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LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles

Research output: Working paper › Preprint

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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

Harvard

Amos, M, Booker, D, Duncan, R, Gouldsbrough, L, Pinder, T, Young, P & Carter, J 2022 'LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles' EarthArXiv. https://doi.org/10.31223/X5664V

APA

Amos, M., Booker, D., Duncan, R., Gouldsbrough, L., Pinder, T., Young, P., & Carter, J. (2022). LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles. EarthArXiv. https://doi.org/10.31223/X5664V

Vancouver

Amos M, Booker D, Duncan R, Gouldsbrough L, Pinder T, Young P et al. LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles. EarthArXiv. 2022 Oct 3. doi: 10.31223/X5664V

Author

Amos, Matt ; Booker, Douglas ; Duncan, Rachael et al. / LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles. EarthArXiv, 2022.

Bibtex

@techreport{233bdd54e5e945a08d62a0d1ca61a0c0,
title = "LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles",
abstract = "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. ",
author = "Matt Amos and Douglas Booker and Rachael Duncan and Lily Gouldsbrough and Thomas Pinder and Paul Young and Jeremy Carter",
year = "2022",
month = oct,
day = "3",
doi = "10.31223/X5664V",
language = "English",
publisher = "EarthArXiv",
type = "WorkingPaper",
institution = "EarthArXiv",

}

RIS

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 - 10.31223/X5664V

DO - 10.31223/X5664V

M3 - Preprint

BT - LancasterAQ: A High Resolution Street Level Dataset of Ultrafine Particles

PB - EarthArXiv

ER -