Copper and Cadmium Binding to Fish Gills: Estimates of Metal–Gill Stability Constants and Modelling of Metal Accumulation

Playle, Richard C.; Dixon, D. George; Burnison, Kent

doi:10.1139/f93-291

Cited by 325 publications

(332 citation statements)

References 32 publications

Supporting

Mentioning

301

Contrasting

Unclassified

Order By: Relevance

“…The binding constants for biotic ligand-cation complexes are adopted from the work of Playle et al (1993) and Playle (1998). Binding constants for metal-organic matter interactions are determined using the Windermere Humic Aqueous Model (WHAM; Tipping, 1994), and inorganic binding constants are determined using the CHESS model (Santore and Driscoll, 1995).…”

Section: The Biotic Ligand Modelmentioning

confidence: 99%

Use of the Biotic Ligand Model to Predict Metal Toxicity to Aquatic Biota in Areas of Differing Geology

Smith¹

2005

ASMR

View full text Add to dashboard Cite

Abstract. This work evaluates the use of the biotic ligand model (BLM), an aquatic toxicity model, to predict toxic effects of metals on aquatic biota in areas underlain by different rock types. The chemical composition of water, soil, and sediment is largely derived from the composition of the underlying rock. Geologic source materials control key attributes of water chemistry that affect metal toxicity to aquatic biota, including: 1) potentially toxic elements, 2) alkalinity, 3) total dissolved solids, and 4) soluble major elements, such as Ca and Mg, which contribute to water hardness. Miller (2002) compiled chemical data for water samples collected in watersheds underlain by ten different rock types, and in a mineralized area in western Colorado. He found that each rock type has a unique range of water chemistry. In this study, the ten rock types were grouped into two general categories, igneous and sedimentary. Water collected in watersheds underlain by sedimentary rock has higher mean pH, alkalinity, and calcium concentrations than water collected in watersheds underlain by igneous rock. Water collected in the mineralized area had elevated concentrations of calcium and sulfate in addition to other chemical constituents. Miller's water-chemistry data were used in the BLM (computer program) to determine copper and zinc toxicity to Daphnia magna. Modeling results show that waters from watersheds underlain by different rock types have characteristic ranges of predicted LC 50 values (a measurement of aquatic toxicity) for copper and zinc, with watersheds underlain by igneous rock having lower predicted LC 50 values than watersheds underlain by sedimentary rock. Lower predicted LC 50 values suggest that aquatic biota in watersheds underlain by igneous rock may be more vulnerable to copper and zinc inputs than aquatic biota in watersheds underlain by sedimentary rock. For both copper and zinc, there is a trend of increasing predicted LC 50 values with increasing dissolved organic carbon (DOC) concentrations. Predicted copper LC 50 values are extremely sensitive to DOC concentrations, whereas alkalinity appears to have an influence on zinc toxicity at alkalinities in excess of about 100 mg/L CaCO 3 . These findings show promise for coupling the BLM (computer program) with measured water-chemistry data to predict metal toxicity to aquatic biota in different geologic settings and under different scenarios. This approach may ultimately be a useful tool for mine-site planning, mitigation and remediation strategies, and ecological risk assessment. Additional

show abstract

Section: The Biotic Ligand Modelmentioning

confidence: 99%

Use of the Biotic Ligand Model to Predict Metal Toxicity to Aquatic Biota in Areas of Differing Geology

Smith¹

2005

ASMR

View full text Add to dashboard Cite

show abstract

“…The next generation equilibrium models such as REDEQL (Morel and Morgan, 1972) and GEOCHEM (Sposito and Mattigod, 1980) incorporated methods of convergence, interfacing NewtonRaphson and successive approximation methods. The Biotic Ligand Model (BLM, Pagenkopf, 1983), almost a derivative of the Free-Ion Model (FIM), is a recent development relating chemical forms of metals with toxicity to organisms (Bell et al, 2002;Campbell 2002;Campbell et al, 2002;Chapman et al, 2003;Di Toro et al, 2001;McGeer et al, 2000;Morgan and Wood, 2004;Playle, 1998;Playle et al, 1993;Tipping, 1994). The model aims at predicting interactions of dissolved metals with aquatic organisms that eventually affect them.…”

