Estimating Octanol-Water Partition Coefficients of Novel Brominated Flame Retardants by Reversed-Phase High-Performance Liquid Chromatography and Computational Models.

Legacy brominated flame retardants, including polybrominated diphenyl ethers (PBDEs), have been classified as persistent organic pollutants and replaced with novel brominated flame retardants (NBFRs). The octanol-water partition coefficients (log KOW) of NBFRs have been computationally estimated, but the log KOW values provided by these methods can differ by 1 to 3 orders of magnitude. Given the importance of this parameter in fate and toxicity models, we indirectly measured the log KOW values of eight NBFRs by their capacity factor (k') on a reversed-phase high-performance liquid chromatography (HPLC) C18 column by isocratic elution and compared these measured values with those estimated by nine computational models. Log KOW values were obtained for the NBFRs 1,2-bis(2,4,6-tribromophenoxy) ethane, pentabromobenzene, pentabromoethylbenzene, pentabromotoluene, 2-ethylhexyl 2,3,4,5-tetrabromobenzoate, allyl 2,4,6-tribromophenylether, 2,3-dibromopropyl-2,4,6-tribromophenyl ether, and bis(2-ethylhexyl) tetrabromophthalate. A training set of phthalates, polychlorinated biphenyls, PBDEs, and halogenated benzenes were chosen to obtain the log k'-log KOW calibration for the NBFRs. The computational models KowWIN, XLogP3, EAS-E Suite, COSMOtherm, DirectML, and Abraham polyparameter linear free energy relationships all predicted the log KOW values of the calibration compounds to within 1 order of magnitude without significant bias. The median of these models predicted log KOW values for the calibration compounds that were close to those known in the literature with root mean square error (RMSE) = 0.224 and for the NBFRs that were close to those measured by HPLC (RMSE = 0.334). Environ Toxicol Chem 2024;00:1-10. © 2024 SETAC.

In Silico Acute Aquatic Hazard Assessment and Prioritization Using a Grouped Target Site Model: A Case Study of Organic Substances Reported in Permian Basin Hydraulic Fracturing Operations.

Hydraulic fracturing (HF) is commonly used to enhance onshore recovery of oil and gas during production. This process involves the use of a variety of chemicals to support the physical extraction of oil and gas, maintain appropriate conditions downhole (e.g., redox conditions, pH), and limit microbial growth. The diversity of chemicals used in HF presents a significant challenge for risk assessment. The objective of the present study is to establish a transparent, reproducible procedure for estimating 5th percentile acute aquatic hazard concentrations (e.g., acute hazard concentration 5th percentiles [HC5s]) for these substances and validating against existing toxicity data. A simplified, grouped target site model (gTSM) was developed using a database (n = 1696) of diverse compounds with known mode of action (MoA) information. Statistical significance testing was employed to reduce model complexity by combining 11 discrete MoAs into three general hazard groups. The new model was trained and validated using an 80:20 allocation of the experimental database. The gTSM predicts toxicity using a combination of target site water partition coefficients and hazard group-based critical target site concentrations. Model performance was comparable to the original TSM using 40% fewer parameters. Model predictions were judged to be sufficiently reliable and the gTSM was further used to prioritize a subset of reported Permian Basin HF substances for risk evaluation. The gTSM was applied to predict hazard groups, species acute toxicity, and acute HC5s for 186 organic compounds (neutral and ionic). Toxicity predictions and acute HC5 estimates were validated against measured acute toxicity data compiled for HF substances. This case study supports the gTSM as an efficient, cost-effective computational tool for rapid aquatic hazard assessment of diverse organic chemicals. Environ Toxicol Chem 2024;43:1161-1172. © 2024 ExxonMobil Petroleum and Chemical BV. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

International Water Quality Guidelines for Polycyclic Aromatic Hydrocarbons: Advances to Improve Jurisdictional Uptake of Guidelines Derived Using The Target Lipid Model.

