Journalartikel
Autorenliste: Liu, Haojie; Wrage-Monnig, Nicole; Lennartz, Bernd
Jahr der Veröffentlichung: 2020
Zeitschrift: Communications Earth & Environment
Bandnummer: 1
Heftnummer: 1
eISSN: 2662-4435
Open Access Status: Gold
DOI Link: https://doi.org/10.1038/s43247-020-00017-2
Verlag: Nature Research
Nitrous oxide (N2O) is approximately 265 times more potent than carbon dioxide (CO2) in atmospheric warming. Degraded peatlands are important sources of N2O. The more a peat soil is degraded, the higher the N2O-N emissions from peat. In this study, soil bulk density was used as a proxy for peat degradation to predict N2O-N emissions. Here we report that the annual N2O-N emissions from European managed peatlands (EU-28) sum up to approximately 145 Gg N year(-1). From the viewpoint of greenhouse gas emissions, highly degraded agriculturally used peatlands should be rewetted first to optimally reduce cumulative N2O-N emissions. Compared to a business-as-usual scenario (no peatland rewetting), rewetting of all drained European peatlands until 2050 using the suggested strategy reduces the cumulative N2O-N emissions by 70%. In conclusion, the status of peat degradation should be made a pivotal criterion in prioritising peatlands for restoration. Rewetting agricultural peatlands first is the best strategy for reducing cumulative nitrous oxide emissions from European peatlands, according to an analysis of soil bulk density as a proxy for peat degradation.
Abstract:
Zitierstile
Harvard-Zitierstil: Liu, H., Wrage-Monnig, N. and Lennartz, B. (2020) Rewetting strategies to reduce nitrous oxide emissions from European peatlands, Communications Earth & Environment, 1(1), Article 17. https://doi.org/10.1038/s43247-020-00017-2
APA-Zitierstil: Liu, H., Wrage-Monnig, N., & Lennartz, B. (2020). Rewetting strategies to reduce nitrous oxide emissions from European peatlands. Communications Earth & Environment. 1(1), Article 17. https://doi.org/10.1038/s43247-020-00017-2
Schlagwörter
NEW-ZEALAND; NUTRIENT STATUS; ORGANIC SOILS; PEAT; PREDICT