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dc.contributor.authorMyrgiotis Ven
dc.contributor.authorWilliams Men
dc.contributor.authorRees RMen
dc.contributor.authorTopp CFEen
dc.date.accessioned2019-04-04T12:20:02Z
dc.date.available2019-04-04T12:20:02Z
dc.date.issued2019
dc.identifier.urihttps://doi.org/10.5194/bg-2018-490
dc.identifier.urihttp://hdl.handle.net/11262/11612
dc.description.abstractThe application of nitrogenous fertilisers to agricultural soils is a major source of anthropogenic N2O emissions. Reducing the nitrogen (N) footprint of agriculture is a global challenge that depends on our ability to quantify the N2O emission intensity of the world's most widespread and productive agricultural systems. In this context, biogeochemistry (BGC) models are widely used to estimate soil N2O emissions in agroecosystems. The choice of spatial scale is crucial because larger scale studies are limited by low input data precision while smaller scale studies lack wider relevance. The robustness of large-scale model predictions depends on preliminary and data-demanding model calibration/validation while relevant studies often omit the performance of output uncertainty analysis and underreport model outputs that would allow a critical assessment of results. This study takes a novel approach on these aspects. The study focuses on arable Eastern Scotland; a data-rich region typical of Northwest Europe in terms of edaphoclimatic conditions, cropping patterns and productivity levels. We used a calibrated and locally-validated BGC model to simulate direct soil N2O emissions along with NO3 leaching and crop N uptake in fields of barley, wheat and oilseed rape. We found that 0.59 % (±0.36) of the applied N is emitted as N2O while 37 % (±6) is taken up by crops and 14 % (±7) is leached as NO3. We show that crop type is a key determinant of N2O emission factors (EF) with cereals having a low (mean EF < 0.6 %), and oilseed rape a high (mean EF = 2.48 %), N2O emission intensity. Fertiliser addition was the most important N2O emissions driver suggesting that appropriate actions can reduce crop N2O intensity. Finally, we estimated a 74 % relative uncertainty around N2O predictions attributable to soil data variability. However, we argue that higher resolution soil data alone might not suffice to reduce this uncertainty.en
dc.language.isoenen
dc.relation.isformatof15057en
dc.relation.ispartofBiogeosciencesen
dc.rightsCopyright © Author(s) 2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.titleEstimating the soil N2O emission intensity of croplands in northwest Europeen
dc.typeArticleen
dc.description.versionAccepted manuscript
rioxxterms.publicationdate2019-01-03
rioxxterms.typeJournal Article/Reviewen
dcterms.dateAccepted2018-12-24
refterms.accessExceptionNAen
refterms.dateDeposit2019-04-04
refterms.depositExceptionpublishedGoldOAen
refterms.depositExceptionExplanationGoldOAen
refterms.panelUnspecifieden
refterms.technicalExceptionNAen
refterms.versionAMen


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