A large number of different of polycyclic aromatic hydrocarbons (PAHs) have been found in environmental media, yet water quality guidelines (WQGs) are only available for a small subset of PAHs, limiting our ability to adequately assess environmental risks from these compounds. The target lipid model (TLM) was published over 20 years ago and has been extensively validated in the literature, but it has still not been widely adopted by jurisdictions to derive WQGs for PAHs. The goal of our study was to better align the methods for deriving TLM-based WQGs with international derivation protocols. This included updating the TLM with rescreened data to identify datapoints by which effect concentrations were estimated rather than measured, modernizing the statistics used to generate the hazard concentration, and testing the applicability of a chronic TLM model rather than using the acute-to-chronic ratio. The results show that the acute TLM model did not deviate substantially from the previous iteration, indicating that the model has reached a point of stability after over 20 years of testing and improvements. Water quality guidelines derived directly from a chronic TLM provided a similar level of protection as previous iterations of the TLM. The major advantage of adopting TLM-derived WQGs is the expanded list of PAH WQGs, which will allow a more fulsome quantification of environmental risks and the ability to apply the model to mixtures. Environ Toxicol Chem 2024;43:686-700. © 2023 SETAC.

pKa prediction of per- and polyfluoroalkyl acids in water using in silico gas phase stretching vibrational frequencies and infrared intensities.

To successfully understand and model the environmental fate of per- and polyfluoroalkyl substances (PFAS), it is necessary to know key physicochemical properties (PChPs) such as pKa; however, measured PChPs of PFAS are scarce and of uncertain reliability. In this study, quantitative structure-activity relationships (QSARs) were developed by correlating calculated (M062-X/aug-cc-pVDZ) vibrational frequencies (VF) and corresponding infrared intensities (IRInt) to the pKa of carboxylic acids, sulfonic acids, phosphonic acids, sulfonamides, betaines, and alcohols. Antisymmetric stretching VF of the anionic species were used for all subclasses except for alcohols where the OH stretching VF performed better. The individual QSARs predicted the pKa for each subclass mostly within 0.5 pKa units from the experimental values. The inclusion of IRInt as a pKa predictor for carboxylic acids improved the results by decreasing the root-mean-square error from 0.35 to 0.25 (n > 100). Application of the developed QSARs to estimate the pKa of PFAS within each subclass revealed that the length of the perfluoroalkyl chain has minimal effect on the pKa, consistent with other models but in stark contrast with the limited experimental data available.

Linear Free Energy Relationship for Predicting the Rate Constants of Munition Compound Reduction by the Fe(II)-Hematite and Fe(II)-Goethite Redox Couples.

Abiotic reduction by iron minerals is arguably the most important fate process for munition compounds (MCs) in subsurface environments. No model currently exists that can predict the abiotic reduction rates of structurally diverse MCs by iron (oxyhydr)oxides. We performed batch experiments to measure the rate constants for the reduction of three classes of MCs (poly-nitroaromatics, nitramines, and azoles) by hematite or goethite in the presence of aqueous Fe2+. The surface area-normalized reduction rate constant (kSA) depended on the aqueous-phase one-electron reduction potential (EH1) of the MC and the thermodynamic state (i.e., pe and pH) of the iron oxide-Feaq2+ system. A linear free energy relationship (LFER), similar to that reported previously for nitrobenzene, successfully captures all MC reduction rate constants that span 6 orders of magnitude: log(kSA)=(1.12±0.04)[0.53EH159mV-(pH+pe)]+(5.52±0.23). The finding that the rate constants of all the different classes of MCs can be described by a single LFER suggests that these structurally diverse nitro compounds are reduced by iron oxide-Feaq2+ couples through a common mechanism up to the rate-limiting step. Multiple mechanistic implications of the results are discussed. This study expands the applicability of the LFER model for predicting the reduction rates of legacy and emerging MCs and potentially other nitro compounds.

Thermodynamic Two-Site Surface Reaction Model for Predicting Munition Constituent Reduction Kinetics with Iron (Oxyhydr)oxides.

