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蜘蛛丝生物监测:城市颗粒物源解析的一种具有成本效益的方法。

Spider web biomonitoring: A cost-effective source apportionment approach for urban particulate matter.

机构信息

Institute of Geosciences, Friedrich Schiller University Jena, Burgweg 11, 07749, Jena, Germany.

Helmholtz Centre for Environmental Research - UFZ, Central Laboratory for Water Analytics & Chemometrics, Brückstraße 3a, 39114, Magdeburg, Germany.

出版信息

Environ Pollut. 2021 Oct 1;286:117328. doi: 10.1016/j.envpol.2021.117328. Epub 2021 May 8.

Abstract

Elevated levels of particulate matter (PM) in urban atmospheres are one of the major environmental challenges of the Anthropocene. To effectively lower those levels, identification and quantification of sources of PM is required. Biomonitoring methods are helpful tools to tackle this problem but have not been fully established yet. An example is the sampling and subsequent analysis of spider webs to whose adhesive surface dust particles can attach. For a methodical inspection, webs of orb-weaving spiders were sampled repeatedly from 2016 to 2018 at 22 locations in the city of Jena, Germany. Contents of Ag, Al, As, B, Ba, Ca, Cd, Co, Cr, Cs, Cu, Fe, K, La, Li, Mg, Mn, Mo, Na, Ni, P, Pb, Rb, S, Sb, Si, Sn, Sr, Th, Ti, V, Y, Zn and Zr were determined in the samples using inductively coupled plasma-mass spectrometry (ICP-MS) and inductively coupled plasma-optical emission spectroscopy (ICP-OES) after aqua regia digestion. Multivariate statistical methods were applied for a detailed evaluation. A combination of cluster analysis and principal component analysis allows for the clear identification of three main sources in the study area: brake wear from car traffic, abrasion of tram/train tracks and particles of geogenic origin. Quantitative source contributions reveal that high amounts of most of the metals are derived from a combination of brake wear and geogenic particles, the latter of which are likely resuspended by moving vehicles. This emphasizes the importance of non-exhaust particles connected to road traffic. Once a source identification has been performed for an area of interest, classification models can be applied to assess air quality for further samples from within the whole study area, offering a tool for air quality assessment. The general validity of this approach is demonstrated using samples from other locations.

摘要

城市大气中颗粒物(PM)水平升高是人类世的主要环境挑战之一。为了有效降低这些水平,需要识别和量化 PM 的来源。生物监测方法是解决这个问题的有用工具,但尚未完全建立。一个例子是采样和随后分析蜘蛛网,灰尘颗粒可以附着在蜘蛛网的粘性表面上。为了进行系统的检查,从 2016 年到 2018 年,在德国耶拿市的 22 个地点,重复采集了圆蛛的蛛网样本。使用电感耦合等离子体质谱(ICP-MS)和电感耦合等离子体发射光谱(ICP-OES)对样品进行分析,确定 Ag、Al、As、B、Ba、Ca、Cd、Co、Cr、Cs、Cu、Fe、K、La、Li、Mg、Mn、Mo、Na、Ni、P、Pb、Rb、S、Sb、Si、Sn、Sr、Th、Ti、V、Y、Zn 和 Zr 的含量。采用多元统计方法进行详细评估。聚类分析和主成分分析的组合允许在研究区域中清楚地识别三个主要来源:汽车交通的刹车磨损、有轨电车/火车轨道的磨损和地球成因颗粒。定量来源贡献表明,大多数金属的高含量来自刹车磨损和地球成因颗粒的组合,后者可能是由移动车辆重新悬浮的。这强调了与道路交通有关的非排放颗粒的重要性。一旦对感兴趣的区域进行了来源识别,可以应用分类模型来评估整个研究区域内的其他样本的空气质量,为空气质量评估提供了一种工具。使用来自其他位置的样本证明了这种方法的一般有效性。

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