Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency.

Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.

Demonstrating the Use of Non-targeted Analysis for Identification of Unknown Chemicals in Rapid Response Scenarios.

Several thousand intentional and unintentional chemical releases occur annually in the U.S., with the contents of almost 30% being of unknown composition. When targeted methods are unable to identify the chemicals present, alternative approaches, including non-targeted analysis (NTA) methods, can be used to identify unknown analytes. With new and efficient data processing workflows, it is becoming possible to achieve confident chemical identifications via NTA in a timescale useful for rapid response (typically 24-72 h after sample receipt). To demonstrate the potential usefulness of NTA in rapid response situations, we have designed three mock scenarios that mimic real-world events, including a chemical warfare agent attack, the contamination of a home with illicit drugs, and an accidental industrial spill. Using a novel, focused NTA method that utilizes both existing and new data processing/analysis methods, we have identified the most important chemicals of interest in each of these designed mock scenarios in a rapid manner, correctly assigning structures to more than half of the 17 total features investigated. We have also identified four metrics (speed, confidence, hazard information, and transferability) that successful rapid response analytical methods should address and have discussed our performance for each metric. The results reveal the usefulness of NTA in rapid response scenarios, especially when unknown stressors need timely and confident identification.

The chemical landscape of high-throughput new approach methodologies for exposure.

The rapid characterization of risk to humans and ecosystems from exogenous chemicals requires information on both hazard and exposure. The U.S. Environmental Protection Agency's ToxCast program and the interagency Tox21 initiative have screened thousands of chemicals in various high-throughput (HT) assay systems for in vitro bioactivity. EPA's ExpoCast program is developing complementary HT methods for characterizing the human and ecological exposures necessary to interpret HT hazard data in a real-world risk context. These new approach methodologies (NAMs) for exposure include computational and analytical tools for characterizing multiple components of the complex pathways chemicals take from their source to human and ecological receptors. Here, we analyze the landscape of exposure NAMs developed in ExpoCast in the context of various chemical lists of scientific and regulatory interest, including the ToxCast and Tox21 libraries and the Toxic Substances Control Act (TSCA) inventory. We examine the landscape of traditional and exposure NAM data covering chemical use, emission, environmental fate, toxicokinetics, and ultimately external and internal exposure. We consider new chemical descriptors, machine learning models that draw inferences from existing data, high-throughput exposure models, statistical frameworks that integrate multiple model predictions, and non-targeted analytical screening methods that generate new HT monitoring information. We demonstrate that exposure NAMs drastically improve the coverage of the chemical landscape compared to traditional approaches and recommend a set of research activities to further expand the development of HT exposure data for application to risk characterization. Continuing to develop exposure NAMs to fill priority data gaps identified here will improve the availability and defensibility of risk-based metrics for use in chemical prioritization and screening. IMPACT: This analysis describes the current state of exposure assessment-based new approach methodologies across varied chemical landscapes and provides recommendations for filling key data gaps.

A Framework for Utilizing High-Resolution Mass Spectrometry and Nontargeted Analysis in Rapid Response and Emergency Situations.

Unknown chemical releases constitute a large portion of the rapid response situations to which the US Environmental Protection Agency is called on to respond. Workflows used to address unknown chemical releases currently involve screening for a large array of known compounds using many different targeted methods. When matches are not found, expert analytical chemistry knowledge is used to propose possible candidates from the available data, which generally includes low-resolution mass spectra and situational clues such as the location of the release, nearby industrial operations, and other field-reported facts. The past decade has witnessed dramatic improvements in capabilities for identifying unknown compounds using high-resolution mass spectrometry (HRMS) and nontargeted analysis (NTA) approaches. Complementary developments in cheminformatics tools have further enabled an increase in NTA throughput and identification confidence. Together with the expanding availability of HRMS instrumentation in monitoring laboratories, these advancements make NTA highly relevant to rapid response scenarios. In this article, we introduce the concept of NTA as it relates to rapid response needs and describe how it can be applied to address unknown chemical releases. We advocate for the consideration of HRMS-based NTA approaches to support future rapid response scenarios. Environ Toxicol Chem 2022;41:1117-1130. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group.

