Foetisch Alexandra, Grunder Adrian, Kuster Benjamin, Stalder Tobias, Bigalke Moritz
Institute of Geography, University of Bern, Hallerstraβe 12, Bern, 3012 Switzerland.
Institute of Applied Geoscience, Technical University of Darmstadt, Schnittspahnstraβe 9, Darmstadt, 64287 Germany.
Microplast nanoplast. 2024;4(1):25. doi: 10.1186/s43591-024-00102-9. Epub 2024 Oct 30.
While tire wear particles (TWP) have been estimated to represent more than 90% of the total microplastic (MP) emitted in European countries and may have environmental health effects, only few data about TWP concentrations and characteristics are available today. The lack of data stems from the fact that no standardized, cost efficient or accessible extraction and identification method is available yet. We present a method allowing the extraction of TWP from soil, performing analysis with a conventional optical microscope and a machine learning approach to identify TWP in soil based on their colour. The lowest size of TWP which could be measured reliably with an acceptable recovery using our experimental set-up was 35 µm. Further improvements would be possible given more advanced technical infrastructure (higher optical magnification and image quality). Our method showed a mean recovery of 85% in the 35-2000 µm particle size range and no blank contamination. We tested for possible interference from charcoal (as another black soil component with similar properties) in the soils and found a reduction of the interference from charcoal by 92% during extraction. We applied our method to a highway adjacent soil at 1 m, 2 m, 5 m, and 10 m and detected TWP in all samples with a tendency to higher concentrations at 1 m and 2 m from the road compared to 10 m from the road. The observed TWP concentrations were in the same order of magnitude as what was previously reported in literature in highway adjacent soils. These results demonstrate the potential of the method to provide quantitative data on the occurrence and characteristics of TWP in the environment. The method can be easily implemented in many labs, and help to address our knowledge gap regarding TWP concentrations in soils.
The online version contains supplementary material available at 10.1186/s43591-024-00102-9.
据估计,在欧洲国家排放的微塑料(MP)总量中,轮胎磨损颗粒(TWP)占比超过90%,且可能对环境健康产生影响,但目前关于TWP浓度和特性的数据却很少。数据匮乏的原因在于,目前尚无标准化、成本效益高或易于操作的提取和鉴定方法。我们提出了一种从土壤中提取TWP的方法,使用传统光学显微镜进行分析,并采用机器学习方法根据TWP的颜色识别土壤中的TWP。使用我们的实验装置能够可靠测量且回收率可接受的TWP最小尺寸为35微米。如果有更先进的技术基础设施(更高的光学放大倍数和图像质量),还可以进一步改进。我们的方法在35 - 2000微米粒径范围内的平均回收率为85%,且无空白污染。我们测试了土壤中木炭(作为另一种具有相似性质的黑色土壤成分)可能产生的干扰,发现在提取过程中来自木炭的干扰减少了92%。我们将该方法应用于距离公路1米、2米、5米和10米处的相邻土壤,在所有样品中均检测到了TWP,与距离公路10米处相比,距离公路1米和2米处的TWP浓度有更高的趋势。观察到的TWP浓度与之前文献中报道的公路相邻土壤中的浓度处于同一数量级。这些结果证明了该方法在提供环境中TWP的存在和特性定量数据方面的潜力。该方法可在许多实验室轻松实施,有助于填补我们在土壤中TWP浓度方面的知识空白。
在线版本包含可在10.1186/s43591 - 024 - 00102 - 9获取的补充材料。