Evaluation of the uncertainties associated with the use of air dispersion modeling to estimate historical community exposure from manufacturers of asbestos-containing products

摘要

Manufacturing of asbestos-containing products can result in the environmental release of asbestos into the surrounding community. Unlike exposures to asbestos during the manufacture or use of asbestos-containing products, community exposure has not been as well-characterized. Asbestos emissions to a community cannot be generalized across all types of manufacturing facilities. In this analysis, a methodology using air dispersion modeling to estimate potential community exposure to asbestos from a hypothetical manufacturer of asbestos-containing friction products from 1965 to 1989 is presented. The USEPA preferred air dispersion model, AERMOD, was used to predict the annual airborne concentrations of asbestos up to 2000 meters from the facility. Continuous emission sources included 1) unloading of asbestos from a box truck, 2) fugitive building emissions prior to 1975, 3) controlled baghouse emissions after 1975, and 4) disposal of scrap asbestos. Prior to the introduction of a baghouse in 1975, asbestos emissions for the hypothetical facility were primarily attributed to the fugitive building emissions. Thereafter, there was a substantial decrease in overall asbestos emissions, with unloading emissions as the greatest contributor. As expected, predicted airborne concentrations of asbestos were greatest closest to the manufacturing facility and decreased by approximately four-fold after the installation of the baghouse in 1975. The uncertainties and sensitivity associated with this methodology were evaluated through the use of different emission methods for unloading asbestos, different particle size assumptions, changes to pollution control technology over time, and varying emission assumptions. This methodology may be applied to similar exposure scenarios to reconstruct historical community exposure to asbestos with manufacturer-specific data and records.