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Research output: Working paper › Preprint
LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles. / Amos, Matt; Booker, Douglas; Duncan, Rachael et al.
EarthArXiv, 2022.Research output: Working paper › Preprint
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TY - UNPB
T1 - LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles
AU - Amos, Matt
AU - Booker, Douglas
AU - Duncan, Rachael
AU - Gouldsbrough, Lily
AU - Pinder, Thomas
AU - Young, Paul
AU - Carter, Jeremy
PY - 2022/10/3
Y1 - 2022/10/3
N2 - We present a mobile dataset of ultrafine particles (UFPs) in Lancaster, UK, with measurements taken by car and bike over 5 days in May 2022. UFPs are a constituent of air pollution and comprise of particulate matter (PM) less than 0.1μm in diameter. UFPs are unregulated and less measured than larger constituents of PM, despite being harmful to health and an important part of the atmospheric and meteorological system. By making mobile UFP measurements, we have produced a street level dataset that captures the high spatial variability of UFPs at the scale an individual experiences it. The dataset is accessible through the LancasterAQ Python package and lends itself to modelling spatially or on a network. This dataset's potential use cases include route planning under constraints of air pollutant exposure, identifying processes that affect air pollution at street level, and investigating the causal relationship between human activity and UFPs.
AB - We present a mobile dataset of ultrafine particles (UFPs) in Lancaster, UK, with measurements taken by car and bike over 5 days in May 2022. UFPs are a constituent of air pollution and comprise of particulate matter (PM) less than 0.1μm in diameter. UFPs are unregulated and less measured than larger constituents of PM, despite being harmful to health and an important part of the atmospheric and meteorological system. By making mobile UFP measurements, we have produced a street level dataset that captures the high spatial variability of UFPs at the scale an individual experiences it. The dataset is accessible through the LancasterAQ Python package and lends itself to modelling spatially or on a network. This dataset's potential use cases include route planning under constraints of air pollutant exposure, identifying processes that affect air pollution at street level, and investigating the causal relationship between human activity and UFPs.
U2 - https://doi.org/10.31223/X5664V
DO - https://doi.org/10.31223/X5664V
M3 - Preprint
BT - LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles
PB - EarthArXiv
ER -