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

改进基于案头的方法，以量化和加强绿色基础设施在不同空间尺度上的空气污染缓解

基本信息

批准号：
2124242
负责人：
金额：
--
依托单位：
University of Surrey
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2124242
关键词：
Improving desk based methods quantifying

项目摘要

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.

空气污染是对人类健康的最大环境危害，在城市地区尤其令人关切，因为城市地区污染物浓度高，潜在的受害者集中。众所周知，绿色基础设施是一种有效的固碳方法，有助于解决相互交织的气候变化问题。污染物也可以通过GI和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GI作为城市空气污染的被动控制系统。有针对性的设计和管理GI可以最大限度地发挥其缓解空气污染的潜力。然而，GI和空气质量之间的关系是复杂的，在特定的城市环境下，加强空气污染减排的植被物种选择的文献是不明确的。在局部范围内，GI可以作为空气污染物和行人之间的屏障，以及捕获或分散环境污染物的手段。在当地范围内进行有效的地理标志设计，包括适当的物种选择，需要了解特定地点的物理和环境条件。然而，在城市规模及以上的资源有效的地理信息系统的设计和实施，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，迫切需要一个务实的框架，促进资源有效的地理标志管理，以改善城市空气质量。这个博士项目的创始目标是建立在学生的硕士项目的结果，其中发现，高分辨率，在现有的GI和低分辨率，基于桌面的方法，利用遥感的空气污染缓解的地面评估之间可能存在妥协。我们打算扩展这种新颖的，基于桌面的方法，包括根据上下文特定的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GI设计框架，以增强城市空气污染缓解，这将涉及一种新的方法，用于生成特定地点的建议，结合实地实验，遥感和公民科学工作的结果。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Green infrastructure for air quality improvement in street canyons.

DOI：
10.1016/j.envint.2020.106288
发表时间：
2021-01
期刊：
Environment international
影响因子：
11.8
作者：
Mamatha Tomson;Prashant Kumar;Y. Barwise;P. Perez;H. Forehead;K. French;L. Morawska;J. Watts
通讯作者：
Mamatha Tomson;Prashant Kumar;Y. Barwise;P. Perez;H. Forehead;K. French;L. Morawska;J. Watts

Mitigating Exposure to Traffic Pollution In and Around Schools: Guidance for Children, Schools and Local Communities.

减轻学校内外的交通污染：儿童、学校和当地社区指南。