Iron (oxyhydr)oxides comprise a significant portion of the redox-active fraction of soils and are key reductants for remediation of sites contaminated with munition constituents (MCs). Previous studies of MC reduction kinetics with iron oxides have focused on the concentration of sorbed Fe(II) as a key parameter. To build a reaction kinetic model, it is necessary to predict the concentration of sorbed Fe(II) as a function of system conditions and the redox state. A thermodynamic framework is formulated that includes a generalized double-layer model that utilizes surface acidity and surface complexation reactions to predict sorbed Fe(II) concentrations that are used for fitting MC reduction kinetics. Monodentate- and bidentate Fe(II)-binding sites are used with individual oxide sorption characteristics determined through data fitting. Results with four oxides (goethite, hematite, lepidocrocite, and ferrihydrite) and four nitro compounds (NB, CN-NB, Cl-NB, and NTO) from six separate studies have shown good agreement when comparing observed and predicted surface area-normalized rate constants. While both site types are required to reproduce the experimental redox titration, only the monodentate site concentration controls the MC reaction kinetics. This model represents a significant step toward predicting the timescales of MC degradation in the subsurface.

Modeling the Partitioning of Anionic Carboxylic and Perfluoroalkyl Carboxylic and Sulfonic Acids to Octanol and Membrane Lipid.

Perfluoroalkyl carboxylic and sulfonic acids (PFCAs and PFSAs, respectively) have low acid dissociation constant values and are, therefore, deprotonated under most experimental and environmental conditions. Hence, the anionic species dominate their partitioning between water and organic phases, including octanol and phospholipid bilayers which are often used as model systems for environmental and biological matrices. However, data for solvent-water (SW) and membrane-water partition coefficients of the anion species are only available for a few per- and polyfluoroalkyl substances (PFAS). In the present study, an equation is derived using a Born-Haber cycle that relates the partition coefficients of the anions to those of the corresponding neutral species. It is shown via a thermodynamic analysis that for carboxylic acids (CAs), PFCAs, and PFSAs, the log of the solvent-water partition coefficient of the anion, log KSW (A- ), is linearly related to the log of the solvent-water partition coefficient of the neutral acid, log KSW (HA), with a unity slope and a solvent-dependent but solute-independent intercept within a PFAS (or CA) family. This finding provides a method for estimating the partition coefficients of PFCAs and PFSAs anions using the partition coefficients of the neutral species, which can be reliably predicted using quantum chemical methods. In addition, we have found that the neutral octanol-water partition coefficient, log KOW , is linearly correlated to the neutral membrane-water partition coefficient, log KMW ; therefore, log KOW , being a much easier property to estimate and/or measure, can be used to predict the neutral log KMW . Application of this approach to KOW and KMW for PFCAs and PFSAs demonstrates the utility of this methodology for evaluating reported experimental data and extending anion property data for chain lengths that are unavailable. Environ Toxicol Chem 2023;42:2317-2328. © 2023 SETAC.

Electron Transfer Energy and Hydrogen Atom Transfer Energy-Based Linear Free Energy Relationships for Predicting the Rate Constants of Munition Constituent Reduction by Hydroquinones.

