Safe and sustainable by design: A computer-based approach to redesign chemicals for reduced environmental hazards

Uncertainty in Environmental Micropollutant Modeling

Water pollution policies have been enacted across the globe to minimize the environmental risks posed by micropollutants (MPs). For regulative institutions to be able to ensure the realization of environmental objectives, they need information on the environmental fate of MPs. Furthermore, there is an urgent need to further improve environmental decision-making, which heavily relies on scientific data. Use of mathematical and computational modeling in environmental permit processes for water construction activities has increased. Uncertainty of input data considers several steps from sampling and analysis to physico-chemical characteristics of MP. Machine learning (ML) methods are an emerging technique in this field. ML techniques might become more crucial for MP modeling as the amount of data is constantly increasing and the emerging new ML approaches and applications are developed. It seems that both modeling strategies, traditional and ML, use quite similar methods to obtain uncertainties. Process based models cannot consider all known and relevant processes, making the comprehensive estimation of uncertainty challenging. Problems in a comprehensive uncertainty analysis within ML approach are even greater. For both approaches generic and common method seems to be more useful in a practice than those emerging from ab initio. The implementation of the modeling results, including uncertainty and the precautionary principle, should be researched more deeply to achieve a reliable estimation of the effect of an action on the chemical and ecological status of an environment without underestimating or overestimating the risk. The prevailing uncertainties need to be identified and acknowledged and if possible, reduced. This paper provides an overview of different aspects that concern the topic of uncertainty in MP modeling.

Multiple criteria decision analysis to support the design of safe and sustainable chemicals and materials

The development of safe and sustainable chemicals and materials is essential to achieve the Zero-Pollution Ambition for a Toxic Free Environment stated in the EU Green Deal. For that, criteria need to be defined and considered since early stage of development. A Safe and Sustainable by Design (SSbD) framework is proposed in an EU Recommendation suggesting the assessment of multiple safety and sustainability aspects of chemicals and materials leaving open how the evaluation and selection of the preferable option should be done. This paper presents a proposal with different options for the use of multiattribute aggregation in an evaluation procedure for the SSbD assessment of chemicals and materials. This proposal is based on i) a review of the literature focusing on Multi-Criteria Decision Analysis (MCDA) application in the SSbD context (i.e. applications considering simultaneously safety and sustainability attributes) and ii) the definition of requisites for MCDA to be applied to the SSBD framework. In the latter, an absolute rather than a relative assessment is preferred as it should be possible for an organization developing a new chemical or material to assess if it is SSbD, without needing to obtain data on all of its possible competitors. Moreover, rank-reversals caused by the introduction of other options are avoided, i.e., assessments of one alternative that depends on other alternatives being assessed simultaneously are not the most adequate. Different options for the aggregation of attributes at different levels are discussed as well as for the consideration of data quality in the evaluation procedure. Regardless the approach selected, the use of multiattribute aggregation does not rule out a richer dashboard presenting not only the overall aggregate result, but also the results obtained in other levels of the hierarchy. Such complementary information is important to understand the strengths and weaknesses that an aggregate result might hide.

Transformers enable accurate prediction of acute and chronic chemical toxicity in aquatic organisms

Environmental hazard assessments are reliant on toxicity data that cover multiple organism groups. Generating experimental toxicity data is, however, resource-intensive and time-consuming. Computational methods are fast and cost-efficient alternatives, but the low accuracy and narrow applicability domains have made their adaptation slow. Here, we present a AI-based model for predicting chemical toxicity. The model uses transformers to capture toxicity-specific features directly from the chemical structures and deep neural networks to predict effect concentrations. The model showed high predictive performance for all tested organism groups-algae, aquatic invertebrates and fish-and has, in comparison to commonly used QSAR methods, a larger applicability domain and a considerably lower error. When the model was trained on data with multiple effect concentrations (EC50/EC10), the performance was further improved. We conclude that deep learning and transformers have the potential to markedly advance computational prediction of chemical toxicity.

Learning from Safe-by-Design for Safe-and-Sustainable-by-Design: Mapping the current landscape of Safe-by-Design reviews, case studies, and frameworks

With the introduction of the European Commission's "Safe and Sustainable-by-Design" (SSbD) framework, the interest in understanding the implications of safety and sustainability assessments of chemicals, materials, and processes at early-innovation stages has skyrocketed. Our study focuses on the "Safe-by-Design" (SbD) approach from the nanomaterials sector, which predates the SSbD framework. In this assessment, SbD studies have been compiled and categorized into reviews, case studies, and frameworks. Reviews of SbD tools have been further classified as quantitative, qualitative, or toolboxes and repositories. We assessed the SbD case studies and classified them into three categories: safe(r)-by-modeling, safe(r)-by-selection, or safe(r)-by-redesign. This classification enabled us to understand past SbD work and subsequently use it to define future SSbD work so as to avoid confusion and possibilities of "SSbD-washing" (similar to greenwashing). Finally, the preexisting SbD frameworks have been studied and contextualized against the SSbD framework. Several key recommendations for SSbD based on our analysis can be made. Knowledge gained from existing approaches such as SbD, green and sustainable chemistry, and benign-by-design approaches needs to be preserved and effectively transferred to SSbD. Better incorporation of chemical and material functionality into the SSbD framework is required. The concept of lifecycle thinking and the stage-gate innovation model need to be reconciled for SSbD. The development of high-throughput screening models is critical for the operationalization of SSbD. We conclude that the rapid pace of both SbD and SSbD development necessitates a regular mapping of the newly published literature that is relevant to this field.

