An Introduction to the Biotic Ligand Model (BLM) 3-01-06 An Introduction to the Biotic Ligand Model (BLM) WQSA: Introduction to the BLM

Generalized BLM Framework 3-01-06 Generalized BLM Framework Competing Cations Metal ion M+2 Free H+ Ca+2 Na+ Organic Ligand Complexes Inorganic Gill Surface (biotic ligand) Metal Binding Site M OH+ M CO3+ M Cl+ M - DOC WQSA: Introduction to the BLM

Biotic Ligand Model Free Ion Model (1993): Chemical model 3-01-06 Biotic Ligand Model Free Ion Model (1993): Chemical model Gill Model (1996):Toxicological model Refinement and incorporation into criterion (2000-2004) 3-01-06 WQSA: Introduction to the BLM

Biotic Ligand Model: What does it do? 3-01-06 Biotic Ligand Model: What does it do? Complements the existing Guideline procedures. Provides a way to account for the effect of water chemistry, in addition to hardness, on metal bioavailability and toxicity. Should lead to an improved capability to assess the potential for adverse effects to aquatic biota. 3-01-06 WQSA: Introduction to the BLM

BLM Parameters (realities and assumptions) 3-01-06 BLM Parameters (realities and assumptions) Inorganic Values from thermodynamic database Organic Values from calibration to chemical measurements with Organic Matter Biotic Values derived from a limited number of accumulation datasets Most parameters assumed to be consistent for other organisms, since ion-transport mechanisms are similar LA50 used account for variation in species sensitivity BLM parameter values: This slide summarizes the parameter values that are used in the BLM The chemical parameters represent thermodynamic values that should remain constant for all BLM applications Biotic ligand parameters may change, but limited data exists for several fish During BLM development we have assumed that values for binding parameters are the same for all organisms To adjust model sensitivity, the only parameter that will be changed is the LA50. WQSA: Introduction to the BLM

Problem with Metals Criteria 3-01-06 Problem with Metals Criteria The same metal concentration exerts different degrees of toxicity from time to time and from place to place. The BLM formulates the key controlling constituents as pH, Ca, Na, CO3, and DOC. 3-01-06 WQSA: Introduction to the BLM

Current Water Quality Criteria (WQC) 3-01-06 Current Water Quality Criteria (WQC) WQC do not typically reflect the effects of other water chemistry factors that are also known to affect metal toxicity. 3-01-06 WQSA: Introduction to the BLM

Effect of Hardness on Toxicity 3-01-06 Effect of Hardness on Toxicity Fathead Minnow Data Effect of Hardness on Copper Toxicity to Fathead Minnows (Erickson et al., 1996) 5 4 R2=0.954 3 Copper LC50 (umol/L) 2 1 50 100 150 200 3-01-06 Hardness (mg/L as CaCO3) WQSA: Introduction to the BLM

Limits of Hardness Normalization 3-01-06 Limits of Hardness Normalization Potentially under-protective at low pH. Over-protective at higher DOC. Requires Water Effect Ratio (WER) for correction. 3-01-06 WQSA: Introduction to the BLM

USEPA Site-specific WQC Methods 3-01-06 USEPA Site-specific WQC Methods Three methods are available for use: Recalculation procedure Water Effect Ratio (WER) procedure Resident species procedure 3-01-06 WQSA: Introduction to the BLM

The Alternative: Biotic Ligand Model 3-01-06 The Alternative: Biotic Ligand Model The BLM quantitatively evaluate the effects of other factors affecting toxicity thus providing an alternative way to evaluate a WER. 3-01-06 WQSA: Introduction to the BLM

Comparison of Approaches 3-01-06 Comparison of Approaches BLM versus WER WER: Comprehensive in scope, but sampling error is high, precision low. BLM: Limited in model formulation, but sampling error low. BLM is implemented as hardness normalization replacement (directly into criterion). WQSA: Introduction to the BLM

