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

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cam.issuedOnline2022-06-07
dc.contributor.authorRoberts, C
dc.contributor.authorShorttle, O
dc.contributor.authorMandel, K
dc.contributor.authorJones, M
dc.contributor.authorIjzermans, R
dc.contributor.authorHirst, B
dc.contributor.authorJonathan, P
dc.contributor.orcidRoberts, C [0000-0002-5184-7485]
dc.contributor.orcidShorttle, O [0000-0002-8713-1446]
dc.contributor.orcidMandel, K [0000-0001-9846-4417]
dc.contributor.orcidHirst, B [0000-0003-2214-3144]
dc.contributor.orcidJonathan, P [0000-0001-7651-9181]
dc.date.accessioned2022-06-07T08:16:29Z
dc.date.available2022-06-07T08:16:29Z
dc.date.issued2022
dc.date.submitted2021-12-21
dc.date.updated2022-06-07T08:16:29Z
dc.description.abstractMethane 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.
dc.identifier.doi10.17863/CAM.85240
dc.identifier.eissn1748-9326
dc.identifier.issn1748-9318
dc.identifier.othererlac7062
dc.identifier.otherac7062
dc.identifier.othererl-113152.r2
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/337831
dc.languageen
dc.language.isoeng
dc.publisherIOP Publishing
dc.publisher.urlhttp://dx.doi.org/10.1088/1748-9326/ac7062
dc.subjectmethane emissions
dc.subjectBayesian inference
dc.subjectremote sensing
dc.subjectatmospheric chemistry
dc.subjectclimate change
dc.titleEnhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference
dc.typeOther
dcterms.dateAccepted2022-05-17
prism.issueIdentifier6
prism.publicationNameEnvironmental Research Letters
prism.volume17
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0
rioxxterms.versionVoR
rioxxterms.versionofrecord10.1088/1748-9326/ac7062

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