B., 2007. Assessing the concentration, speciation, and toxicity of dissolved metals during mixing of acid-mine drainage and ambient river water downstream of the Elizabeth Copper Mine, Vermont, USA. Applied Geochemistry 22, 930-952.

40. STUDY AREA Elizabeth Copper Mine Superfund Site Vermont, USA X Economic Minerals Pyrrhotite [Fe1-xS (x=0-0.2)] Chalcopyrite (CuFeS2) Sphalerite (ZnS) x x 4 sites Seeps at base of TP1

41. GEOCHEMISTRY

42. SURFACE WATER TOXICITY TESTS Reference Reference Hathaway et al. (2001)

43. PREDICTED TOXICITY TU = observed [Me]/LC50 or TU = observed [Me]/CMC

44. CASE STUDY – LESSONS LEARNED • Chemical Speciation of Metals • Can be highly variable at mine site due to ranges in pH & DOC • Cd & Zn primarily exist as free metal ions (Cd+2 & Zn+2) & inorganic complexes • Cu ranges from primarily free metal ions (Cu+2) & inorganic complexes at low pH to primarily Cu-DOC complexes at higher pH • Predicted Toxicity • Variable depending on site-specific chemical conditions • Variable among organisms & metals • Hardness-based predicted LC50 lower (larger TU) than BLM predicted LC50 for Cd & Zn, whereas CMC-hardness is higher (lower TU) than CMC-BLM for Cu. • Comparisons of observed & predicted toxicity at this site suggest that Cu is the metal of concern.

45. OVERALL CONCLUSIONS Biotic Ligand Model (BLM) PRO Links chemical speciation with bioavailability and toxicity Generates a prediction of toxicity for site-specific chemical conditions Potential alternative to expensive toxicological testing Easy to use CON To date, Cu is the only metal with BLM in EPA Aquatic Life Criteria One metal- one organism (no competition among organisms or metals) Need complete analysis of water (estimation of some parameters, such as DOC, could lead to incorrect toxicity predictions) Need to interpret inevitable variability in temporal and spatial predictions of toxicity at a given site For mineralized systems, need to incorporate Fe and Al, metal-binding capabilities of fractionated DOC, and high concentrations of multiple metals in BLM predictions

46. References Cited Balistrieri, L.S., Seal, R.R., Piatak, N.M., and Paul, B., 2007, Assessing the concentration, speciation, and toxicity of dissolved metals during mixing of acid-mine drainage and ambient river water downstream of the Elizabeth Copper Mine, Vermont, USA: Appl. Geochem., v. 22, p. 930-952. Hathaway, E.M., Lovely, W.P., Acone, S.E., and Foster, S.A., 2001, The other side of mining: Environmental assessment and the process for developing a cleanup approach for the Elizabeth Mine: Society of Economic Geologists Guidebook Series 35, p. 277-293. McKnight, D.M., Bencala, K.E., Zellweger, G.W., Aiken, G.R., Feder, G.L., and Thorn, K.A., 1992, Sorption of dissolved organic carbon by hydrous aluminum and iron oxides occurring at the confluence of Deer Creek with the Snake River, Summit County, Colorado: Environ. Sci. Technol., v. 26, p. 1388-1396. Pagenkopf, G.K., 1983, Gill surface interaction model for trace-metal toxicity to fishes: Role of complexation, pH, and water hardness: Environ. Sci. Technol., v. 17, p. 342-347. Reiley, M.C., 2007, Science, policy, and trends of metals risk assessment at EPA: How understanding metals bioavailability has changed metals risk assessment at US EPA: Aquat. Toxicol., v. 84, p. 292-298. Santore, R.C., and Driscoll, C.T., 1995, The CHESS model for calculating chemical equilibria in soils and solutions, in Loeppert, R., Schwab, A.P., Goldberg, S. (eds.), Chemical Equilibrium and Reaction Models, SSSA Special Publication 42: Soil Science Society of America, American Society of Agronomy, Madison, WI. Smith, K.S., Hageman, P.L., Briggs, P.H., Sutley, S.J., McCleskey, R.B., Livo, K.E., Verplanck, P.L., Adams, M.G., and Gemery-Hill, P.A., 2007, Questa baseline and pre-mining ground-water quality investigation: 19. Leaching characteristics of composited materials from mine waste-rock piles and naturally altered areas near Questa, New Mexico: U.S. Geological Survey Scientific Investigations Report 2006-5165, 49 p. (Available online at http://pubs.usgs.gov/sir/2006/5165/) Smith, K.S., Ranville, J.F., Diedrich, D.J., McKnight, D.M., and Sofield, R.M., 2009, Consideration of iron-organic matter interactions when predicting aquatic toxicity of copper in mineralized areas, in Proceedings of Securing the Future and the 8th International Conference on Acid Rock Drainage (ICARD), Theme 6--Environmental Impacts, Skellefteå, Sweden, June 22-26, 2009, 9 p. (Available online at http://www.proceedings-stfandicard-2009.com/) Tipping, E., 1994, WHAM--A chemical equilibrium model and computer code for waters, sediments, and soils incorporating a discrete site/electrostatic model of ion-binding by humic substances: Comput. Geosci., v. 20, p. 973-1023.

