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The electron accepting capacity (EAC) of soil plays a pivotal role in the biogeochemical cycling of nutrients and transformation of redox-labile contaminants. Prior EAC studies of soils and soil constituents utilized different methods, reductants, and mediators, making cross-study comparison difficult. This study was conducted to quantify and compare the EACs of two soil constituents (hematite and Leonardite humic acid) and 12 soils of diverse composition, using chemical redox titration (CRT) with dithionite as the reductant and mediated electrochemical reduction (MER) with diquat as the mediator. The EACs of hematite and humic acid measured by CRT (EAC CRT ) and MER (EAC MER ) are similar and close to the theoretical/reported values. For soils, EAC CRT and EAC MER increased with iron and organic carbon (TOC) contents, suggesting iron and carbon were the main contributors to soil EAC. EAC CRT > EAC MER for all soils, and their difference (ΔEAC = EAC CRT - EAC MER ) increased with TOC, presumably due to the longer contact time in CRT and thus more complete reduction of carbonaceous redox moieties. We propose an equation that relates EAC CRT to EAC MER (ΔEAC = 1796 f TOC + 32) and another that predicts EAC CRT from dithionite-reducible Fe and TOC (EAC CRT = 2705 μmol e - /g C × f TOC + 17907 μmol e - /g Fe × f Fe dithionite-reducible ). Our results suggest that at least 10-15% of soil organic carbon contributed to EAC CRT .

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 K OW ) of NBFRs have been computationally estimated, but the log K OW 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 K OW 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 K OW 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 K OW 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 K OW values of the calibration compounds to within 1 order of magnitude without significant bias. The median of these models predicted log K OW 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;43:2105-2114. © 2024 SETAC., (© 2024 SETAC.)

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., (© 2024 ExxonMobil Petroleum and Chemical BV. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

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., (© 2023 SETAC.)

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 K SW (A - ), is linearly related to the log of the solvent-water partition coefficient of the neutral acid, log K SW (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 K OW , is linearly correlated to the neutral membrane-water partition coefficient, log K MW ; therefore, log K OW , being a much easier property to estimate and/or measure, can be used to predict the neutral log K MW . Application of this approach to K OW and K MW 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., (© 2023 SETAC.)

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 p K a ; 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 (IR Int ) to the p K a 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 p K a for each subclass mostly within 0.5 p K a units from the experimental values. The inclusion of IR Int as a p K a 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 p K a of PFAS within each subclass revealed that the length of the perfluoroalkyl chain has minimal effect on the p K a , consistent with other models but in stark contrast with the limited experimental data available.

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 Fe 2+ . The surface area-normalized reduction rate constant ( k SA ) depended on the aqueous-phase one-electron reduction potential ( E H 1 ) of the MC and the thermodynamic state (i.e., pe and pH) of the iron oxide-Fe aq 2+ 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 ( k S A ) = ( 1.12 ± 0.04 ) [ 0.53 E H 1 59 m V - ( p H + p e ) ] + ( 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-Fe aq 2+ 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.

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.

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.

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., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Kathryn Platt, Paul Imhoff, Dominic Di Toro, Richard Carbonaro, Herbert Allen, Nicolette Bugher reports financial support was provided by ExxonMobil Environmental and Property Solutions Company and ExxonMobil Biomedical Sciences Inc. Linda Eastcott reports a relationship with ExxonMobil Environmental and Property Solutions Company that includes: employment. Thomas Parkerton reports a relationship with ExxonMobil Biomedical Sciences Inc that includes: employment., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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., (© 2022 ExxonMobil Biomedical Science Inc. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

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.

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 (k M ) with incomplete pathway or metabolite details was proposed. The value of k M can be derived as 2 t ln 1 f PC ( t ) ) , with f PC (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 k M values agreed well with k M 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)/k M ) but will likely produce biased k M 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., (© 2021 SETAC.)

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 ( k Obs ) 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 k Obs 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.

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., (© 2020 SETAC.)

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-Fe 2+ redox couple to assess the importance of this process for the attenuation and remediation of NTO. Fe 2+ (aq) was either added (type I) or formed through hematite reduction by dithionite (type II). In the presence of both hematite and Fe 2+ (aq) , NTO was quantitatively reduced to 3-amino-1,2,4-triazol-5-one following first-order kinetics. The surface area-normalized rate constant ( k SA ) 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-Fe 2+ couples, i.e., log  k SA = -(pe + pH) + constant. Sulfite, a major dithionite oxidation product, lowered k SA in type II system by ∼10-fold via at least two mechanisms: by complexing Fe 2+ and thereby raising pe, and by making hematite more negatively charged and hence impeding NTO adsorption. This study demonstrates the importance of iron oxide-Fe 2+ 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.

