Evaluating the Control Banding Nanotool: a qualitative risk assessment method for controlling nanoparticle exposures

Zalk, David M.; Paik, Samuel Y.; Swuste, Paul

doi:10.1007/s11051-009-9678-y

Cited by 122 publications

(96 citation statements)

References 30 publications

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“…Benchmark particles could provide a quantitative link to the current hazard and control banding schemes that have qualitative descriptors of severity and likelihood of adverse effects (e.g., low to high severity, and unlikely to probable) (Maynard 2007;Schulte et al 2008;Zalk et al 2009;ANSES 2010). Exposure control decisions are typically based on exposure frequency, amount used, and dustiness of material as well as the hazardous properties of the material.…”

Section: Discussion and Next Stepsmentioning

confidence: 99%

“…These include: relative hazard and risk ranking frameworks for nanomaterials (Linkov et al 2007Tervonen et al 2009;Grieger et al 2012), nanomaterial-specific control banding schemes (Zalk et al 2009;ANSES 2010), and the United Nations' globally harmonized system of classification and labelling of chemicals which was recently adopted in the U.S. (77 FR 17574, March 26, 2012). However, absolute risk estimates or risk-based OELs for reference or benchmark materials within these categories are needed to link the hazard and relative risk information to the level of exposure control needed to protect workers (e.g., at a minimum, order of magnitude bands, Naumann et al 1996;Ader et al 2005).…”

Section: Categorical Approachesmentioning

confidence: 99%

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Development of risk-based nanomaterial groups for occupational exposure control

et al. 2012

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Given the almost limitless variety of nanomaterials, it will be virtually impossible to assess the possible occupational health hazard of each nanomaterial individually. The development of science-based hazard and risk categories for nanomaterials is needed for decision-making about exposure control practices in the workplace. A possible strategy would be to select representative (benchmark) materials from various mode of action (MOA) classes, evaluate the hazard and develop risk estimates, and then apply a systematic comparison of new nanomaterials with the benchmark materials in the same MOA class. Poorly soluble particles are used here as an example to illustrate quantitative risk assessment methods for possible benchmark particles and occupational exposure control groups, given mode of action and relative toxicity. Linking such benchmark particles to specific exposure control bands would facilitate the translation of health hazard and quantitative risk information to the development of effective exposure control practices in the workplace. A key challenge is obtaining sufficient dose-response data, based on standard testing, to systematically evaluate the nanomaterials' physical-chemical factors influencing their biological activity. Categorization processes involve both science-based analyses and default assumptions in the absence of substance-specific information. Utilizing data and information from related materials may facilitate initial determinations of exposure control systems for nanomaterials.

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Section: Discussion and Next Stepsmentioning

confidence: 99%

Section: Categorical Approachesmentioning

confidence: 99%

Development of risk-based nanomaterial groups for occupational exposure control

et al. 2012

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“…Out of the reviewed tools only Paik et al (2008) and Stoffenmanager Nano were tested in real case studies. Paik et al (2008) assessed four representative MNs activities for their risk level and potential control schemes, while Zalk et al (2009) used the same tool to address twenty-seven real industrial activities. Stoffenmanager Nano was tested in some of the industrial workplaces studied in the EU-funded SCAFFOLD project.…”

Section: Control Banding and Risk Screening Toolsmentioning

confidence: 99%

Frameworks and tools for risk assessment of manufactured nanomaterials

Hristozov

Gottardo

Semenzin

et al. 2016

Environment International

101

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Commercialization of nanotechnologies entails a regulatory requirement for understanding their environmental, health and safety (EHS) risks. Today we face challenges to assess these risks, which emerge from uncertainties around the interactions of manufactured nanomaterials (MNs) with humans and the environment. In order to reduce these uncertainties, it is necessary to generate sound scientific data on hazard and exposure by means of relevant frameworks and tools. The development of such approaches to facilitate the risk assessment (RA) of MNs has become a dynamic area of research. The aim of this paper was to review and critically analyse these approaches against a set of relevant criteria. The analysis concluded that none of the reviewed frameworks were able to fulfill all evaluation criteria. Many of the existing modelling tools are designed to provide screeninglevel assessments rather than to support regulatory RA and risk management. Nevertheless, there is a tendency towards developing more quantitative, higher-tier models, capable of incorporating uncertainty into their analyses. There is also a trend towards developing validated experimental protocols for material identification and hazard testing, reproducible across laboratories. These tools could enable a shift from a costly case-by-case RA of MNs towards a targeted, flexible and efficient process, based on grouping and read-across strategies and compliant with the 3R (Replacement, Reduction, Refinement) principles. In order to facilitate this process, it is important to transform the current efforts on developing databases and computational models into creating an integrated data and tools infrastructure to support the risk assessment and management of MNs.

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“…Meanwhile the conceptual source-receptor model for nanoparticles can be used as a framework for characterization of exposure in a control-banding tool, similar to the underlying model of the Stoffenmanager for inhalation exposure to ''conventional'' particles (Marquart et al, 2008) and the control-banding tool for handling powders described by Zalk et al (2009).…”

Section: Discussionmentioning

confidence: 99%

Conceptual model for assessment of inhalation exposure to manufactured nanoparticles

Schneider

Brouwer²,

Koponen

et al. 2011

J Expo Sci Environ Epidemiol

105

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As workplace air measurements of manufactured nanoparticles are relatively expensive to conduct, models can be helpful for a first tier assessment of exposure. A conceptual model was developed to give a framework for such models. The basis for the model is an analysis of the fate and underlying mechanisms of nanoparticles emitted by a source during transport to a receptor. Four source domains are distinguished; that is, production, handling of bulk product, dispersion of ready-to-use nanoproducts, fracturing and abrasion of end products. These domains represent different generation mechanisms that determine particle emission characteristics; for example, emission rate, particle size distribution, and source location. During transport, homogeneous coagulation, scavenging, and surface deposition will determine the fate of the particles and cause changes in both particle size distributions and number concentrations. The degree of impact of these processes will be determined by a variety of factors including the concentration and size mode of the emitted nanoparticles and background aerosols, source to receptor distance, and ventilation characteristics. The second part of the paper focuses on to what extent the conceptual model could be fit into an existing mechanistic predictive model for ''conventional'' exposures. The model should be seen as a framework for characterization of exposure to (manufactured) nanoparticles and future exposure modeling.

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Evaluating the Control Banding Nanotool: a qualitative risk assessment method for controlling nanoparticle exposures

Cited by 122 publications

References 30 publications

Development of risk-based nanomaterial groups for occupational exposure control

Development of risk-based nanomaterial groups for occupational exposure control

Frameworks and tools for risk assessment of manufactured nanomaterials

Conceptual model for assessment of inhalation exposure to manufactured nanoparticles

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