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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.

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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.

References

  1. Quan, Z., Zhang, X., Fang, Y. & Davidson, E. A. Different quantification approaches for nitrogen use efficiency lead to divergent estimates with varying advantages. Nat. Food 2, 241–245 (2021).

    Article  Google Scholar 

  2. Emissions from Agriculture and Forest Land: Global, Regional and Country Trends 1990–2019 FAOSTAT Analytical Brief Series No. 25 (FAO, 2021); http://www.fao.org/3/cb5293en/cb5293en.pdf

  3. Tian, H. et al. A comprehensive quantification of global nitrous oxide sources and sinks. Nature 586, 248–256 (2020).

    Article  ADS  CAS  PubMed  Google Scholar 

  4. Clark, M. A. et al. Global food system emissions could preclude achieving the 1.5° and 2 °C climate change targets. Science 370, 705–708 (2020).

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Portmann, R. W., Daniel, J. S. & Ravishankara, A. R. Stratospheric ozone depletion due to nitrous oxide: influences of other gases. Phil. Trans. R. Soc. B 367, 1256–1264 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. The Future of Food and Agriculture: Alternative Pathways to 2050 (FAO, 2018); http://www.fao.org/3/I8429EN/i8429en.pdf

  7. Bodirsky, B. L. et al. Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution. Nat. Commun. 5, 3858 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  8. de Vries, W., Kros, J., Kroeze, C. & Seitzinger, S. P. Assessing planetary and regional nitrogen boundaries related to food security and adverse environmental impacts. Curr. Opin. Environ. Sustain. 5, 392–402 (2013).

    Article  Google Scholar 

  9. Zhang, X. et al. Managing nitrogen for sustainable development. Nature 528, 51–59 (2015).

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Decock, C. Mitigating nitrous oxide emissions from corn cropping systems in the midwestern US: potential and data gaps. Environ. Sci. Technol. 48, 4247–4256 (2014).

    Article  ADS  MathSciNet  CAS  PubMed  Google Scholar 

  11. Groffman, P. M. et al. Challenges to incorporating spatially and temporally explicit phenomena (hotspots and hot moments) in denitrification models. Biogeochemistry 93, 49–77 (2009).

    Article  CAS  Google Scholar 

  12. Ogle, S. M., Butterbach-Bahl, K., Cardenas, L., Skiba, U. & Scheer, C. From research to policy: optimizing the design of a national monitoring system to mitigate soil nitrous oxide emissions. Curr. Opin. Environ. Sustain. 47, 28–36 (2020).

    Article  Google Scholar 

  13. Calvo Buendia, E. et al. (eds) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019).

  14. Gerber, J. S. et al. Spatially explicit estimates of N2O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management. Glob. Change Biol. 22, 3383–3394 (2016).

    Article  ADS  Google Scholar 

  15. Shcherbak, I., Millar, N. & Robertson, G. P. Global metaanalysis of the nonlinear response of soil nitrous oxide (N2O) emissions to fertilizer nitrogen. Proc. Natl Acad. Sci. USA 111, 9199–9204 (2014).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wang, Q. et al. Data-driven estimates of global nitrous oxide emissions from croplands. Natl Sci. Rev. 7, 441–452 (2020).

    Article  CAS  PubMed  Google Scholar 

  17. Dorich, C. D. et al. Improving N2O emission estimates with the global N2O database. Curr. Opin. Environ. Sustain. 47, 13–20 (2020).

    Article  Google Scholar 

  18. Heffer, P., Gruère, A. & Roberts, T. Assessment of Fertilizer Use by Crop at the Global Level (International Fertilizer Association, 2014).

  19. Stehfest, E. & Bouwman, L. N2O and NO emission from agricultural fields and soils under natural vegetation: summarizing available measurement data and modeling of global annual emissions. Nutr. Cycl. Agroecosyst. 74, 207–228 (2006).

    Article  CAS  Google Scholar 

  20. Wang, Y. et al. Soil pH as the chief modifier for regional nitrous oxide emissions: new evidence and implications for global estimates and mitigation. Glob. Change Biol. 24, E617–E626 (2018).

    Article  Google Scholar 

  21. Grueber, C. E., Nakagawa, S., Laws, R. J. & Jamieson, I. G. Multimodel inference in ecology and evolution: challenges and solutions. J. Evol. Biol. 24, 699–711 (2011).

