Demou Evangelia, Hellweg Stefanie, Wilson Michael P, Hammond S Katharine, Mckone Thomas E
Institute of Environmental Engineering, ETH Zurich, CH-8093 Zürich, Switzerland.
Environ Sci Technol. 2009 Aug 1;43(15):5804-10. doi: 10.1021/es803551y.
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) multizone 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. Multizone 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.
我们使用从汽车维修行业中使用“气雾剂”溶剂产品的工人的测量数据,以及使用这些产品进行现场实验以模拟相同暴露条件的数据,对三种暴露模型进行了评估。这三种暴露模型分别是:(1)均匀混合单箱模型,(2)多区域模型,以及(3)涡扩散模型。在估计排放率、扩散率和近场尺寸等参数时,使用了随时间变化的实时呼吸区挥发性有机化合物(VOC)浓度测量、远场区域综合样本以及模拟实验。我们评估了模型输入要求的差异及其在预测建模中的有效性。单箱模型无法模拟暴露浓度的时间分布,但在长时间的时间加权暴露方面表现良好。然而,该模型需要针对空间浓度梯度进行调整。多区域模型和扩散模型可能解决这个问题。然而,我们发现可靠地使用这两种模型都需要大量的现场数据,以适当地定义扩散率或近场尺寸等关键参数。我们得出结论,将这些模型应用于预测工作场所的VOC暴露是困难的。然而,对于生命周期评估中的比较暴露情景,它们可能是有用的。