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在意大利城市工业环境中,12 种树种的空气颗粒物捕获效率与叶片特性之间的关系。

Relationships between air particulate matter capture efficiency and leaf traits in twelve tree species from an Italian urban-industrial environment.

机构信息

Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Via Marconi 2, 05010 Porano, TR, Italy.

Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Via Marconi 2, 05010 Porano, TR, Italy; Biophysics and Nanoscience Centre, Department of Ecological and Biological Sciences (DEB), University of Tuscia, Largo dell'Università snc, 01100 Viterbo, Italy.

出版信息

Sci Total Environ. 2020 May 20;718:137310. doi: 10.1016/j.scitotenv.2020.137310. Epub 2020 Feb 14.

Abstract

Air pollution in the urban environment is widely recognized as one of the most harmful threats for human health. International organizations such as the United Nations and the European Commission are highlighting the potential role of nature in mitigating air pollution and are now funding the implementation of Nature-Based Solutions, especially at the city level. Over the past few decades, the attention of the scientific community has grown around the role of urban forest in air pollution mitigation. Nevertheless, the understanding on Particulate Matter (PM) retention mechanisms by tree leaves is still limited. In this study, twelve tree species were sampled within an urban park of an industrial city. Two techniques were used for leaf analysis: Vacuum/Filtration and Scanning Electron Microscopy coupled with Energy Dispersive X-ray spectroscopy, in order to obtain a quali-quantitative analysis of the different PM size fractions. Results showed that deposited PM loads vary significantly among species. Different leaf traits, including micro and macromorphological characteristics, were observed, measured and ranked, with the final aim to relate them with PM load. Even if no significant correlation between each single leaf characteristic and PM deposition was observed (p > 0.05), multivariate analysis revealed relationships between clusters of leaf traits and deposited PM. Thus, by assigning a score to each trait, an Accumulation index (Ai) was calculated, which was significantly related to the leaf deposited PM load (p ≤ 0.05).

摘要

城市环境中的空气污染被广泛认为是对人类健康最有害的威胁之一。联合国和欧盟委员会等国际组织强调了自然在减轻空气污染方面的潜在作用,现在正在为自然解决方案的实施提供资金,特别是在城市层面。在过去几十年中,科学界对城市森林在减轻空气污染方面的作用的关注不断增加。然而,树叶对颗粒物(PM)的截留机制的理解仍然有限。在这项研究中,在一个工业城市的城市公园内采样了 12 种树木。使用了两种叶片分析技术:真空/过滤和扫描电子显微镜结合能量色散 X 射线光谱法,以便对不同 PM 粒径分数进行定性和定量分析。结果表明,不同物种之间的沉积 PM 负荷差异很大。观察、测量和排列了不同的叶片特征,包括微观和宏观形态特征,最终目的是将它们与 PM 负荷联系起来。尽管没有观察到单个叶片特征与 PM 沉积之间存在显著相关性(p>0.05),但多元分析揭示了叶片特征簇与沉积 PM 之间的关系。因此,通过为每个特征分配一个分数,计算了一个累积指数(Ai),该指数与叶片沉积 PM 负荷显著相关(p≤0.05)。

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