Comparison of species sensitivity distributions constructed with predicted acute toxicity data from interspecies correlation estimation models and measured acute data for benzo[a]pyrene

Transcriptomics Points-of-Departure (tPODs) to Support Hazard Assessment of Benzo[a]pyrene in Early-Life-Stage Rainbow Trout

New approach methods (NAMs) are urgently needed to address the significant ethical and economic concerns associated with live animal testing as well as the low throughput associated with current toxicity testing frameworks. NAMs such as rapid mechanistic early-life-stage fish assays are promising alternatives to current hazard assessment approaches, as they can be used to derive toxicity thresholds and guide decision-makers on identifying or prioritizing chemicals of concern. This study aimed to derive benchmark concentrations from RNaseq data (transcriptomic points-of-departure; tPOD) from a short-term exposure study with early life stages of rainbow trout (RBT; Oncorhynchus mykiss) using benzo[a]pyrene (B[a]P) as the model compound. tPODs were then calibrated with higher organizational-level responses observed during an extended 28 day exposure period. RBT were exposed from 1 to 28 days post-hatch (dph) to 0.079, 0.35, 1.5, 7.4, and 29 μg/L (28 d time weighted average measured) B[a]P, as well as 0.05% dimethyl sulfoxide and water only controls. Benchmark concentration analysis of transcriptomic responses at 4 dph, based on the most sensitive transcriptomic features, yielded tPODs between 0.028 and 0.47 μg/L B[a]P. At 28 dph, Cyp1a1 exhibited significantly increased catalytic activity, with biochemical POD, bPODEROD,28dph of 0.599 μg/L B[a]P, while morphometric analysis showed significant growth inhibition in terms of length, with apical POD, aPODlength,28dph of 1.77 μg/L B[a]P, with a notable decreasing trend in body weight. A toxicity pathway model constructed from genes and apical end points exhibiting concentration-dependent responses provided further evidence supporting the utility of tPODs from short-term RBT early-life-stage assay to support chemical risk assessment to guide decision-makers in chemical testing prioritization.

Evaluation of interspecies correlation estimation models to increase taxonomic diversity while reducing reliance on animal testing for chemicals evaluated under the Toxic Substances Control Act

The U.S. Environmental Protection Agency is committed to the implementation of new approach methodologies (NAMs) to enhance the scientific basis for chemical hazard assessments. Chemical evaluations under the Toxic Substance Control Act (TSCA) are often conducted with limited test data and are well suited for NAMs applications. Interspecies correlation estimation (ICE) models are log-linear least squares regressions of the sensitivity between two species that estimate the acute toxicity of an untested species from the sensitivity of a surrogate. Interspecies correlation estimation models have been developed from and validated for diverse chemical modes of action, but their application in TSCA chemical assessments has not been previously evaluated. We use ICE models and a dataset of measured acute values for five chemicals, increasing the taxonomic diversity from which concentrations of concern (CoCs) are derived. Concentrations of concern were developed using approaches typically applied in TSCA risk evaluations, including application of assessment factors to the most sensitive species and the development of species sensitivity distributions where a minimum of eight species are represented by measured data. These CoCs were compared with those derived from datasets supplemented with ICE-predicted values, as well as comparing ICE predicted species mean acute values (SMAVs) to their respective measured values. Interspecies correlation estimation models predicted SMAVs within a factor of 5 and 10 for 87% and 92% of measured values, respectively. The CoCs developed from measured data only and data supplemented with ICE predicted toxicity were generally within five-fold, showing comparable protection. The taxonomic diversity in the ICE supplemented dataset was substantially higher than the measured data for species sensitivity distributions, providing a data-driven way of reducing uncertainty and potentially reducing the need for assessment factors. Interspecies correlation estimation models show promise as a NAM to improve the taxonomic representation included in chemical evaluations under TSCA.

