Home > Research > Publications & Outputs > Enhanced monitoring of atmospheric methane from...

Research

Links

Text available via DOI:

Keywords

View graph of relations

Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference

Research output: Contribution to Journal/Magazine › Letter › peer-review

Published

Standard

Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference. / Roberts, Clayton; Shorttle, Oliver; Mandel, Kaisey et al.
In: Environmental Research Letters, Vol. 17, No. 6, 064037, 01.06.2022.

Research output: Contribution to Journal/Magazine › Letter › peer-review

Harvard

Roberts, C, Shorttle, O, Mandel, K, Jones, M, Ijzermans, R, Hirst, B & Jonathan, P 2022, 'Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference', Environmental Research Letters, vol. 17, no. 6, 064037. https://doi.org/10.1088/1748-9326/ac7062

APA

Roberts, C., Shorttle, O., Mandel, K., Jones, M., Ijzermans, R., Hirst, B., & Jonathan, P. (2022). Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference. Environmental Research Letters, 17(6), Article 064037. https://doi.org/10.1088/1748-9326/ac7062

Vancouver

Roberts C, Shorttle O, Mandel K, Jones M, Ijzermans R, Hirst B et al. Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference. Environmental Research Letters. 2022 Jun 1;17(6):064037. doi: 10.1088/1748-9326/ac7062

Author

Roberts, Clayton ; Shorttle, Oliver ; Mandel, Kaisey et al. / Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference. In: Environmental Research Letters. 2022 ; Vol. 17, No. 6.

Bibtex

@article{a055d86bc2474b9fa74a81d6306f62e7,
title = "Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference",
abstract = "Abstract: Methane is a strong greenhouse gas, with a higher radiative forcing per unit mass and shorter atmospheric lifetime than carbon dioxide. The remote sensing of methane in regions of industrial activity is a key step toward the accurate monitoring of emissions that drive climate change. Whilst the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinal-5P satellite is capable of providing daily global measurement of methane columns, data are often compromised by cloud cover. Here, we develop a statistical model which uses nitrogen dioxide concentration data from TROPOMI to efficiently predict values of methane columns, expanding the average daily spatial coverage of observations of the Permian basin from 16% to 88% in the year 2019. The addition of predicted methane abundances at locations where direct observations are not available will support inversion methods for estimating methane emission rates at shorter timescales than is currently possible.",
keywords = "Letter, methane emissions, Bayesian inference, remote sensing, atmospheric chemistry, climate change",
author = "Clayton Roberts and Oliver Shorttle and Kaisey Mandel and Matthew Jones and Rutger Ijzermans and Bill Hirst and Philip Jonathan",
year = "2022",
month = jun,
day = "1",
doi = "10.1088/1748-9326/ac7062",
language = "English",
volume = "17",
journal = "Environmental Research Letters",
issn = "1748-9326",
publisher = "IOP Publishing Ltd",
number = "6",

}

RIS

TY - JOUR

T1 - Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference

AU - Roberts, Clayton

AU - Shorttle, Oliver

AU - Mandel, Kaisey

AU - Jones, Matthew

AU - Ijzermans, Rutger

AU - Hirst, Bill

AU - Jonathan, Philip

PY - 2022/6/1

Y1 - 2022/6/1

N2 - Abstract: Methane is a strong greenhouse gas, with a higher radiative forcing per unit mass and shorter atmospheric lifetime than carbon dioxide. The remote sensing of methane in regions of industrial activity is a key step toward the accurate monitoring of emissions that drive climate change. Whilst the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinal-5P satellite is capable of providing daily global measurement of methane columns, data are often compromised by cloud cover. Here, we develop a statistical model which uses nitrogen dioxide concentration data from TROPOMI to efficiently predict values of methane columns, expanding the average daily spatial coverage of observations of the Permian basin from 16% to 88% in the year 2019. The addition of predicted methane abundances at locations where direct observations are not available will support inversion methods for estimating methane emission rates at shorter timescales than is currently possible.

AB - Abstract: Methane is a strong greenhouse gas, with a higher radiative forcing per unit mass and shorter atmospheric lifetime than carbon dioxide. The remote sensing of methane in regions of industrial activity is a key step toward the accurate monitoring of emissions that drive climate change. Whilst the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinal-5P satellite is capable of providing daily global measurement of methane columns, data are often compromised by cloud cover. Here, we develop a statistical model which uses nitrogen dioxide concentration data from TROPOMI to efficiently predict values of methane columns, expanding the average daily spatial coverage of observations of the Permian basin from 16% to 88% in the year 2019. The addition of predicted methane abundances at locations where direct observations are not available will support inversion methods for estimating methane emission rates at shorter timescales than is currently possible.

KW - Letter

KW - methane emissions

KW - Bayesian inference

KW - remote sensing

KW - atmospheric chemistry

KW - climate change

U2 - 10.1088/1748-9326/ac7062

DO - 10.1088/1748-9326/ac7062

M3 - Letter

VL - 17

JO - Environmental Research Letters

JF - Environmental Research Letters

SN - 1748-9326

IS - 6

M1 - 064037

ER -