No single linear free energy relationship (LFER) exists that can predict reduction rate constants of all munition constituents (MCs). To address this knowledge gap, we measured the reduction rates of MCs and their surrogates including nitroaromatics [NACs; 2,4,6-trinitrotoluene (TNT), 2,4-dinitroanisole (DNAN), 2-amino-4,6-dinitrotoluene (2-A-DNT), 4-amino-2,6-dinitrotoluene (4-A-DNT), and 2,4-dinitrotoluene (DNT)], nitramines [hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and nitroguanidine (NQ)], and azoles [3-nitro-1,2,4-triazol-5-one (NTO) and 3,4-dinitropyrazole (DNP)] by three dithionite-reduced quinones (lawsone, AQDS, and AQS). All MCs/NACs were reduced by the hydroquinones except NQ. Hydroquinone and MC speciations were varied by controlling pH, permitting the application of a speciation model to determine second-order rate constants (k) from observed pseudo-first-order rate constants. The intrinsic reactivity of MCs (oxidants) decreased upon deprotonation, while the opposite was true for hydroquinones (reductants). The rate constants spanned ∼6 orders of magnitude in the order NTO ≈ TNT > DNP > DNT ≈ DNAN ≈ 2-A-DNT > DNP- > 4-A-DNT > NTO- > RDX. LFERs developed using density functional theory-calculated electron transfer and hydrogen atom transfer energies and reported one-electron reduction potentials successfully predicted k, suggesting that these structurally diverse MCs/NACs are all reduced by hydroquinones through the same mechanism and rate-limiting step. These results increase the applicability of LFER models for predicting the fate and half-lives of MCs and related nitro compounds in reducing environments.

Ferrocyanide enhanced evaporative flux to remediate soils contaminated with produced water brine.

Accidental releases of highly saline produced water (PW) to land can impact soil quality. The release of associated salts can clog soil pores, disperse soil clays, and inhibit plants and other soil biota. This study explores a novel remediation technique using ferrocyanide to enhance the evaporative flux of soil porewater to transport dissolved salts to the soil surface, where crystallization then occurs. The addition of ferrocyanide modifies crystal growth that enhances salt transport, allowing salt efflorescence on the soil surface and physical removal. Release sites were simulated through beaker sand column experiments using two PWs collected from the Permian Basin. PW composition altered efflorescence, with up to ten times as much ferrocyanide required in PWs than comparable concentrations of pure NaCl solutions. The addition of EDTA reduced dissolved cation competition for the ferrocyanide ion, improving PW salt recovery at the soil surface. The speciation model, PHREEQC, was used to predict the onset of salt precipitation as a function of evaporative water loss and model the effect of aqueous ferrocyanide and EDTA speciation on efflorescence. The results highlight the utility of predictive modeling for optimizing additive dosages for a given release of PW.

Modeling Time-Dependent Aquatic Toxicity of Hydrocarbons: Role of Organism Weight, Temperature, and Substance Hydrophobicity.

Oil spill exposures are highly dynamic and are not comparable to laboratory exposures used in standard toxicity tests. Toxicokinetic-toxicodynamic (TKTD) models allow translation of effects observed in the laboratory to the field. To improve TKTD model calibration, new and previously published data from 148 tests were analyzed to estimate rates characterizing the time course of toxicity for 10 fish and 42 invertebrate species across 37 hydrocarbons. A key parameter in the TKTD model is the first-order rate that incorporates passive elimination, biotransformation, and damage repair processes. The results indicated that temperature (4-26 °C), organism size (0.0001-10 g), and substance log octanol-water partition coefficient (2-6) had limited influence on this parameter, which exhibited a 5th to 95th percentile range of 0.2-2.5 day-1 (median 0.7 day-1 ). A species sensitivity distribution approach is proposed to quantify the variability of this parameter across taxa, with further studies needed for aliphatic hydrocarbons and plant species. Study findings allow existing oil spill models to be refined to improve effect predictions. Environ Toxicol Chem 2022;41:3070-3083. © 2022 ExxonMobil Biomedical Science Inc. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Modeling the Reduction Kinetics of Munition Compounds by Humic Acids.

