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Commercialization of rechargeable lithium‐ion (Li‐ion) batteries has revolutionized the design of portable electronic devices and is facilitating the current transition to electric vehicles. The technological specifications of Li‐ion batteries continue to evolve through the introduction of various high‐risk liquid electrolyte chemicals, yet critical evaluation of the physical, environmental, and human health hazards of these substances is lacking. Using the GreenScreen for Safer Chemicals approach, we conducted a chemical hazard assessment (CHA) of 103 electrolyte chemicals categorized into seven chemical groups: salts, carbonates, esters, ethers, sulfoxides–sulfites–sulfones, overcharge protection additives, and flame‐retardant additives. To minimize data gaps, we focused on six toxicity and hazard data sources, including three empirical and three nonempirical predictive data sources. Furthermore, we investigated the structural similarities among selected electrolyte chemicals using the ChemMine tool and the simplified molecular input line entry system inputs from PubChem to evaluate whether chemicals with similar structures exhibit similar toxicity. The results demonstrate that salts, overcharge protection additives, and flame‐retardant additives contain the most toxic components in the electrolyte solutions. Furthermore, carbonates, esters, and ethers account for most flammability hazards in Li‐ion batteries. This study supports the complementary use of quantitative structure–activity relationship models to minimize data gaps and inconsistencies in CHA. Integr Environ Assess Manag 2024;20:2231–2244. © 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points: Chemical hazard assessment was conducted for 103 electrolyte chemicals, categorized into seven groups, used in lithium‐ion batteries.Most of the 103 electrolyte chemicals exhibited high levels of concern relative to human health and environmental hazard endpoints.Nonempirical predictive data sources are essential for filling data gaps commonly encountered in empirical data sources.Structure similarity analysis highlights that chemicals with structure similarity correlate with similar hazard endpoints, increasing the value of predictive data sources. [ABSTRACT FROM AUTHOR]

Batteries are important for promoting renewable energy, but, like most engineered products, they contain multiple hazardous materials. The purpose of this study is to evaluate industrial-scale batteries using GreenScreen® for Safer Chemicals, an established chemical hazard assessment (CHA) framework, and to develop a systematic, transparent methodology to quantify the CHA results, harmonize them, and aggregate them into single-value hazard scores, which can facilitate quantitative comparison and a robust evaluation of data gaps, inconsistencies, and uncertainty through the implementation of carefully selected scenarios and stochastic multicriteria acceptability analysis (SMAA). Using multiple authoritative toxicity data sources, six battery products are evaluated: three lithium-ion batteries (lithium iron phosphate, lithium nickel cobalt manganese hydroxide, and lithium manganese oxide), and three redox flow batteries (vanadium redox, zinc-bromine, and all-iron). The CHA results indicate that many materials in these batteries, including reagents and intermediates, inherently exhibit high hazard; therefore, safer materials should be identified and considered in future designs. The scenario analysis and SMAA, combined, provide a quantitative evaluation framework to support the decision-making needed to compare alternative technologies. Thus, this study highlights specific strategies to reduce the use of hazardous materials in complex engineered products before they are widely used in this rapidly-expanding industry sector.

Background. Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods. HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_ PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals' emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results. The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. [ABSTRACT FROM AUTHOR]

A key component of ecological risk assessments is to develop evidence-based benchmarks to assess potential hazards to various receptors. To ensure that toxicity value development is performed using the best available science, the reliability (or inherent scientific quality) of these studies must be considered. The degree of reliability can be evaluated via critical appraisal tools (CATs), though application of such methods assessing ecotoxicological literature for toxicity value development is not well established compared to human health assessments. A review of existing CATs revealed that there is currently no approach that considers the full range of biases that should be considered for appraisal of internal validity in ecotoxicological studies. Recognizing the need for a comprehensive ecotoxicity study assessment framework that addresses risk of bias (RoB) for the interpretation of study reliability, we propose the Ecotoxicological Study Reliability (EcoSR) framework. This framework builds upon the classic RoB assessment approach, frequently applied in human health assessments. EcoSR adds reliability and key criteria specific to ecotoxicity studies from existing appraisal methods, emphasizing those used by regulatory bodies. Additionally, the framework recommends a priori customization based on assessment goals. EcoSR is comprised of two tiers: an optional preliminary screening (Tier 1) and a full reliability assessment (Tier 2). The framework outlines a systematic approach for conducting ecotoxicity study appraisals that enhances transparency and consistency in determining study reliability. The EcoSR framework provides flexibility and can be refined and applied to a variety of chemical classes. This framework represents a significant step towards improving the transparency and reproducibility of ecotoxicological study appraisals; ultimately, contributing to more informed and reliable toxicity value development within the ecological sciences., (© The Author(s) 2025. Published by Oxford University Press on behalf of the Society of Environmental Toxicology and Chemistry. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

