A large study of combustion particle exposures for drivers of diesel-powered trucks was conducted in collaboration with an epidemiologic study of lung cancer outcomes for workers in the trucking industry. Three components of diesel exhaust combustion particles (PM(2.5), elemental carbon, and organic carbon) were measured inside the driver cabs of diesel-powered trucks from 36 different trucking terminals across the United States between 2001 and 2005. In-cab particle exposures for drivers assigned to both short and long distance trips were observed, as well as information on the smoking status of the driver, truck characteristics such as age and model, and weather conditions during the sampling session. This article summarizes these findings and describes the relationship between exhaust particles and various determinants of exposure. The results suggest that in-cab particle exposures are positively related to smoking, ambient particle concentrations, truck age, and open windows, with other significant modifying factors such as weather. This study represents the largest and most comprehensive exposure assessment of drivers in the trucking industry, encompassing a 4-year period of observations on diesel and exhaust particle exposures nationwide. The results are relevant not only to the occupational group of truck drivers being examined but also to the general population that live, commute, or work within proximity to diesel-fueled traffic or trucking terminals.
Diesel exhaust is a complex chemical mixture that has been linked to lung cancer mortality in a number of epidemiologic studies. However, the dose-response relationship remains largely undefined, and the specific components responsible for carcinogenicity have not been identified. Although previous focus has been on the particulate phase, diesel exhaust includes a vapor phase of numerous volatile organic compounds (VOCs) and aldehydes that are either known or suspected carcinogens, such as 1,3-butadiene, benzene, and formaldehyde. However, there are relatively few studies that quantify exposure to VOCs and aldehydes in diesel-heavy and other exhaust-related microenvironments. As part of a nationwide assessment of exposure to diesel exhaust in the trucking industry, we collected measurements of VOCs and aldehydes at 15 different U.S. trucking terminals and in city truck drivers (with 6 repeat site visits), observing average shift concentrations in truck cabs and at multiple background and work area locations within each terminal. In this paper, we characterize occupational exposure to 18 different VOCs and aldehydes, as well as relationships with particulate mass (elemental carbon in PM < 1 μ m and PM 2.5 ) across locations to determine source characteristics. Our results show that occupational exposure to VOCs and aldehydes varies significantly across the different sampling locations within each terminal, with significantly higher exposures noted in the work environments over background levels (p < 0.01). A structural equation model performed well in predicting terminal exposures to VOCs and aldehydes as a function of job, background levels, weather conditions, proximity to a major road, and geographic location (R 2 = 0.2-0.4 work area; R 2 = 0.5-0.9 background).
Personal exposure to particle-phase molecular markers was measured at a trucking terminal in St Louis, MO, as part of a larger epidemiologic project aimed at assessing carbonaceous fine particulate matter (PM) exposure in this occupational setting. The integration of parallel personal exposure, ambient worksite area and ambient urban background (St Louis Supersite) measurements provided a unique opportunity to track the work-related exposure to carbonaceous fine PM in a freight terminal. The data were used to test the proposed personal exposure model in this occupational setting:Personal exposure ¼ urban background þ work site background þ personal activityTo accurately assess the impact of PM emission sources, particularly motor vehicle exhaust, and organic elemental carbon (OCEC) analysis and nonpolar organic molecular marker analysis by thermal desorption-gas chromatography/mass spectrometry (TD-GCMS) were conducted on all of the PM samples. EC has been used as a tracer for diesel exhaust in urban areas, however, the emission profile for diesel exhaust is dependent upon the operating conditions of the vehicle and can vary considerably within a fleet. Hopanes, steranes, polycyclic aromatic hydrocarbons and alkanes were measured by TD-GCMS. Hopanes are source-specific organic molecular markers for lubricating oil present in motor vehicle exhaust. The concentrations of OC, EC and the organic tracers were averaged to obtain average profiles to assess differences in the personal, worksite area and urban background samples, and were also correlated individually by sample time to evaluate the exposure model presented above. Finally, a chemical mass balance model was used to apportion the motor vehicle and cigarette-smoke components of the measured OC and EC for the average personal exposure, worksite area and urban background samples.
This study analyzes the temporal variability of occupational and environmental exposures to fine particulate matter in the U.S. trucking industry and tests the predictive ability of a novel multilayer statistical approach to occupational exposure modeling using structural equation modeling (SEM) techniques. For these purposes, elemental carbon mass in PM<1 µm at six U.S. trucking terminals were measured twice during the same season up to 2 years apart, observing concentrations in the indoor loading dock (median EC: period 1 = 0.65 µg/m 3 ; period 2 = 0.94 µg/m 3 ) and outdoor background location (median EC: period 1 = 0.46 µg/m 3 ; period 2 = 0.67 µg/m 3 ), as well as in the truck cabs of local drivers while on the road (median EC: period 1=1.09 µg/m 3 ; period 2 = 1.07 µg/ m 3 ). There was a general trend toward higher exposures during the second sampling trips; however, these differences were statistically significant in only a few cases and were largely attributable to changes in weather patterns (wind speed, precipitation, etc.). Once accounting for systematic prediction errors in background concentrations, the SEM approach provided a strong fit for workrelated exposures in this occupational setting.
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