| Summary: | 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 microm 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 microg/m(3); period 2 = 0.94 microg/m(3)) and outdoor background location (median EC: period 1 = 0.46 microg/m(3); period 2 = 0.67 microg/m(3)), as well as in the truck cabs of local drivers while on the road (median EC: period 1 = 1.09 microg/m(3); period 2 = 1.07 microg/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 work-related exposures in this occupational setting.
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