A comprehensive assessment of chemical alternatives (ACA) is necessary to avoid regrettable substitution. In a preceding study, an analysis of six hazard assessment methods found that none of them are fully aligned with the hazard assessment criteria of Article 57 of the European REACH regulation, indicating a need for a method better reflecting hazard assessment schemes in European chemical regulations. This paper presents a multiple-criteria decision analysis (MCDA) method for the ACA that takes the criteria of Article 57 of REACH into account. Investigated and presented are objective hierarchies, the aggregation of objectives, the curvature of the value functions, weights, and the introduction of a classification threshold. The MCDA-ACA method allows for the aggregation of hazards in such a way that poor performance in one hazard cannot be compensated for by good performance in another hazard. The method parameters were developed and tested using two data sets with the aim to classify chemical alternatives into acceptable (nonregrettable) and unacceptable (regrettable) alternatives according to the regulations set in Europe. The flexibility of the general method was explored by adapting the method to align with two hazard assessment schemes, Article 57 of REACH and GreenScreen. The results show that MCDA-ACA is so flexible and transparent that it can easily be adapted to various hazard assessment schemes.

BACKGROUND: Workplace Hazardous Materials Information System (WHMIS) training is obligatory for Ontario workplaces. The purpose of this training is to help workers understand the health and safety issues associated with using chemicals, including how to understand the information contained in the Safety Data Sheets (SDSs) that come with all chemicals. However, many workers still do not know how hazardous workplace chemicals can be and they find it difficult to objectively determine the level of hazard posed by the chemicals they use. OBJECTIVE: A team of researchers, unions, and health and safety associations created a tool for Joint Health and Safety Committees (JHSC) of small and medium-sized businesses to help them identify, assess and prioritize the health hazards posed by workplace chemicals using SDSs as the primary source of information. METHODS: The team recruited the JHSCs of six workplaces to pilot the usefulness of the Chemical Hazard Assessment and Prioritization (CHAP) tool. The CHAP tool helps workplaces rank their chemicals within one of five hazard levels using information contained in SDSs. RESULTS: Despite a difficult recruitment process, the participating JHSCs thought the CHAP process of assessing and prioritizing their workplace chemicals was useful. It raised their awareness of chemical hazards, increased their understanding of SDSs, and helped them prioritize their chemicals for improved control measures. CONCLUSIONS: Small and medium-sized businesses found the tool to be useful, but suggested that an electronic version would be easier to use. [ABSTRACT FROM AUTHOR]

The continual introduction of new chemicals into the market necessitates fast, efficient testing strategies for evaluating their toxicity. Ideally, these high-throughput screening (HTS) methods should capture the entirety of biological complexity while minimizing reliance on expensive resources that are required to assess diverse phenotypic endpoints. In recent years, the zebrafish (Danio rerio) has become a preferred vertebrate model to conduct rapid in vivo toxicity tests. Previously, using HTS data on 1060 chemicals tested as part of the ToxCast program, we showed that early, 24 h post-fertilization (hpf), behavioral responses of zebrafish embryos are predictive of later, 120 h post-fertilization, adverse developmental endpoints—indicating that embryonic behavior is a useful endpoint related to observable morphological effects. Here, our goal was to assess the contributions (i.e., information gain) from multiple phenotypic data streams and propose a framework for efficient identification of chemical hazards. We systematically swept through analysis parameters for data on 24 hpf behavior, 120 hpf behavior, and 120 hpf morphology to optimize settings for each of these assays. We evaluated the concordance of data from behavioral assays with that from morphology. We found that combining information from behavioral and mortality assessments captures early signals of potential chemical hazards, obviating the need to evaluate a comprehensive suite of morphological endpoints in initial screens for toxicity. We have demonstrated that such a screening strategy is useful for detecting compounds that elicit adverse morphological responses, in addition to identifying hazardous compounds that do not disrupt the underlying morphology. The application of this design for rapid preliminary toxicity screening will accelerate chemical testing and aid in prioritizing chemicals for risk assessment.