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 E H 1 ( ArNO 2 ) of the NAC reaction ArNO 2 + e - → ArNO 2 • - . If E H 1 ( ArNO 2 ) is not available, it has been proposed that E H 1 ( ArNO 2 ) 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 ArNO 2 + 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., (© 2020 SETAC.)

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 ( E H 1 ) of NAC as a predictor, and thus, their utility is limited by the availability of E H 1 data. A promising new approach that utilizes computed hydrogen atom transfer (HAT) Gibbs free energy instead of E H 1 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.

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., (© 2018 SETAC.)

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., (© 2018 SETAC.)

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., (Copyright © 2018. Published by Elsevier Ltd.)

The toxicity of petroleum can increase considerably after exposure to solar radiation, during which certain components in the mixture, including polycyclic aromatic hydrocarbons (PAHs), absorb light in ultraviolet and visible portions of the solar radiation spectrum. A phototoxic target lipid model (PTLM), previously developed to predict the phototoxicity of single PAHs, is validated for 4 species (Americamysis bahia, Rhepoxynius abronius, Daphnia magna, and Pimephales promelas) exposed to 12 compounds that are components of petroleum, including alkylated PAHs and dibenzothiophene. The PTLM is also used to predict the phototoxicity of binary and ternary mixtures of 3 PAHs, pyrene, anthracene, and fluoranthene, to A. bahia and Menidia beryllina. Finally, it is used to predict the toxicity of water accommodated fractions of neat and naturally weathered Macondo crude oil samples from the Deepwater Horizon oil spill sites. The Gulf of Mexico species, including A. bahia, M. beryllina, Cyprinodon variegatus, and Fundulus grandis were exposed to the oil samples under natural and simulated solar radiation. The results support the applicability of the PTLM for predicting the phototoxicity of petroleum. Environ Toxicol Chem 2018;37:2165-2174. © 2018 SETAC., (© 2018 SETAC.)

The target lipid model (TLM) has been previously applied to predict the aquatic toxicity of hydrocarbons and other nonionic organic chemicals and for deriving the concentrations above which 95% of species should be protected (HC5 values). Several concerns have been identified with the TLM-derived HC5 when it is applied in a substance risk assessment context. These shortcomings were addressed by expanding the acute and chronic toxicity databases to include more diverse taxonomic groups and increase the number of species. The TLM was recalibrated with these expanded databases, resulting in critical target lipid body burdens and acute-to-chronic ratios that met the required guidelines for using species sensitivity distributions in substance risk assessment. The HC5 equation was further revised to consider covarying model parameters. The calculated HC5 values derived from the revised TLM framework were validated using an independent data set for hydrocarbons comprising 106 chronic values across plants, invertebrates, and fish. Assuming a sum binomial distribution, the 95% confidence limit for a 5% failure is between 0.8 and 9.2%. Eight chronic values fell below the HC5, corresponding to an excursion of 7.5%, which falls within the expected uncertainty bounds. Thus, calculated HC5s derived from the revised TLM framework were found to be consistent with the intended protection goals. Environ Toxicol Chem 2018;37:1579-1593. © 2018 SETAC., (© 2018 SETAC.)

Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent-water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent-water, plant cuticle-water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent-water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent-water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle-water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.