Possible Causes of Extreme Variation of Benzo[a]pyrene Acute Toxicity Test on Daphnia magna

There are enormous differences in benzo[a]pyrene (BaP) acute toxicity tests on Daphnia magna, according to previous publications. The explanations of the reasons for this extreme variation are necessary. In this context, the acute toxicity tests of different experiment conditions (light/dark, culture medium, and solvent) were conducted on Daphnia magna with BaP as the toxicant of concern. Based on the experiments above, molecular dynamics (MD) simulations were employed to investigate the mechanisms of action. According to our results, the significant influence of light exposure on the acute toxicity test of BaP (p < 0.05) on D. magna was recorded. On the basis of the MD simulations, it was possible that BaP may not affect the normal operation of Superoxide Dismutase and Catalase directly, and it could be quickly transferred from the body through Glutathione S-transferase and Cytochromes P450. Therefore, when exposed to light, the oxidative stress process intensifies, causing damage to Daphnia magna. Apparently, the ecotoxicity tests based on inhibition for D. magna cannot adequately reflect the toxic effects of BaP.

Uncertainty analysis and updated user guidance for interspecies correlation estimation models and low toxicity compounds

Interspecies correlation estimation (ICE) models are log-linear relationships of acute sensitivity between two species that estimate the sensitivity of an untested species from the known sensitivity of a surrogate. As ICE model use increases globally, additional user guidance is required to ensure consistent use across chemicals and applications. The present study expands ICE uncertainty analyses and user guidance with a focus on low toxicity compounds whose acute values (i.e., reported as mg/L) can be greater than those used to develop a model. In these cases, surrogate values may be outside the ICE model domain and require additional extrapolations to predict acute toxicity. We use the extensive, standardized acute toxicity database underlying ICE models to broadly summarize inter-test variability of acute toxicity data as a measure by which model prediction accuracy can be evaluated. Using the data and models found on the USEPA Web-ICE (www3.epa.gov/webice), we created a set of "truncated" models from data corresponding to the lower 75th percentile of surrogate toxicity. We predicted toxicity for chemicals in the upper 25th percentile as both μg/L beyond the model domain and converted to mg/L (i.e., "scaled" value) and compared these predictions with those from cross-validation of whole ICE models and to the measured value. For ICE models with slopes in the range 0.66-1.33, prediction accuracy of scaled values did not differ from the accuracy of the models when data were entered as μg/L within or beyond the model domain. An uncertainty analysis of ICE confidence intervals was conducted and an interval range of two orders of magnitude was determined to minimize type I and II errors when accepting or rejecting ICE predictions. We updated the ICE user guidance based on these analyses to advance the state of the science for ICE model application and interpretation. Integr Environ Assess Manag 2024;20:1554-1565. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

Aquatic life criteria of hydrothermal liquefaction wastewater via ecotoxicity test and modeling

Wastewater resulting from hydrothermal liquefaction (HTL-AP) of biowaste is gaining attention as an emerging hazardous material. However, there is a lack of specific and systematic ecotoxicity studies on HTL-AP. This study addresses this gap by conducting acute toxicity tests on HTL-AP using typical aquatic species and integrating these results with predicted toxicity values from interspecies correlation estimation models to establish aquatic life criteria. HTL-AP exhibited significant toxicity with LC50 of 956.12-3645.4 mg/L, but demonstrated moderate toxicity compared to common freshwater pollutants like commercial microbicides, personal care products, and insect repellents. The resulting hazardous concentration for 5 % of species (HC5), the criterion maximum concentration, and the short-term water quality criteria for aquatic were 506.0, 253.0, and 168.7 mg/L, respectively. Notably, certain organisms like Misgurnus anguillicaudatus and Cipangopaludina chinensis showed high tolerance to HTL-AP, likely due to their metabolic capabilities on HTL-AP components. The significant decrease in HC5 values for some HTL-AP substances compared to pure compounds could indicate the synergistic inhibition effects among HTL-AP compositions. Furthermore, according to the established criteria, HTL-AP required significantly less diluted water (13 t) than carbendazim (1009 t) to achieve biosafety, indicating a safer release. This research establishes a preliminary water quality criterion for HTL-AP, offering a valuable reference for risk assessment and prediction in the utilization of HTL-AP within environmental contexts.