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

Predicting compound amenability with liquid chromatography-mass spectrometry to improve non-targeted analysis.

With the increasing availability of high-resolution mass spectrometers, suspect screening and non-targeted analysis are becoming popular compound identification tools for environmental researchers. Samples of interest often contain a large (unknown) number of chemicals spanning the detectable mass range of the instrument. In an effort to separate these chemicals prior to injection into the mass spectrometer, a chromatography method is often utilized. There are numerous types of gas and liquid chromatographs that can be coupled to commercially available mass spectrometers. Depending on the type of instrument used for analysis, the researcher is likely to observe a different subset of compounds based on the amenability of those chemicals to the selected experimental techniques and equipment. It would be advantageous if this subset of chemicals could be predicted prior to conducting the experiment, in order to minimize potential false-positive and false-negative identifications. In this work, we utilize experimental datasets to predict the amenability of chemical compounds to detection with liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS). The assembled dataset totals 5517 unique chemicals either explicitly detected or not detected with LC-ESI-MS. The resulting detected/not-detected matrix has been modeled using specific molecular descriptors to predict which chemicals are amenable to LC-ESI-MS, and to which form(s) of ionization. Random forest models, including a measure of the applicability domain of the model for both positive and negative modes of the electrospray ionization source, were successfully developed. The outcome of this work will help to inform future suspect screening and non-targeted analyses of chemicals by better defining the potential LC-ESI-MS detectable chemical landscape of interest.

A quest to identify suitable organic tracers for estimating children's dust ingestion rates.

Chemical exposure via dust ingestion is of great interest to researchers and regulators because children are exposed to dust through their daily activities, and as a result, to the many chemicals contained within dust. Our goal was to develop a workflow to identify and rank organic chemicals that could be used as tracers to calculate children's dust ingestion rates. We proposed a set of criteria for a chemical to be considered a promising tracer. The best tracers must be (1) ubiquitous in dust, (2) unique to dust, (3) detectable as biomarkers in accessible biological samples, and (4) have available or obtainable ADME information for biomarker-based exposure reconstruction. To identify compounds meeting these four criteria, we developed a workflow that encompasses non-targeted analysis approaches, literature and database searching, and multimedia modeling. We then implemented an ad hoc grading system and ranked candidate chemicals based on fulfillment of our criteria (using one small, publicly available dataset to show proof of concept). Initially, five chemicals (1,3-diphenylguanidine, leucine, piperine, 6:2/8:2 fluorotelomer phosphate diester, 6:2 fluorotelomer phosphate diester) appeared to satisfy many of our criteria. However, a rigorous manual investigation raised many questions about the applicability of these chemicals as tracers. Based on the results of this initial pilot study, no individual compounds can be unequivocally considered suitable tracers for calculating dust ingestion rates. Future work must therefore consider larger datasets, generated from broader measurement studies and literature searches, as well as refinements to selection criteria, to identify robust and defensible tracer compounds.

Expanded coverage of non-targeted LC-HRMS using atmospheric pressure chemical ionization: a case study with ENTACT mixtures.

Non-targeted analysis (NTA) is a rapidly evolving analytical technique with numerous opportunities to improve and expand instrumental and data analysis methods. In this work, NTA was performed on eight synthetic mixtures containing 1264 unique chemical substances from the U.S. Environmental Protection Agency's Non-Targeted Analysis Collaborative Trial (ENTACT). These mixtures were analyzed by atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) using both positive and negative polarities for a total of four modes. Out of the 1264 ENTACT chemical substances, 1116 were detected in at least one ionization mode, 185 chemicals were detected using all four ionization modes, whereas 148 were not detected. Forty-four chemicals were detected only by APCI, and 181 were detected only by ESI. Molecular descriptors and physicochemical properties were used to assess which ionization type was preferred for a given compound. One ToxPrint substructure (naphthalene group) was found to be enriched in compounds only detected using APCI, and eight ToxPrints (e.g., several alcohol moieties) were enriched in compounds only detected using ESI. Examination of physicochemical parameters for ENTACT chemicals suggests that those with higher aqueous solubility preferentially ionized by ESI-. While ESI typically detects a larger number of compounds, APCI offers chromatograms with less background, fewer co-elutions, and additional chemical space coverage, suggesting both should be considered for broader coverage in future NTA research. Graphical abstract.