Question: can accumulation be uniquely related to a toxic effect? 3-01-06 Question: can accumulation be uniquely related to a toxic effect? (Data: MacRae, 1994 and 1999) ) % TOTAL Cu = 10 ug/L ( y i t a l 100 r t o M t u o r 80 T w o b n i a 60 R GILL LA50 e l i ~10 nmol/g n w e v u J 40 r u o H - 2 1 20 10 20 30 40 50 24-Hour Gill Cu (nmol/g wet weight) WQSA: Introduction to the BLM

Importance of Organic Matter 3-01-06 Importance of Organic Matter Data from Clemson U. (WERF BLM Project) WQSA: Introduction to the BLM

Predicted Versus Measured LC50s 3-01-06 Predicted Versus Measured LC50s K+2 added WQSA: Introduction to the BLM

Summary & Conclusions Water chemistry affects metal toxicity. 3-01-06 Summary & Conclusions Water chemistry affects metal toxicity. Metal concentration, complexation and competition are important. Toxicity can be predicted by knowing the metal: biotic ligand concentration (i.e., LA50). Same concepts apply to other metals ….. Must consider thermodynamics WQSA: Introduction to the BLM

3-01-06 Beginning with consideration of species sensitivity, we will explore how the BLM may be applied to other organisms and to other metals (e.g., Ag, Cd, Ni, Pb and Zn). WQSA: Introduction to the BLM

Application to Organisms 3-01-06 Application to Organisms +LA50 -LA50 WQSA: Introduction to the BLM

Cu BLM: Ceriodaphnia dubia 3-01-06 Cu BLM: Ceriodaphnia dubia 1000 100 Predicted LC50 (ug/L) 10 1 1 10 100 1000 WQSA: Introduction to the BLM

Cu BLM: Daphnia pulex ) L / g u ( 5 C L D E T C I D E R P 3-01-06 Cu BLM: Daphnia pulex 1 10 100 1000 CT DEP (Dunbar, 1996) Table 1, WQC Document Data ) L / g u ( 5 C L D E T C I D E R P 1 10 100 1000 MEASURED LC50 (ug/L) WQSA: Introduction to the BLM

Cu BLM: Invertebrate Summary 3-01-06 Cu BLM: Invertebrate Summary 1000 D. magna D. pulicaria H. azteca C. dubia D. pulex 100 BLM Predicted Cu LC50 (ug/L) 10 1 1 10 100 1000 Measured Cu LC50 (ug/L) WQSA: Introduction to the BLM

3-01-06 Cu BLM 1 10 100 1000 10000 Fathead minnows, Lab Fathead minnows, Field + D. pulex (CT DEP, Dunbar, 1996) P R E D I C T L 5 ( u g / ) + + + + + + + + + + + + + + + + + 1 10 100 1000 10000 MEASURED LC50 (ug/L) WQSA: Introduction to the BLM

3-01-06 Ag BLM WQSA: Introduction to the BLM

Cadmium solubility exceeded 3-01-06 Cd BLM Rainbow Trout Data 10000 Davies et al, 1993 * Cusimano et al, 1986 1000 ) L Hollis et al / g Pascoe et al u ( 5 Cadmium solubility exceeded C L 100 d C D E * T C I 10 D E R P * 1 * 0.1 0.1 1 10 100 1000 10000 MEASURED Cd LC50 (ug/L) WQSA: Introduction to the BLM

Ni BLM: Fathead Minnow Results 3-01-06 Ni BLM: Fathead Minnow Results BLM Predicted vs Measured Ni LC50 for Fathead Minnows 1000 Meyer et al., 1999 (1-6g, LA50=291 nmol/g) Pickering and Henderson, 1966 ( 1-2g, LA50=51 nmol/g) Schubauer-Berigan et al., 1993 ( < 24 hr old, LA50=6.7 nmol/g) 100 BLM Predicted Ni LC50 (mg/L) 10 1 1 10 100 1000 Measured Ni LC50 (mg/L) WQSA: Introduction to the BLM

