Simulating Urban Air Pollution In The Lab

近年来，越来越多的证据表明空气污染对健康的危害，这导致全球数百万人死亡，每年有数万人在英国死亡。这项研究旨在提高我们模拟城市空气污染和风模式的能力，为影响人们健康和福祉的政策提供信息。这些科学进步将通过应用先进的航空航天方法来实现，包括比例模型空气动力学测试，在现实生活中的建筑物中进行现场测量，以及将测量与计算流体动力学模型耦合的数据驱动方法。这些新的方法有望揭示从工业和城市来源的污染物的分散和运输的理解，并提高我们的能力，监测，建模和控制空气中的污染，在当地和城市规模的城市流动的关键。这些技术使我们能够填补我们的知识空白，了解当地流动模式对行人舒适度，建筑优化，空气质量和宏观天气预测的影响。比例模型空气动力学实验将侧重于使用最先进的光学诊断工具，以揭示风的模式，这是建筑物模型内部和周围的污染扩散机制。在该研究的第一部分，新的实验开发使用比例模型在循环水隧道与染料作为空气污染的代理。这些实验成功地复制了大气边界层条件，突出了高层建筑物在加强地面污染物垂直迁移出城市树冠层方面的重要性。在这一扩展中，粒子跟踪技术和透明城市模型将被用来揭示街道和城市峡谷内的流动特征的动态。实验室测量将通过对现实生活中的建筑物的现场测量来补充。这是通过使用南安普顿校园建筑的跨学科合作成为可能。这些测量将是验证模型的机会，并将纳入新的数据驱动方法，用于分析结果并将其转化为行业影响。数据驱动的方法旨在降低湍流模型的复杂性，填补缺失的信息，并揭示流动的物理特性。城市空气动力学提供了一个非常适合这种方法的新应用，因为关键的流动特征预计将由地形锚定，并且由于流动的速度和浓度特性需要在物理中捕获，因此是新颖的。通过与风力工程界的密切合作，将继续促进对行业的影响。将继续通过模拟南安普顿市空气污染的个案研究，支持对政策的影响，并为国家战略文件作出贡献。通过该奖学金进行的公众宣传也突出了空气动力学不仅与飞机和赛车汽车有关，而且各种各样的人都可以在这个领域工作，展示“城市空气动力学”作为一个新兴的研究领域。这个奖学金的扩展是一个机会，以这些基础为基础，扩大我们发现的新科学的跨学科适用性，并将结果转化为进一步的政策-相关和行业影响。

There has been increased evidence in recent years about the health risks of air pollution, which contribute to millions of deaths globally and tens of thousands of UK deaths annually. This research is about improving our ability to model urban air pollution and wind patterns to inform policy affecting people's health and wellbeing. These scientific advances will be achieved by applying advanced aerospace approaches including scale-model aerodynamic testing, in-situ measurements in real-life buildings, and data-driven methods coupling measurements to computational fluid dynamics models. These novel approaches promise to reveal understanding of the dispersion and transport of pollutants from industrial and urban sources and advance our ability to monitor, model, and control airborne pollution at the local and city scales critical for urban flows. These techniques allow us to fill a gap in our knowledge about the influence of local flow patterns to pedestrian comfort, building optimisation, air quality, and macroscale weather prediction. The scale-model aerodynamics experiments will focus on using state-of-the-art optical diagnostic tools to reveal the wind patterns that are the mechanisms of pollution dispersion in and around building models. In the first part of this fellowship, novel experiments were developed using scale models in a recirculating water tunnel with dye as a proxy for air pollution. These experiments successfully replicated atmospheric boundary layer conditions and highlighted the importance of tall buildings in enhancing vertical transport of ground-level pollution out of the urban canopy. In this extension, particle tracking techniques and transparent city models will be employed to reveal the dynamics of the flow features at street level and within urban canyons.The lab measurements will be supplemented by in-situ measurements of real-life buildings. This is made possible by an interdisciplinary collaboration using University of Southampton campus buildings. These measurements will be an opportunity to validate models and will feed into the new data-driven approaches that will be used to analyse the results and translate them into industry impact. Data-driven methods aim to reduce the complexity of the turbulent flow models, fill in missing information, and reveal physics of the flow. Urban aerodynamics provides a novel application well-suited to this approach as key flow features are expected to be anchored by the terrain and novel as both velocity and concentration properties of the flow need to be captured in the physics.Impact to industry will continue to be fostered by working closely with the wind engineering community. Impact to policy will continue to be supported through case studies simulating air pollution in the city of Southampton and contributing to national strategy documents. The public outreach made possible through this fellowship also highlights that aerodynamics is not only relevant to aeroplanes and race cars and that a diversity of people can work in this field, showcasing "urban aerodynamics" as an emerging field of research.This fellowship extension is an opportunity to build on these foundations to broaden the inter-disciplinary applicability of the new science we uncover and translate the results into further policy-relevant and industry-relevant impact.