Predicted no-effect concentration for eight PAHs and their ecological risks in seven major river systems of China

The initial step in the assessment of the ecological risk of pollutants is to determine the predicted no-effect concentration (PNEC). However, ecological risk assessments of eight carcinogenic polycyclic aromatic hydrocarbons (PAHs), including dimethylbenz[a]anthracene (DMBA), methylcholanthrene (MCA), benzo(a)anthracene (BaA), chrysene (CHR), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), and dibenzo(a,h)anthracene (DBA), are rarely conducted due to the lack of their PNECs based on test data. In this study, quantitative structure-activity relationship (QSAR) models and interspecies correlation estimation (ICE) models were combined to predict the acute toxicity of these eight target PHAs. A Kolmogorov-Smirnov analysis for species sensitivity distributions (SSDs) of native and all species was conducted. There was no significant difference between the predictions for native Chinese species and the predictions for all species by the QSAR-ICE models. In addition, the feasibility of the QSAR-ICE models was demonstrated by comparing the SSD curves constructed by measured toxicity data of BaP and those predicted by the QSAR-ICE models. The PNECs of the eight PAHs were estimated based on the SSDs and acute to chronic ratio (ACR) method; these data were 0.071 μg/L, 0.033 μg/L, 0.049 μg/L, 0.114 μg/L, 0.019 μg/L, 0.021 μg/L, 0.038 μg/L and 0.054 μg/L for DMBA, DBA, BaP, MCA, BaA, CHR, BbF, BkF, respectively. The higher PNECs of the alkylated PAHs suggested their lower ecological risks. Based on the mixed risk quotient (mRQ) of PAHs through the concentration addition (CA) model, high ecological risk watersheds, such as the Songhua River (mRQ = 1.95), the Liao River (mRQ = 4.59), and the Huai River (mRQ = 1.93), were identified.

Optimized Derivation of Predicted No-Effect Concentrations (PNECs) for Eight Polycyclic Aromatic Hydrocarbons (PAHs) Using HC10 Based on Acute Toxicity Data

For persistent organic pollutants, a concern of environmental supervision, predicted no-effect concentrations (PNECs) are often used in ecological risk assessment, which is commonly derived from the hazardous concentration of 5% (HC₅) of the species sensitivity distribution (SSD). To address the problem of a lack of toxicity data, the objectives of this study are to propose and apply two improvement ideas for SSD application, taking polycyclic aromatic hydrocarbons (PAHs) as an example: whether the chronic PNEC can be derived from the acute SSD curve; whether the PNEC may be calculated by HC₁₀ to avoid solely statistical extrapolation. In this study, the acute SSD curves for eight PAHs and the chronic SSD curves for three PAHs were constructed. The quantity relationship of HC₅s between the acute and chronic SSD curves was explored, and the value of the assessment factor when using HC₁₀ to calculate PNEC was derived. The results showed that, for PAHs, the chronic PNEC can be estimated by multiplying the acute PNEC by 0.1, and the value of the assessment factor corresponding to HC₁₀ is 10. For acenaphthene, anthracene, benzo[a]pyrene, fluoranthene, fluorene, naphthalene, phenanthrene, and pyrene, the chronic PNECs based on the acute HC₁₀s were 0.8120, 0.008925, 0.005202, 0.07602, 2.328, 12.75, 0.5731, and 0.05360 μg/L, respectively.

