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Introduction Increased rates of leukaemia have been found among tanker crews. Occupational exposures to the leukomogen benzene during loading, unloading, and tank cleaning are possible causes. Studies on older types of tankers carrying gasoline with most handling being done manually have revealed important exposures to benzene. Our study explores benzene exposures on tankers with both automatic and manual systems. Correlations between benzene exposure and benzene in alveolar air (AlvBe), benzene in urine (UBe), and trans , trans -muconic acid (ttMA) in urine were investigated. Methods Forty-three male seafarers (22 deck crewmembers and 21 not on deck) on five Swedish different product and chemical tankers transporting 95- or 98-octane gasoline were investigated between 1995 and 1998. The tankers used closed systems for the loading and unloading of gasoline but stripping and tank cleaning were done manually. Benzene in respiratory air was measured using personal passive dosimeters during a 4-h work shift. Samples for biomarker analyses were collected pre- and post-shift. Smoking did occur and crewmembers did not use any respiratory protection during work. Results The average 4-h benzene exposure level for exposed was 0.45 mg m−3 and for non-exposed 0.02 mg m−3. Benzene exposure varied with type of work (range 0.02–143 mg m−3). AlvBe, UBe, and ttMA were significantly higher in post-shift samples among exposed and correlated with exposure level (r = 0.89, 0.74, and 0.57, respectively). Smoking did not change the level of significance among exposed. Discussion Benzene in alveolar air, unmetabolized benzene, and ttMA in urine are potential biomarkers for occupational benzene exposure. Biomarkers were detectable in non-exposed, suggesting benzene exposure even for other work categories on board tankers. Work on tankers carrying gasoline with more or less closed handling of the cargo may still lead to significant benzene exposure for deck crewmembers, and even exceed the Swedish Occupational Exposure Limit (OEL; 8-h time-weighted average [TWA]) of 1.5 mg m−3. [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]

Objectives: Although corticosteroids have been used for over 50 years as anti-inflammatory and anti-proliferative agents, few studies have examined their exposure levels and health effects on workers employed in the corticosteroid manufacturing industry. The aims of the study reported here were to develop a tape-stripping technique for monitoring budesonide (a corticosteroid used in inhalators for treating respiratory diseases) and to apply the method in a pilot study to estimate the potential dermal exposure to budesonide among workers at a pharmaceutical formulation site. [ABSTRACT FROM PUBLISHER]

When assessing occupational exposures, repeated measurements are in most cases required. Repeated measurements are more resource intensive than a single measurement, so careful planning of the measurement strategy is necessary to assure that resources are spent wisely. The optimal strategy depends on the objectives of the measurements. Here, two different models of random effects analysis of variance (ANOVA) are proposed for the optimization of measurement strategies by the minimization of the variance of the estimated log-transformed arithmetic mean value of a worker group, i.e. the strategies are optimized for precise estimation of that value. The first model is a one-way random effects ANOVA model. For that model it is shown that the best precision in the estimated mean value is always obtained by including as many workers as possible in the sample while restricting the number of replicates to two or at most three regardless of the size of the variance components. The second model introduces the ‘shared temporal variation’ which accounts for those random temporal fluctuations of the exposure that the workers have in common. It is shown for that model that the optimal sample allocation depends on the relative sizes of the between-worker component and the shared temporal component, so that if the between-worker component is larger than the shared temporal component more workers should be included in the sample and vice versa. The results are illustrated graphically with an example from the reinforced plastics industry. If there exists a shared temporal variation at a workplace, that variability needs to be accounted for in the sampling design and the more complex model is recommended. [ABSTRACT FROM AUTHOR]

A self-operated personal sampling technique called ‘self assessment of exposure’ (SAE) has been suggested as an easy method for collecting inhalation exposure data, as the workers themselves are performing the sampling. Employers and employees have raised the question of whether a different estimate of the air concentration is likely to be obtained depending on whether the sampler is fastened at the left or the right shoulder. In order to answer this question, the exposure to styrene vapour in two different small enterprises within the reinforced plastics industry was measured. Seven workers participated and the air sampling was performed by diffusive sampling. We observed no statistically significant difference in the determined air concentration of styrene between the left and right shoulder (P = 0.878). The results strongly indicate that the fastening of a sampler on the left or right shoulder does not produce a difference in the estimation of the inhalation exposure. SAE can thus be used to collect reliable exposure data of styrene vapour. The reliability of SAE will most certainly inspire occupational hygienists, physicians and other experts to involve the workers in repeated exposure measurements. Taking the exposure variability into account, repeated measurements are crucial when evaluating acute and chronic health effects following inhalation exposure to gases and vapours from chemical hazards. [ABSTRACT FROM AUTHOR]