Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom.
Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom; Institute for Sustainability, University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom; Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, the University of Dublin, Ireland..
Sci Total Environ. 2024 Mar 1;914:169713. doi: 10.1016/j.scitotenv.2023.169713. Epub 2023 Dec 30.
This study investigated influences of leaf traits on particulate matter (PM) wash-off and (re)capture (i.e., net removal) over time. Leaf samples were taken before and after three rainfall events from a range of 10 evergreen woody plants (including five different leaf types), which were positioned with an optical particle counter alongside a busy road. Scanning electron microscopy was used to quantify the density (no./mm), mass (μg/cm), and elemental composition of deposited particles. To enable leaf area comparison between scale-like leaves and other leaf types, a novel metric (FSA: foliage surface area per unit branch length) was developed, which may be utilised by future research. Vehicle-related particles constituted 15 % of total deposition, and there was a notable 50 % decrease in the proportion of tyre wear particles after rainfall. T. baccata presented the lowest proportion (11.1 %) of vehicle-related particle deposition but the most consistent performance in terms of net PM removal. Only four of the 10 plant specimens (C. japonica, C. lawsoniana, J. chinensis, and T. baccata) presented effective PM wash-off across all particle size fractions and rainfall intensities, with a generally positive relationship observed between rainfall intensity and wash-off. Mass deposition was more significantly determined by particle size than number density. Interestingly, larger particles were also less easily washed off than smaller particles. Some traits typically considered to be advantageous (e.g., greater hairiness) may in fact hinder net removal over time due to retention under rainfall. Small leaf area is one trait that may promote both accumulation and wash-off. However, FSA was found to be the most influential trait, with an inverse relationship between FSA and wash-off efficacy. This finding poses trade-offs and opportunities for green infrastructure design, which are discussed. Finally, numerous areas for future research are recommended, underlining the importance of systems approaches in developing vegetation management frameworks.
本研究调查了叶片性状随时间推移对颗粒物(PM)冲刷和(再)捕获(即净去除)的影响。从一系列 10 种常绿木本植物(包括五种不同的叶片类型)中采集了降雨前后的叶片样本,这些植物与一条繁忙的道路并排放置在光学粒子计数器旁。扫描电子显微镜用于量化沉积粒子的密度(个/mm)、质量(μg/cm)和元素组成。为了能够在鳞片状叶片和其他叶片类型之间进行叶片面积比较,开发了一种新的度量标准(FSA:单位枝长的叶面积),未来的研究可能会使用该度量标准。与车辆相关的颗粒占总沉积量的 15%,降雨后轮胎磨损颗粒的比例明显下降了 50%。T. baccata 叶片表现出最低的车辆相关颗粒沉积比例(11.1%),但在净 PM 去除方面表现最为稳定。在所有颗粒大小和降雨强度下,仅有 10 种植物标本中的 4 种(C. japonica、C. lawsoniana、J. chinensis 和 T. baccata)表现出有效的 PM 冲刷效果,降雨强度与冲刷效果之间呈正相关关系。质量沉积更多地受颗粒大小而不是颗粒数密度决定。有趣的是,较大的颗粒比较小的颗粒更不容易被冲刷掉。一些通常被认为是有利的特征(例如,更多的毛发)实际上可能会因为在降雨时被截留而阻碍净去除。小的叶面积是一个可能促进积累和冲刷的特征。然而,FSA 被发现是最具影响力的特征,FSA 与冲刷效果呈反比关系。这一发现为绿色基础设施设计带来了权衡和机遇,对此进行了讨论。最后,推荐了未来研究的众多领域,强调了系统方法在开发植被管理框架中的重要性。