An integrated health risk assessment with control banding for nanomaterials exposure
Process Safety Progress, ISSN: 1547-5913, Vol: 41, Issue: S1, Page: S84-S97
2022
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Nanomaterials are known to cause biological effects to humans through various routes of exposure such as injection, intravenous, oral, and inhalation. The risk analyses through conventional qualitative or semi-quantitative approaches, such as control banding tools with limited safety data, and information on the risks posed by nanomaterials, have created uncertainties in decision-making by various stakeholders. Therefore, an integrated Nanomaterial Risk (NanoRisk) framework that incorporates the Bayesian Network (BN) model, control banding, and process parameters focusing on humidity, the mass of nanomaterials, and operating temperatures was developed to assess the hazards of nanomaterials and their potential biological effects to human health as a result of exposure. The proposed risk assessment was applied to nanomaterials used in the paint and coating industry (nano-silica, nano-titanium, and nano-silver), and the nodes of the BN model were constructed from physiochemical properties, biological effects, routes of exposure, and types of studies extracted from published data. The flexible analytic approach of the BN model allows for a valuable prediction of hazard exposure towards nanomaterials, thus facilitating decision-making. Furthermore, the integrated framework proposes suitable control measures to reduce the hazard exposure according to the hazard level at different modes of operation. The distinctive feature of NanoRisk demonstrates comprehensive analysis and results that are comparable with previously developed methods.
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