000868419 001__ 868419
000868419 005__ 20210130004216.0
000868419 0247_ $$2doi$$a10.1016/j.envres.2019.108806
000868419 0247_ $$2ISSN$$a0013-9351
000868419 0247_ $$2ISSN$$a1096-0953
000868419 0247_ $$2Handle$$a2128/23789
000868419 0247_ $$2pmid$$apmid:31627026
000868419 0247_ $$2WOS$$aWOS:000497259100015
000868419 037__ $$aFZJ-2020-00022
000868419 082__ $$a610
000868419 1001_ $$0P:(DE-HGF)0$$aWu, Di$$b0$$eCorresponding author
000868419 245__ $$aQuantifying N2O reduction to N2 during denitrification in soils via isotopic mapping approach: Model evaluation and uncertainty analysis
000868419 260__ $$aSan Diego, Calif.$$bElsevier$$c2019
000868419 3367_ $$2DRIVER$$aarticle
000868419 3367_ $$2DataCite$$aOutput Types/Journal article
000868419 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1578398166_27693
000868419 3367_ $$2BibTeX$$aARTICLE
000868419 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000868419 3367_ $$00$$2EndNote$$aJournal Article
000868419 520__ $$aThe last step of denitrification, i.e. the reduction of N2O to N2, has been intensively studied in the laboratory to understand the denitrification process, predict nitrogen fertiliser losses, and to establish mitigation strategies for N2O. However, assessing N2 production via denitrification at large spatial scales is still not possible due to lack of reliable quantitative approaches. Here, we present a novel numerical “mapping approach” model using the δ15Nsp/δ18O slope that has been proposed to potentially be used to indirectly quantify N2O reduction to N2 at field or larger spatial scales. We evaluate the model using data obtained from seven independent soil incubation studies conducted under a He–O2 atmosphere. Furthermore, we analyse the contribution of different parameters to the uncertainty of the model. The model performance strongly differed between studies and incubation conditions. Re-evaluation of the previous data set demonstrated that using soils-specific instead of default endmember values could largely improve model performance. Since the uncertainty of modelled N2O reduction was relatively high, further improvements to estimate model parameters to obtain more precise estimations remain an on-going matter, e.g. by determination of soil-specific isotope fractionation factors and isotopocule endmember values of N2O production processes using controlled laboratory incubations. The applicability of the mapping approach model is promising with an increasing availability of real-time and field based analysis of N2O isotope signatures.
000868419 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0
000868419 588__ $$aDataset connected to CrossRef
000868419 7001_ $$0P:(DE-HGF)0$$aWell, Reinhard$$b1
000868419 7001_ $$0P:(DE-HGF)0$$aCárdenas, Laura M.$$b2
000868419 7001_ $$0P:(DE-HGF)0$$aFuß, Roland$$b3
000868419 7001_ $$0P:(DE-HGF)0$$aLewicka-Szczebak, Dominika$$b4
000868419 7001_ $$0P:(DE-HGF)0$$aKöster, Jan Reent$$b5
000868419 7001_ $$0P:(DE-Juel1)142357$$aBrüggemann, Nicolas$$b6
000868419 7001_ $$0P:(DE-Juel1)145865$$aBol, Roland$$b7
000868419 773__ $$0PERI:(DE-600)1467489-0$$a10.1016/j.envres.2019.108806$$gVol. 179, p. 108806 -$$nPart A$$p108806 -$$tEnvironmental research$$v179$$x0013-9351$$y2019
000868419 8564_ $$uhttps://juser.fz-juelich.de/record/868419/files/Wu_etal_Environ_Res_postprint_final.pdf$$yPublished on 2019-10-10. Available in OpenAccess from 2021-10-10.
000868419 8564_ $$uhttps://juser.fz-juelich.de/record/868419/files/Wu_etal_Environ_Res_postprint_final.pdf?subformat=pdfa$$xpdfa$$yPublished on 2019-10-10. Available in OpenAccess from 2021-10-10.
000868419 909CO $$ooai:juser.fz-juelich.de:868419$$pdnbdelivery$$pVDB$$pVDB:Earth_Environment$$pdriver$$popen_access$$popenaire
000868419 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)142357$$aForschungszentrum Jülich$$b6$$kFZJ
000868419 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145865$$aForschungszentrum Jülich$$b7$$kFZJ
000868419 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0
000868419 9141_ $$y2019
000868419 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000868419 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences
000868419 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000868419 915__ $$0StatID:(DE-HGF)0530$$2StatID$$aEmbargoed OpenAccess
000868419 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bENVIRON RES : 2017
000868419 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000868419 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000868419 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000868419 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000868419 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000868419 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences
000868419 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000868419 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000868419 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000868419 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz
000868419 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000868419 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000868419 980__ $$ajournal
000868419 980__ $$aVDB
000868419 980__ $$aUNRESTRICTED
000868419 980__ $$aI:(DE-Juel1)IBG-3-20101118
000868419 9801_ $$aFullTexts