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Airborne exposure patterns from a passenger source in aircraft cabins

机译:机舱内客源的空中暴露方式

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摘要

Airflow is a critical factor that influences air quality, airborne contaminant distribution, and disease transmission in commercial airliner cabins. The general aircraft-cabin air-contaminant transport effect model seeks to build exposure-spatial relationships between contaminant sources and receptors, quantify the uncertainty, and provide a platform for incorporation of data from a variety of studies. Knowledge of infection risk to flight crews and passengers is needed to form a coherent response to an unfolding epidemic, and infection risk may have an airborne pathogen exposure component. The general aircraf-tcabin air-contaminant transport effect model was applied to datasets from the University of Illinois and Kansas State University and also to case study information from a flight with probable severe acute respiratory syndrome transmission. Data were fit to regression curves, where the dependent variable was contaminant concentration (normalized for source strength and ventilation rate), and the independent variable was distance between source and measurement locations. The data-driven model showed exposure to viable small droplets and post-evaporation nuclei at a source distance of several rows in a mock-up of a twin-aisle airliner with seven seats per row. Similar behavior was observed in tracer gas, particle experiments, and flight infection data for severe acute respiratory syndrome. The study supports the airborne pathway as part of the matrix of possible disease transmission modes in aircraft cabins.
机译:气流是影响空气质量,空气中污染物分布和商业客机舱内疾病传播的关键因素。通用的飞机客舱空气污染物运输效应模型旨在建立污染物源与受体之间的暴露空间关系,量化不确定性,并提供一个整合各种研究数据的平台。需要对飞行机组人员和乘客有感染风险的知识,以形成对不断发展的流行病的一致反应,并且感染风险可能具有空气传播的病原体暴露成分。通用的航空客舱空气污染物运输效应模型已应用于伊利诺伊大学和堪萨斯州立大学的数据集,并且还用于案例研究中可能传播严重急性呼吸系统综合症的信息。数据拟合回归曲线,其中因变量是污染物浓度(针对源强度和通风速率进行了标准化),而自变量是源与测量位置之间的距离。数据驱动的模型显示,在双排客机(每排有七个座位)的模型中,在几行源距处暴露于可行的小液滴和蒸发后核。在示踪气体,颗粒实验和飞行感染数据中,对于严重的急性呼吸综合症也观察到了类似的行为。该研究支持机载通道作为机舱内可能的疾病传播模式矩阵的一部分。

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