Solid-phase microextraction fibers coated with polydimethylsiloxane (PDMS) provide a convenient passive sampling format to characterize bioavailability of petroleum substances. Hydrocarbons absorb onto PDMS in proportion to both freely dissolved concentrations and partitioning properties of the individual constituents, which parallels the mechanistic basis used to predict aquatic toxicity in the PETROTOX model. When deployed in a non-depletive manner, combining SPME with thermal desorption and quantification using gas chromatography-flame ionization creates a biomimetic extraction (BE) procedure that has the potential to simplify aquatic hazard assessments of petroleum substances since the total moles of all hydrocarbons sorbed to the fiber can be related to toxic thresholds in target lipid of aquatic organisms. The objective of this work is to describe the technical basis for applying BE measurements to predict toxicity of petroleum substances. Critical BE-based PDMS concentrations corresponding to adverse effects were empirically derived from toxicity tests on different petroleum substances with multiple test species. The resulting species sensitivity distribution (SSD) of PDMS effect concentrations was then compared and found consistent with the previously reported target lipid-based SSD. Further, BE data collected on samples of aqueous media dosed with a wide range of petroleum substances were highly correlated to predicted toxic units derived using the PETROTOX model. These findings provide justification for applying BE in environmental hazard and risk evaluations of petroleum substances and related mixtures., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Constants for a Terrestrial Biotic Ligand Model (TBLM) to predict the Cu toxicity to barley root elongation (RE) were developed from controlled sand culture experiments. These constants were used to predict RE in soil culture. The competition of H + , Ca 2+ , and Mg 2+ to Cu 2+ toxicity were studied individually and independently, and linear relationships between EC50 free Cu 2+ and H + , Ca 2+ , and Mg 2+ activities were found, meaning that the cations H + , Ca 2+ , and Mg 2+ will alleviate the toxicity of Cu 2+ in solutions. Toxicity accompanying increasing concentration of solution ions other than Cu 2+ was observed and modeled as an osmotic effect which improved soil culture toxicity prediction. The Root Mean Square Error (RMSE) of %RE and EC50 (50% effective concentration) for soil toxicity prediction using TBLM parameters developed from sand culture are 13.0 and 0.23 respectively, which are as good as that of 14.0 and 0.24 using parameters that developed from soil culture itself. A model including the activity at the root plasma membrane surface was tested and found not to provide improvement over the use of bulk solution activity to predict metal toxicity. TBLM parameters obtained from water solution culture were unable to accurately predict the EC50s in soils whereas the parameters obtained from sand culture were able to predict the toxicity in soils. Including the toxicity of CuOH + was found to improve the toxicity prediction slightly., (Copyright © 2017. Published by Elsevier Inc.)

Plants growing in the soils at military ranges and surrounding locations are exposed, and potentially able to uptake, munitions compounds (MCs). The extent to which a compound is transferred from the environment into organisms such as plants, referred to as bioconcentration, is conventionally measured through uptake experiments with field/synthetic soils. Multiple components/phases that vary among different soil types and affect the bioavailability of the MC, however, hinder the ability to separate the effects of soil characteristics from the MC chemical properties on the resulting plant bioconcentration. To circumvent the problem, this work presents a protocol to measure steady state bioconcentration factors (BCFs) for MCs in barley (Hordeum vulgare L.) using inert laboratory sand rather than field/synthetic soils. Three MCs: 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (2,4-DNT), and 2,4-dinitroanisole (2,4-DNAN), and two munition-like compounds (MLCs): 4-nitroanisole (4-NAN) and 2-methoxy-5-nitropyridine (2-M-5-NPYNE) were evaluated. Approximately constant plant biomass and exposure concentrations were achieved within a one-month period that produced steady state log BCF values: 0.62 ± 0.02, 0.70 ± 0.03, 1.30 ± 0.06, 0.52 ± 0.03, and 0.40 ± 0.05 L kg plant dwt -1 for TNT, 2,4-DNT, 2,4-DNAN, 4-NAN, and 2-M-5-NPYNE, respectively. Furthermore, results suggest that the upper-bounds of the BCFs can be estimated within an order of magnitude by measuring the partitioning of the compounds between barley biomass and water. This highlights the importance of partition equilibrium as a mechanism for the uptake of MCs and MLCs by barley from interstitial water. The results from this work provide chemically meaningful data for prediction models able to estimate the bioconcentration of these contaminants in plants., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

A partitioning-based model is presented to estimate the bioconcentration of five munitions compounds and two munition-like compounds in grasses. The model uses polyparameter linear free energy relationships (pp-LFERs) to estimate the partition coefficients between soil organic carbon and interstitial water and between interstitial water and the plant cuticle, a lipid-like plant component. Inputs for the pp-LFERs are a set of numerical descriptors computed from molecular structure only that characterize the molecular properties that determine the interaction with soil organic carbon, interstitial water, and plant cuticle. The model is validated by predicting concentrations measured in the whole plant during independent uptake experiments with a root-mean-square error (log predicted plant concentration-log observed plant concentration) of 0.429. This highlights the dominant role of partitioning between the exposure medium and the plant cuticle in the bioconcentration of these compounds. The pp-LFERs can be used to assess the environmental risk of munitions compounds and munition-like compounds using only their molecular structure as input.

