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.
Ultrafine particles (UFPs) emission generated from devices such as printer and photocopy machines are known as potential risks to human health. However, limited information is available to study UFPs exposure generate from larger printer. Thus, this study aimed to determine the concentration of UFPs such as particle number (PN) and lung deposited surface area (LDSA) and investigates the influence of physical environment factors on UFPs in two types of offset lithographic printing rooms such as monochrome and color, across West Malaysia. The measurements of PN and LDSA were taken by using a condensation particle counter and the diffusion charger dosimeter during the printing activities. The mean values for PN and LDSA are 22215 particles/cm 3 and 43 µm 2 /cm 3 , respectively. The exposure of UFPs from the monochrome room was found to be significantly higher than the color room (p < 0.001 for PN; p < 0.001 for LDSA) due to variation in the ventilation system. Based on correlation analysis, the physical environment factors, such as relative humidity, temperature, and air movement, were observed to influence the UFPs concentrations in printing room. The findings imply that a good selection of the ventilation system is important to minimize worker"s exposure to UFPs emission.
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