Ni BLM: Fathead Minnow & Invertebrate Results 3-01-06 A Comparison of BLM Predicted vs Measured Nickel LC50 1000 Fathead Minnows, 1-6 g Fathead Minnows, 1-2 g 100 Fathead Minnows, < 24hr old Daphnia magna Ceriodaphnia dubia 10 BLM Predicted Ni LC50 (mg/L) Ceriodaphnia dubia 1 pH effects 0.1 0.01 0.01 0.1 1 10 100 1000 Measured Ni LC50 (mg/L) WQSA: Introduction to the BLM

3-01-06 Pb BLM WQSA: Introduction to the BLM

Zn BLM All available datasets - Rainbow trout 100,000 10,000 1000 3-01-06 Zn BLM All available datasets - Rainbow trout 100,000 > Actual LC50 Greater 10,000 > 1000 PREDICTED Zn LC50 (ug/L) 100 10 10 100 1000 10,000 100,000 MEASURED Zn LC50 (ug/L) WQSA: Introduction to the BLM

San Francisco Bay Case Study 3-01-06 San Francisco Bay Case Study BLM Application to Mytilus edulis 1 10 100 Measured Cu EC50 (ug/L) CONTROLS (TOC = 1.0 mg/L) BLM Predicted vs.Observed EC50s for M. edulis (Data: City of San Jose WPCP) BLM Predicted Cu EC50 (ug/L) WQSA: Introduction to the BLM

Validation of BLM For Mytilus 3-01-06 Validation of BLM For Mytilus BLM Results Multiple Estuaries WQSA: Introduction to the BLM

How did EPA incorporate the BLM into the criteria process? Characterize the water chemistry for sufficient number of taxonomic groups to meet minimum data requirements. Normalize acute studies (LC50) to standard water condition using the BLM. Use normalized data to calculate 5 percentile FAV. A LA50 is associated to this FAV. Given site-specific water chemistry, this LA50 is used by the BLM to evaluate a site-specific FAV. The site-specific AWQC = FAV/2.

Advantages of using the BLM 3-01-06 Advantages of using the BLM  Water chemistry data are cheaper to obtain than are bioassays.  Historical data may be used providing for the capability to make hind-casts.  Improves our understanding of how water chemistry affects metal availability and toxicity.  A combination of bioassay-based methods and computational methods may be used. WQSA: Introduction to the BLM

EPA Draft Copper Criteria 3-01-06 EPA Draft Copper Criteria Released December 2003 Draft document: BLM-normalized freshwater criterion. BLM model used as a replacement for the hardness equation. Allows prediction of acute WQC using an approach similar to that of predicting organism toxicity. WQSA: Introduction to the BLM

Summary and Conclusions 3-01-06 Summary and Conclusions Species sensitivity has important implications for the derivation of site-specific water quality criteria. The BLM has been successfully applied to a number of organisms with varying sensitivity to copper and other metals. The BLM can be used to calculate site specific copper criteria that agrees remarkably well with bioassay-based WER studies. BLM may eliminate the need for WER studies. WQSA: Introduction to the BLM

Summary and Conclusions 3-01-06 Summary and Conclusions The BLM compares well in freshwater environments. A site-specific criteria can be developed in less time and with lower costs. The BLM can be used to develop estimates of spatial or temporal variation in metal bioavailability. WQSA: Introduction to the BLM

