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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]