47. References Cited, cont. U.S. Environmental Protection Agency, 1976, Quality criteria for water (Red Book): U.S. Environmental Protection Agency, EPA 440/9-76-023. U.S. Environmental Protection Agency, 1986, Quality criteria for water (Gold Book): U.S. Environmental Protection Agency, EPA 440/5-86-001. U.S. Environmental Protection Agency, 1994, Interim guidance on determination and use of water-effect ratios for metals: U.S. Environmental Protection Agency, EPA-823-B-94-001, February, 1994, 184 p. U.S. Environmental Protection Agency, 1995, Stay of federal water quality criteria for metals; Administrative stay (FRL-5196-2): Federal Register, v. 60, no. 86 (4 May 1995), p. 22228-22229. U.S. Environmental Protection Agency, 2007, Aquatic life ambient freshwater quality criteria – copper: 2007 revision: U.S. Environmental Protection Agency, EPA-822-R-07-001, February, 2007, 204 p. (Available online at http://www.epa.gov/waterscience/criteria/copper/2007/index.htm) U.S. Environmental Protection Agency, 2009, National recommended water quality criteria: U.S. Environmental Protection Agency Office of Water, 21 p. (Available online at http://www.epa.gov/ost/criteria/wqctable/)

48. Biotic Ligand Model – Information Sources 2007 Updated Aquatic Life Copper Criteria: Download of complete criteria document, Fact Sheet, Federal Register Notice, Biotic Ligand Model (BLM) .exe file, and user’s guide (EPA 822-R-07-001) http://water.epa.gov/scitech/swguidance/waterquality/standards/criteria/aqlife/pollutants/copper/2007_index.cfm Download of BLM Windows Interface Version, BLM-Monte Version, and User’s Guides http://www.hydroqual.com/wr_blm.html The Biotic Ligand Model: Technical Support Document for Its Application to the Evaluation of Water Quality Criteria for Copper (EPA 822-R-03-027) http://www.epa.gov/waterscience/criteria/copper/2007/blm-tsd.pdf Copper Aquatic Life Criteria: Supplementary Training Materials http://water.epa.gov/scitech/swguidance/waterquality/standards/criteria/aqlife/pollutants/copper/faq_index.cfm Water Quality Standards Academy: Copper Biotic Ligand Module http://water.epa.gov/learn/training/standardsacademy/blm_index.cfm http://water.epa.gov/learn/training/standardsacademy/references.cfm

49. Biotic Ligand Model – Selected General References

50. Biotic Ligand Model – Our Papers Balistrieri, L.S., and Blank, R.G., 2008, Dissolved and labile concentrations of Cd, Cu, Pb, and Zn in the South Fork Coeur d’Alene River, Idaho: Comparisons among chemical equilibrium models and implications for biotic ligand models: Applied Geochemistry, v. 23, p. 3355-3371. Balistrieri, L.S., Seal, R.R. II, Piatak, N.M., and Paul, B., 2007, Assessing the concentration, speciation, and toxicity of dissolved metals during mixing of acid-mine drainage and ambient river water downstream of the Elizabeth Copper Mine, Vermont, USA: Applied Geochemistry, v. 22, p. 930-952. Smith, K.S., 2005, Use of the biotic ligand model to predict metal toxicity to aquatic biota in areas of differing geology, in Proceedings of the 2005 National Meeting of the American Society of Mining and Reclamation, Breckenridge, Colorado, June 19-23, 2005, p. 1134-1154. (Available online at dept.ca.uky.edu/asmr/W/Full%20Papers%202005/1134-Smith-CO.pdf) Smith, K.S., 2007, Strategies to predict metal mobility in surficial mining environments, Chapter 3, in DeGraff, J.V., ed., Reviews in Engineering Geology, v. 17, Understanding and Responding to Hazardous Substances at Mine Sites in the Western United States: Geological Society of America, p. 25-45. (doi:10.1130/2007.4017(03)) Smith, K.S., Ranville, J.F., Adams, M.K., Choate, L.M., Church, S.E., Fey, D.L., Wanty, R.B., and Crock, J.G., 2006, Predicting toxic effects of copper on aquatic biota in mineralized areas by using the biotic ligand model, in Proceedings of the Seventh International Conference on Acid Rock Drainage (ICARD 7), St. Louis, Missouri, March 26-30, 2006, p. 2055-2077. (Available online at http://www.imwa.info/docs/imwa_2006/2055-Smith-CO.pdf) Smith, K.S., Ranville, J.F., Diedrich, D.J. McKnight, D.M., and Sofield, R.M., 2009, Consideration of iron-organic matter interactions when predicting aquatic toxicity of copper in mineralized areas, in Proceedings of Securing the Future and 8th International Conference on Acid Rock Drainage (ICARD), Skellefteå, Sweden, June 22-26, 2009, 9 p. (Available online at http://www.proceedings-stfandicard-2009.com/) Todd, A.S., Brinkman, S., Wolf, R.E., Lamothe, P.J., Smith, K.S., and Ranville, J.F., 2009, An enriched stable-isotope approach to determine the gill-zinc binding properties of juvenile rainbow trout (Oncorhynchus mykiss) during acute zinc exposures in hard and soft waters: Environmental Toxicology and Chemistry, v. 28, no. 6, p. 1233-1243. Wolf, R.E., Todd, A.S., Brinkman, S., Lamothe, P.J., Smith, K.S., and Ranville, J.F., 2009, Measurement of total Zn and Zn isotope ratios by quadrupole ICP-MS for evaluation of Zn uptake in gills of brown trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss): Talanta, v. 80, p. 676-684.