Original and improved interspecies correlation estimation models in China for potential application in water quality criteria

Fluoranthene (FLU) has gained much attention in recent years because of its continuous discharge in natural waters and toxicity to aquatic ecosystems. However, it is difficult to control and manage FLU pollution because of the lack of a rational and scientific water quality criteria (WQC) of FLU. To solve these data gaps, the US EPA established an interspecies correlation estimation (ICE) model, which can be utilized to develop the SSD and HC₅ (hazardous concentration, 5th percentile). Moreover, an improved model was developed using a combination of North American ICE models supplemented with China-specific species. In this study, to verify the applicability of the two ICE models, measured acute toxicity data for FLU were obtained from 9 acute toxicity tests using indigenous Chinese aquatic species from different taxonomic levels. Original and improved ICE-based SSD curves, which were generated using 3 surrogate species (Daphnia magna, Oncorhynchus mykiss, and Lepomis macrochirus), were compared with SSD curves based on measured data. The results showed that HC₅ was 1.838, 1.062, and 0.570 mg/L for the original ICE, improved ICE, and measured data, respectively. The improved ICE-based HC₅ value for FLU was within twofold of the HC₅ value based on measure data, while the original ICE-based HC₅ value was threefold higher than the HC₅ value based on measure data. This indicated that the improved ICE had better predictability in extrapolating data with acceptable deviation than the original ICE. Furthermore, their differences between HC₅ derived from two SSD curves were not significant. Generally, the improved ICE model was verified as a valid approach for generating SSDs with limited toxicity data and for deriving WQC for FLU.

Reliable and Representative Estimation of Extrapolation Model Application in Deriving Water Quality Criteria for Antibiotics

Deriving water quality benchmarks based on the species sensitivity distribution (SSD) is crucial for assessing the ecological risks of antibiotics. The application of extrapolation methods such as interspecies correlation estimation (ICE) and acute-to-chronic ratios (ACRs) can effectively supplement insufficient toxicity data for these emerging contaminants. Acute-to-chronic ratios can predict chronic toxicity from acute toxicity, and ICE can extrapolate an acute toxicity value from one species to another species. The present study explored the impact of two extrapolation methods on the reliability of SSDs by analyzing different scenarios. The results show that, compared with the normal and Weibull distributions, the logistic model was the best-fitting model. For most antibiotics, SSDs derived by extrapolation have high reliability, with 82.9% of R² values being higher than 0.9, and combining ICE and ACR methods can bring a maximum increase of 10% in R² . Based on the results of Monte Carlo simulation, the statistical uncertainty brought by ICE in SSD is 10-40 times larger than that brought by ACR, and combining the two methods could reduce uncertainty. In addition, the sensitivity test showed that whether the toxicity data came from extrapolation or actual measurement, the lower the value of toxicity endpoints was, the greater the bias caused by the corresponding species in every scenario. Combining the two aforementioned extrapolation methods could effectively increase the stability of SSD, with their bias nearly equal to 1. Environ Toxicol Chem 2023;42:191-204. © 2022 SETAC.

Comparison of the sensitivity between indigenous and exotic aquatic species for fluoranthene and derivation of water quality criteria (WQC)

Fluoranthene (FLU) has shown relatively high toxicity to aquatic life as a priority polycyclic aromatic hydrocarbon (PAH). Considering the toxic effects of FLU on aquatic organisms and its high detection frequency in the aquatic environment, it is necessary and critical to derive FLU water quality criteria (WQC) for the protection of aquatic organisms and ecological risk assessment. However, due to the lack of toxicity data at different classification levels, there has been no research about the WQC of FLU. In this study, nine acute and three chronic toxicity tests were carried out on 9 Chinese indigenous aquatic species from different classification levels to obtain toxicity data. According to the US EPA guidelines, the criterion maximum concentration of 0.570 mg/L and the criterion continuous concentration of 0.174 mg/L were developed. There is no significant difference when comparing the species sensitivity distributions between indigenous and exotic species. Therefore, it is possible to use toxicity data from organisms in different areas for ecological risk assessment of FLU. CAPSULE: We compared the sensitivity between indigenous and exotic aquatic species for fluoranthene and derived its water quality criteria.

