Improving desk-based methods for quantifying and enhancing air pollution mitigation by green infrastructure at different spatial scales

空气污染是对人类健康的最大环境危害，在污染物浓度升高和潜在患者聚集的城市地区尤其令人关切。众所周知，绿色基础设施（GI）是一种有效的碳封存方法，从而有助于解决错综复杂的气候变化问题。污染物也可以通过GI与周围大气之间的各种物理、生物和化学相互作用直接减轻。越来越多的证据支持使用地理指数作为城市空气污染的被动控制系统。有针对性地设计和管理地理标志可以最大限度地发挥其缓解空气污染的潜力。然而，GI与空气质量之间的关系是复杂的，关于特定城市环境下加强空气污染减排的植被物种选择的文献并不明确。在局部范围内，地理标志可以作为空气污染物和行人之间的屏障，也可以作为捕获或分散环境污染物的手段。有效的局部地理标志设计，包括适当的物种选择，需要对特定地点的物理和环境条件进行评估。然而，城市及以上规模的资源有效地理标志设计和实施需要有效的评估方法和广泛适用的原则。迄今为止的研究结果表明，迫切需要一个实用的框架，促进资源有效的GI管理，以改善城市空气质量。该博士项目的创始目标是建立在该学生硕士项目的成果基础上，该项目发现，在利用现有地理特征对空气污染缓解进行的高分辨率实地评估与利用遥感的低分辨率桌面方法之间可能存在妥协。我们打算扩展这种新颖的、基于桌面的方法，以包含根据上下文特定输入标准生成的设计建议。这个博士项目的目的是开发一个地理标志设计框架，以加强城市空气污染的缓解，这将涉及一种新的方法，用于产生特定地点的建议，结合现场实验、遥感和公民科学工作的结果。

Air pollution is the greatest environmental hazard to human health, and of particular concern in urban areas, where elevated pollutant concentrations and potential sufferers converge. Green infrastructure (GI) is known to be an effective method of carbon sequestration, thereby helping to tackle the intertwined issue of climate change. Pollutants may also be directly mitigated through various physical, biological and chemical interactions between GI and the surrounding atmosphere. A mounting body of evidence supports the use of GI as a passive control system for urban air pollution. Targeted design and management of GI can maximise its air pollution mitigation potential. However, the relationship between GI and air quality is complex, and the literature regarding vegetation species selection for enhanced air pollution abatement under specific urban contexts is not clear-cut. At local scale, GI can act as a barrier between air pollutants and pedestrians as well as a means to capture or disperse ambient pollutants. Efficient GI design at local scale, including appropriate species selection, requires an appreciation of site-specific physical and environmental conditions. Resource-effective GI design and implementation at city scale and above, however, requires efficient assessment methodologies and broadly applicable principles. Research findings to date illustrate that there is an urgent need for a pragmatic framework that facilitates resource-effective GI management for improved urban air quality. The founding objective of this PhD project is to build upon results from the student's Masters project, in which it was found that a compromise may exist between high-resolution, on-the-ground assessments of air pollution mitigation by existing GI and lower-resolution, desk-based methodologies that utilise remote sensing. We intend to extend this novel, desk-based approach to include design recommendations that are generated according to context-specific input criteria. The aim of this PhD project is to develop a GI design framework for enhanced urban air pollution mitigation, which will involve a novel methodology for the generation of site-specific recommendations, incorporating results from field experimentation, remote sensing, and citizen science work.