Department of Occupational Health, Faculty of health, Shahid Sadoughi University of Medical Sciences, Iran.
Ind Health. 2013;51(5):545-51. doi: 10.2486/indhealth.2012-0130. Epub 2013 Aug 2.
Applicability of two mathematical models in inhalation exposure prediction (well mixed room and near field-far field model) were validated against standard sampling method in one operation room for isoflurane. Ninety six air samples were collected from near and far field of the room and quantified by gas chromatography-flame ionization detector. Isoflurane concentration was also predicted by the models. Monte Carlo simulation was used to incorporate the role of parameters variability. The models relatively gave more conservative results than the measurements. There was no significant difference between the models and direct measurements results. There was no difference between the concentration prediction of well mixed room model and near field far field model. It suggests that the dispersion regime in room was close to well mixed situation. Direct sampling showed that the exposure in the same room for same type of operation could be up to 17 times variable which can be incorporated by Monte Carlo simulation. Mathematical models are valuable option for prediction of exposure in operation rooms. Our results also suggest that incorporating the role of parameters variability by conducting Monte Carlo simulation can enhance the strength of prediction in occupational hygiene decision making.
两种数学模型（全混流室模型和近场-远场模型）在异氟烷吸入暴露预测中的适用性，通过标准采样方法在一个手术室中进行了验证。从房间的近场和远场采集了 96 个空气样本，并通过气相色谱-火焰离子化检测器进行定量。模型还预测了异氟烷浓度。蒙特卡罗模拟用于纳入参数变异性的作用。模型给出的结果相对比测量结果更保守。模型与直接测量结果之间没有显著差异。全混流室模型和近场-远场模型的浓度预测结果没有差异。这表明房间内的扩散状态接近全混流情况。直接采样表明，对于相同类型的手术，同一房间内的暴露量可能高达 17 倍，可以通过蒙特卡罗模拟进行合并。数学模型是预测手术室暴露的有价值的选择。我们的结果还表明，通过进行蒙特卡罗模拟纳入参数变异性的作用，可以增强职业卫生决策中预测的强度。
