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Global mapping of crop-specific emission factors highlights hotspots of nitrous oxide mitigation

Nature Food volume 2, pages 886–893 (2021)Cite this article

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Abstract

Mitigating soil nitrous oxide (N2O) emissions is essential for staying below a 2 °C warming threshold. However, accurate assessments of mitigation potential are limited by uncertainty and variability in direct emission factors (EFs). To assess where and why EFs differ, we created high-resolution maps of crop-specific EFs based on 1,507 georeferenced field observations. Here, using a data-driven approach, we show that EFs vary by two orders of magnitude over space. At global and regional scales, such variation is primarily driven by climatic and edaphic factors rather than the well-recognized management practices. Combining spatially explicit EFs with N surplus information, we conclude that global mitigation potential without compromising crop production is 30% (95% confidence interval, 17–53%) of direct soil emissions of N2O, equivalent to the entire direct soil emissions of China and the United States combined. Two-thirds (65%) of the mitigation potential could be achieved on one-fifth of the global harvested area, mainly located in humid subtropical climates and across gleysols and acrisols. These findings highlight the value of a targeted policy approach on global hotspots that could deliver large N2O mitigation as well as environmental and food co-benefits.

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Fig. 1: Spatial patterns of N2O EFs for direct soil emissions.
Fig. 2: Relative importance by variable in shaping EF patterns.
Fig. 3: Distribution of dominant drivers regulating variation in N2O EFs.
Fig. 4: Global cropland N2O mitigation potentials by crop.

Data availability

The global cropland N2O emission observation datasets compiled for this study are available in Supplementary Data 1. The global input datasets of fertilization, irrigation and tillage practices developed for this study are available at https://doi.org/10.6084/m9.figshare.14842965. The model outputs, including global gridded maps of N2O EFs and mitigation potential (including means and 95% CIs), are available at https://doi.org/10.6084/m9.figshare.14844069. The climate data are available at https://crudata.uea.ac.uk/cru/data/hrg/. The soil data are available at https://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/. The harvested area and crop yield data are available at http://www.earthstat.org/harvested-area-yield-175-crops/. Source data are provided with this paper.

Code availability

The computer code for statistics, global prediction and uncertainty estimation is available at https://doi.org/10.6084/m9.figshare.16353480.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (grant nos 41671464 to F.Z. and 41830751 to X.J.), the China Postdoctoral Science Foundation (grant no. 2019M660301 to X.C.), the US National Science Foundation (grant no. 1903722 to H.T.) and the French ANR under the CLAND ‘Investissements d'avenir’ programme (grant no. ANR-16-CONV-0003 to P.C.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank Z. Shang from the University of Aberdeen for sharing the dataset that includes growing-season and whole-year EFs and the fallow EF models. We acknowledge field experimentalists for publishing or sharing chamber-based observations of N2O flux. We acknowledge FAO and IFA for national statistics on synthetic fertilizers, and we thank 38 agencies for subnational statistics on synthetic fertilizers. The views expressed in this publication are those of the authors and do not necessarily reflect the views or policies of FAO. We also acknowledge IIASA, CGIAR, the University of East Anglia, the University of Minnesota and V. Porwollik from the Potsdam Institute for Climate Impact Research for sharing other model input data.

Author information

Authors and Affiliations

  1. Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China

    Xiaoqing Cui, Feng Zhou, Wulahati Adalibieke, Yan Bo, Qihui Wang & Dongqiang Zhu

  2. Laboratoire des Sciences du Climat et de l’Environnement, LSCE, Gif sur Yvette, France

    Philippe Ciais

  3. Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus

    Philippe Ciais

  4. Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, USA

    Eric A. Davidson

  5. Statistics Division, Food and Agriculture Organization of the United Nations, Rome, Italy

    Francesco N. Tubiello

  6. Department of Statistics, The Pennsylvania State University, State College, PA, USA

    Xiaoyue Niu

  7. College of Tropical Crops, Hainan University, Haikou, China

    Xiaotang Ju

  8. Global Carbon Project, CSIRO Oceans and Atmosphere, Canberra, Australian Capital Territory, Australia

    Josep G. Canadell

  9. Department of Earth Sciences – Geochemistry, Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands

    Alexander F. Bouwman

  10. PBL Netherlands Environmental Assessment Agency, the Hague, the Netherlands

    Alexander F. Bouwman

  11. Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao, China

    Alexander F. Bouwman

  12. Department of Earth System Science, Woods Institute for the Environment, and Precourt Institute for Energy, Stanford University, Stanford, CA, USA

    Robert B. Jackson

  13. Department of Ecosystem Science and Sustainability and Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA

    Nathaniel D. Mueller

  14. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

    Xunhua Zheng

  15. Department of Environmental Studies, New York University, New York, NY, USA

    David R. Kanter

  16. International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, USA

    Hanqin Tian

  17. Agricultural Clean Watershed Research Group, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China

    Xiaoying Zhan

Authors
  1. Xiaoqing Cui
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  2. Feng Zhou
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Contributions

F.Z. designed the study. X.C., X.N. and F.Z. performed all computational analyses. F.Z. and X.C. drafted the paper. X.C., Q.W., W.A., X. Zhan and Y.B. collected the data and prepared the figures and tables. All authors reviewed and commented on the manuscript.

Corresponding author

Correspondence to Feng Zhou.

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The authors declare no competing interests.

Additional information

Peer review information Nature Food thanks David Makowski, Klaus Butterbach-Bahl and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Texts 1–4, Figs. 1–26 and Tables 1–13.

Reporting Summary

Supplementary Data 1

Global cropland N2O emission observation dataset.

Source data

Source Data Fig. 1

Unprocessed western blots and/or gels.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Unprocessed western blots and/or gels.

Source Data Fig. 4

Statistical source data.

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Cui, X., Zhou, F., Ciais, P. et al. Global mapping of crop-specific emission factors highlights hotspots of nitrous oxide mitigation. Nat Food 2, 886–893 (2021). https://doi.org/10.1038/s43016-021-00384-9

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