SIGMA: Spectral Interpretation using Gaussian Mixtures and Autoencoder

Tung, Po‐Yen; Sheikh, Hassan Aftab; Ball, Matthew R.; Nabiei, Farhang; Harrison, R. J.

doi:10.1002/essoar.10511396.1

Cited by 2 publications

(3 citation statements)

References 44 publications

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“…However, our results suggest that high PM levels in such microenvironments should be as strictly regulated as any other busy urban street in London. Since LU PM originates primarily from tube operations, the amount of resuspended dust in the system could be reduced by removing accumulated dust on the tracks, using magnetic lters in ventilation systems to remove magnetic PM (43) or placing screen doors between the platform and train to reduces PM exposure on platforms (44).…”

Section: Discussionmentioning

confidence: 99%

“…S8) at the University of Cambridge using a Thermo sher Quanta-650F SEM equipped with a backscatter electron (BSE), a secondary electron (SE), and an energy-dispersive spectroscopy (EDS) detector. Segmentation of the chemical maps and unmixing of overlapping chemical spectra was performed using a machine-learning autoencoder technique 43 . This procedure was used to provide a low-resolution overview of the PM and to identify representative regions of interest for further investigation using an FEI Tecnai F20 FEG TEM.…”

Section: Electron Microscopymentioning

confidence: 99%

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London Underground air pollution particles are finer than you think

Sheikh

Tung

Ringe

et al. 2022

Preprint

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Particulate matter (PM) concentration levels in the London Underground (LU) are higher than London background levels, and beyond World Health Organization defined limits. Wheel, track, and brake abrasion are the primary sources of particulate matter, producing predominantly Fe-rich particles that make the LU microenvironment particularly well suited to study using environmental magnetism. Here we combine magnetic properties, high-resolution electron microscopy, and electron tomography to characterize the structure, chemistry, and morphometric properties of LU particles in three dimensions with nanoscale resolution. Our findings show that LU PM is dominated by 5-500 nm particles of oxidized magnetite, occurring as 0.1-2 µm aggregated clusters, skewing the size-fractioned concentration of PM artificially to larger sizes when measured with traditional monitors. Magnetic properties are largely independent of the PM filter size (PM10, PM4, and PM2.5), and demonstrate the presence of superparamagnetic, single-domain, and vortex/pseudo-single domain signals only (i.e., no multi-domain particles > 1 µm). The oxidized state of the particles suggests that PM exposure in the LU is dominated by resuspension of aged dust particles relative to freshly abraded, metallic particles from the wheel/track/brake system, suggesting that periodic removal of accumulated dust from underground tunnels might provide a cost-effective strategy for reducing exposure. The abundance of ultrafine particles identified here could have particularly adverse health impacts as their smaller size makes it possible to pass from lungs to the blood stream. Magnetic methods are shown to provide an accurate assessment of ultrafine PM characteristics, providing a robust route to monitoring, and potentially mitigating this hazard.

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Section: Discussionmentioning

confidence: 99%

Section: Electron Microscopymentioning

confidence: 99%

London Underground air pollution particles are finer than you think

Sheikh

Tung

Ringe

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…S9) at the University of Cambridge using a Thermofisher Quanta-650F SEM equipped with a backscatter electron (BSE), a secondary electron (SE), and an energy-dispersive spectroscopy (EDS) detector. Segmentation of the chemical maps and unmixing of overlapping chemical spectra was performed using a machine-learning autoencoder technique 50 . This procedure was used to provide a low-resolution overview of the PM and to identify representative regions of interest for further investigation using an FEI Tecnai F20 FEG TEM.…”

Section: Magnetic Characterisationmentioning

confidence: 99%

Magnetic and microscopic investigation of airborne iron oxide nanoparticles in the London Underground

Sheikh

Tung

Ringe

et al. 2022

Sci Rep

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Particulate matter (PM) concentration levels in the London Underground (LU) are higher than London background levels and beyond World Health Organization (WHO) defined limits. Wheel, track, and brake abrasion are the primary sources of particulate matter, producing predominantly Fe-rich particles that make the LU microenvironment particularly well suited to study using environmental magnetism. Here we combine magnetic properties, high-resolution electron microscopy, and electron tomography to characterize the structure, chemistry, and morphometric properties of LU particles in three dimensions with nanoscale resolution. Our findings show that LU PM is dominated by 5–500 nm particles of maghemite, occurring as 0.1–2 μm aggregated clusters, skewing the size-fractioned concentration of PM artificially to larger sizes when measured with traditional monitors. Magnetic properties are largely independent of the PM filter size (PM10, PM4, and PM2.5), and demonstrate the presence of superparamagnetic (< 30 nm), single-domain (30–70 nm), and vortex/pseudo-single domain (70–700 nm) signals only (i.e., no multi-domain particles > 1 µm). The oxidized nature of the particles suggests that PM exposure in the LU is dominated by resuspension of aged dust particles relative to freshly abraded, metallic particles from the wheel/track/brake system, suggesting that periodic removal of accumulated dust from underground tunnels might provide a cost-effective strategy for reducing exposure. The abundance of ultrafine particles identified here could have particularly adverse health impacts as their smaller size makes it possible to pass from lungs to the blood stream. Magnetic methods are shown to provide an accurate assessment of ultrafine PM characteristics, providing a robust route to monitoring, and potentially mitigating this hazard.

show abstract

SIGMA: Spectral Interpretation using Gaussian Mixtures and Autoencoder

Cited by 2 publications

References 44 publications

London Underground air pollution particles are finer than you think

London Underground air pollution particles are finer than you think

Magnetic and microscopic investigation of airborne iron oxide nanoparticles in the London Underground

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