Dissolved organic matter (DOM) comprises a sizeable portion of the redox-active constituents in the environment and is an important reductant for the abiotic transformation of nitroaromatic compounds and munition constituents (NACs/MCs). Building a predictive kinetic model for these reactions would require the energies associated with both the reduction of the NACs/MCs and the oxidation of the DOM. The heterogeneous and unknown structure of DOM, however, has prohibited reliable determination of its oxidation energies. To overcome this limitation, humic acids (HAs) were used as model DOM, and their redox moieties were modeled as a collection of quinones of different redox potentials. The reduction and oxidation energies of the NACs/MCs and hydroquinones, respectively, via hydrogen atom transfer (HAT) reactions were then calculated quantum chemically. HAT energies have been used successfully in a linear free energy relationship (LFER) to predict second-order rate constants for NAC reduction by hydroquinones. Furthermore, a linear relationship between the HAT energies and the reduction potentials of quinones was established, which allows estimation of hydroquinone reactivity (i.e., rate constants) from HA redox titration data. A training set of three HAs and two NACs/MCs was used to generate a mean HA redox profile that successfully predicted reduction kinetics in multiple HA/MC systems.

Determination of In Vivo Biotransformation Kinetics Using Early-Time Biota Concentrations.

Technical challenges have hampered the characterization of biotransformation kinetics-a critical link in understanding and predicting the toxicokinetics and ecotoxicology of organic compounds. A shortcut approach to characterize the in vivo biotransformation rate constant (kM ) with incomplete pathway or metabolite details was proposed. The value of kM can be derived as 2tln1fPC(t)) , with fPC (t) being the molar equivalent fraction of the parent compound (PC) at an early time t in both constant exposure and decay source chemical uptake scenarios. The approximation-based kM values agreed well with kM values derived from rigorous fitting or toxicokinetic modeling (n = 42, root mean square error = 0.30) with accuracy exceeding those of typical toxicokinetic or partitioning models. The method is accurate when sampling time is adequately resolved (i.e., t < ln(2)/kM ) but will likely produce biased kM values with improper time-averaging. The approximate equation yields consistent theoretical expectations for fast and slow biotransformation reactions and is fully compatible with standard bioaccumulation and toxicity testing protocols. The simplification strategy circumvents statistical complications and numerical issues inherent in regressing or modeling the toxicokinetics of multimetabolite systems and may be adapted to similar problems at other physiological scales or ecotoxicological contexts. The method can help advance interspecies comparison of chemical metabolism and support the development of in vitro-in vivo extrapolations and in silico models needed for building next-generation ecological and health risk-assessment practices. Environ Toxicol Chem 2022;41:148-158. © 2021 SETAC.

Reductive Transformation of 3-Nitro-1,2,4-triazol-5-one (NTO) by Leonardite Humic Acid and Anthraquinone-2,6-disulfonate (AQDS).

3-Nitro-1,2,4-triazol-5-one (NTO) is a major and the most water-soluble constituent in the insensitive munition formulations IMX-101 and IMX-104. While NTO is known to undergo redox reactions in soils, its reaction with soil humic acid has not been evaluated. We studied NTO reduction by anthraquinone-2,6-disulfonate (AQDS) and Leonardite humic acid (LHA) reduced with dithionite. Both LHA and AQDS reduced NTO to 3-amino-1,2,4-triazol-5-one (ATO), stoichiometrically at alkaline pH and partially (50-60%) at pH ≤ 6.5. Due to NTO and hydroquinone speciation, the pseudo-first-order rate constants (kObs) varied by 3 orders of magnitude from pH 1.5 to 12.5 but remained constant from pH 4 to 10. This distinct pH dependency of kObs suggests that NTO reactivity decreases upon deprotonation and offsets the increasing AQDS reactivity with pH. The reduction of NTO by LHA deviated continuously from first-order behavior for >600 h. The extent of reduction increased with pH and LHA electron content, likely due to greater reactivity of and/or accessibility to hydroquinone groups. Only a fraction of the electrons stored in LHA was utilized for NTO reduction. Electron balance analysis and LHA redox potential profile suggest that the physical conformation of LHA kinetically limited NTO access to hydroquinone groups. This study demonstrates the importance of carbonaceous materials in controlling the environmental fate of NTO.

A Unified Linear Free Energy Relationship for Abiotic Reduction Rate of Nitroaromatics and Hydroquinones Using Quantum Chemically Estimated Energies.