Cited and Supplemental References on the BLM and Related Topics 3-01-06 Bibliography Cited and Supplemental References on the BLM and Related Topics Chapman, G.A., S. Ota and F. Recht, January 1980. “Effects of Water Hardness on the Toxicity of Metals to Daphnia magna,” a USEPA project status report. City of San José. 1998. Development of a site-specific water quality criterion for copper in South San Francisco Bay. San José/Santa Clara Water Pollution Control Plant, San José, CA. 171 pp. Cusimano, R.F., D.F. Brakke and G.A. Chapman 1986. Effects of pH on the toxicities of cadmium, copper and zinc to steelhead trout (Salmo gairdneri). Can.J.Fish.Aquat.Sci. 43(8):1497-1503. Davis, A. and D. Ashenberg. 1989. The aqueous geochemistry of the Berkeley Pit, Butt, Montana, U.S.A. Appl. Geochem. 4:23-36. Dunbar, L.E., 1996b. “Derivation of a Site-Specific Dissolved Copper Criteria for Selected Freshwater Streams in Connecticut,” Falmouth MA, Connecticut DEP, Water Toxics Program, Falmouth, MA. (excerpt from an uncited report that was received from author) Erickson, R.J., D.A. Benoit and V.R. Mattson, 1987. “A Prototype Toxicity Factors Model For Site-Specific Copper Water Quality Criteria,” revised September 5, 1996, United States Environmental Protection Agency, Environmental Research Laboratory-Duluth, Duluth, MN. Erickson, R.J., D.A. Benoit, V.R. Mattson, H.P. Nelson Jr. and E.N. Leonard, 1996. “The Effects of Water Chemistry on the Toxicity of Copper to Fathead Minnows,” Environmental Toxicology and Chemistry, 15(2): 181-193. MacRae, R.K., December, 1994. “The Copper Binding Affinity of Rainbow Trout (Oncorhynchus mykiss) and Brook Trout (Salvelinus fontinalis) Gills,” a thesis submitted to the Department of Zoology and Physiology and The Graduate School of the University of Wyoming in partial fulfillment of the requirements for the degree of Master of Science in Zoology and Physiology. MacRae, R.K., D.E. Smith, N. Swoboda-Colberg, J.S. Meyer and H.L. Bergman, 1999. “Copper Binding Affinity of Rainbow Trout (Oncorhynchus mykiss) and Brook Trout (Salvelinus fontinalis) Gills: Implications for Assessing Bioavailable Metal,” Environmental Toxicology and Chemistry, 18(6): 1180-1189. Meyer, J.S., R.C. Santore, J.P. Bobbitt, L.D. DeBrey, C.J. Boese, P.R. Paquin, H.E. Allen, H.L. Bergman and D.M. DiToro, 1999. “Binding of Nickel and Copper to Fish Gills Predicts Toxicity When Water Hardness Varies, But Free-ion Activity Does Not,” Environmental Science and Technology, 33(6): 913-916. Pickering, Q.H., and C. Henderson, 1966. “The Acute Toxicity of Some Heavy Metals to Different Species of Warmwater Fishes,” International Journal of Air and Water Pollution, 10: 453-463. Playle, R., L. Hollis, N. Janes and K. Burnison, August 6-9, 1995. “Silver, Copper, Cadmium, Dissolved Organic Carbon, and Fish,” extended abstract in Transport, Fate and Effects of Silver in the Environment, 3rd International Conference Proceedings of Argentum, an International Conference, Washington, DC. Schubauer-Berigan, M.K., J.R. Dierkes, P.D. Monson and G.T. Ankley, 1993. “pH-Dependent Toxicity of Cd, Cu, Ni, Pb and Zn to Ceriodaphnia dubia, Pimephales promelas, Hyalella azteca and Lumbriculus variegatus,” Environmental Toxicology and Chemistry, 12: 1261-1266. Stephan, C.E., D.I. Mount, D.J. Hansen, J.H. Gentile, G.A. Chapman and W.A. Brungs, January 1985. “Guidelines for Deriving Numerical National Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses,” USEPA Office of Research and Development, Environmental Research Laboratories: Duluth, Minnesota; Narragansett, Rhode Island and Corvallis, Oregon, 98 pp. WQSA: Introduction to the BLM