Dominic M. Di Toro

Predicting sediment metal toxicity using a sediment biotic ligand model: methodology and initial application

An extension of the simultaneously extracted metals/acid-volatile sulfide (SEM/AVS) procedure is presented that predicts the acute and chronic sediment metals effects concentrations. A biotic ligand model (BLM) and a pore water-sediment partitioning model are used to predict the sediment concentration that is in equilibrium with the biotic ligand effects concentration. This initial application considers only partitioning to sediment particulate organic carbon. This procedure bypasses the need to compute the details of the pore-water chemistry. Remarkably, the median lethal concentration on a sediment organic carbon (OC)-normalized basis, SEM*(x,OC), is essentially unchanged over a wide range of concentrations of pore-water hardness, salinity, dissolved organic carbon, and any other complexing or competing ligands. Only the pore-water pH is important. Both acute and chronic exposures in fresh- and saltwater sediments are compared to predictions for cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) based on the Daphnia magna BLM. The SEM*(x,OC) concentrations are similar for all the metals except cadmium. For pH = 8, the approximate values (micromol/gOC) are Cd-SEM*(xOC) approximately equal to 100, Cu-SEM*(x,OC) approximately equal to 900, Ni-SEMoc approximately equal to 1,100, Zn-SEM*(x,OC) approximately equal to 1,400, and Pb-SEM*(x,OC) approximately equal to 2,700. This similarity is the explanation for an empirically observed dose-response relationship between SEM and acute and chronic effects concentrations that had been observed previously. This initial application clearly demonstrates that BLMs can be used to predict toxic sediment concentrations without modeling the pore-water chemistry.

Predicting the toxicity of neat and weathered crude oil: toxic potential and the toxicity of saturated mixtures.

The toxicity of oils can be understood using the concept of toxic potential, or the toxicity of each individual component of the oil at the water solubility of that component. Using the target lipid model to describe the toxicity and the observed relationship of the solubility of oil components to log (Kow), it is demonstrated that components with lower log (Kow) have greater toxic potential than those with higher log (Kow). Weathering removes the lower-log (Kow) chemicals with greater toxic potential, leaving the higher-log (Kow) chemicals with lower toxic potential. The replacement of more toxically potent compounds with less toxically potent compounds lowers the toxicity of the aqueous phase in equilibrium with the oil. Observations confirm that weathering lowers the toxicity of oil. The idea that weathering increases toxicity is based on the erroneous use of the total petroleum hydrocarbons or the total polycyclic aromatic hydrocarbons (PAHs) concentration as if either were a single chemical that can be used to gauge the toxicity of a mixture, regardless of its makeup. The toxicity of the individual PAHs that comprise the mixture varies. Converting the concentrations to toxic units (TUs) normalizes the differences in toxicity. A concentration of one TU resulting from the PAHs in the mixture implies toxicity regardless of the specific PAHs that are present. However, it is impossible to judge whether 1 microg/L of total PAHs is toxic without knowing the PAHs in the mixture. The use of toxic potential and TUs eliminates this confusion, puts the chemicals on the same footing, and allows an intuitive understanding of the effects of weathering.

Validation of the target lipid model for toxicity assessment of residual petroleum constituents: Monocyclic and polycyclic aromatic hydrocarbons

A method is presented for developing scientifically defensible, numeric guidelines for residual petroleum-related constituents, specifically monocyclic aromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs), in the water column. The guidelines are equivalent to a HC5 (i.e., hazard concentration to 5% of the tested species, or the concentration that protects 95% of the tested species). The model of toxicity used in this evaluation is the target lipid model (TLM) that was developed for assessing the toxicity of type I narcotic chemicals. An acute to chronic ratio is used for chronic expression and sublethal effects. The TLM is evaluated by comparing predicted and observed toxicity of these petroleum components. The methodology is capable of predicting both the acute and chronic toxicity of MAHs and PAHs in single exposures and in mixtures. For acute exposures, the TLM was able to predict the toxicity to within a factor of three to five. The use of toxic units was an effective metric for expressing the toxicity of mixtures. Within the uncertainty bounds, the TLM correctly predicted where sublethal effects of edemas, hemorrhaging, and other abnormalities were observed to occur in early life-stage exposure to PAHs. The computed HC5s were lower than no-observed-effect concentrations based on growth, reproduction, and mortality endpoints and sublethal effects. The methodology presented can be used by the oil spill community to compare residual concentrations of PAHs against defensible, numeric guidelines to assess potential ecological impacts.