A QSAR-ICE-SSD model prediction of the PNECs for alkylphenol substances and application in ecological risk assessment for rivers of a megacity

Alkylphenols (APs) are ubiquitous and generally present in higher residue levels in the environment. The present work focuses on the development of a set of in silico models to predict the aquatic toxicity of APs with incomplete/unknown toxicity data in aquatic environments. To achieve this, a QSAR-ICE-SSD model was constructed for aquatic organisms by combining quantitative structure-activity relationship (QSAR), interspecies correlation estimation (ICE), and species sensitivity distribution (SSD) models in order to obtain the hazardous concentrations (HCs) of selected APs. The research indicated that the keywords "alkylphenol" and "nonylphenol" were most commonly studied. The selected ICE models were robust (R2: 0.70-0.99; p-value < 0.01). All models had a high reliability cross- validation success rates (>75%), and the HC5 predicted with the QSAR-ICE-SSD model was 2-fold than that derived with measured experimental data. The HC5 values demonstrated nearly linear decreasing trend from 2-MP to 4-HTP, while the decreasing trend from 4-HTP to 4-DP became shallower, indicates that the toxicity of APs to aquatic organisms increases with the addition of alkyl carbon chain lengths. The ecological risks assessment (ERA) of APs revealed that aquatic organisms were at risk from exposure to 4-NP at most river stations (the highest risk quotient (RQ) = 1.51), with the highest relative risk associated with 2.9% of 4-NP detected in 82.9% of the sampling sites. The targeted APs posed potential ecological risks in the Yongding and Beiyun River according to the mixture ERA. The potential application of QSAR-ICE-SSD models could satisfy the immediate needs for HC5 derivations without the need for additional in vivo testing.

Water quality criteria for lanthanum for freshwater aquatic organisms derived via species sensitivity distributions and interspecies correlation estimation models

The increasing exploitation and application of rare earth elements (REEs) may induce hazardous risks to freshwater aquatic organisms. Due to the lack of water quality criteria (WQC) and sufficient reliable toxicity data, little information is available on the ecological risk of REEs in surface water. In this study, lanthanum (La) toxicity data were collected from published toxicological studies, and the data quality was assessed using a toxicological data reliability assessment tool. To obtain more toxicity data, Daphnia magna, Cyprinus carpio, and Dania rerio embryos were selected as surrogate species, and an interspecies correlation estimation (ICE) model was used to predict the toxicity of La for untested species. The species sensitivity distributions (SSDs) of La toxicity and WQC were investigated. Differences were observed in the hazardous concentrations for 5% of species (HC₅), but no statistically significant differences were noted in the SSD curves between the measured acute toxicity data and the predicted data. For the SSDs constructed from the measured toxicity data, the ICE-predicted toxicity data and all acute data supplemented with the ICE-predicted data, the acute WQC values of La were 88, 1022 and 256 μg/L, respectively. According to the SSD and corresponding HC₅ of chronic toxicity data, the chronic WQC was 14 μg/L. The results provide a scientific reference for establishing WQC for freshwater aquatic organisms and ecological risk assessments of REEs.

Deriving convincing human health ambient water quality criteria for benzo[a]pyrene and providing basis for the water quality management: The impacts of national bioaccumulation factors and probabilistic modeling

Science-based water quality criteria are the cornerstone of water quality standards. This paper improved the methodology for the derivation of human health water quality criteria (HHWQC) and applied it for benzo[a]pyrene (BaP) to provide a scientific basis for the management of polycyclic aromatic hydrocarbons (PAHs) in surface waters. First, the national bioaccumulation factors (BAFs) for BaP were derived using field-measured BAFs and field-measured biota-sediment accumulation factors (BSAFs) across China, respectively, which results were comparable and demonstrated the reliability of the obtained national BAFs for BaP. The HHWQC for BaP derived using the probabilistic approach were 3.98-4.70 ng/L and were comparable with those derived by the deterministic approach, suggesting the accuracy of derived HHWQC for BaP. Through the probabilistic approach, the probability distributions of lifetime incremental cancer risk from BaP in water were provided and the consumption rates of aquatic products at trophic level 2 and 3 were identified as factors influencing risks of BaP significantly. The derived HHWQC for BaP in China are approximately 33-36 times higher than those in the United States because of the high national BAFs and cancer slope factor of BaP used for the United States. In addition, the recommended HHWQC for BaP conform to the situation in China and are approximately 1.5 times higher than the standard value of BaP in the current National Surface Water Quality Standard (GB 3838-2002) in China (2.80 ng/L), which will play an important role in the amendment of National Surface Water Quality Standard in the future. Approximately 36% of the studied surface freshwater in China contains BaP with levels exceeding the recommended HHWQC, suggesting the pollution of BaP in surface freshwater is severe and needs to be given more attention. This study is significant for the scientific development of HHWQC worldwide and the management of pollutants in water.