Crude oils contain a mixture of hydrocarbons, including phototoxic polycyclic aromatic hydrocarbons (PAHs) that have the ability to absorb ultraviolet (UV) light. Absorption of UV light by PAHs can substantially increase their toxicity to marine organisms. The objective of the present study was to examine the potential for phototoxicity of fresh and naturally weathered Macondo crude oils alone and in combination with the dispersant Corexit 9500 to mysid shrimp (Americamysis bahia), inland silverside (Menidia beryllina), sheepshead minnow (Cyprinodon variegatus), and Gulf killifish (Fundulus grandis). Acute toxicity tests were conducted using combinations of natural or artificial sunlight and low-energy water-accommodated fractions (WAFs) of fresh and weathered Macondo crude oils collected from the Gulf of Mexico. Studies were also conducted to compare the phototoxicity resulting from natural and artificial sunlight. Fresh Macondo crude oil was more phototoxic than weathered crude oils, both in the presence and in the absence of UV light. Differences in toxicity between fresh and weathered crude oils were likely attributed to lighter-ringed PAHs in fresh crude oils. Phototoxic PAHs were relatively resistant to weathering compared with lighter-ringed PAHs. The addition of Corexit 9500 to crude oil increased toxicity compared with tests with crude oil alone, by increasing phototoxic PAH concentrations in WAFs. Macondo crude oils had the potential to be phototoxic to Gulf of Mexico marine organisms if specific light conditions and PAH concentrations were present during the Deepwater Horizon oil spill. Environ Toxicol Chem 2017;36:2640-2650. © 2017 SETAC., (© 2017 SETAC.)

Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.

Crude oils are composed of an assortment of hydrocarbons, some of which are polycyclic aromatic hydrocarbons (PAHs). Polycyclic aromatic hydrocarbons are of particular interest due to their narcotic and potential phototoxic effects. Several studies have examined the phototoxicity of individual PAHs and fresh and weathered crude oils, and several models have been developed to predict PAH toxicity. Fingerprint analyses of oils have shown that PAHs in crude oils are predominantly alkylated. However, current models for estimating PAH phototoxicity assume toxic equivalence between unsubstituted (i.e., parent) and alkyl-substituted compounds. This approach may be incorrect if substantial differences in toxic potency exist between unsubstituted and substituted PAHs. The objective of the present study was to examine the narcotic and photo-enhanced toxicity of commercially available unsubstituted and alkylated PAHs to mysid shrimp (Americamysis bahia). Data were used to validate predictive models of phototoxicity based on the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap approach and to develop relative effect potencies. Results demonstrated that photo-enhanced toxicity increased with increasing methylation and that phototoxic PAH potencies vary significantly among unsubstituted compounds. Overall, predictive models based on the HOMO-LUMO gap were relatively accurate in predicting phototoxicity for unsubstituted PAHs but are limited to qualitative assessments. Environ Toxicol Chem 2017;36:2043-2049. © 2017 SETAC., (© 2017 SETAC.)

Polycyclic aromatic hydrocarbons (PAHs) are known to exhibit photo-induced toxicity. Hundreds to thousands of PAH parent and substituted compounds are found in the environment, and developing a predictive model applicable to a wide variety of PAHs and organisms is a necessary precursor to environmental risk assessments. There has been evolutionary progress in phototoxicity modeling since 1977. In the present study, a comprehensive review of the models developed to predict phototoxicity of PAHs is presented. The contributions of each of the models to the state of the art are discussed. The models are compared in terms of their scope of applicability to different organisms, PAHs, endpoints (median lethal time and median lethal concentration), and light conditions. The current state of the science that accounts for the key elements of phototoxicity modeling, including the differences in species sensitivity, the partitioning of PAHs into the target lipid of the organisms, and light absorption by the chemicals, as well as light exposure time and conditions, is discussed. In addition, the remaining issues that need to be addressed are explored: the effect of time-varying exposures to light and PAH concentrations, and the lack of a mechanistic understanding that can explain the failure of the Bunsen-Roscoe law of reciprocity. Environ Toxicol Chem 2017;36:1138-1148. © 2016 SETAC., (© 2016 SETAC.)

A phototoxic target lipid model (PTLM) is developed to predict phototoxicity of individual polycyclic aromatic hydrocarbons (PAHs) measured either as median lethal concentration (LC50) or median lethal time (LT50) for a 50% toxic response. The model is able to account for the differences in the physical/chemical properties of PAHs, test species sensitivities, and variations in light source characteristics, intensity, and length of exposure. The PTLM is based on the narcotic target lipid model (NTLM) of PAHs. Both models rely on the assumption that mortality occurs when the toxicant concentration in the target lipid of the organism reaches a threshold concentration. The PTLM is applied to observed LC50s and LT50s for 20 individual PAHs, 15 test species-including arthropods, fishes, amphibians, annelids, mollusks, and algae-exposed to simulated solar and various UV light sources, for exposure times varying from less than 1 h to 100 h, a total of 333 observations. The LC50 concentrations range from less than 0.1 µg/L to greater that 10 4  µg/L. The model has 2 fitting parameters that are constant and apply to all PAHs and organisms. The root mean square errors of prediction for log(LC50) and log(LT50) are 0.473 and 0.382, respectively. The results indicate that the PTLM can predict the phototoxicity of single PAHs over a wide range of exposure conditions and to organisms with a wide range of sensitivities. Environ Toxicol Chem 2017;36:926-937. © 2016 SETAC., (© 2016 SETAC.)

