Institute of Chemistry, University of Graz, 8010, Graz, Austria.
The Atomic Medicine Initiative, University of Technology Sydney, 15 Broadway, Ultimo, NSW, 2007, Australia.
Anal Bioanal Chem. 2022 Jul;414(18):5671-5681. doi: 10.1007/s00216-022-04052-0. Epub 2022 Apr 28.
The analysis of natural and anthropogenic nanomaterials (NMs) in the environment is challenging and requires methods capable to identify and characterise structures on the nanoscale regarding particle number concentrations (PNCs), elemental composition, size, and mass distributions. In this study, we employed single particle inductively coupled plasma-mass spectrometry (SP ICP-MS) to investigate the occurrence of NMs in the Melbourne area (Australia) across 63 locations. Poisson statistics were used to discriminate between signals from nanoparticulate matter and ionic background. TiO-based NMs were frequently detected and corresponding NM signals were calibated with an automated data processing platform. Additionally, a method utilising a larger mass bandpass was developed to screen for particulate high-mass elements. This procedure identified Pb-based NMs in various samples. The effects of different environmental matrices consisting of fresh, brackish, or seawater were mitigated with an aerosol dilution method reducing the introduction of salt into the plasma and avoiding signal drift. Signals from TiO- and Pb-based NMs were counted, integrated, and subsequently calibrated to determine PNCs as well as mass and size distributions. PNCs, mean sizes, particulate masses, and ionic background levels were compared across different locations and environments.
对环境中天然和人为纳米材料（NMs）的分析具有挑战性，需要能够识别和表征纳米级结构的方法，包括颗粒数量浓度（PNC）、元素组成、尺寸和质量分布。在本研究中，我们采用单颗粒电感耦合等离子体质谱（SP ICP-MS）在澳大利亚墨尔本地区的 63 个地点进行了 NM 的研究。泊松统计用于区分纳米颗粒物质和离子背景的信号。经常检测到基于 TiO2 的 NM，并使用自动化数据处理平台对 NM 信号进行校准。此外，还开发了一种利用更大质量带宽的方法来筛选高质量元素的颗粒物。该程序在各种样品中识别出基于 Pb 的 NM。采用气溶胶稀释法减轻了由淡水、微咸水或海水组成的不同环境基质的影响，该方法可减少盐进入等离子体并避免信号漂移。对 TiO2 和 Pb 基 NM 的信号进行计数、积分，并随后进行校准，以确定 PNC 以及质量和尺寸分布。比较了不同地点和环境下的 PNC、平均粒径、颗粒质量和离子背景水平。
