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dc.contributor.authorOumami, Safae
dc.contributor.authorArteta, Joaquim
dc.contributor.authorGuidard, Vincent
dc.contributor.authorTulet, Pierre
dc.contributor.authorHamer, Paul David
dc.date.accessioned2024-06-12T08:25:13Z
dc.date.available2024-06-12T08:25:13Z
dc.date.created2024-05-14T11:23:31Z
dc.date.issued2024
dc.identifier.citationGeoscientific Model Development. 2024, 17 (8), 3385-3408.en_US
dc.identifier.issn1991-959X
dc.identifier.urihttps://hdl.handle.net/11250/3133657
dc.description.abstractIsoprene, a key biogenic volatile organic compound, plays a pivotal role in atmospheric chemistry. Due to its high reactivity, this compound contributes significantly to the production of tropospheric ozone in polluted areas and to the formation of secondary organic aerosols. The assessment of biogenic emissions is of great importance for regional and global air quality evaluation. In this study, we implemented the biogenic emission model MEGANv2.1 (Model of Emissions of Gases and Aerosols from Nature, version 2.1) in the surface model SURFEXv8.1 (SURface EXternalisée in French, version 8.1). This coupling aims to improve the estimation of biogenic emissions using the detailed vegetation-type-dependent treatment included in the SURFEX vegetation ISBA (Interaction between Soil Biosphere and Atmosphere) scheme. This scheme provides vegetation-dependent parameters such as leaf area index and soil moisture to MEGAN. This approach enables a more accurate estimation of biogenic fluxes compared to the stand-alone MEGAN model, which relies on average input values for all vegetation types. The present study focuses on the assessment of the SURFEX–MEGAN model isoprene emissions. An evaluation of the coupled SURFEX–MEGAN model results was carried out by conducting a global isoprene emission simulation in 2019 and by comparing the simulation results with other MEGAN-based isoprene inventories. The coupled model estimates a total global isoprene emission of 443 Tg in 2019. The estimated isoprene is within the range of results obtained with other MEGAN-based isoprene inventories, ranging from 311 to 637 Tg. The spatial distribution of SURFEX–MEGAN isoprene is consistent with other studies, with some differences located in low-isoprene-emission regions. Several sensitivity tests were conducted to quantify the impact of different model inputs and configurations on isoprene emissions. Using different meteorological forcings resulted in a ±5 % change in isoprene emissions using MERRA (Modern-Era Retrospective analysis for Research and Applications) and IFS (Integrated Forecasting System) compared with ERA5. The impact of using different emission factor data was also investigated. The use of PFT (plant functional type) spatial coverage and PFT-dependent emission potential data resulted in a 12 % reduction compared to using the isoprene emission potential gridded map. A significant reduction of around 38 % in global isoprene emissions was observed in the third sensitivity analysis, which applied a parameterization of soil moisture deficit, particularly in certain regions of Australia, Africa, and South America. The significance of coupling the SURFEX and MEGAN models lies particularly in the ability of the coupled model to be forced with meteorological data from any period. This means, for instance, that this system can be used to predict biogenic emissions in the future. This aspect of our work is significant given the changes that biogenic organic compounds are expected to undergo as a result of changes in their climatic factors.en_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleEvaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1en_US
dc.title.alternativeEvaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1en_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© Author(s) 2024.en_US
dc.source.pagenumber3385-3408en_US
dc.source.volume17en_US
dc.source.journalGeoscientific Model Developmenten_US
dc.source.issue8en_US
dc.identifier.doi10.5194/gmd-17-3385-2024
dc.identifier.cristin2268448
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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