Anushka Elangasinghe , Hamesh Patel , Kim N. Dirks , Ayrton Hamilton , Wenxia (Wendy) Fan , Shuoyu Chen , Nick Talbot , Shanon Lim , Jed Januch , Martin Brook , Brett Wells , David E. Williams , Perry Davy , Woodrow Pattinson , Jennifer A. Salmond
{"title":"A novel approach for quantifying elongated airborne mineral particles (EMPs) using an automated scanning electron microscope (SEM)","authors":"Anushka Elangasinghe , Hamesh Patel , Kim N. Dirks , Ayrton Hamilton , Wenxia (Wendy) Fan , Shuoyu Chen , Nick Talbot , Shanon Lim , Jed Januch , Martin Brook , Brett Wells , David E. Williams , Perry Davy , Woodrow Pattinson , Jennifer A. Salmond","doi":"10.1016/j.atmosenv.2025.121217","DOIUrl":null,"url":null,"abstract":"<div><div>Exposure to carcinogenic elongated mineral particles (EMPs), such as erionite, found in rocks and released into the air by construction, quarrying, or roading activities, poses a significant possible health risk due to their respirable size and potential for airborne dispersion. The detection of EMPs in the air is typically achieved by filter sampling and subsequent examination using a range of microscopic methods, including phase contrast microscopy (PCM) and scanning electron microscope (SEM). Such analyzes require the manual searching for fibers through many image fields and are both labor-intensive and time-consuming. Moreover, these methods do not result in conclusive particle identification, limiting their effectiveness in large-scale monitoring programmes. This paper introduces a novel methodology for the automated detection and quantification of EMPs using an automated SEM with energy dispersive spectroscopy (EDS) to identify fibers on pre-sampled polycarbonate (PC) filters. This method provides a streamlined workflow for fiber identification based on their size, morphology, and elemental composition. Performance evaluation (PE) standards were prepared by spiking filters with a series of known concentrations of one EMP, namely erionite, and fiber concentrations were measured using the automated SEM-EDS approach. Our results demonstrate a linear relationship (R<sup>2</sup> = 0.98∗∗∗) between the erionite mass percentage in a bulk sample and the fiber counts in an aerosolized air volume, with a detection limit of 7.4 f/cc. The approach can be optimized based on the time available for analysis and the choice of detection limit suitable for the specific site and application. Additionally, the automated SEM-EDS method has been applied to real-world air samples collected from Auckland, New Zealand, showing promising results for fiber detection in complex environmental matrices.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"354 ","pages":"Article 121217"},"PeriodicalIF":4.2000,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Environment","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S135223102500192X","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Exposure to carcinogenic elongated mineral particles (EMPs), such as erionite, found in rocks and released into the air by construction, quarrying, or roading activities, poses a significant possible health risk due to their respirable size and potential for airborne dispersion. The detection of EMPs in the air is typically achieved by filter sampling and subsequent examination using a range of microscopic methods, including phase contrast microscopy (PCM) and scanning electron microscope (SEM). Such analyzes require the manual searching for fibers through many image fields and are both labor-intensive and time-consuming. Moreover, these methods do not result in conclusive particle identification, limiting their effectiveness in large-scale monitoring programmes. This paper introduces a novel methodology for the automated detection and quantification of EMPs using an automated SEM with energy dispersive spectroscopy (EDS) to identify fibers on pre-sampled polycarbonate (PC) filters. This method provides a streamlined workflow for fiber identification based on their size, morphology, and elemental composition. Performance evaluation (PE) standards were prepared by spiking filters with a series of known concentrations of one EMP, namely erionite, and fiber concentrations were measured using the automated SEM-EDS approach. Our results demonstrate a linear relationship (R2 = 0.98∗∗∗) between the erionite mass percentage in a bulk sample and the fiber counts in an aerosolized air volume, with a detection limit of 7.4 f/cc. The approach can be optimized based on the time available for analysis and the choice of detection limit suitable for the specific site and application. Additionally, the automated SEM-EDS method has been applied to real-world air samples collected from Auckland, New Zealand, showing promising results for fiber detection in complex environmental matrices.
期刊介绍:
Atmospheric Environment has an open access mirror journal Atmospheric Environment: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review.
Atmospheric Environment is the international journal for scientists in different disciplines related to atmospheric composition and its impacts. The journal publishes scientific articles with atmospheric relevance of emissions and depositions of gaseous and particulate compounds, chemical processes and physical effects in the atmosphere, as well as impacts of the changing atmospheric composition on human health, air quality, climate change, and ecosystems.