Soluble nickel inhibits HIF-prolyl-hydroxylases creating persistent hypoxic signaling in A549 cells

Soluble nickel compounds are carcinogenic to humans although the mechanism by which they cause cancer remains unclear. One major consequence of exposure to nickel is the stabilization of hypoxia inducible factor‐1α (HIF‐1α), a protein known to be overexpressed in a variety of cancers. In this study, we report a persistent stabilization of HIF‐1α by nickel chloride up to 72 h after the removal of nickel from the culture media. In addition, we show that the HIF‐prolyl hydroxylases (PHDs) are inhibited when cells are exposed to nickel and that they remain repressed for up to 72 h after nickel is removed. We then show that nickel can inhibit purified HIF‐PHDs 2 in vitro, through direct interference with the enzyme. Through theoretical calculations, we also demonstrate that nickel may be able to replace the iron in the active site of this enzyme, providing a plausible mechanism for the persistent inhibition of HIF‐PHDs by nickel. The data presented suggest that nickel can interfere with HIF‐PHD directly and does not inhibit the enzyme by simply depleting cellular factors, such as iron or ascorbic acid. Understanding the mechanisms by which nickel can inhibit HIF‐PHDs and stabilize HIF‐1α may be important in the treatment of cancer and ischemic diseases.

Validation of the narcosis target lipid model for petroleum products: Gasoline as a case study

The narcosis target lipid model (NTLM) was used to predict the toxicity of water-accommodated fractions (WAFs) of six gasoline blending streams to algae (Pseudokirchnereilla subcapitata, formerly Selenastrum capricornutum), juvenile rainbow trout (Oncorhynchus mykiss), and water flea (Daphnia magna). Gasolines are comprised of hydrocarbons that on dissolution into the aqueous phase are expected to act via narcosis. Aquatic toxicity data were obtained using a lethal-loading test in which WAFs were prepared using different gasoline loadings. The compositions of the gasolines were determined by analysis of C3 to C13 hydrocarbons grouped in classes of n-alkanes, iso-alkanes, aromatics, cyclic alkanes, and olefins. A model was developed to compute the concentrations of hydrocarbon blocks in WAFs based on gasoline composition and loading. The model accounts for the volume change of the gasoline, which varies depending on loading and volatilization loss. The predicted aqueous composition of WAFs compared favorably to measurements, and the predicted aqueous concentrations of WAFs were used in the NTLM to predict the aquatic toxicity of the gasolines. For each gasoline loading and species, total toxic units (TUs) were computed with an assumption of additivity. The acute toxicity of gasolines was predicted to within a factor of two for algae and daphnids. Predicted TUs overestimated toxicity to trout because of experimental factors that were not considered in the model. This analysis demonstrates the importance of aliphatic hydrocarbon loss to headspace during WAF preparation and the contribution of both aromatic and aliphatic hydrocarbons test to the toxicity of gasolines in closed systems and loss of aliphatics to headspace during WAF preparation. Model calculations indicate that satisfactory toxicity predictions can be achieved by describing gasoline composition using a limited number of aromatic and aliphatic hydrocarbon blocks with different octanol-water partition coefficients.

Mechanistic sediment quality guidelines based on contaminant bioavailability: Equilibrium partitioning sediment benchmarks

Globally, estimated costs to manage (i.e., remediate and monitor) contaminated sediments are in the billions of U.S. dollars. Biologically based approaches for assessing the contaminated sediments which pose the greatest ecological risk range from toxicity testing to benthic community analysis. In addition, chemically based sediment quality guidelines (SQGs) provide a relatively inexpensive line of evidence for supporting these assessments. The present study summarizes a mechanistic SQG based on equilibrium partitioning (EqP), which uses the dissolved concentrations of contaminants in sediment interstitial waters as a surrogate for bioavailable contaminant concentrations. The EqP-based mechanistic SQGs are called equilibrium partitioning sediment benchmarks (ESBs). Sediment concentrations less than or equal to the ESB values are not expected to result in adverse effects and benthic organisms should be protected, while sediment concentrations above the ESB values may result in adverse effects to benthic organisms. In the present study, ESB values are reported for 34 polycyclic aromatic hydrocarbon, 32 other organic contaminants, and seven metals (cadmium, chromium, copper, nickel, lead, silver, zinc). Also included is an overview of EqP theory, ESB derivation, examples of applying ESB values, and considerations when using ESBs. The ESBs are intended as a complement to existing sediment-assessment tools, to assist in determining the extent of sediment contamination, to help identify chemicals causing toxicity, and to serve as targets for pollutant loading control measures.