Examining NTA performance and potential using fortified and reference house dust as part of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT).

Non-targeted analysis (NTA) methods are being increasingly used to aid in the identification of unknown compounds in the environment, a problem that has challenged environmental chemists for decades. Despite its increased use, quality assurance practices for NTA have not been well established. Furthermore, capabilities and limitations of certain NTA methods have not been thoroughly evaluated. Standard reference material dust (SRM 2585) was used here to evaluate the ability of NTA to identify previously reported compounds, as well as a suite of 365 chemicals that were spiked at various stages of the analytical procedure. Analysis of the unaltered SRM 2585 extracts revealed that several previously reported compounds can be identified by NTA, and that correct identification was dependent on concentration. A manual inspection of unknown features in SRM 2585 revealed the presence of two chlorinated and fluorinated compounds in high abundance, likely precursors to perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS). A retrospective analysis of data from the American Healthy Homes Survey revealed that these compounds were present in 42% of sampled homes. Spiking the dust at various stages of sample preparation revealed losses from extraction, cleanup, and instrumental analysis; the log Kow for individual compounds influenced the overall recovery levels but no pattern could be discerned from the various degrees of interference that the matrix had on the ionization efficiency of the spiked chemicals. Analysis of the matrix-free chemical mixture at low, medium, and high concentrations led to more correct identifications than analysis at one, very high concentration. Varying the spiked amount and identifying reported compounds at known concentrations allowed an estimation of the lower limits of identification (LOIs) for NTA, analogous to limits of detection in targeted analysis. The LOIs were much lower than levels in dust that would be likely to cause bioactivity in humans, indicating that NTA is useful for identifying and monitoring compounds that may be of toxicological concern. Graphical abstract.

In silico MS/MS spectra for identifying unknowns: a critical examination using CFM-ID algorithms and ENTACT mixture samples.

High-resolution mass spectrometry (HRMS) enables rapid chemical annotation via accurate mass measurements and matching of experimentally derived spectra with reference spectra. Reference libraries are generated from chemical standards and are therefore limited in size relative to known chemical space. To address this limitation, in silico spectra (i.e., MS/MS or MS2 spectra), predicted via Competitive Fragmentation Modeling-ID (CFM-ID) algorithms, were generated for compounds within the U.S. Environmental Protection Agency's (EPA) Distributed Structure-Searchable Toxicity (DSSTox) database (totaling, at the time of analysis, ~ 765,000 substances). Experimental spectra from EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) mixtures (n = 10) were then used to evaluate the performance of the in silico spectra. Overall, MS2 spectra were acquired for 377 unique compounds from the ENTACT mixtures. Approximately 53% of these compounds were correctly identified using a commercial reference library, whereas up to 50% were correctly identified as the top hit using the in silico library. Together, the reference and in silico libraries were able to correctly identify 73% of the 377 ENTACT substances. When using the in silico spectra for candidate filtering, an examination of binary classifiers showed a true positive rate (TPR) of 0.90 associated with false positive rates (FPRs) of 0.10 to 0.85, depending on the sample and method of candidate filtering. Taken together, these findings show the abilities of in silico spectra to correctly identify true positives in complex samples (at rates comparable to those observed with reference spectra), and efficiently filter large numbers of potential false positives from further consideration. Graphical abstract.

Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples.

The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.

The Next Generation Blueprint of Computational Toxicology at the U.S. Environmental Protection Agency.