Salmo trutta is more sensitive than Oncorhynchus mykiss to early-life stage exposure to retene

Salmonids are known to be among the most sensitive fish to dioxin-like compounds (DLCs), but very little is known about the sensitivity of the brown trout (Salmo trutta), which has declined and is endangered in several countries of Europe and Western Asia. We investigated the sensitivity of brown trout larvae to a widespread dioxin-like PAH, retene (3.2 to 320 μg.L^-1), compared to the larvae of a salmonid commonly used in toxicology studies, the rainbow trout (Oncorhynchus mykiss). Mortality, growth, cyp1a induction and the occurrence of deformities were measured after 15 days of exposure. Brown trout larvae showed a significantly higher mortality at 320 μg.L^-1 compared to rainbow trout larvae. While the occurrence of deformities was only significantly increased at 320 μg.L^-1 for the rainbow trout, brown trout larvae displayed pericardial edemas and hemorrhages already at 10 or 100 μg.L^-1. cyp1a induction was increased significantly already at ≥3.2 μg.L^-1 for the brown trout, versus ≥32 μg.L^-1 for the rainbow trout. Least square regression analysis of the concentration-response relationships suggested that S. trutta larvae were at least 2 times more sensitive than O. mykiss larvae for cyp1a induction. The present study suggests that S. trutta larvae are more sensitive than O. mykiss larvae to a potent DLC, retene. As it is possible that S. trutta populations have declined partly because of pollution by DLCs, we recommend generating more data regarding the sensitivity of threatened fish populations, in order to ensure better risk assessment.

Polycyclic aromatic compounds (PACs) in the Canadian environment: The challenges of ecological risk assessments

Ecological risk assessments (ERAs) of polycyclic aromatic compounds (PACs), as single congeners or in mixtures, present technical challenges that raise concerns about their accuracy and validity for Canadian environments. Of more than 100,000 possible PAC structures, the toxicity of fewer than 1% have been tested as individual compounds, limiting the assessment of complex mixtures. Because of the diversity in modes of PAC action, the additivity of mixtures cannot be assumed, and mixture compositions change rapidly with weathering. In vertebrates, PACs are rapidly oxygenated by cytochrome P450 enzymes, often to metabolites that are more toxic than the parent compound. The ability to predict the ecological fate, distribution and effects of PACs is limited by toxicity data derived from tests of a few responses with a limited array of test species, under optimal laboratory conditions. Although several models are available to predict PAC toxicity and rank species sensitivity, they were developed with data biased by test methods, and the reported toxicities of many PACs exceed their solubility limits. As a result, Canadian Environmental Quality Guidelines for a few individual PACs provide little support for ERAs of complex mixtures in emissions and at contaminated sites. These issues are illustrated by reviews of three case studies of PAC-contaminated sites relevant to Canadian ecosystems. Interactions among ecosystem characteristics, the behaviour, fate and distribution of PACs, and non-chemical stresses on PAC-exposed species prevented clear associations between cause and effect. The uncertainties of ERAs can only be reduced by estimating the toxicity of a wider array of PACs to species typical of Canada's diverse geography and environmental conditions. Improvements are needed to models that predict toxicity, and more field studies of contaminated sites in Canada are needed to understand the ecological effects of PAC mixtures.