Comparative chemical hazard assessment, which compares hazards for several endpoints across several chemicals, can be used for a variety of purposes including alternatives assessment and the prioritization of chemicals for further assessment. A new framework was developed to compile and integrate chemical hazard data for several human health and ecotoxicity endpoints from public online sources including hazardous chemical lists, Globally Harmonized System hazard codes (H-codes) or hazard categories from government health agencies, experimental quantitative toxicity values, and predicted values using Quantitative Structure–Activity Relationship (QSAR) models. QSAR model predictions were obtained using EPA's Toxicity Estimation Software Tool. Java programming was used to download hazard data, convert data from each source into a consistent score record format, and store the data in a database. Scoring criteria based on the EPA's Design for the Environment Program Alternatives Assessment Criteria for Hazard Evaluation were used to determine ordinal hazard scores (i.e., low, medium, high, or very high) for each score record. Different methodologies were assessed for integrating data from multiple sources into one score for each hazard endpoint for each chemical. The chemical hazard assessment (CHA) Database developed in this study currently contains more than 990,000 score records for more than 85,000 chemicals. The CHA Database and the methods used in its development may contribute to several cheminformatics, public health, and environmental activities. [ABSTRACT FROM AUTHOR]

Chemical hazard assessment (CHA), which aims to investigate the inherent hazard potential of chemicals, has been developed with the purpose of promoting safer consumer products. Despite the increasing use of CHA in recent years, finding adequate and reliable toxicity data required for CHA is still challenging due to issues regarding data completeness and data quality. Also, collecting data from primary toxicity reports or literature can be time consuming, which promotes the use of secondary data sources instead. In this study, we evaluate and characterize numerous secondary data sources on the basis of 5 performance attributes: reliability, adequacy, transparency, volume, and ease of use. We use GreenScreen for Safer Chemicals v1.4 as the CHA framework, which defines the endpoints of interest used in this analysis. We focused upon 34 data sources that reflect 3 types of secondary data: chemical‐oriented data sources, hazard‐trait–oriented data sources, and predictive data sources. To integrate and analyze the evaluation results, we applied 2 multicriteria decision analysis (MCDA) methodologies: multiattribute utility theory (MAUT) and stochastic multiobjective acceptability analysis (SMAA). Overall, the findings in this research program allow us to explore the relative importance of performance criteria and the data source quality for effectively conducting CHA. Integr Environ Assess Manag 2019;00:1–14. © 2019 SETAC Key Points: The evaluation and characterization of secondary data sources through multicriteria decision analysis (MCDA) provide an innovative quantitative approach on guiding how to choose and evaluate data sources for chemical hazard assessment.Through MCDA analysis, the chemical‐oriented data sources exhibit better performance compared to hazard‐trait–oriented data sources and predictive data sources for chemical hazard assessment.The sensitivity analysis in multiattribute utility theory (MAUT) indicates the final score for each data source will vary by changing the weighting factor for each performance attribute, and some common trends can be captured for the 3 different types of data sources.The applications of MAUT and stochastic multiobjective acceptability analysis (SMAA) are complementary for making decisions on which data sources are more suitable for chemical hazard assessment and which performance attributes are of greatest importance. [ABSTRACT FROM AUTHOR]

Various chemicals used in hydraulic fracturing have raised environmental and human health (EHH) concerns regarding water resources contamination, leading to the transition towards the use of chemicals with minimum EHH hazards. Chemical hazard screening and indexing approaches have been used to measure the chemical hazard of hydraulic fracturing, and each approach is associated with inherent advantages and limitations. In this study, the two chemical hazard assessment approaches were discussed, and an integrated chemical hazard screening and indexing system was developed to combine the strengths of the two approaches. The integrated system was applied to assess the EHH hazards of representative hydraulic fracturing chemicals used in British Columbia, Canada. The hazard screening results showed that more than half of the ingredients and additives were classified into high hazard groups. Moreover, the integrated system generated more critical hazard assessment results than two hazard indexing systems, revealing that using the individual hazard indexing approach could result in underestimated EHH hazards for chemicals. The integrated system can significantly improve the data confidence levels of hazard assessment results compared to a previously developed indexing system. The integrated system can also help formulate fracturing fluids with low EHH hazards by identifying ingredients of high hazard concerns. [ABSTRACT FROM AUTHOR]