    Article  CAS  PubMed  Google Scholar 

  22. Butterbach-Bahl, K., Baggs, E. M., Dannenmann, M., Kiese, R. & Zechmeister-Boltenstern, S. Nitrous oxide emissions from soils: how well do we understand the processes and their controls? Phil. Trans. R. Soc. B 368, 20130122 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Nelson, M. B., Martiny, A. C. & Martiny, J. B. H. Global biogeography of microbial nitrogen-cycling traits in soil. Proc. Natl Acad. Sci. USA 113, 8033–8040 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Venterea, R. T. Nitrite-driven nitrous oxide production under aerobic soil conditions: kinetics and biochemical controls. Glob. Change Biol. 13, 1798–1809 (2007).

    Article  ADS  Google Scholar 

  25. Griffis, T. J. et al. Nitrous oxide emissions are enhanced in a warmer and wetter world. Proc. Natl Acad. Sci. USA 114, 12081–12085 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  26. Parn, J. et al. Nitrogen-rich organic soils under warm well-drained conditions are global nitrous oxide emission hotspots. Nat. Commun. 9, 1135 (2018).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  27. Wu, G. et al. Effects of soil warming and increased precipitation on greenhouse gas fluxes in spring maize seasons in the North China Plain. Sci. Total Environ. 734, 139269 (2020).

    Article  ADS  CAS  PubMed  Google Scholar 

  28. Balaine, N. et al. Changes in relative gas diffusivity explain soil nitrous oxide flux dynamics. Soil Sci. Soc. Am. J. 77, 1496–1505 (2013).

    Article  ADS  CAS  Google Scholar 

  29. Hall, S. J., Reyes, L., Huang, W. & Homyak, P. M. Wet spots as hotspots: moisture responses of nitric and nitrous oxide emissions from poorly drained agricultural soils. J. Geophys. Res. Biogeosci. 123, 3589–3602 (2018).

    Article  CAS  Google Scholar 

  30. Paustian, K. et al. Climate-smart soils. Nature 532, 49–57 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  31. Jiang, Y. et al. Water management to mitigate the global warming potential of rice systems: a global meta-analysis. Field Crops Res. 234, 47–54 (2019).

    Article  Google Scholar 

  32. Mei, K. et al. Stimulation of N2O emission by conservation tillage management in agricultural lands: a meta-analysis. Soil Tillage Res. 182, 86–93 (2018).

    Article  Google Scholar 

  33. Xia, L. et al. Can knowledge-based N management produce more staple grain with lower greenhouse gas emission and reactive nitrogen pollution? A meta-analysis. Glob. Change Biol. 23, 1917–1925 (2017).

    Article  ADS  Google Scholar 

  34. Cui, Z. et al. Pursuing sustainable productivity with millions of smallholder farmers. Nature 555, 363–366 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  35. EU Nitrogen Expert Panel Nitrogen Use Efficiency (NUE): An Indicator for the Utilization of Nitrogen in Agriculture and Food Systems (Wageningen University, Alterra, 2015).

  36. Springmann, M. et al. Options for keeping the food system within environmental limits. Nature 562, 519–525 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  37. Thompson, R. L. et al. Acceleration of global N2O emissions seen from two decades of atmospheric inversion. Nat. Clim. Change 9, 993–998 (2019).

    Article  ADS  CAS  Google Scholar 

  38. Wagner-Riddle, C. et al. Globally important nitrous oxide emissions from croplands induced by freeze–thaw cycles. Nat. Geosci. 10, 279–283 (2017).

    Article  ADS  CAS  Google Scholar 

  39. Kritee, K. et al. High nitrous oxide fluxes from rice indicate the need to manage water for both long- and short-term climate impacts. Proc. Natl Acad. Sci. USA 115, 9720–9725 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kravchenko, A. N. et al. Hotspots of soil N2O emission enhanced through water absorption by plant residue. Nat. Geosci. 10, 496–500 (2017).

    Article  ADS  CAS  Google Scholar 

  41. Phalke, A. R. et al. Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine. ISPRS J. Photogramm. Remote Sens. 167, 104–122 (2020).

    Article  ADS  Google Scholar 

  42. Roe, S. et al. Contribution of the land sector to a 1.5 °C world. Nat. Clim. Change 9, 817–828 (2019).

    Article  ADS  Google Scholar 

  43. Lam, S. K., Suter, H., Mosier, A. R. & Chen, D. Using nitrification inhibitors to mitigate agricultural N2O emission: a double-edged sword? Glob. Change Biol. 23, 485–489 (2017).

    Article  ADS  Google Scholar 

  44. Liu, Y. et al. Genomic basis of geographical adaptation to soil nitrogen in rice. Nature 590, 600–605 (2021).

    Article  ADS  CAS  PubMed  Google Scholar 

  45. Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 490, 254–257 (2012).

    Article  ADS  CAS  PubMed  Google Scholar 

  46. Zhan, X. et al. Improved estimates of ammonia emissions from global croplands. Environ. Sci. Technol. 55, 1329–1338 (2021).