Section: Introductionmentioning

confidence: 99%

Modeling chemical speciation of copper in River Yamuna at Delhi, India

Jagadeesh¹,

Azeez²,

Banerjee

2006

Chemical Speciation & Bioavailability

View full text Add to dashboard Cite

Chemical modeling of copper in the river Yamuna was attempted by an equilibrium constant method, using a computer program COCSOC developed for the purpose. Concentrations of metals (Cu, Ca and Mg), ligands (organics, carbonates and bicarbonates) and stability constants of the probable complexes were the inputs for the modified Newton -Raphson iteration. The model adequately predicted concentrations of various copper species, even without taking into consideration solid phases, other competing metals and ligands. The free cupric ion concentrations estimated were in the range of 10 À 17 to 10 À 16 M, undetectable by ion selective electrodes in the water from the river. The non-convergence of equilibrium computations for certain data sets at some sampling sites indicates the prevailing nonequilibrium conditions in the river due to large-scale release of ligands and metal ions through several drains.

show abstract

“…Toxicity is modeled as a simple, empirical correlate of this accumulation and, to the extent that toxicity involves internalization of the metal and transport to other sites, this is assumed to be proportional to accumulation at the gill surface. Playle and associates [13,14] supplied key early support for this model by demonstrating toxic metal accumulation on fish gills to be reduced both by metal-complexing ligands and by other cations, and also by measuring key model parameters.Regulatory application of such a model was hampered by the limited availability of suitable effects data for a variety of species and the lack of appropriate meta-analysis of available data. Also problematic was measuring or predicting metal speciation for the complex mixtures of organic matter in natural waters, although significant advances were also being made regarding this [5,15].…”

mentioning

confidence: 99%

The biotic ligand model approach for addressing effects of exposure water chemistry on aquatic toxicity of metals: Genesis and challenges

Erickson

2013

Enviro Toxic and Chemistry

View full text Add to dashboard Cite

A major uncertainty in many aquatic risk assessments for toxic chemicals is the aggregate effect of the physicochemical characteristics of exposure media on toxicity and how this affects extrapolation of laboratory test results to natural systems. A notable example of this is how metal toxicity in freshwater varies because of factors such as water hardness, alkalinity, pH, dissolved organic carbon, and suspended solids. This has been the subject of hundreds of studies over the last 50 yr and of various papers in Environmental Toxicology and Chemistry since its inception, including 4 of the "Top 100" cited papers [1][2][3][4]. One study found median lethal concentrations (LC50s) for acute copper toxicity to fathead minnows to vary by more than 100-fold across various exposure water compositions well within the range observed in natural systems [1]. Approaches for modeling and predicting such variation have also been the subject of these efforts. An important example of this is the biotic ligand model (BLM), an approach first described and implemented in Di Toro et al. [2] and Santore et al. [3], and a focus of considerable research activity and regulatory development over the last 15 years. GENESIS OF THE BLM APPROACHThe BLM represents an integration of decades of work regarding metal speciation, accumulation, toxicity, and physiology [5] that can be only briefly summarized here. Studies in the 1960s and 1970s demonstrated that the toxicity of several metals to freshwater organisms varied with hardness, alkalinity, pH, and organic ligands, for which 2 major mechanisms were inferred [6][7][8]. First, the toxicity of a metal varies with its chemical speciation and often is closely correlated with the "free" (uncomplexed) metal ion, although in some situations other metal species contribute to accumulation or toxicity. Second, cations such as calcium and hydrogen ions can have effects on toxicity independent of toxic metal speciation; these cations were postulated to ameliorate toxicity by competing with toxic metal ions for binding sites on the gill [9]. These mechanisms pertain to bioavailability-how exposure conditions affect the amount of metal accumulation relative to the total concentration in the exposure medium. However, calcium was also recognized to have effects on gill permeability and thus could affect toxicity other than as a competing cation [6,8].Some of these early toxicological findings were incorporated into water quality regulations, such as the hardness dependence of the US Environmental Protection Agency's (USEPA) aquatic life criteria for metals [10]. However, such simple correlation models incompletely describe the effects of exposure chemistry. A broader, mechanistic perspective of these effects was articulated by Morel [11], and by Pagenkopf [12] in his gill surface interaction model (GSIM). In the GSIM, bioavailability is modeled based on the binding of toxic metal species (free metal or other species) to sites on the gill surface, this binding being affected by 1) metal speciation that det...

show abstract

Copper and Cadmium Binding to Fish Gills: Estimates of Metal–Gill Stability Constants and Modelling of Metal Accumulation

Cited by 325 publications

References 32 publications

Use of the Biotic Ligand Model to Predict Metal Toxicity to Aquatic Biota in Areas of Differing Geology

Use of the Biotic Ligand Model to Predict Metal Toxicity to Aquatic Biota in Areas of Differing Geology

Modeling chemical speciation of copper in River Yamuna at Delhi, India

The biotic ligand model approach for addressing effects of exposure water chemistry on aquatic toxicity of metals: Genesis and challenges

Contact Info

Product

Resources

About