Alternatives assessment: An analysis on progress and future needs for research and practice

Alternatives assessment is a science-policy approach to support the informed substitution of chemicals of concern in consumer products and industries, with the intent of avoiding regrettable substitution and facilitating the transition to safer, more sustainable chemicals and products. The field of alternatives assessment has grown steadily in recent decades, particularly after the publication of specific frameworks and the inclusion of substitution and alternatives assessment requirements in a number of policy contexts. Previously, 14 research and practice needs for the field were outlined across five critical areas: comparative hazard assessment, comparative exposure characterization, lifecycle considerations, decision-making and decision analysis, and professional practice. The aim of the current article is twofold: to highlight methodological advances in the growing field of alternatives assessment based on identified research and practice needs and to propose areas for future developments. We assess advances in the field based on the analysis of a broad literature review that captured 154 sources published from 2013 to 2022. The results indicate that research conducted advanced many of the needs identified, but several remain underaddressed. Although the field has clearly grown and taken root over the past decade, there are still research and practice gaps, most notably on the hazard assessment of mixtures or different forms of chemicals, the integration of lifecycle considerations, and the development of practical approaches to address trade-offs in decision-making. We propose modifications to four of the prior research and practice needs in addition to new needs, including the development of standardized hazard assessment approaches for chemical mixtures as well as better integration of equity and/or justice considerations into assessments. Integr Environ Assess Manag 2024;00:1-18. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Systematic computational toxicity analysis of the ozonolytic degraded compounds of azo dyes: Quantitative structure-activity relationship (QSAR) and adverse outcome pathway (AOP) based approach

The present study identifies and analyses the degraded products of three azo dyes (Reactive Orange 16, Reactive Red 120, and Direct Red 80) and proffers their in silico toxicity predictions. In our previously published work, the synthetic dye effluents were degraded using an ozonolysis-based Advanced Oxidation Process. In the present study, the degraded products of the three dyes were analysed using GC-MS at endpoint strategy and further subjected to in silico toxicity analysis using Toxicity Estimation Software Tool (TEST), Prediction Of TOXicity of chemicals (ProTox-II), and Estimation Programs Interface Suite (EPI Suite). Several physiological toxicity endpoints, such as hepatotoxicity, carcinogenicity, mutagenicity, cellular and molecular interactions, were considered to assess the Quantitative Structure-Activity Relationships (QSAR) and adverse outcome pathways. The environmental fate of the by-products in terms of their biodegradability and possible bioaccumulation was also assessed. Results of ProTox-II suggested that the azo dye degradation products are carcinogenic, immunotoxic, and cytotoxic and displayed toxicity towards Androgen Receptor and Mitochondrial Membrane Potential. TEST results predicted LC50 and IGC50 values for three organisms Tetrahymena pyriformis, Daphnia magna, and Pimephales promelas. EPISUITE software via the BCFBAF module surmises that the degradation products' bioaccumulation (BAF) and bioconcentration factors (BCF) are high. The cumulative inference of the results suggests that most degradation by-products are toxic and need further remediation strategies. The study aims to complement existing tests to predict toxicity and prioritise the elimination/reduction of harmful degradation products of primary treatment procedures. The novelty of this study is that it streamlines in silico approaches to predict the nature of toxicity of degradation by-products of toxic industrial affluents like azo dyes. These approaches can assist the first phase of toxicology assessments for any pollutant for regulatory decision-making bodies to chalk out appropriate action plans for their remediation.

Integrated data-driven cross-disciplinary framework to prevent chemical water pollution

Access to a clean and healthy environment is a human right and a prerequisite for maintaining a sustainable ecosystem. Experts across domains along the chemical life cycle have traditionally operated in isolation, leading to limited connectivity between upstream chemical innovation to downstream development of water-treatment technologies. This fragmented and historically reactive approach to managing emerging contaminants has resulted in significant externalized societal costs. Herein, we propose an integrated data-driven framework to foster proactive action across domains to effectively address chemical water pollution. By implementing this integrated framework, it will not only enhance the capabilities of experts in their respective fields but also create opportunities for novel approaches that yield co-benefits across multiple domains. To successfully operationalize the integrated framework, several concerted efforts are warranted, including adopting open and FAIR (findable, accessible, interoperable, and reusable) data practices, developing common knowledge bases/platforms, and staying vigilant against new substance "properties" of concern.

[The history of emerging substances in Austria]

Over time, many different groups of substances became the focus of interest, so their occurrence, behaviour and effects were studied. While in the 1990s, it was detergents and the formation of foam in water, later the causes of discolouration around tanneries were researched, as well as the presence of chemicals and pollutants near industrial plants. Organochlorine pesticides, brominated flame retardants, perfluoroalkyl substances or PFAS, organotin compounds are some examples of such Emerging substances. After pesticides and industrial chemicals, active pharmaceutical ingredients, cosmetics and personal care products have also become "Emerging substances". Ultimately, however, it is the effect of the substances-whether persistent, bioaccumulative, mobile, toxic or even endocrine disruption-that attracts attention and triggers legal regulations. As the substances and the methods for their detection changed, so did the corresponding legislation. This in turn led to the use of new or slightly modified substances and substance groups. Innovative methods such as non-targeted analytics and biological effect tests or bioassays are now being utilised to address the variety and combined effects of the existing substances. In order to ensure comprehensive groundwater and water protection, the investigation and assessment methods must be developed. Furthermore, the existing and newly acquired knowledge need to be translated into regulatory consequences more quickly. Beyond that, a comprehensive societal transformation with regard to the sustainable use of natural water resources is essential for environmentally sound and healthy development. This must therefore be implemented on many different levels; with knowledge transfer and awareness-raising also having a significant role to play.