Short-Duration Characterization of Source Emissions for Use in Predictive Software Models to Assess Worker Exposure: A Note of Caution

T. McManus, A. Haddad
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引用次数: 1

Abstract

This article reports on use of advanced Near-Field—Far-Field software for assessing short- versus long-duration data obtained minute-by-minute at two distances from a small source of an evaporating solvent located in an isolated subsurface structure (a type of confined space) accessed through a manhole containing one or two opening(s). The software uses this data to predict worker exposure to airborne chemical substances. Initial flash-off of volatile components was readily visible in graphs prepared from some tests and especially so in initial output from the calibration utility contained in the modelling software. The calibration utility orients the mathematics of the software to measured data. The calibration utility indicated constant magnitude from longer-duration emissions consistent with constant composition. Source characterization of emissions from solvents containing multiple ingredients and constant initial mass deserves careful consideration because initial emissions may not represent overall behavior. This situation indicates the potential to bias predictions of worker and other types of exposure utilizing the same mathematics. This is especially the case during source characterization using measurements of short duration. This study advocates for further investigation to develop guidelines for source characterization during use of modelling software that minimize the potential for error in exposure assessment.
用于评估工人暴露的预测软件模型的源排放的短时间特征:注意事项
本文报告了使用先进的近场-远场软件来评估在两个距离上从位于隔离地下结构(一种密闭空间)的蒸发溶剂的小源处每分钟获得的短期和长期数据,该蒸发溶剂通过包含一个或两个孔的沙井进入。该软件利用这些数据来预测工人接触空气中的化学物质。挥发性成分的初始闪光很容易在一些测试准备的图表中看到,特别是在建模软件中包含的校准实用程序的初始输出中。校准实用程序将软件的数学应用于测量数据。校准实用程序表明,与恒定成分一致的长时间排放的恒定量级。含有多种成分和恒定初始质量的溶剂的排放源表征值得仔细考虑,因为初始排放可能不能代表整体行为。这种情况表明,使用相同的数学方法对工人和其他类型的暴露进行预测可能存在偏差。在使用短时间测量的源表征期间尤其如此。本研究提倡进一步研究,以制定在使用建模软件期间的源表征指南,以最大限度地减少暴露评估中错误的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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