We evaluated three exposure models with data obtained from measurements among workers who use"aerosol" solvent products in the vehicle repair industry and with field experiments using these products to simulate the same exposure conditions. The three exposure models were the: 1) homogeneously-mixed-one-box model, 2) multi-zone model, and 3) eddy-diffusion model. Temporally differentiated real-time breathing zone volatile organic compound (VOC) concentration measurements, integrated far-field area samples, and simulated experiments were used in estimating parameters, such as emission rates, diffusivity, and near-field dimensions. We assessed differences in model input requirements and their efficacy for predictive modeling. The One-box model was not able ...
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Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (United States)
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We evaluated three exposure models with data obtained from measurements among workers who use"aerosol" solvent products in the vehicle repair industry and with field experiments using these products to simulate the same exposure conditions. The three exposure models were the: 1) homogeneously-mixed-one-box model, 2) multi-zone model, and 3) eddy-diffusion model. Temporally differentiated real-time breathing zone volatile organic compound (VOC) concentration measurements, integrated far-field area samples, and simulated experiments were used in estimating parameters, such as emission rates, diffusivity, and near-field dimensions. We assessed differences in model input requirements and their efficacy for predictive modeling. The One-box model was not able to resemble the temporal profile of exposure concentrations, but it performed well concerning time-weighted exposure over extended time periods. However, this model required an adjustment for spatial concentration gradients. Multi-zone models and diffusion-models may solve this problem. However, we found that the reliable use of both these models requires extensive field data to appropriately define pivotal parameters such as diffusivity or near-field dimensions. We conclude that it is difficult to apply these models for predicting VOC exposures in the workplace. However, for comparative exposure scenarios in life-cycle assessment they may be useful.
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Demou, Evangelia; Hellweg, Stefanie; Wilson, Michael P.; Hammond, S. Katharine & McKone, Thomas E.Evaluating indoor exposure modeling alternatives for LCA: A case study in the vehicle repair industry,
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May 1, 2009;
Berkeley, California.
(digital.library.unt.edu/ark:/67531/metadc926735/:
accessed April 24, 2018),
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