Spatially explicit estimates of N2 O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management

James S. Gerber, Kimberly M. Carlson, David Makowski, Nathaniel D. Mueller, Iñaki Garcia de Cortazar-Atauri, Petr Havlík, Mario Herrero, Marie Launay, Christine S. O'Connell, Pete Smith, Paul C. West

Research output: Contribution to journalArticlepeer-review

62 Scopus citations

Abstract

With increasing nitrogen (N) application to croplands required to support growing food demand, mitigating N2O emissions from agricultural soils is a global challenge. National greenhouse gas emissions accounting typically estimates N2O emissions at the country scale by aggregating all crops, under the assumption that N2O emissions are linearly related to N application. However, field studies and meta-analyses indicate a nonlinear relationship, in which N2O emissions are relatively greater at higher N application rates. Here, we apply a super-linear emissions response model to crop-specific, spatially explicit synthetic N fertilizer and manure N inputs to provide subnational accounting of global N2O emissions from croplands. We estimate 0.66 Tg of N2O-N direct global emissions circa 2000, with 50% of emissions concentrated in 13% of harvested area. Compared to estimates from the IPCC Tier 1 linear model, our updated N2O emissions range from 20% to 40% lower throughout sub-Saharan Africa and Eastern Europe, to >120% greater in some Western European countries. At low N application rates, the weak nonlinear response of N2O emissions suggests that relatively large increases in N fertilizer application would generate relatively small increases in N2O emissions. As aggregated fertilizer data generate underestimation bias in nonlinear models, high-resolution N application data are critical to support accurate N2O emissions estimates.

Original languageEnglish (US)
Pages (from-to)3383-3394
Number of pages12
JournalGlobal change biology
Volume22
Issue number10
DOIs
StatePublished - Oct 1 2016

Bibliographical note

Funding Information:
We are grateful to Stefan Siebert for advice on reconciling the Monfreda datasets of yield and area and the Portmann dataset for irrigated area of rice. We thank Deepak Ray and Jonathan Foley for helpful comments. Research support to J.G., K.C., N.M, and P.W. was primarily provided by the Gordon and Betty Moore Foundation and the Institute on Environment, with additional support from NSF Hydrologic Sciences grant 1521210 for N.M., and additional support to J.G. and P.W. whose efforts contribute to Belmont Forum/FACCE-JPI funded DEVIL project (NE/M021327/1). M.H. was supported by CSIRO's OCE Science Leaders Programme and the Agriculture Flagship. Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© 2016 John Wiley & Sons Ltd

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • NO
  • climate change
  • emissions
  • flooded rice
  • greenhouse gas
  • manure
  • meta-analysis
  • nitrogen
  • nitrous oxide
  • sustainable agriculture

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