Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum–maximum estimates: 12.2–23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9–17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2–11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies—particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O–climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.
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Acknowledgements This paper is the result of a collaborative international effort under the umbrella of the Global Carbon Project (a project of Future Earth and a research partner of the World Climate Research Programme) and International Nitrogen Initiative. This research was made possible partly by Andrew Carnegie Fellowship award no. G-F-19-56910; NSF grant nos 1903722,1243232 and 1922687; NASA grant nos NNX14AO73G, NNX10AU06G, NNX11AD47G and NNX14AF93G; NOAA grant nos NA16NOS4780207 and NA16NOS4780204; National Key R&D Program of China (grant no. 2017YFA0604702); National Natural Science Foundation of China (grant no. 41961124006); and OUC-AU Joint Center Program. E.T.B., P.R., G.P.P., R.L.T. and P.S. acknowledge funding support from VERIFY project (EC H2020 grant no. 776810); P.S. also acknowledges funding from the EC H2020 grant no. 641816 (CRESCENDO); A.I. acknowledges funding support from JSPS KAKENHI grant (no. 17H01867); G.B., F.J. and S.L. acknowledge support from the Swiss National Science Foundation (no. 200020_172476) and EC H2020 grant no. 821003 (Project 4C) and no. 820989 (Project COMFORT); A.L. acknowledges support from DFG project SFB754/3; S.Z. acknowledges support from EC H2020 grant no. 647204; K.C.W. and D.B.M. acknowledge support from NASA (IDS grant no. NNX17AK18G) and NOAA (grant no. NA13OAR4310086); P.A.R. acknowledges NASA Award NNX17AI74G; M.M. acknowledges support from the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS) Environmental Change Programme (2016-2021); B.D.E. acknowledges the support from ARC Linkage Grants LP150100519 and LP190100271; M.J.P. acknowledges the US Department of Energy grant no. DE-SC0012536, Lawrence Livermore National Laboratory B628407 and NASA MAP program grant no. NNX13AL12G; S.B. was supported by the EC H2020 with the CRESCENDO project (grant no. 641816) and by the COMFORT project (grant no. 820989), and also acknowledges the support of the team in charge of the CNRM-CM climate model; F.Z. acknowledges the support from the National Natural Science Foundation of China (41671464). Supercomputing time was provided by the Météo-France/DSI supercomputing center. P.K.P. is partly supported by Environment Research and Technology Development Fund (#2-1802) of the Ministry of the Environment, Japan; R.L. acknowledges support from the French state aid managed by the ANR under the ‘Investissements d’avenir’ programme with the reference ANR-16-CONV-0003. NOAA ground-based observations of atmospheric N2O are supported by NOAA’s Climate Program Office under the Atmospheric Chemistry Carbon Cycle and Climate (AC4) theme. The AGAGE stations measuring N2O are supported by NASA (USA) grants NNX16AC98G to MIT and NNX16AC97G and NNX16AC96G to SIO, and by BEIS (UK) for Mace Head, NOAA (USA) for Barbados, and CSIRO and BoM (Australia) for Cape Grim. F.N.T. acknowledges funding from FAO regular programme. The views expressed in this publication are those of the author(s) and do not necessarily reflect the views or policies of FAO. P.C. acknowledges support from ERC Synergy Grant Imbalance-P and the ANR Cland Convergence Institute. We also thank S. Frolking for constructive comments and suggestions that have helped to improve this paper. The statements made and views expressed are solely the responsibility of the authors.
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PubMed: MeSH publication types
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- Research Support, Non-U.S. Gov't
- Research Support, U.S. Gov't, Non-P.H.S.