A critical step in systematic reviews of potential health hazards is the structured evaluation of the strengths and weaknesses of the included studies; risk of bias is a term often used to represent this process, specifically with respect to the evaluation of systematic errors that can lead to inaccurate (biased) results (i.e. focusing on internal validity). Systematic review methods developed in the clinical medicine arena have been adapted for use in evaluating environmental health hazards; this expansion raises questions about the scope of risk of bias tools and the extent to which they capture the elements that can affect the interpretation of results from environmental and occupational epidemiology studies and in vivo animal toxicology studies, (the studies typically available for assessment of risk of chemicals). One such element, described here as “sensitivity”, is a measure of the ability of a study to detect a true effect or hazard. This concept is similar to the concept of the sensitivity of an assay; an insensitive study may fail to show a difference that truly exists, leading to a false conclusion of no effect. Factors relating to study sensitivity should be evaluated in a systematic manner with the same rigor as the evaluation of other elements within a risk of bias framework. We discuss the importance of this component for the interpretation of individual studies, examine approaches proposed or in use to address it, and describe how it relates to other evaluation components. The evaluation domains contained within a risk of bias tool can include, or can be modified to include, some features relating to study sensitivity; the explicit inclusion of these sensitivity criteria with the same rigor and at the same stage of study evaluation as other bias-related criteria can improve the evaluation process. In some cases, these and other features may be better addressed through a separate sensitivity domain. The combined evaluation of risk of bias and sensitivity can be used to identify the most informative studies, to evaluate the confidence of the findings from individual studies and to identify those study elements that may help to explain heterogeneity across the body of literature. [ABSTRACT FROM AUTHOR]

Abstract: Sewage sludge has been used as fertilizer for agricultural land over a long time. This is part of a sustainable practice utilizing and recycling the macronutrients back to land. During the last decades, questions have been raised concerning the risks related to heavy metals and xenobiotic organic compounds (XOCs) present in the sludge. Application on land used for agriculture is, therefore, not socially acceptable in some countries, e.g., Sweden. In this study, literature reviews showed that 541 XOCs potentially could be present in sewage sludge due to their presence in e.g. construction materials, pharmaceuticals, personal care products etc. 192 compounds have been quantified in sewage sludge, which indicate that, although many XOCs have been measured in sludge, there are potentially a vast number of compounds present that have not been analyzed for yet. In a hazard identification of the quantified compounds using their inherent properties and environmental fate it was shown that 99 XOCs could be classified as being hazardous with regard to the solid phase and 23 were found to be priority pollutants in the subsequent hazard assessment. The final selected priority pollutants can act as indicators when assessing sludge quality. They were compared with European legislations and discussed in regard for pointing out the need for mitigation such as substitution. Furthermore, the potential need for implementation of sludge treatment trains in order to meet the society''s needs was addressed. [Copyright &y& Elsevier]

Chemical hazard assessment (CHA), designed to evaluate the inherent hazard of chemicals used in everyday consumer products, is gaining in popularity and rigor. Although CHA is being more commonly used by industry and government organizations, there is limited information in the academic literature on the merits and limitations of CHA methods. In the current study, the significance of the need to use multiple data sources to successfully complete a CHA is explored. Specifically, a case study approach is used in which more than one hundred organic substances used in the synthesis of organic solar cells are evaluated using the GreenScreen® for Safer Chemicals framework as the basis for the CHA. Seven data sources, including three chemical-oriented, two hazard-trait-oriented, and two predictive data sources, are utilized to minimize data gaps and allow for complete assessments for most of the chemicals of interest. Findings from sensitivity analysis using single data sources and combinations of data sources highlight that the CHA outcomes can vary considerably as a function of data sources used, which highlights the importance of identifying and/or creating more comprehensive and standardized data sources., (Copyright © 2018 Elsevier B.V. All rights reserved.)