Methods for obtaining accurate predictions of solvent-water partitioning for neutral organic chemicals (e.g., K ow ) are well-established. However, methods that provide comparable accuracy are not available for predicting the solvent-water partitioning of ionic species. Previous methods for addressing charge contributions to solvent-water partitioning rely on charged solute descriptors which are obtained from regressions to neutral species descriptors as well as charged descriptors which are specific to unique charge-functionalities and structural moieties. This paper presents a method for obtaining Abraham poly-parameter linear free energy relationship (pp-LFER) descriptors using quantum chemical calculations and molecular structure, only. The method utilizes a large number of solvent-water systems to overcome large errors in individual quantum chemical computations of ionic solvent-water partition coefficients. The result is a single set of quantum-chemically estimated Abraham solute parameters (QCAP) which are solvent-independent, and can be used to predict the solvent-water partitioning of ionic species. Predictions of solvent-water partition coefficients for ionic species using quantum-chemically estimated Abraham parameters (QCAPs) are shown to provide improved accuracy compared over both existing Absolv-estimated Abraham solute parameters (AAP) as well as direct a priori quantum chemical (QC) calculations for partitioning of anionic solutes in 4 organic solvent-water systems (RMS = 0.740, 2.48 and 0.426 for the Absolv, QC and QCAP methods, respectively). For quaternary amine cations in the octanol-water system the RMS errors of the solvent-water partition coefficients were larger and similar between the two Abraham models (RMSE = 0.997 and 1.16, for the AAP and QCAP methods, respectively). Both methods showed significant improvement over direct QC calculations (RMSE = 2.82)., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

There is concern about the environmental fate and effects of munition constituents (MCs). Polyparameter linear free energy relationships (pp-LFERs) that employ Abraham solute parameters can aid in evaluating the risk of MCs to the environment. However, poor predictions using pp-LFERs and ABSOLV estimated Abraham solute parameters are found for some key physico-chemical properties. In this work, the Abraham solute parameters are determined using experimental partition coefficients in various solvent-water systems. The compounds investigated include hexahydro-1,3,5-trinitro-1,3,5-triazacyclohexane (RDX), octahydro-1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane (HMX), hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine (MNX), hexahydro-1,3,5-trinitroso-1,3,5-triazine (TNX), hexahydro-1,3-dinitroso-5- nitro-1,3,5-triazine (DNX), 2,4,6-trinitrotoluene (TNT), 1,3,5-trinitrobenzene (TNB), and 4-nitroanisole. The solvents in the solvent-water systems are hexane, dichloromethane, trichloromethane, octanol, and toluene. The only available reported solvent-water partition coefficients are for octanol-water for some of the investigated compounds and they are in good agreement with the experimental measurements from this study. Solvent-water partition coefficients fitted using experimentally derived solute parameters from this study have significantly smaller root mean square errors (RMSE = 0.38) than predictions using ABSOLV estimated solute parameters (RMSE = 3.56) for the investigated compounds. Additionally, the predictions for various physico-chemical properties using the experimentally derived solute parameters agree with available literature reported values with prediction errors within 0.79 log units except for water solubility of RDX and HMX with errors of 1.48 and 2.16 log units respectively. However, predictions using ABSOLV estimated solute parameters have larger prediction errors of up to 7.68 log units. This large discrepancy is probably due to the missing R2NNO2 and R2NNO2 functional groups in the ABSOLV fragment database., (Copyright © 2016. Published by Elsevier Ltd.)

Barley, Hordeum vulgare (Doyce), was grown in the 3 media of soil, hydroponic sand solution (sand), and hydroponic water solution (water) culture at the same environmental conditions for 4 d. Barley roots were scanned, and root morphology was analyzed. Plants grown in the 3 media had different root morphology and nickel (Ni) toxicity response. Root elongations and total root lengths followed the sequence soil > sand > water. Plants grown in water culture were more sensitive to Ni toxicity and had greater root hair length than those from soil and sand cultures, which increased root surface area. The unit root surface area as root surface area per centimeter of length of root followed the sequence water > sand > soil and was found to be related with root elongation. Including the unit root surface area, the difference in root elongation and 50% effective concentration were diminished, and percentage of root elongations can be improved with a root mean square error approximately 10% for plants grown in different media. Because the unit root surface area of plants in sand culture is closer to that in soil culture, the sand culture method, not water culture, is recommended for toxicity parameter estimation. Environ Toxicol Chem 2016;35:2125-2133. © 2016 SETAC., (© 2016 SETAC.)

