Johnston Karen L, Phillips Margaret L, Esmen Nurtan A, Hall Thomas A
Department of Occupational and Environmental Health, College of Public Health, University of Oklahoma Health Sciences Center, 801 N.E. 13th Street, Oklahoma City, OK 73104, USA.
Ann Occup Hyg. 2005 Mar;49(2):147-53. doi: 10.1093/annhyg/meh072.
Estimation and Assessment of Substance Exposure (EASE) is an artificial intelligence program developed by UK's Health and Safety Executive to assess exposure. EASE computes estimated airborne concentrations based on a substance's vapor pressure and the types of controls in the work area. Though EASE is intended only to make broad predictions of exposure from occupational environments, some occupational hygienists might attempt to use EASE for individual exposure characterizations. This study investigated whether EASE would accurately predict actual sampling results from a chemical manufacturing process. Personal breathing zone time-weighted average (TWA) monitoring data for two volatile organic chemicals--a common solvent (toluene) and a specialty monomer (chloroprene)--present in this manufacturing process were compared to EASE-generated estimates. EASE-estimated concentrations for specific tasks were weighted by task durations reported in the monitoring record to yield TWA estimates from EASE that could be directly compared to the measured TWA data. Two hundred and six chloroprene and toluene full-shift personal samples were selected from eight areas of this manufacturing process. The Spearman correlation between EASE TWA estimates and measured TWA values was 0.55 for chloroprene and 0.44 for toluene, indicating moderate predictive values for both compounds. For toluene, the interquartile range of EASE estimates at least partially overlapped the interquartile range of the measured data distributions in all process areas. The interquartile range of EASE estimates for chloroprene fell above the interquartile range of the measured data distributions in one process area, partially overlapped the third quartile of the measured data in five process areas and fell within the interquartile range in two process areas. EASE is not a substitute for actual exposure monitoring. However, EASE can be used in conditions that cannot otherwise be sampled and in preliminary exposure assessment if it is recognized that the actual interquartile range could be much wider and/or offset by a factor of 10 or more.
物质暴露估计与评估(EASE)是英国健康与安全执行局开发的一个用于评估暴露情况的人工智能程序。EASE根据一种物质的蒸气压以及工作区域内的控制类型来计算估计的空气传播浓度。尽管EASE仅旨在对职业环境中的暴露情况进行大致预测,但一些职业卫生学家可能会尝试使用EASE来进行个体暴露特征描述。本研究调查了EASE是否能准确预测化学制造过程中的实际采样结果。将该制造过程中存在的两种挥发性有机化合物——一种常用溶剂(甲苯)和一种特种单体(氯丁二烯)的个人呼吸带时间加权平均(TWA)监测数据与EASE生成的估计值进行了比较。针对特定任务的EASE估计浓度通过监测记录中报告的任务持续时间进行加权,以得出EASE的TWA估计值,从而可以直接与实测的TWA数据进行比较。从该制造过程的八个区域中选取了206个氯丁二烯和甲苯的全时段个人样本。EASE的TWA估计值与实测TWA值之间的斯皮尔曼相关性,氯丁二烯为0.55,甲苯为0.44,表明这两种化合物的预测值中等。对于甲苯,在所有工艺区域中,EASE估计值的四分位间距至少部分与实测数据分布的四分位间距重叠。氯丁二烯的EASE估计值的四分位间距在一个工艺区域高于实测数据分布的四分位间距,在五个工艺区域部分与实测数据的第三四分位数重叠,在两个工艺区域内落在四分位间距范围内。EASE不能替代实际的暴露监测。然而,如果认识到实际的四分位间距可能会宽得多和/或偏移10倍或更多倍,那么EASE可用于无法进行其他采样的情况以及初步暴露评估。