Epidemiological studies have associated particulate air pollution with reduced cognitive performance (Zhang et al., 2018), development of diseases in the pulmonary and cardiovascular systems (Devlin et al., 2014;Schwarze et al., 2006;Seaton et al., 1995), and dementia (H. Chen et al., 2017). The biological mechanisms behind higher risk of cardio-respiratory diseases in an air-polluted urban environment have been studied and associated with ultrafine particles (Leitte et al., 2012;Miller et al., 2017;Penttinen et al., 2001). The size, morphology, and chemical composition of particles are critical in gauging detrimental effects to human health. Conventional air pollution indices classify and monitor PM as a function of its aerodynamic diameter: Exposure to PM 0.1 (≤0.1 μm), often referred to as ultrafine particles (UFPs), is of increasing focus and concern because of UFPs potential adverse health implications, as small particles can exert higher toxicity than larger particles (Ohlwein et al., 2019). UFPs can be drawn into the body via ingestion (Calderón-Garcidueñas et al., 2020), skin (Araviiskaia et al., 2019), olfactory transport, and through the lungs, entering the alveoli and penetrating biological membranes, effectively translocating to almost all organs (
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.
Hyperspectral imaging (HSI) data is a two-dimensional pixelated data set, where each pixel stores a one-dimensional array of spectral data, forming a three-dimensional datacube. HSI data provides vast quantities of spatial and spectral information and has been widely applied in various fields, such as remote sensing (Blackburn, 2006), vegetation and water source control (
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.
Hyperspectral imaging (HSI) data is a two-dimensional pixelated data set, where each pixel stores a one-dimensional array of spectral data, forming a three-dimensional datacube. HSI data provides vast quantities of spatial and spectral information and has been widely applied in various fields, such as remote sensing (Blackburn, 2006), vegetation and water source control (
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