Predictive models for linear sorption of solutes onto various media, e.g., soil organic carbon, are well-established; however, methods for predicting parameters for nonlinear isotherm models, e.g., Freundlich and Langmuir models, are not. Predicting nonlinear partition coefficients is complicated by the number of model parameters to fit n isotherms (e.g., Freundlich (2n) or Polanyi-Manes (3n)). The purpose of this paper is to present a nonlinear adsorption model with only one chemically specific parameter. To accomplish this, several simplifications to a log-normal Langmuir (LNL) isotherm model with 3n parameters were explored. A single sorbate-specific binding constant, the median Langmuir binding constant, and two global sorbent parameters; the total site density and the standard deviation of the Langmuir binding constant were employed. This single-solute specific (ss-LNL) model (2 + n parameters) was demonstrated to fit adsorption data as well as the 2n parameter Freundlich model. The LNL isotherm model is fit to four data sets composed of various chemicals sorbed to graphite, charcoal, and activated carbon. The RMS errors for the 3-, 2-, and 1-chemical specific parameter models were 0.066, 0.068, 0.069, and 0.113, respectively. The median logarithmic parameter standard errors for the four models were 1.070, 0.4537, 0.382, and 0.201 respectively. Further, the single-parameter model was the only model for which there were no standard errors of estimated parameters greater than a factor of 3 (0.50 log units). The surprising result is that very little decrease in RMSE occurs when two of the three parameters, σκ and qmax, are sorbate independent. However, the large standard errors present in the other models are significantly reduced. This remarkable simplification yields the single sorbate-specific parameter (ss-LNL) model.

Procedures for accurately predicting linear partition coefficients onto various sorbents (e.g., organic carbon, soils, clay) are reliable and well established. However, similar procedures for the prediction of sorption parameters of nonlinear isotherm models are not. The purpose of this paper is to present a procedure for predicting nonlinear isotherm parameters, specifically the median Langmuir binding constants, K̃L, obtained utilizing the single-chemical parameter log-normal Langmuir isotherm developed in the accompanying work. A reduced poly parameter linear free energy relationship (pp-LFER) is able to predict median Langmuir binding constants for graphite, charcoal, and Darco granular activated carbon (GAC) adsorption data. For the larger F400 GAC data set, a single pp-LFER model was insufficient, as a plateau is observed for the median Langmuir binding constants of larger molecular volume sorbates. This volumetric cutoff occurs in proximity to the median pore diameter for F400 GAC. A log-linear relationship exists between the aqueous solubility of these large compounds and their median Langmuir binding constants. Using this relationship for the chemicals above the volumetric cutoff and the pp-LFER below the cutoff, the median Langmuir binding constants can be predicted with a root-mean square error for graphite (n = 13), charcoal (n = 11), Darco GAC (n = 14), and F400 GAC (n = 44) of 0.129, 0.307, 0.407, and 0.424, respectively.

A Terrestrial Biotic Ligand Model (TBLM) for Ni toxicity to barley root elongation (RE) developed from experiments conducted in sand culture was used to predict toxicity in non-calcareous soils. Ca(2+) and Mg(2+) concentrations and pH in sand solution were varied individually and TBLM parameters were computed. EC50 increased as Mg(2+) increased, whereas the effect of Ca(2+) was insignificant. TBLM parameters developed from sand culture were validated by toxicity tests in eight Ni-amended, non-calcareous soils. Additional to Ni(2+) toxicity, toxicity from all solution ions was modelled independently as an osmotic effect and needed to be included for soil culture results. The EC50s and EC10s in soil culture were predicted within twofold of measured results. These are close to the results obtained using parameters estimated from the soil culture data itself., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Substance risk assessments require estimation of predicted no-effect concentrations (PNECs) in soil and sediment. The present study applies the target lipid model (TLM) and equilibrium partitioning (EqP) model to toxicity data to evaluate the extrapolation of the TLM-derived aquatic PNECs to these compartments. This extrapolation assumes that the sensitivity of aquatic species is similar to that of terrestrial and benthic species. The acute species sensitivity distribution, expressed in terms of species-specific critical target lipid body burdens, was computed using the TLM-EqP framework and found to span a similar range as the aquatic organism species sensitivity distribution but with a slightly lower median value (less than 2 times). The species sensitivity distribution for acute-to-chronic ratios also exhibited a similar range and distribution across species, suggesting similar mechanisms of action. This hypothesis was further tested by comparing empirical soil/sediment chronic effect levels to the calculated PNEC derived using TLM-EqP. The results showed that 95% of the compiled chronic effects data fell above the PNEC, confirming an adequate protection level. These findings support the conclusion that TLM-derived aquatic PNECs can be successfully extrapolated to derive credible PNECs for soil and sediment compartments., (© 2014 SETAC.)

