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Background: Nano-specific inhalation exposure models could potentially be effective tools to assess and control worker exposure to nano-objects, and their aggregates and agglomerates (NOAA). However, due to the lack of reliable and consistent collected NOAA exposure data, the scientific basis for validation of the existing NOAA exposure models is missing or limited. The main objective of this study was to gain more insight into the effect of various determinants underlying the potential on the concentration of airborne NOAA close to the source with the purpose of providing a scientific basis for existing and future exposure inhalation models., Method: Four experimental studies were conducted to investigate the effect of 11 determinants of emission on the concentration airborne NOAA close to the source during dumping of ~100% nanopowders. Determinants under study were: nanomaterial, particle size, dump mass, height, rate, ventilation rate, mixing speed, containment, particle surface coating, moisture content of the powder, and receiving surface. The experiments were conducted in an experimental room (19.5 m3) with well-controlled environmental and ventilation conditions. Particle number concentration and size distribution were measured using real-time measurement devices., Results: Dumping of nanopowders resulted in a higher number concentration and larger particles than dumping their reference microsized powder (P < 0.05). Statistically significant more and larger particles were also found during dumping of SiO2 nanopowder compared to TiO2/Al2O3 nanopowders. Particle surface coating did not affect the number concentration but on average larger particles were found during dumping of coated nanopowders. An increase of the powder's moisture content resulted in less and smaller particles in the air. Furthermore, the results indicate that particle number concentration increases with increasing dump height, rate, and mass and decreases when ventilation is turned on., Discussion: These results give an indication of the direction and magnitude of the effect of the studied determinants on concentrations close to the source and provide a scientific basis for (further) development of existing and future NOAA inhalation exposure models., (© The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Tiered or stepwise approaches to assess occupational exposure to nano-objects, and their agglomerates and aggregates have been proposed, which require decision rules (DRs) to move to a next tier, or terminate the assessment. In a desk study the performance of a number of DRs based on the evaluation of results from direct reading instruments was investigated by both statistical simulations and the application of the DRs to real workplace data sets. A statistical model that accounts for autocorrelation patterns in time-series, i.e. autoregressive integrated moving average (ARIMA), was used as 'gold' standard. The simulations showed that none of the proposed DRs covered the entire range of simulated scenarios with respect to the ARIMA model parameters, however, a combined DR showed a slightly better agreement. Application of the DRs to real workplace datasets (n = 117) revealed sensitivity up to 0.72, whereas the lowest observed specificity was 0.95. The selection of the most appropriate DR is very much dependent on the consequences of the decision, i.e. ruling in or ruling out of scenarios for further evaluation. Since a basic assessment may also comprise of other type of measurements and information, an evaluation logic was proposed which embeds the DRs, but furthermore supports decision making in view of a tiered-approach exposure assessment., (© The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)