预测由于有机溶剂泄漏造成的室内蒸汽浓度。

Charles B Keil, Mark Nicas
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引用次数: 0

摘要

相对较小的挥发性液体泄漏会导致短期的高浓度暴露。由于这些暴露的短暂性,可以排除空气采样。作为一种替代方法,暴露评估可以通过数学建模来完成。小泄漏的蒸汽释放率在泄漏后立即达到最高,并随着可用于传质的表面积的减少和蒸发冷却液体而降低。任何现有的蒸发速率模型都没有描述这种减少的排放速率。作者提出了一个蒸发速率模型,该模型将变化的排放量描述为指数递减。蒸发速率由蒸发速率参数alpha控制,其单位为min(-1),可根据实验测量估计。作者测量了一系列化合物和不同大小的泄漏物的alpha值。他们发现,对于只含有C、H和O的碳氢化合物,可以用公式来估计α: α =0.000524 VP + 0.0108 SA/Vol,其中VP是液体的蒸气压,SA/Vol是表面积与体积比。接下来,作者将指数下降的发射率与近场/远场色散结构结合到一个混合良好的房间中,以预测蒸汽浓度。在测试室内进行了初步实验,将测量的浓度与模型预测的浓度进行比较。基于ANSI室内空气模型评价标准,混合良好的房间模型表现良好。预测的近场浓度与基于ANSI标准的测量值的拟合程度较差,尽管总体上它们确实捕获了观察到的时间剖面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting room vapor concentrations due to spills of organic solvents.

Relatively small spills of volatile liquids can result in short-term, high-concentration exposures. Because of the transient nature of these exposures, air sampling may be precluded. As an alternative, exposure assessment can be done by mathematical modeling. The vapor emission rate from small spills is highest immediately following the spill and decreases as the surface area available for mass transfer decreases and evaporation cools the liquid. This decreasing emission rate is not described by any of the existing evaporation rate models. The authors present an evaporation rate model that describes the changing emissions as exponentially decreasing. The rate of decrease is governed by an evaporation rate parameter alpha, which has the unit of min(-1) and can be estimated based on experimental measurements. The authors measured alpha for a suite of compounds and different sizes of spill. They found that alpha can be estimated for hydrocarbons containing only C, H, and O with the equation: alpha=0.000524 VP + 0.0108 SA/Vol, where VP is the vapor pressure of the liquid and SA/Vol is the surface area to volume ratio. Next, the authors integrated the exponentially decreasing emission rate into a well-mixed room versus a near field/far field dispersion construct to predict vapor concentrations. A preliminary experiment was conducted in a test room to compare measured concentrations with the concentrations predicted by the models. The well-mixed room model performed well based on ANSI indoor air model evaluation criteria. The predicted near field concentrations showed a poor fit to the measured values based on the ANSI criteria, although overall they did capture the observed time profile.

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