Development of human health ambient water quality criteria of 12 polycyclic aromatic hydrocarbons (PAH) and risk assessment in China

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed in various environmental media and have thus attracted extensive attention worldwide. To prevent and control PAH pollution in China, the study of ambient water quality criteria (AWQC), human health risks, and aquatic ecological risk is critical. There are no reports to date on the human health AWQC of PAHs in China. Therefore, this study first derived the human health AWQC values of 12 PAHs based on exposure data and bioaccumulation factor in China. We found that local exposure parameters and other relevant factors were key during the development of AWQC in different countries and regions, which led to differences with the reference value recommended by USEPA. Based on the incremental life time cancer risk (ILCR), hazard quotients (HQ) and potentially affected fraction (PAF) methods, the health and ecological risks of 16 PAHs were assessed subsequently. And the results are as follows: the non-carcinogenic PAHs' health risks ranged from 1.01 × 10^-10 to 1.60 × 10^-9, and carcinogenic PAH health risks ranged from 5.03 × 10^-7 to 4.74 × 10^-5. The toxic effects of 8 PAHs on aquatic organisms exhibited the following order: benzo (a) pyrene (BaP) > anthracene (Ant) > pyrene (Pye) > phenanthrene (Phe) > fluoranthene (Flua) > acenaphthene (Ace) > fluorene (Flu) > naphthalene (Nap). Among these, the ecological risks posed by Ant and BaP were the highest, according to the HQ and PAF methods.

Effective extrapolation models for ecotoxicity of benzene, toluene, ethylbenzene, and xylene (BTEX)

Benzene homologues have significant toxic effects to aquatic organisms. In this study, the acute toxicity data of benzene, toluene, ethylbenzene and xylene (BTEX) were collected and screened, and the toxicity extrapolation model of paired BTEX was established. The results showed that except the correlation between benzene and xylene was not strong due to insufficient data, the linear correlation of the other five paired BTEX was good (p < 0.01), and R² fitted by the four out of five paired BTEX was greater than 0.85. The cross validation showed that ethylbenzene-xylene model was optimal, and for most species (81.8%), the established five BTEX models had a prediction error of less than 10%. Also, these extrapolation models were validated by experimental results of Pseudorasbora parva. The difference between the predicted and measured values of the acute toxicity of BTEX was less than 1 fold, which indicated that the extrapolation model had high accuracy.

Development and use of interspecies correlation estimation models in China for potential application in water quality criteria

Establishment of numerical water quality criteria (WQC) has brought increasing interest in China. However, toxicity data to develop robust WQC values (number of toxicity data ≥8) of contaminants based solely on endemic and indigenous species are insufficient. In this study, interspecies correlation estimation (ICE) models were developed using a combination of North American ICE models supplemented with China-specific species to resolve this problem. A total of 207 significant surrogate-predicted models (p < 0.05, F-test) were derived: 119, 66 and 22 models for vertebrates, invertebrates and plant surrogate species, respectively. Model cross-validation success rate (≥80%), mean square error (MSE, ≤ 0.54), R² (≥0.78) and taxonomic distance (≤4, within the same class) were selected as guiding criteria to screen the resulted ICE models. The differences of 5th percentile hazard concentrations (HC₅s) for 6 chemicals (2,4-dichlorophenol, triclosan, tetrabromobisphenol A, nitrobenzene, perfluorooctane sulfonate and octabromodiphenyl ether) calculated from ICE-based and measured toxicity-based SSDs were within 3-fold among models. Although the number of derived ICE models was not comprehensive and continues to be improved, they can already be used in the development of WQC targeting protection of aquatic life and environmental risk assessments for chemicals lacking toxicity data.

