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The aim of this study was to make a preliminary evaluation of the University of North Carolina passive aerosol sampler (UNC sampler) for personal air sampling of particles. Nine personal air samplings of respirable fraction were conducted in an open-pit mine, with pairwise UNC samplers and a respirable cyclone mounted on the chest of workers. UNC samples were analyzed with scanning electron microscopy (SEM) and to some extent energy dispersive X-ray spectroscopy (EDS). Respirable cyclone filter samples were weighed. Correlations and particle elemental compositions were described. Microscopic imaging of the collection surface showed that the particles were heterogeneously deposited across the surface of the UNC sampler. Collected particles were shaped as gravel particles and the resulting particle size distribution in air showed a peak at ca. 3 µm aerodynamic diameter, similarly to what has previously been reported from the same mine. The elemental composition indicated mineral origin. All correlations between the airborne mass concentrations from UNC samplers and respirable cyclones (Pearson = 0.54 and Spearman = 0.43) and between pairs of parallel UNC samplers (Pearson = 0.55 and Spearman = 0.67) were weak. The UNC sampler mass concentrations were approximately 30 times higher than those measured with the respirable cyclone. In conclusion, the UNC sampler, when used for personal sampling in a mine, provides a reasonable particle size distribution and the deposited particles appeared to be of mineral origin and not from textile or skin but the approximately 30-fold overestimation of mass concentrations when comparing with respirable cyclone sampling indicates that further improvements are necessary. Positioning of the sampler may be critical and moving the UNC sampler from the chest to e.g. the top of a helmet might be an improvement. Grounding of the sampler in order to avoid static electricity might also be useful. The UNC sampler should continue to be researched for personal sampling, as passive sampling might become a useful alternative to more laborious sampling techniques. [ABSTRACT FROM AUTHOR]

Objectives: In an occupational environment, passive sampling could be an alternative to active sampling with pumps for sampling of dust. One passive sampler is the University of North Carolina passive aerosol sampler (UNC sampler). It is often analysed by microscopic imaging. Promising results have been shown for particles above 2.5 µm, but indicate large underestimations for PM2.5. The aim of this study was to evaluate, and possibly improve, the UNC sampler for stationary sampling in a working environment. Methods: Sampling was carried out at 8-h intervals during 24 h in four locations in an open pit mine with UNC samplers, respirable cyclones, PM10 and PM2.5 impactors, and an aerodynamic particle sizer (APS). The wind was minimal. For quantification, two modifications of the UNC sampler analysis model, UNC sampler with hybrid model and UNC sampler with area factor, were compared with the original one, UNC sampler with mesh factor derived from wind tunnel experiments. The effect of increased resolution for the microscopic imaging was examined. Results: Use of the area factor and a higher resolution eliminated the underestimation for PM10 and PM2.5. The model with area factor had the overall lowest deviation versus the impactor and the cyclone. The intraclass correlation (ICC) showed that the UNC sampler had a higher precision and better ability to distinguish between different exposure levels compared to the cyclone (ICC: 0.51 versus 0.24), but lower precision compared to the impactor (PM10: 0.79 versus 0.99; PM2.5: 0.30 versus 0.45). The particle size distributions as calculated from the different UNC sampler analysis models were visually compared with the distributions determined by APS. The distributions were obviously different when the UNC sampler with mesh factor was used but came to a reasonable agreement when the area factor was used. Conclusions: High resolution combined with a factor based on area only, results in no underestimation of small particles compared to impactors and cyclones and a better agreement with the APS's particle size distributions. The UNC sampler had lower precision than the impactors, but higher than the respirable cyclone. The UNC sampler with area factor could be used for PM2.5, PM10 and respirable fraction measurements in this working environment without wind. [ABSTRACT FROM AUTHOR]

