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Soil nitrite measurements have potential to estimate nitrous oxide emissions

Abstract

Spatio-temporal fluctuations in soil N2O emissions are well documented, but it is difficult to predict the location of ‘hot spots’ and the timing of ‘hot moments’ of N2O emissions from agroecosystems with dynamic, heterogeneous soil environments. Although the soil nitrite (NO2) concentration is a potential indicator of soil N2O production, it is seldom measured. This perspective paper explains the emerging methods for NO2 quantification with ion-selective electrodes and infrared spectroscopy, and describes how these tools may be used to adjust nitrogen fertilization through site-specific management. We envision a new system for soil N2O mitigation that integrates knowledge from portable NO2 sensors, machine learning, and the internet of things to predict the ‘hot spots’ and ‘hot moments’ of N2O in agroecosystems. This integrated system will produce a real-time soil NO2 map that is validated by in situ soil NO2 sensors. The integrated system requires further development of ion-selective electrodes and spectrometric methods for real-time NO2 quantification under field conditions, as well as appropriate machine learning models and communication technologies. Our concept supports the adoption of site-specific nitrogen fertilizer management as a strategy to reduce soil N2O emissions from agroecosystems.

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Acknowledgements

We sincerely acknowledge the financial support of the Natural Science and Engineer Research Council of Canada (NSERC) through Discovery Grant # RGPIN–2017–05391 and the AgroPhytoSciences program (NSERC-CREATE 449133-2014). We also sincerely thank Yu-Yi Tsai for helping with the artwork.

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Correspondence to Joann K. Whalen.

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Hung, CY., Whalen, J.K. Soil nitrite measurements have potential to estimate nitrous oxide emissions. Nutr Cycl Agroecosyst 118, 1–8 (2020). https://doi.org/10.1007/s10705-020-10079-5

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Keywords

  • Nitrous oxide mitigation
  • Real-time soil sensor
  • Ion-selective electrode
  • Near-infrared spectroscopy
  • Internet of things