    Article  ADS  CAS  PubMed  Google Scholar 

  47. Jiang, W. et al. Is rice field a nitrogen source or sink for the environment? Environ. Pollut. 283, 117122 (2021).

    Article  CAS  PubMed  Google Scholar 

  48. Zhang, X. et al. Quantification of global and national nitrogen budgets for crop production. Nat. Food 2, 529–540 (2021).

    Article  Google Scholar 

  49. Kanter, D. R. et al. Nitrogen pollution policy beyond the farm. Nat. Food 1, 27–32 (2020).

    Article  Google Scholar 

  50. van den Hoogen, J. et al. Soil nematode abundance and functional group composition at a global scale. Nature 572, 194–198 (2019).

    Article  ADS  PubMed  Google Scholar 

  51. Bates, D., Maechler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  52. Sacks, W. J., Deryng, D., Foley, J. A. & Ramankutty, N. Crop planting dates: an analysis of global patterns. Glob. Ecol. Biogeogr. 19, 607–620 (2010).

    Google Scholar 

  53. Zhang, B. et al. Global manure nitrogen production and application in cropland during 1860–2014: a 5 arcmin gridded global dataset for Earth system modeling. Earth Syst. Sci. Data 9, 667–678 (2017).

    Article  ADS  Google Scholar 

  54. FAOSTAT Data (FAO, accessed 18 June 2020); http://www.fao.org/faostat/en/#data/GT (Emissions—Agriculture); http://www.fao.org/faostat/en/#data/RL (Land Use)

  55. Cao, P., Lu, C. & Yu, Z. Historical nitrogen fertilizer use in agricultural ecosystems of the contiguous United States during 1850–2015: application rate, timing, and fertilizer types. Earth Syst. Sci. Data 10, 969–984 (2018).

    Article  ADS  Google Scholar 

  56. Compilation Data of National Agricultural Product Cost and Benefit for China (the Ratio of Each Synthetic Fertilizer Product Applied for Each Crop in 2001 and 2005) (China Statistics Press, 2001 and 2005); http://data.cnki.net/Yearbook/Single/N2010090051

  57. Aneja, V. P. et al. Reactive nitrogen emissions from crop and livestock farming in India. Atmos. Environ. 47, 92–103 (2012).

    Article  ADS  CAS  Google Scholar 

  58. IFASTAT Data (International Fertilizer Association, accessed 18 June 2020); https://www.ifastat.org/databases/plant-nutrition

  59. Monfreda, C., Ramankutty, N. & Foley, J. A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Glob. Biogeochem. Cycles 22, GB1022 (2008).

    Article  ADS  Google Scholar 

  60. Porwollik, V., Rolinski, S., Heinke, J. & Müller, C. Generating a rule-based global gridded tillage dataset. Earth Syst. Sci. Data 11, 823–843 (2019).

    Article  ADS  Google Scholar 

  61. Portmann, F. T. Global Estimation of Monthly Irrigated and Rainfed Crop Areas on a 5 Arc-Minute Grid. PhD thesis, Univ. Frankfurt (2011).

  62. Meier, J., Zabel, F. & Mauser, W. A global approach to estimate irrigated areas—a comparison between different data and statistics. HESS 22, 1119–1133 (2018).

    ADS  Google Scholar 

  63. Asia Least-Cost Greenhouse Gas Abatement Strategy (ALGAS) (Asian Development Bank, Global Environment Facility and United Nations Development Program, 1998).

  64. Zhang, W., Yu, Y., Huang, Y., Li, T. & Wang, P. Modeling methane emissions from irrigated rice cultivation in China from 1960 to 2050. Glob. Change Biol. 17, 3511–3523 (2011).

    Article  ADS  Google Scholar 

  65. Carlson, K. M. et al. Greenhouse gas emissions intensity of global croplands. Nat. Clim. Change 7, 63–68 (2017).

    Article  ADS  CAS  Google Scholar 

  66. Barton, K. Mu-MIn: Multi-Model Inference. R package version 0.12.2/r18 (2009); http://R-Forge.R-project.org/projects/mumin/

  67. Beer, C. et al. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329, 834–838 (2010).

    Article  ADS  CAS  Google Scholar 

  68. Maaz, T. M. et al. Meta-analysis of yield and nitrous oxide outcomes for nitrogen management in agriculture. Glob. Change Biol. 27, 2343–2360 (2021).

    Article  ADS  Google Scholar 

  69. Arnhold, E. R-environment package for regression analysis. Pesqui. Agropecu. Bras. 53, 870–873 (2018).

    Article  Google Scholar 

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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

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  1. Xiaoqing Cui
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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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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.

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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.

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Unprocessed western blots and/or gels.

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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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