Objectives: Dust is generally sampled on a filter using air pumps, but passive sampling could be a cost-effective alternative. One promising passive sampler is the University of North Carolina passive aerosol sampler (UNC sampler). The aim of this study is to characterize and compare the UNC sampler's performance with PM10 and PM2.5 impactors in a working environment. Methods: Area sampling was carried out at different mining locations using UNC samplers in parallel with PM2.5 and PM10 impactors. Two different collection surfaces, polycarbonate (PC) and carbon tabs (CT), were employed for the UNC sampling. Sampling was carried out for 4-25 hours. Results: The UNC samplers underestimated the concentrations compared to PM10 and PM2.5 impactor data. At the location with the highest aerosol concentration, the time-averaged mean of PC showed 24% and CT 35% of the impactor result for PM2.5. For PM10, it was 39% with PC and 58% with CT. Sample blank values differed between PC and CT. For PM2.5, PC blank values were ~7 times higher than those of CT, but only 1.8 times higher for PM10. The blank variations were larger for PC than for CT. Conclusions: Particle mass concentrations appear to be underestimated by the UNC sampler compared to impactors, more so for PM2.5 than for PM10. CT may be preferred as a collection surface because the blank values were lower and less variable than for PC. Future validations in the working environment should include respirable dust sampling. [ABSTRACT FROM AUTHOR]

Background: Measurements of exposure to vibrations from hand-held tools are often conducted on a single occasion. However, repeated measurements may be crucial for estimating the actual dose with good precision. In addition, knowledge of determinants of exposure could be used to improve working conditions. The aim of this study was to assess hand–arm vibration (HAV) exposure during different grinding operations, in order to obtain estimates of the variance components and to evaluate the effect of work postures.Methods: Ten experienced operators used two compressed air-driven angle grinders of the same make in a simulated work task at a workplace. One part of the study consisted of using a grinder while assuming two different working postures: at a standard work bench (low) and on a wall with arms elevated and the work area adjusted to each operator’s height (high). The workers repeated the task three times. In another part of the study, investigating the wheel wear, for each grinder, the operators used two new grinding wheels and with each wheel the operator performed two consecutive 1-min grinding tasks. Both grinding tasks were conducted on weld puddles of mild steel on a piece of mild steel. Measurements were taken according to ISO-standard 5349 [the equivalent hand–arm-weighted acceleration (m s−2) averaged over 1 min]. Mixed- and random-effects models were used to investigate the influence of the fixed variables and to estimate variance components.Results: The equivalent hand–arm-weighted acceleration assessed when the task was performed on the bench and at the wall was 3.2 and 3.3 m s−2, respectively. In the mixed-effects model, work posture was not a significant variable. The variables ‘operator’ and ‘grinder’ together explained only 12% of the exposure variability and ‘grinding wheel’ explained 47%; the residual variability of 41% remained unexplained. When the effect of grinding wheel wear was investigated in the random-effects model, 37% of the variability was associated with the wheel while minimal variability was associated with the operator or the grinder and 37% was unexplained. The interaction effect of grinder and operator explained 18% of the variability. In the wheel wear test, the equivalent hand–arm-weighted accelerations for Grinder 1 during the first and second grinding minutes were 3.4 and 2.9 m s−2, respectively, and for Grinder 2, they were 3.1 and 2.9 m s−2, respectively. For Grinder 1, the equivalent hand–arm-weighted acceleration during the first grinding minute was significantly higher (P = 0.04) than during the second minute.Conclusions: Work posture during grinding operations does not appear to affect the level of HAV. Grinding wheels explained much of the variability in this study, but almost 40% of the variance remained unexplained. The considerable variability in the equivalent hand–arm-weighted acceleration has an impact on the risk assessment at both the group and the individual level. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine workers' mental interpretation models developed in response to occupational chemical exposure. The study was performed in six companies within the reinforced plastics industry in northern Sweden, in which styrene was used; 32 workers participated in the study. Each worker performed between four and seven exposure measurements. Before receiving each result of the second to seventh measurements, the workers were asked to predict the level of their next exposure measurement. Their predictions were evaluated with respect to two judgmental principles: coherence (that the predictions are based on logical decision rules, that is, the mean value of the prior exposure levels); and correspondence (the predictions have high empirical accuracy) by calculating the mean absolute percent forcast error (MAPE). The coherence principle was tested by comparing each of the workers' predictions with the mean, median, and last exposure level (last value) of the prior measurements. The correspondence principle was tested by comparing the worker's prediction with the outcome of the measurement. The coherence principle was found to be the best descriptor of the workers' predictions and the median model had the best fit. The mean model had a similar but significantly poorer fit (MAPE values of 29 and 31, respectively). The correspondence model had a poor fit with a MAPE of 54. The workers' predictions were generally lower than their average exposures. We conclude that the workers' interpretation model can be best described by a coherence model rather than by a correspondence model. [ABSTRACT FROM AUTHOR]