Determining the fate of nitroaromatic compounds (NACs) in the environment requires the use of predictive models for compounds and conditions for which experimental data are insufficient. Previous studies have developed linear free energy relationships (LFERs) that relate the thermodynamic energy of NAC reduction to its corresponding rate constant. We present a comprehensive LFER that incorporates both the reduction and oxidation half-reactions through quantum chemically calculated energies. Environ Toxicol Chem 2020;39:2389-2395. © 2020 SETAC.

Reduction of 3-Nitro-1,2,4-Triazol-5-One (NTO) by the Hematite-Aqueous Fe(II) Redox Couple.

3-Nitro-1,2,4-triazol-5-one (NTO) is an insensitive munition compound (MC) that has replaced legacy MC. NTO can be highly mobile in soil and groundwater due to its high solubility and anionic nature, yet little is known about the processes that control its environmental fate. We studied NTO reduction by the hematite-Fe2+ redox couple to assess the importance of this process for the attenuation and remediation of NTO. Fe2+(aq) was either added (type I) or formed through hematite reduction by dithionite (type II). In the presence of both hematite and Fe2+(aq), NTO was quantitatively reduced to 3-amino-1,2,4-triazol-5-one following first-order kinetics. The surface area-normalized rate constant (kSA) showed a strong pH dependency between 5.5 and 7.0 and followed a linear free energy relationship (LFER) proposed in a previous study for nitrobenzene reduction by iron oxide-Fe2+ couples, i.e., log kSA = -(pe + pH) + constant. Sulfite, a major dithionite oxidation product, lowered kSA in type II system by ∼10-fold via at least two mechanisms: by complexing Fe2+ and thereby raising pe, and by making hematite more negatively charged and hence impeding NTO adsorption. This study demonstrates the importance of iron oxide-Fe2+ in controlling NTO transformation, presents an LFER for predicting NTO reduction rate, and illustrates how solutes can shift the LFER by interacting with either iron species.

Hydrogen Atom Transfer Reaction Free Energy as a Predictor of Abiotic Nitroaromatic Reduction Rate Constants: A Comprehensive Analysis.

A linear free energy model is presented that predicts the second-order rate constant for the abiotic reduction of nitroaromatic compounds (NACs). Previously presented models use the one-electron reduction potential EH1(ArNO2) of the NAC reaction ArNO2+e-→ArNO2•- . If EH1(ArNO2) is not available, it has been proposed that EH1(ArNO2) be computed directly or estimated from the gas-phase electron affinity (EA). The model proposed uses the Gibbs free energy of the hydrogen atom transfer (HAT) reaction ArNO2+H•→ArNOOH• as the parameter in the linear free energy model. Both models employ quantum chemical computations for the required thermodynamic energies. The available and proposed models are compared using experimentally determined second-order rate constants from 5 investigations from the literature in which a variety of NACs were exposed to a variety of reductants. A comprehensive analysis utilizing all the NACs and reductants demonstrate that the HAT energy model and the experimental one-electron reduction potential model have similar root mean square errors and residual error probability distributions. In contrast, the model using the computed EA has a more variable residual error distribution with a significant number of outliers. The results suggest that a linear free energy model utilizing computed HAT reaction free energy produces a more reliable prediction of the NAC abiotic reduction second-order rate constant than previously available methods. The advantages of the proposed HAT energy model and its mechanistic implications are discussed as well. Environ Toxicol Chem 2020;39:1678-1684. © 2020 SETAC.

Experimental Validation of Hydrogen Atom Transfer Gibbs Free Energy as a Predictor of Nitroaromatic Reduction Rate Constants.

