论文标题
一个简单的模型，用于呼出的气溶胶液滴与空中颗粒物之间的碰撞结果：旨在了解空气污染对机源性病毒传播的影响
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
论文作者
论文摘要
与液滴相互作用的情况相比，缺少一个液滴和颗粒之间碰撞结果的模型。采用现有的模型，以成功预测液滴 - 滴滴碰撞的结果（结合，拉伸或反射性分离）和分离后特征（大小，数量和速度），并适应它们以考虑到不可延迟的，不可延迟的，不可接近的粒子，并带有新模型，以下是corriptical confiption corlict corl confiption coll confiction coll confictial coll confictial coll confictial corlictial confictial。新模型的预测与低粘度状态下液滴粒子碰撞的实验观察非常吻合。 然后将模型应用于由呼吸，语音，咳嗽和打喷嚏产生的呼吸道气溶胶与环境空气中的颗粒物（PM）之间的碰撞，以评估这些相互作用对包括COVID-19的气溶胶中包含的病原体的增强病原体传播的潜在贡献。结果表明，在逼真的条件下，气溶胶-PM碰撞可以丰富较小（更持续的）气溶胶馏分的病原体含量，并将病原体转移到可以深入呼吸道深处的PM颗粒表面。在更好地了解呼吸道气溶胶的大小和速度分布的背景下，该模型可用于预测高环境PM水平可能在多大程度上导致病原体（例如Covid-19）导致空中感染。
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.
