Optimising the performance of air cleaning technology for mitigation of infection in hospital environments

这次大流行提高了人们对许多建筑物通风不足的认识，包括卫生保健机构，在这些地方，通风不良可能会造成严重的感染风险。空气净化技术为改善室内空气提供了一种可行的方法，越来越多的证据表明，基于过滤器的设备可有效降低空气传播感染风险。然而，关于它们在防止表面污染、用于减少其他空气污染物、与室内空气流动的复杂相互作用以及设备智能操作方面的作用的数据有限。利兹大学和空气哨兵有限公司之间的合作将探索基于过滤器的空气净化新方法的设计和优化。该项目将采用实验和计算相结合的方法。利兹生物气溶胶室的受控实验将包括从空气和表面取样和培养微生物，以及在设置中使用不同的空气净化设备实时测量物理环境参数。也可以在包括医院病房在内的现实环境中进行实验测量。基于计算流体动力学（CFD）的建模方法将用于模拟空气净化装置与室内空气流动和污染源的相互作用。来自这两种方法的数据将用于评估性能特征、控制优化和瞬态情景下的有效性等方面。

The pandemic has raised awareness of the inadequacy of ventilation in many buildings including healthcare settings where there can be significant infection risks posed by poor ventilation. Air cleaning technologies offer a feasible approach for improving indoor air with increasing evidence that filter based units are effective to mitigate airborne infection risks. However, there is limited data around their role at preventing surface contamination, use for reducing other air pollutants, complex interactions with indoor air flows and smart operation of devices. This collaboration between the University of Leeds and Air Sentry Ltd will explore the design and optimisation of novel approaches to filter-based air cleaning. The project will use a combination of experimental and computational approaches. Controlled experiments in the Leeds bioaerosol chamber will involve sampling and culturing microorganisms from the air and on surfaces, as well as real-time measurement of physical environmental parameters with different air cleaning devices in the setting. Experimental measurements in real-world settings including hospital wards may also be carried out. Modelling approaches based on Computational Fluid Dynamics (CFD) will be used simulate the interaction of the air cleaning device with the airflows and pollutant sources in indoor spaces. Data from both approaches will be used assess aspects such as performance characteristics, optimisation of controls and the effectiveness under transient scenarios.