湍流脉动下人际间吸入暴露特征及影响机制
Characteristics and influencing mechanisms of interpersonal inhalation exposure under turbulent fluctuations
摘要:
本研究采用大涡模拟方法,聚焦于高频次的呼吸活动,通过解析湍流脉动作用下的传染性呼吸道颗粒(IRPs)输运轨迹及易感者的吸入暴露结果,系统探讨了瞬时的吸入暴露特征及影响机制。结果表明:近距离(0.5 m)下,易感者的瞬时吸入暴露呈现间断性和波动性特征,超过30%的吸气阶段内未发生吸入,暴露过程中占比不足10%的异常暴露值对累积暴露风险的贡献率可高达55.88%;湍流脉动影响下的呼出气流内部涡结构差异是引起瞬时暴露波动的关键因素;近距离暴露事件中存在IRPs集中到达易感者呼吸区的时段,其与吸气阶段的耦合程度越高,暴露波动性越强;忽视瞬时暴露波动的影响可能导致现有防控措施在峰值驱动的传播事件中失效,未来应进一步建立基于病毒特性的分类防控体系。
Abstract:
This study adopts the large eddy simulation (LES) method, focusing on high-frequency respiratory activities, to systematically investigate transient inhalation exposure characteristics and influencing mechanisms by resolving infectious respiratory particles (IRPs) transport trajectories under turbulent fluctuations and susceptible individuals’ inhalation exposure outcomes. The results show that at close distances (0.5 m), susceptible individuals’ transient inhalation exposure exhibits intermittent and fluctuating characteristics, with over 30% of inhalation phases showing no inhalation occurrence, where abnormal exposure values accounting for less than 10% of the exposure process contribute up to 55.88% to cumulative exposure risk. The differences in vortex structures within exhaled airflow under turbulent fluctuations are the key factor causing transient exposure fluctuations. During close-range exposure events, there exist periods when IRPs concentrate in the susceptible individuals’ breathing zones, with higher coupling degree between these periods and inhalation phases leading to stronger exposure fluctuations. Ignoring the impact of transient exposure fluctuations may render existing prevention and control measures ineffective during peak-driven transmission events. In the future, a classified prevention and control system grounded in viral characteristics should be further established.
Keywords:infectious respiratory particle; transient inhalation exposure; turbulent fluctuation; large eddy simulation; respiratory activity; virus prevention and control


