Evaluation of the well mixed room and near-field far-field models in occupational settings

Drawing appropriate conclusions about a scenario for which the exposure is truly unacceptable drives appropriate exposure and risk management, and protects the health and safety of those individuals. To ensure the vast majority of these decisions are accurate, these decisions must be based upon proven approaches and tools. When these decisions are based solely on professional judgment guided by subjective inputs, however, they are more than likely wrong, and biased, underestimating the true exposure. Models have been shown anecdotally to be useful in accurately predicting exposure but their use in occupational hygiene has been limited. Possible reasons are a general lack of guidance on model selection and use and scant model input data. The lack of systematic evaluation of the models is also an important factor. This research is the second phase of work building upon the robust evaluation of the Well Mixed Room (WMR) and Near Field Far Field (NF-FF) models under controlled conditions in an exposure chamber,^[5] in which good concordance between measured and modeled airborne concentrations of three solvents under a range of conditions was observed. In real world environments, the opportunity to control environmental conditions is limited and measuring the model inputs directly can be challenging; in many cases, model inputs must be estimated indirectly without measurement. These circumstances contribute to increased model input uncertainty and consequent uncertainty in the output. Field studies of model performance directly inform us about how well models predict exposures given these practical limitations, and are, therefore, an important component of model evaluation. The evaluation included ten diverse contaminant-exposure scenarios at five workplaces involving six different contaminants. A database of parameter values and measured and modeled exposures was developed and will be useful for modeling similar scenarios in the future.

针对暴露水平确实不可接受的场景得出恰当结论，有助于制定合理的暴露与风险管理策略，保护相关人员的健康与安全。为确保绝大多数此类决策的准确性，决策必须基于经过验证的方法与工具。然而，若决策仅依赖由主观输入引导的专业判断，则很可能出现错误且带有偏倚，低估真实的暴露水平。据零散经验显示，模型可用于准确预测暴露水平，但它们在职业卫生（occupational hygiene）领域的应用却十分有限。造成这一局限的可能原因包括：普遍缺乏关于模型选择与使用的指导，且模型输入数据十分匮乏。此外，缺乏对模型的系统性评估也是重要影响因素。本研究为第二阶段工作，基于此前在暴露舱（exposure chamber）受控条件下对充分混合室（Well Mixed Room, WMR）和近场远场（Near Field Far Field, NF-FF）模型开展的严谨评估展开，此前的研究中观察到，在多种条件下三种溶剂的实测空气浓度与模型预测浓度之间具有良好的一致性^[5]。在现实环境中，对环境条件的控制能力有限，直接测量模型输入参数也颇具挑战；在许多情况下，模型输入参数必须在无实测数据的情况下间接估算。此类情况会加剧模型输入的不确定性，进而导致输出结果的不确定性。针对模型性能开展现场研究，可直接反映模型在面临这些实际限制时的暴露预测效果，因此是模型评估的重要组成部分。本次评估涵盖了5家工作场所的10种不同污染物-暴露场景，涉及6种不同污染物。研究构建了一套包含参数值、实测暴露与模型预测暴露的数据库，该数据库将可为未来类似场景的建模工作提供助力。