We present a phased approach for evaluating the effects of physical, biological, chemical, and psychosocial stressors that may act in combination. Although a phased concept is common to many risk-based approaches, it has not been explicitly outlined for the assessment of combined effects of multiple stressors. The approach begins with the development of appropriate conceptual models and assessment end points. The approach then proceeds through a screening stage wherein stressors are evaluated with respect to their potential importance as contributors to risk. Stressors are considered individually or as a combination of independent factors with respect to one or more common assessment end points. As necessary, the approach then proceeds to consider interactions among stressors. We make a distinction between applications that begin with effects of concern (effects based) or with specific stressors (stressor based). We describe a number of tools for use within the phased approach. The methods profiled are ones that have been applied to yield results that can be communicated to a wide audience. The latter characteristic is considered especially important because multiple stressor problems usually involve exposures to communities or to ecologic regions with many stakeholders.
Scientists, activists, industry, and governments have raised concerns about health and environmental risks of nanoscale materials. The Society for Risk Analysis convened experts in September 2008 in Washington, DC to deliberate on issues relating to the unique attributes of nanoscale materials that raise novel concerns about health risks. This article reports on the overall themes and findings of the workshop, uncovering the underlying issues for each of these topics that become recurring themes. The attributes of nanoscale particles and other nanomaterials that present novel issues for risk analysis are evaluated in a risk analysis framework, identifying challenges and opportunities for risk analysts and others seeking to assess and manage the risks from emerging nanoscale materials and nanotechnologies. Workshop deliberations and recommendations for advancing the risk analysis and management of nanotechnologies are presented.
The historical approach to assessing health risks of environmental chemicals has been to evaluate them one at a time. In fact, we are exposed every day to a wide variety of chemicals and are increasingly aware of potential health implications. Although considerable progress has been made in the science underlying risk assessments for real-world exposures, implementation has lagged because many practitioners are unaware of methods and tools available to support these analyses. To address this issue, the US Environmental Protection Agency developed a toolbox of cumulative risk resources for contaminated sites, as part of a resource document that was published in 2007. This paper highlights information for nearly 80 resources from the toolbox and provides selected updates, with practical notes for cumulative risk applications. Resources are organized according to the main elements of the assessment process: (1) planning, scoping, and problem formulation; (2) environmental fate and transport; (3) exposure analysis extending to human factors; (4) toxicity analysis; and (5) risk and uncertainty characterization, including presentation of results. In addition to providing online access, plans for the toolbox include addressing nonchemical stressors and applications beyond contaminated sites and further strengthening resource accessibility to support evolving analyses for cumulative risk and sustainable communities.
At disposal sites for wastes containing radium (Ra), vegetative stabilization may allow escape of radon (Rn) via uptake and mass flow of the gas in the plant transpiration stream. The main objectives of this work were to determine the magnitude and factors of such transport. Corn (Zea mays L.), sunflower (Helianthus annuus L.), and tall fescue (Festuca arundinacea Schreb.) were grown in uranium mill railings solids containing 226Ra (4.4 × 103 Bq kg−1). The quantities of 222Rn released by the plants in a controlled environment chamber were measured in relation to water transpired and leaf areas. The 226Ra and 222Rn in corn xylem liquid, and diffusion of 222Rn across paraffin wax barriers, were also measured. The 222Rn release rates by the plants ranged from about 8 to 28 mBq s−1 m−2 of leaf area, and were unrelated to the quantity of water transpired. Generally, the plants tended to release twice as much radon at 15°C than at 30°C, a phenomenon explained in part by the increased solubility of Rn in water at the lower temperature. We suggest that the bulk of 222Rn released by the plants is taken up by mass flow in water, but at the leaf mesophyll Rn diffuses independently of water, through the entire leaf cross‐section, unimpeded by the cuticle and epicuticular wax. The species of plant does not appear to be a major factor in the quantity of Rn released to the air; rather, the amount of Rn released into the atmosphere from a given area of vegetated land is expected to be in direct proportion to the leaf area index.
Perfluoroalkyl and polyfluoroalkyl substances (PFAS) pose a significant hazard because of their widespread industrial uses, environmental persistence, and bioaccumulation. A growing, increasingly diverse inventory of PFAS, including 8163 chemicals, has recently been updated by the U.S. Environmental Protection Agency. However, with the exception of a handful of well-studied examples, little is known about their human toxicity potential because of the substantial resources required for in vivo toxicity experiments. We tackle the problem of expensive in vivo experiments by evaluating multiple machine learning (ML) methods, including random forests, deep neural networks (DNN), graph convolutional networks, and Gaussian processes, for predicting acute toxicity (e.g., median lethal dose, or LD50) of PFAS compounds. To address the scarcity of toxicity information for PFAS, publicly available datasets of oral rat LD50 for all organic compounds are aggregated and used to develop state-of-the-art ML source models for transfer learning. A total of 519 fluorinated compounds containing two or more C-F bonds with known toxicity are used for knowledge transfer to ensembles of the best-performing source model, DNN, to generate the target models for the PFAS domain with access to uncertainty. This study predicts toxicity for PFAS with a defined chemical structure. To further inform prediction confidence, the transfer-learned model is embedded within a SelectiveNet architecture, where the model is allowed to identify regions of prediction with greater confidence and abstain from those with high uncertainty using a calibrated cutoff rate.
The Society for Risk Analysis (SRA) has a history of bringing thought leadership to topics of emerging risk. In September 2014, the SRA Emerging Nanoscale Materials Specialty Group convened an international workshop to examine the use of alternative testing strategies (ATS) for manufactured nanomaterials (NM) from a risk analysis perspective. Experts in NM environmental health and safety, human health, ecotoxicology, regulatory compliance, risk analysis, and ATS evaluated and discussed the state of the science for in vitro and other alternatives to traditional toxicology testing for NM. Based on this review, experts recommended immediate and near-term actions that would advance ATS use in NM risk assessment. Three focal areas-human health, ecological health, and exposure considerations-shaped deliberations about information needs, priorities, and the next steps required to increase confidence in and use of ATS in NM risk assessment. The deliberations revealed that ATS are now being used for screening, and that, in the near term, ATS could be developed for use in read-across or categorization decision making within certain regulatory frameworks. Participants recognized that leadership is required from within the scientific community to address basic challenges, including standardizing materials, protocols, techniques and reporting, and designing experiments relevant to real-world conditions, as well as coordination and sharing of large-scale collaborations and data. Experts agreed that it will be critical to include experimental parameters that can support the development of adverse outcome pathways. Numerous other insightful ideas for investment in ATS emerged throughout the discussions and are further highlighted in this article.
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