The bioconcentration factor (BCF) of neutral and weakly polar organic chemicals in fish is modeled using independently calibrated models of chemical partitioning (freely dissolved fraction of chemical in the aqueous phase [φsys ] and wet-weight fish-water partition coefficient [KFW ]), respiratory exchange (respiratory update rate constant [k1 ], and respiratory elimination rate constant [k2  = k1 /KFW ]), and biotransformation (whole-body biotransformation rate constant [kM ]) as BCF = φsys KFW /(1 + kM /k2 ). Existing k1 models tend to overestimate for chemicals with log KOW  < 3.5, which constituted 30% to 50% of the examined chemicals. A revised k1 model covering a wider log KOW range (0-8.5) is presented k1  = (5.46 × 10(-6) MW + 0.261/KOW )(-1) , where MW is the molecular weight. The biotransformation rate constant kM is modeled using biota internal partitioning and Abraham parameters as reactivity descriptors. The reductionist model was tested using 3 different BCF data sets (US Environmental Protection Agency's Estimation Programs Interface [EPI], n = 548; Hertfordshire, n = 210; Arnot-Gobas, n = 1855) and compared with the following 3 state-of-the-art models: 1) the EPI Suite BCFBAF module, 2) the European Commision's Computer Assisted Evaluation of industrial chemical Substances According to Regulations (CAESAR), and 3) the EPI/Arnot mechanistic kinetic model. The reductionist model performed comparably with the alternative models (root mean square errors [RMSEs] = 0.72-0.77), with only 5 fitting parameters and no training against experimental BCFs. Respiratory elimination and biotransformation dominate the total depuration (i.e., [k2  + kM ]/kT  ≥ 0.8) for approximately 98% of the data entries, thus validating the reductionist approximation. Mechanistic models provide greater insights into bioaccumulation and are more sensitive to biological variation. All three BCF data sets and relevant properties and checkpoint values necessary for reproducing predictions of the reductionist model have been documented. The present study shows that a streamlined mechanistic model of BCF is possible for assessment purposes., (Copyright © 2013 SETAC.)

A model for whole-body in vivo biotransformation of neutral and weakly polar organic chemicals in fish is presented. It considers internal chemical partitioning and uses Abraham solvation parameters as reactivity descriptors. It assumes that only chemicals freely dissolved in the body fluid may bind with enzymes and subsequently undergo biotransformation reactions. Consequently, the whole-body biotransformation rate of a chemical is retarded by the extent of its distribution in different biological compartments. Using a randomly generated training set (n = 64), the biotransformation model is found to be: log (HLφfish ) = 2.2 (±0.3)B - 2.1 (±0.2)V - 0.6 (±0.3) (root mean square error of prediction [RMSE] = 0.71), where HL is the whole-body biotransformation half-life in days, φfish is the freely dissolved fraction in body fluid, and B and V are the chemical's H-bond acceptance capacity and molecular volume. Abraham-type linear free energy equations were also developed for lipid-water (Klipidw ) and protein-water (Kprotw ) partition coefficients needed for the computation of φfish from independent determinations. These were found to be 1) log Klipidw  = 0.77E - 1.10S - 0.47A - 3.52B + 3.37V + 0.84 (in Lwat /kglipid ; n = 248, RMSE = 0.57) and 2) log Kprotw  = 0.74E - 0.37S - 0.13A - 1.37B + 1.06V - 0.88 (in Lwat /kgprot ; n = 69, RMSE = 0.38), where E, S, and A quantify dispersive/polarization, dipolar, and H-bond-donating interactions, respectively. The biotransformation model performs well in the validation of HL (n = 424, RMSE = 0.71). The predicted rate constants do not exceed the transport limit due to circulatory flow. Furthermore, the model adequately captures variation in biotransformation rate between chemicals with varying log octanol-water partitioning coefficient, B, and V and exhibits high degree of independence from the choice of training chemicals. The present study suggests a new framework for modeling chemical reactivity in biological systems., (Copyright © 2013 SETAC.)

