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dc.contributor.authorPrairie, Yves T.
dc.contributor.authorMercier-Blais, Sara
dc.contributor.authorHarrison, John
dc.contributor.authorSoued, Cynthia
dc.contributor.authordel Giorgio, Paul
dc.contributor.authorHarby, Atle
dc.contributor.authorAlm, Jukka
dc.contributor.authorChanudet, Vincent
dc.contributor.authorNahas, Roy
dc.date.accessioned2021-09-27T13:02:55Z
dc.date.available2021-09-27T13:02:55Z
dc.date.created2021-08-10T14:07:41Z
dc.date.issued2021
dc.identifier.issn1364-8152
dc.identifier.urihttps://hdl.handle.net/11250/2783784
dc.description.abstractHuman-made reservoirs are now recognized as potentially significant sources of greenhouse gases, comparable to other anthropogenic sources, yet efforts to estimate these reservoir emissions have been hampered by the complexity of the underlying processes and a lack of coherent budgeting approaches. Here we present a unique modelling framework, the G-res Tool, which was explicitly designed to estimate the net C footprint of reservoirs across the globe. The framework involves the development of statistically robust empirical models describing the four major emission pathways for carbon-based greenhouse gases (GHG) from reservoirs: diffusive CO2 and CH4 emissions, bubbling CH4 emissions from the reservoir surface, and CH4 emissions due to degassing downstream the reservoir, based on an extensive meta-analysis of published data from the past three decades. These empirical models allow the prediction of reservoir-specific emissions, how they may shift over time and account for naturally occurring GHG generating pathways in aquatic networks.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleA new modelling framework to assess biogenic GHG emissions from reservoirs: The G-res toolen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holderThe Authorsen_US
dc.source.volume143en_US
dc.source.journalEnvironmental Modelling & Softwareen_US
dc.identifier.doi10.1016/j.envsoft.2021.105117
dc.identifier.cristin1925087
dc.source.articlenumber115117en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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