Development of interspecies correlation estimation (ICE) models to predict the reproduction toxicity of EDCs to aquatic species

Endocrine disrupting chemicals (EDCs) threaten the reproductive fitness of aquatic organisms at concentrations lower than those associated with longevity and development. However, the small number of aquatic species assessed for reproductive toxicity has limited the ecological risk assessment of EDCs, making sensible decisions more difficult. In response to this, interspecies correlation estimation (ICE) models were established for EDCs to enable the estimation of reproduction toxicity values to a wider range of organisms. A total of 16 ICE models of EDCs for 6 surrogate species were statistically significant. Of the 16 models, 37.5% (6 models) had a cross-validation success rate > 60%, with a relatively small model squared error, indicating that the model fit is robust. These model results implied that the action of EDCs for each species pair might involve the same mechanisms, and taxonomic relationships did not influence the prediction precision. The cross-validation success rate corroborated the consistency between the projected and experimental values for the EDC ICE models. Sixty-seven percent of the projected values fell within a 10-fold difference of the experimental data. The results indicated that a proven ICE model can greatly increase the amount of EDCs chronic toxicity data for predicted species, without the need for extensive animal experiments, thus providing substitute chronic toxicity data for rapid assessment of EDCs ecological risks.

Derivation of freshwater water quality criteria for dibutyltin dilaurate from measured data and data predicted using interspecies correlation estimate models

Dibutyltin dilaurate (DBTL) is an organotin compound that has been widely detected in aquatic environments. However, the ecological risk assessment for DBTL is hard to perform due to the absence of water quality criteria (WQC) and lack of toxicity data. In this study, toxicity data were obtained from acute and chronic toxicity tests using aquatic species resident in China. Based on the species sensitivity distributions (SSDs) constructed from these test data, the acute water quality criterion (AWQC) and chronic water quality criterion (CWQC) were then derived to be 132 μg/L and 31.9 μg/L for DBTL. In order to valid the predicted data in the application to the protective criteria development and hazard assessment, the web-based interspecies correlation estimation (Web-ICE) system was used to estimate acute toxicities. Here two acute toxicity data groups for surrogate species were chosen from experimental data and QSAR Toolbox-predicted data separately, giving estimated data for prediction species using Web-ICE software. According to Kolmogorov-Smirnov test results, Web-ICE-based SSDs and measurement-based SSD were not significantly different. The results showed that the differences between measurement-based (132 μg/L) and Web-ICE-based AWQCs (39.7 μg/L and 58.5 μg/L) were statistically acceptable. Under certain conditions, it is therefore worth considering using the QSAR Toolbox plus Web-ICE method here to provide a beneficial supplement for developing preliminarily screen level toxicities in WQC when little or no relevant information are available. Besides, the geographic distribution of species was demonstrated not to be a significant factor in SSD establishment and WQC derivation.

Efficacy of Ozonation Treatments of Smoked Fish for Reducing Its Benzo[a]pyrene Concentration and Toxicity

Ozone is widely used in food processing, for example, to decompose mycotoxins or pesticide residues, to extend the shelf life of products, and for sanitation. The objective of this study was to assess the possibility of expanding the application of ozone for oxidative degradation of polycyclic aromatic hydrocarbons (PAHs). The evaluation was conducted by ozonation of a benzo[a]pyrene (BaP) standard solution and smoked fish (sprats) contaminated with PAHs. The effect of ozonation was immediate in the BaP solution; 89% of this toxic compound was decomposed after only 1 min of treatment. However, the impact of ozonation on the smoked sprats was less pronounced, even after prolonged treatment. The final reduction in benzo[b]fluoranthene and BaP concentrations in smoked sprats contaminated with PAHs was 34 and 46%, respectively, after 60 min of ozonation, but no significant decrease of benzo[a]anthracene and chrysene concentrations was observed. To evaluate the safety of ozonation, the toxicity of the ozone-treated BaP standard solution was investigated. In vitro toxicity was evaluated using human hepatocellular carcinoma and mouse embryonic fibroblast cell lines as models. The cytotoxicity of the BaP standard solution significantly increased after ozonation, indicating a pronounced negative effect in terms of food safety.