High volume in situ surface water samples were collected from a tidal tributary of the Delaware Estuary using an Infiltrex sampling system equipped with a 1 μm particle filter and a XAD-2 resin column. Particulate and dissolved phase polychlorinated biphenyl (PCB) congeners were analyzed using high resolution gas chromatography/high resolution mass spectrometry to obtain detection levels in the femtograms per liter range. The data were fit to a four-phase equilibrium partitioning model including freely dissolved PCB, PCB bound to particulate organic carbon (POC), PCB bound to dissolved organic carbon (DOC), and PCB bound to black carbon (BC). Isotherms were assumed to be linear for POC and DOC and nonlinear for BC. The partition coefficient between BC and dissolved PCB was assumed to depend on the dihedral angle between the phenyl rings. Following parameter optimization, the correlation coefficient between the log of the modeled and measured apparent distribution coefficient Kp,app was 0.94, and the RMSE was 0.189 log units. Including BC in the model reduces the dissolved PCB phase concentration in the water column for all congeners, especially for the non-ortho and mono-ortho substituted congeners.

In this study, we propose a general kinetics model for heavy metal adsorption and desorption reactions in soils when soil organic matter (SOM) is the dominant adsorbent. The kinetics model, integrated with the equilibrium speciation model WHAM VI, specifically considers metal reactions with SOM and dissolved organic matter (DOM) and accounts for the variations of solution chemistry. Metal reactions with SOM are associated with two groups of sites, one from the monodentate sites and another one from the bidentate and tridentate sites. There are three model parameters, desorption rate coefficients of the two groups of SOM sites for each metal and reactive organic carbon (ROC) for each soil. The applicability of the kinetics model was mainly examined with three elements, Cu, Pb, and Zn, which demonstrate different binding ability with organic matter. The kinetic data were collected with a stirred-flow reactor covering a wide range of experimental conditions, including varying SOM, DOM, Ca, and metal concentrations, reaction pHs, and different flow rates. The kinetics model has been successfully applied to describe heavy metal adsorption and desorption on soils under various reaction conditions.

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., (Copyright © 2012 SETAC.)

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., (Copyright © 2012 SETAC.)

Dissolved constituents of crude oil, particularly polycyclic aromatic hydrocarbons (PAHs), can contribute substantially to the toxicity of aquatic organisms. Measured aqueous concentrations of high-molecular weight PAHs (e.g., chrysenes, benzo[a]pyrene) as well as long-chain aliphatic hydrocarbons can exceed the theoretical solubility of these sparingly soluble compounds. This is attributed to the presence of a "microdroplet" or colloidal oil phase. It is important to be able to quantify the dissolved fraction of these compounds in oil-in-water preparations that are commonly used in toxicity assays because the interpretation of test results often assumes that the compounds are dissolved. A method is presented to determine the microdroplet contribution in crude oil-in-water preparations using a comparison of predicted and measured aqueous concentrations. Measured concentrations are reproduced in the model by including both microdroplets and dissolved constituents of petroleum hydrocarbons. Microdroplets were found in all oil-water preparation data sets analyzed. Estimated microdroplet oil concentrations typically ranged from 10 to 700 µg oil/L water. The fraction of dissolved individual petroleum hydrocarbons ranges from 1.0 for highly soluble compounds (e.g., benzene, toluene, ethylbenzene, and xylene) to far less than 0.1 for sparingly soluble compounds (e.g., chrysenes) depending on the microdroplet oil concentration. The presence of these microdroplets complicates the interpretation of toxicity test data because they may exert an additional toxic effect due to a change in the exposure profile. The implications of the droplet model on toxicity are also discussed in terms of both dissolved hydrocarbons and microdroplets., (Copyright © 2012 SETAC.)

Cyclic volatile methyl siloxanes (cVMS) are important consumer materials that are used in personal care products and industrial applications. These compounds have gained increased attention in recent years following the implementation of chemical legislation programs worldwide. Industry-wide research programs are being conducted to characterize the persistence, bioaccumulation, and toxicity (PBT) properties of cVMS materials. As part of this larger effort, a tissue-based risk assessment was performed to further inform the regulatory decision-making process. Measured tissue concentrations of cVMS compounds in fish and benthic invertebrates are compared with critical target lipid body burdens (CTLBBs) as estimated with the target lipid model (TLM) to evaluate risk. Acute and chronic toxicity data for cVMS compounds are compared with data for nonpolar organic chemicals to validate application of the TLM in this effort. The analysis was extended to estimate the contribution from metabolites to the overall cVMS-derived tissue residues using a food chain model calibrated to laboratory and field data. Concentrations of cVMS materials in biota from several trophic levels (e.g., invertebrates, fish) are well below the estimated CTLBBs associated with acute and chronic effects. This analysis, when combined with the limited biomagnification potential for cVMS compounds that was observed in the field, suggests that there is little risk of adverse effects from cVMS materials under present-day emission levels., (Copyright © 2012 SETAC.)