呼出气溶胶液滴和空气中颗粒物之间碰撞结果的简单模式：了解空气污染对空气中病毒传播的影响
A simple model for the outcomes of collisions between exhaled aerosol droplets and airborne particulate matter: Towards an understanding of the influence of air pollution on airborne viral transmission
摘要：
与液滴-液滴相互作用的情况相反，缺乏根据碰撞后液滴体积的分布来预测液滴和颗粒之间的碰撞结果的模型。以现有的模型，成功地预测的结果（聚结，拉伸或反射分离）和分离后的特性（尺寸，数量和速度的液滴液滴碰撞和调整它们，以考虑到不可扩展的，不可变形的颗粒与不同的润湿性特性，提出了一个新的模型液滴颗粒碰撞。新模型的预测与实验观察的液滴-颗粒碰撞在低粘度制度。然后将该模型应用于呼吸、言语、咳嗽和打喷嚏产生的呼吸气溶胶与环境空气中颗粒物（PM）之间的碰撞，以评估这些相互作用对气溶胶中所含病原体（包括COVID-19）传播增强的潜在贡献。结果表明，在现实条件下，气溶胶-PM碰撞有可能使较小（因此更持久）气溶胶组分的病原体含量富集，并将病原体转移到可以深入呼吸道的PM颗粒表面。在更好地了解呼吸气溶胶的尺寸和速度分布的背景下，该模型可用于预测高环境PM水平可能导致病原体（如COVID-19）空气传播感染的程度。
英文摘要：
A model that predicts the outcome of collisions between droplets and particles in terms of the distribution of the droplet volume post-collision is lacking, in contrast to the case for droplet-droplet interactions. Taking existing models that successfully predict the outcomes (coalescence, stretching or reflexive separation) and post-separation characteristics (sizes, numbers and velocities of the resulting droplets) of droplet-droplet collisions and adapting them to take into account an inextensible, non-deformable particle with varying wettability characteristics, a new model is presented for droplet-particle collisions. The predictions of the new model agree well with experimental observations of droplet-particle collisions in low-viscosity regimes. The model is then applied to the case of collisions between respiratory aerosols generated by breath, speech, cough and sneeze and ambient airborne particulate material (PM) in order to assess the potential contribution of these interactions to the enhanced transmission of pathogens contained in the aerosol, including COVID-19. The results show that under realistic conditions it is possible for aerosol-PM collisions to enrich the pathogen content of smaller (and so more persistent) aerosol fractions, and to transfer pathogens to the surface of PM particles that can travel deep into the respiratory tract. In the context of better knowledge of the size and velocity distributions of respiratory aerosols, this model may be used to predict the extent to which high ambient PM levels may contribute to airborne infection by pathogens such as COVID-19.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
