Estimating fractions of N2O emissions from nitrification and denitrification using data assimilation Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.1007/s10533-025-01268-x
Nitrous oxide (N 2 O) emissions play a significant role in global warming and stratospheric ozone depletion. Nitrification and denitrification represent the primary pathways of N 2 O emissions in agroecosystems. However, modelling the responses of nitrification, denitrification, and subsequent N 2 O emissions to soil conditions and nitrification inhibitors remains challenging, as the fractions of N 2 O emissions derived from nitrification and denitrification used in model simulations cannot be directly measured. In this study, we estimated soil nitrification, denitrification, N 2 O emissions, and their related parameters via data assimilation under various soil moisture levels [water-filled pore space (WFPS) at 50% and 70%], incubation temperature (15, 25 and 35 °C) and nitrification inhibitor application (DMPP, 3MPTZ and C 2 H 2 ) in cereal and vegetable production systems in Australia. We found that the contribution of nitrification to N 2 O emissions (i.e., the fraction of N 2 O emitted from nitrification, $${f}_{{\text{N}}_2{\text{O}}\_nit}$$ ) decreased with increasing temperature and moisture content, whereas denitrification dominated N 2 O production (i.e., the fraction of N 2 O emitted from denitrification, $${f}_{N2O\_dni}$$ ) under 70% WFPS regardless of temperatures. Under fertilizer N application, the use of nitrification inhibitors decreased $${f}_{{\text{N}}_2{\text{O}}\_nit}$$ but increased $${f}_{N2O\_dni}$$ . The efficacy of nitrification inhibitors in mitigating N 2 O emissions varied with environmental conditions. In this study, we demonstrate the use of data assimilation to constrain key parameters for predicting nitrification, denitrification and associated N 2 O emissions in response to soil environments and management practices. Integrating this technique into ecosystem process-based models has the potential to enhance model accuracy by reducing uncertainties and biases.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s10533-025-01268-x
- https://link.springer.com/content/pdf/10.1007/s10533-025-01268-x.pdf
- OA Status
- hybrid
- Cited By
- 2
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4414025645
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4414025645Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s10533-025-01268-xDigital Object Identifier
- Title
-
Estimating fractions of N2O emissions from nitrification and denitrification using data assimilationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-09-05Full publication date if available
- Authors
-
Baobao Pan, Yuanyuan Huang, Longlong Xia, Junyi Liang, Rui Liu, Yiqi Luo, Zhenggang Du, Deli Chen, Shu Kee LamList of authors in order
- Landing page
-
https://doi.org/10.1007/s10533-025-01268-xPublisher landing page
- PDF URL
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https://link.springer.com/content/pdf/10.1007/s10533-025-01268-x.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
- OA URL
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https://link.springer.com/content/pdf/10.1007/s10533-025-01268-x.pdfDirect OA link when available
- Concepts
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Denitrification, Nitrification, Environmental science, Data assimilation, Assimilation (phonology), Simultaneous nitrification-denitrification, Environmental chemistry, Hydrology (agriculture), Environmental engineering, Chemistry, Nitrogen, Meteorology, Geology, Geography, Linguistics, Philosophy, Geotechnical engineering, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
- References (count)
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61Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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