The U.S. Environmental Protection Agency (EPA) is faced with the challenge of efficiently and credibly evaluating chemical safety often with limited or no available toxicity data. The expanding number of chemicals found in commerce and the environment, coupled with time and resource requirements for traditional toxicity testing and exposure characterization, continue to underscore the need for new approaches. In 2005, EPA charted a new course to address this challenge by embracing computational toxicology (CompTox) and investing in the technologies and capabilities to push the field forward. The return on this investment has been demonstrated through results and applications across a range of human and environmental health problems, as well as initial application to regulatory decision-making within programs such as the EPA's Endocrine Disruptor Screening Program. The CompTox initiative at EPA is more than a decade old. This manuscript presents a blueprint to guide the strategic and operational direction over the next 5 years. The primary goal is to obtain broader acceptance of the CompTox approaches for application to higher tier regulatory decisions, such as chemical assessments. To achieve this goal, the blueprint expands and refines the use of high-throughput and computational modeling approaches to transform the components in chemical risk assessment, while systematically addressing key challenges that have hindered progress. In addition, the blueprint outlines additional investments in cross-cutting efforts to characterize uncertainty and variability, develop software and information technology tools, provide outreach and training, and establish scientific confidence for application to different public health and environmental regulatory decisions.

Using prepared mixtures of ToxCast chemicals to evaluate non-targeted analysis (NTA) method performance.

Non-targeted analysis (NTA) methods are increasingly used to discover contaminants of emerging concern (CECs), but the extent to which these methods can support exposure and health studies remains to be determined. EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) was launched in 2016 to address this need. As part of ENTACT, 1269 unique substances from EPA's ToxCast library were combined to make ten synthetic mixtures, with each mixture containing between 95 and 365 substances. As a participant in the trial, we first performed blinded NTA on each mixture using liquid chromatography (LC) coupled with high-resolution mass spectrometry (HRMS). We then performed an unblinded evaluation to identify limitations of our NTA method. Overall, at least 60% of spiked substances could be observed using selected methods. Discounting spiked isomers, true positive rates from the blinded and unblinded analyses reached a maximum of 46% and 65%, respectively. An overall reproducibility rate of 75% was observed for substances spiked into more than one mixture and observed at least once. Considerable discordance in substance identification was observed when comparing a subset of our results derived from two separate reversed-phase chromatography methods. We conclude that a single NTA method, even when optimized, can likely characterize only a subset of ToxCast substances (and, by extension, other CECs). Rigorous quality control and self-evaluation practices should be required of labs generating NTA data to support exposure and health studies. Accurate and transparent communication of performance results will best enable meaningful interpretations and defensible use of NTA data. Graphical abstract ᅟ.

Use of carbon isotopic ratios in nontargeted analysis to screen for anthropogenic compounds in complex environmental matrices.

Analytical data for ultra-high-performance liquid chromatography (UHPLC), nontargeted, high-resolution, mass-spectrometry (HR/MS) molecular features from a wide array of samples are used to calculate 13C112C(n-1)/12Cn isotopologue ratios. These ratios increase with molecular carbon number roughly following a trend defined by atmospheric carbon. When the effective source reservoir 13C/12C ratio is calculated from the isotopologue ratio (assuming a fractionation factor of unity), features in biotic samples uniformly are tightly grouped, proximate to atmospheric 13C/12C ratio. In contrast, features in soil natural organic matter (NOM), dust NOM and anthropogenic compounds range from proximate to relatively divergent from atmospheric 13C/12C. For the NOM, 13C/12C ratios are consistent with an expected preferential volatilization of 12C, rendering features in soil NOM 13C-enriched and some features in dust NOM 13C-depleted. Anthropogenic compounds tend to diverge most dramatically from atmospheric 13C/12C, generally toward 13C-depletion, but pesticides we tested tended toward 13C-enriched. This pattern is robust and evident in: i) anthropogenic vs natural features in dust; ii) perfluorinated compounds in standards and as soil contaminants; and iii) sunscreen compounds in commercial products and wastewater. Considering the observed wide 13C/12C range for anthropogenic compounds, we suggest Rayleigh distillation during synthetic processes commonly favors one isotope over the other, rendering a source reservoir that is progressively depleted as synthesis proceeds and, consequently, generates a wide variation in 13C/12C for man-made products. However, kinetic-isotopic effects and/or synthesis from petroleum/natural gas might contribute to the anthropogenic isotopic signature as well. Regardless of cause, 13C/12C can be used to cull HR/MS molecular features that are more likely to be of anthropogenic or non-biotic origin.

EPA's non-targeted analysis collaborative trial (ENTACT): genesis, design, and initial findings.