PETROTOX: An aquatic toxicity model for petroleum substances

A spreadsheet model (PETROTOX) is described that predicts the aquatic toxicity of complex petroleum substances from petroleum substance composition. Substance composition is characterized by specifying mass fractions in constituent hydrocarbon blocks (HBs) based on available analytical information. The HBs are defined by their mass fractions within a defined carbon number range or boiling point interval. Physicochemical properties of the HBs are approximated by assigning representative hydrocarbons from a database of individual hydrocarbons with associated physicochemical properties. A three-phase fate model is used to simulate the distribution of each structure among the water-, air-, and oil-phase liquid in the laboratory test system. Toxicity is then computed based on the predicted aqueous concentrations and aquatic toxicity of each structure and the target lipid model. The toxicity of the complex substance is computed assuming additivity of the contribution of the individual assigned hydrocarbons. Model performance was evaluated by using direct comparisons with measured toxicity data for petroleum substances with sufficient analytical characterization to run the model. Indirect evaluations were made by comparing predicted toxicity distributions using analytical data on petroleum substances from different product categories with independent, empirical distributions of toxicity data available for the same categories. Predictions compared favorably with measured aquatic toxicity data across different petroleum substance categories. These findings demonstrate the utility of PETROTOX for assessing environmental hazards of petroleum substances given knowledge of substance composition.

Application of the narcosis target lipid model to algal toxicity and deriving predicted-no-effect concentrations

The narcosis target lipid model (TLM) was developed to predict the toxicity of chemicals to aquatic organisms that act via narcosis. It is based on the hypothesis that target lipid is the site of toxic action within the organism, that octanol is the appropriate surrogate, and that target lipid has the same physical-chemical properties in all organisms. Here the TLM is extended to available freshwater green algal toxicity data to support a narcosis toxic mode-of-action (TMoA) effect assessment. For each species, significant linear relationships were observed between log(median effective concentration [EC50]) and log(Kow) of the test chemicals. The slope of the log-log relationship statistically was similar to the universal narcosis slope of -0.945 that was derived from an earlier analysis of the TLM to nonalgal species. Critical target lipid body burdens (CTLBB), C(L)* were estimated for each algal species from the intercepts of the regressions and found to be within the range (43-398 micromol/g octanol) reported previously, indicating that algae exhibit a similar sensitivity distribution relative to other aquatic species. The TLM is used to derive the predicted-no-effect concentrations (PNECs) using the hazardous concentration to 5% species (HC5) statistical extrapolation procedure. This calculation requires an analysis of the variability of the universal slope, the C(L)*, and the acute-to-chronic ratio. The PNECs derived using this procedure were consistent with chronic-no-effect concentrations reported for narcotic chemicals. This is in contrast to PNECs derived from limited chemical-specific toxicity data and default application factors. It is concluded that coupling the TLM to the HC5 extrapolation procedure allows optimal use of available toxicity data for deriving environmental quality criteria with a narcotic TMoA.

Effect of soil properties on copper release in soil solutions at low moisture content

Copper partitioning at moisture content of 1.2-fold the field moisture capacity (corresponding to a soil water potential of 7.84 J/kg; pF = 1.9) was studied in 11 soils with pH 3.4 to 6.8 and an organic matter content of 4.1 to 233 g C/kg. Soil solutions were separated with the centrifuge method and analyzed to determine pH, Cu2+ activity, dissolved organic carbon, and Cu, Ca, Mg, and Na concentrations. Soil organic matter content, total Cu content, and soil pH were the main variables explaining variation in Cu activity in soil solutions. Based on total Cu, soil organic matter content, and soil solution pH, the Windermere Humic Aqueous Model (WHAM) VI assemblage model provided estimates of Cu2+ activity, {Cu2}, with a root mean square error of the predicted pCu (i.e., -log{Cu2+}) of 0.77.

Technical basis for polar and nonpolar narcotic chemicals and polycyclic aromatic hydrocarbon criteria. III. A polyparameter model for target lipid partitioning

A method is presented for extending the target lipid model (TLM) of narcotic toxicity to polar narcotic chemicals. The proposed polyparameter TLM extends the applicability of the TLM by including polar compounds and removing explicit chemical class corrections. The validity of the model is tested using a data set of 1,687 acute toxicity tests for 42 aquatic species, including fish, amphibians, arthropods, mollusks, polychaetes, coelenterates, protozoans, and algae, and 398 chemicals. The target lipid-water partition coefficient is computed using the Abraham polyparameter model. This replaces use of the octanol-water partition coefficient so that the partitioning of polar narcotic chemicals can be described correctly. The model predicts the log median lethal concentration with a root mean square error of 0.460 for nonpolar and polar chemicals and 0.501 for only polar chemicals.