Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference
Authors
Jones, Matthew
Ijzermans, Rutger
Hirst, Bill
Jonathan, Philip
Publication Date
2022-06-01Journal Title
ENVIRONMENTAL RESEARCH LETTERS
ISSN
1748-9326
Publisher
IOP Publishing
Volume
17
Issue
6
Language
en
Type
Other
This Version
VoR
Metadata
Show full item recordCitation
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. [Other]. https://doi.org/10.1088/1748-9326/ac7062
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
Identifiers
erlac7062, ac7062, erl-113152.r2
External DOI: https://doi.org/10.1088/1748-9326/ac7062
This record's DOI: https://doi.org/10.17863/CAM.85240
Rights
Licence:
http://creativecommons.org/licenses/by/4.0
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