In August 2015, the US Environmental Protection Agency (EPA) convened a workshop entitled "Advancing non-targeted analyses of xenobiotic chemicals in environmental and biological media." The purpose of the workshop was to bring together the foremost experts in non-targeted analysis (NTA) to discuss the state-of-the-science for generating, interpreting, and exchanging NTA measurement data. During the workshop, participants discussed potential designs for a collaborative project that would use EPA resources, including the ToxCast library of chemical substances, the DSSTox database, and the CompTox Chemicals Dashboard, to evaluate cutting-edge NTA methods. That discussion was the genesis of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT). Nearly 30 laboratories have enrolled in ENTACT and used a variety of chromatography, mass spectrometry, and data processing approaches to characterize ten synthetic chemical mixtures, three standardized media (human serum, house dust, and silicone band) extracts, and thousands of individual substances. Initial results show that nearly all participants have detected and reported more compounds in the mixtures than were intentionally added, with large inter-lab variability in the number of reported compounds. A comparison of gas and liquid chromatography results shows that the majority (45.3%) of correctly identified compounds were detected by only one method and 15.4% of compounds were not identified. Finally, a limited set of true positive identifications indicates substantial differences in observable chemical space when employing disparate separation and ionization techniques as part of NTA workflows. This article describes the genesis of ENTACT, all study methods and materials, and an analysis of results submitted to date. Graphical abstract ᅟ.

Integrating tools for non-targeted analysis research and chemical safety evaluations at the US EPA.

Tens-of-thousands of chemicals are registered in the U.S. for use in countless processes and products. Recent evidence suggests that many of these chemicals are measureable in environmental and/or biological systems, indicating the potential for widespread exposures. Traditional public health research tools, including in vivo studies and targeted analytical chemistry methods, have been unable to meet the needs of screening programs designed to evaluate chemical safety. As such, new tools have been developed to enable rapid assessment of potentially harmful chemical exposures and their attendant biological responses. One group of tools, known as "non-targeted analysis" (NTA) methods, allows the rapid characterization of thousands of never-before-studied compounds in a wide variety of environmental, residential, and biological media. This article discusses current applications of NTA methods, challenges to their effective use in chemical screening studies, and ways in which shared resources (e.g., chemical standards, databases, model predictions, and media measurements) can advance their use in risk-based chemical prioritization. A brief review is provided of resources and projects within EPA's Office of Research and Development (ORD) that provide benefit to, and receive benefits from, NTA research endeavors. A summary of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) is also given, which makes direct use of ORD resources to benefit the global NTA research community. Finally, a research framework is described that shows how NTA methods will bridge chemical prioritization efforts within ORD. This framework exists as a guide for institutions seeking to understand the complexity of chemical exposures, and the impact of these exposures on living systems.

Enantiomer-specific measurements of current-use pesticides in aquatic systems.

Some current-use pesticides are chiral and have nonsuperimposable mirror images called enantiomers that exhibit identical physical-chemical properties but can behave differently when in contact with other chiral molecules (e.g., regarding degradation and uptake). These differences can result in variations in enantiomer presence in the environment and potentially change the toxicity of pesticide residues. Several current-use chiral pesticides are applied in urban and agricultural areas, with increased potential to enter watersheds and adversely affect aquatic organisms. The present study describes a stereoselective analytical method for the current-use pesticides fipronil, cis-bifenthrin, cis-permethrin, cypermethrin, and cyfluthrin. We show use of the method by characterizing enantiomer fractions in environmental sample extracts (sediment and water), and laboratory-dosed fish and concrete extracts previously collected by California organizations. Enantiomer fractions for most environmental samples are the same as racemic standards (equal amounts of enantiomers, enantiomer fraction = 0.5) and therefore are not expected to differ in toxicity from racemic mixtures typically tested. In laboratory-derived samples, enantiomer fractions are more frequently nonracemic and favor the less toxic enantiomer; permethrin enantiomer fractions range from 0.094 to 0.391 in one type of concrete runoff and enantiomer fractions of bifenthrin in dosed fish range from 0.378 to 0.499. We use enantiomer fractions as a screening tool to understand environmental exposure and explore ways this uncommon measurement could be used to better understand toxicity and risk. Environ Toxicol Chem 2018;37:99-106. Published 2017 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.