Nitroaromatic compounds (NACs) are a class of prevalent contaminants. Abiotic reduction is an important fate process that initiates NAC degradation in the environment. Many linear free energy relationship (LFER) models have been developed to predict NAC reduction rates. Almost all LFERs to date utilize experimental aqueous-phase one-electron reduction potential ( EH1) of NAC as a predictor, and thus, their utility is limited by the availability of EH1 data. A promising new approach that utilizes computed hydrogen atom transfer (HAT) Gibbs free energy instead of EH1 as a predictor was recently proposed. In this study, we evaluated the feasibility of HAT energy for predicting NAC reduction rate constants. Using dithionite-reduced quinones, we measured the second-order rate constants for the reduction of seven NACs by three hydroquinones of different protonation states. We computed the gas-phase energies for HAT and electron affinity (EA) of NACs and established HAT- and EA-based LFERs for six hydroquinone species. The results suggest that HAT energy is a reliable predictor of NAC reduction rate constants and is superior to EA. This is the first independent, experimental validation of HAT-based LFER, a new approach that enables rate prediction for a broad range of structurally diverse NACs based solely on molecular structures.

Target site model: Application of the polyparameter target lipid model to predict aquatic organism acute toxicity for various modes of action.

A database of 2049 chemicals with 47 associated modes of action (MoA) was compiled from the literature. The database includes alkanes, polycyclic aromatic hydrocarbons, pesticides, inorganic, and polar compounds. Brief descriptions of some critical MoA classification groups are provided. The MoA from the 14 sources were assigned using a variety of reliable experimental and modeling techniques. Toxicity information, chemical parameters, and solubility limits were combined with the MoA label information to create the data set used for model development. The model database was used to generate linear free energy relationships for each specific MoA using multilinear regression analysis. The model uses chemical-specific Abraham solute parameters estimated from AbSolv to determine MoA-specific solvent parameters. With this procedure, critical target site concentrations are determined for each genus. Statistical analysis showed a wide range in values of the solvent parameters for the significant MoA. Environ Toxicol Chem 2019;38:222-239. © 2018 SETAC.

Target site model: Predicting mode of action and aquatic organism acute toxicity using Abraham parameters and feature-weighted k-nearest neighbors classification.

A database of 1480 chemicals with 47 associated modes of action compiled from the literature encompasses a wide range of chemical classes (alkanes, polycyclic aromatic hydrocarbons, pesticides, and polar compounds) and includes toxicity data for 79 different aquatic genera. The data were split into a calibration group and a validation group (80/20) to apply k-nearest neighbors (k-NN) methodology to predict the toxic mode of action for the compound. Other approaches were tested (support vector machines and linear discriminant analysis) as well as variations in the k-NN technique (distance weighting, feature weighting). Best-prediction results were found with k = 3, in a voting platform with optimized feature weighting. Using the predicted mode of action, the appropriate polyparameter target site model for that mode of action is applied to calculate the 50% lethal concentration (LC50). Predicted LC50s for the validation database resulted in a root-mean squared error (RMSE) of 0.752. This can be compared to an RMSE of 0.655 for the same validation set using the reference mode of action labels. The complete database resulted in an RMSE of 0.793 for reference mode of action labels. This confirms that the classification model has sufficient accuracy for predicting the mode of action and for determining toxicity using the target site model. Environ Toxicol Chem 2019;38:375-386. © 2018 SETAC.

The aquatic hazard of hydrocarbon liquids and gases and the modulating role of pressure on dissolved gas and oil toxicity.

Hydrostatic pressure enhances gas solubility and potentially alters toxicity and risks of oil and gas releases to deep-sea organisms. This study has two primary objectives. First, the aquatic hazard of dissolved hydrocarbon gases is characterized using results of previously published laboratory and field studies and modeling. The target lipid model (TLM) is used to predict effects at ambient pressure, and results are compared to effect concentrations derived from extrapolation of liquid alkane hazard data. Second, existing literature data are used to quantify and predict pressure effects on toxicity using an extension of the TLM framework. Results indicate elevated pressure mitigates narcosis, particularly for sensitive species. A simple adjustment is proposed to allow TLM-based estimates of acute effect and TLM-derived HC5 values (concentrations intended to provide 95% species protection) for oil or gas constituents to be calculated at depth. Future applications, and opportunities and challenges for providing validation, are discussed.