Preprints
https://doi.org/10.5194/egusphere-2026-1482
https://doi.org/10.5194/egusphere-2026-1482
26 Mar 2026
 | 26 Mar 2026
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Towards a Remote Sensing Solution to Quantify Nitrous Oxide Emissions by Integrating Shortwave and Thermal Infrared Bands

Ayesha Riaz, Kang Sun, Brian D. Baker, Brian Buma, Karen E. Cady-Pereira, Christopher Chan Miller, William C. Eddy III, Betsy M. Farris, Thomas U. Kampe, Eric A. Kort, Nathan P. Leisso, Robert Spurr, Emily R. Stuchiner, and Wendy H. Yang

Abstract. Nitrous oxide (N2O) is a potent greenhouse gas whose emissions are dominated by natural and agricultural soils and are highly heterogeneous and episodic, yet existing observational techniques lack the spatial coverage and near-surface sensitivity needed to resolve this variability. In this study, we evaluate a remote sensing framework that integrates shortwave infrared (SWIR) and thermal infrared (TIR) spectral bands to enhance the detectability of column-integrated N2O mixing ratio (XN2O). To implement this, we expand the capacity of the SPLAT–VLIDORT radiative transfer model to jointly simulate both spectral regions and apply linear sensitivity analysis to quantify the XN2O measurement error and vertical sensitivity under realistic environmental conditions and instrumental designs. This framework is applied to both airborne and spaceborne instruments to evaluate the influence of platform characteristics on retrieval performance. The joint SWIR–TIR setting improves near-surface sensitivity relative to the TIR band alone while maintaining the low XN2O measurement error. It achieves single-sounding measurement error of approximately 3.2 ppb for an airborne instrument with a ground footprint size of 20 m and 1.1 ppb for spaceborne instrument with a footprint size of 0.7 km, while retaining sensitivity to the near-surface layers. Assuming XN2O variability is observable at twice the precision, natural XN2O variability inferred from in situ aircraft N2O observations in the US Midwest becomes observable beyond spatial aggregation scales of ∼ 2.5 km for airborne and ∼ 22 km for spaceborne instruments, subject to significant XN2O variation between flights. An independent, emission-based detectability analysis indicates that XN2O variability induced by uniform emissions of 5 nmol m−2 s−1 becomes observable beyond spatial averaging of about 2.1 km for airborne and 8.4 km for spaceborne instruments. Together, these results constitute a quantitative basis for N2O detectability using a joint SWIR–TIR setting, with a focus on diffuse soil emissions that are more difficult to detect yet dominate the global N2O budget, and they provide practical guidance for future N2O dedicated missions.

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Ayesha Riaz, Kang Sun, Brian D. Baker, Brian Buma, Karen E. Cady-Pereira, Christopher Chan Miller, William C. Eddy III, Betsy M. Farris, Thomas U. Kampe, Eric A. Kort, Nathan P. Leisso, Robert Spurr, Emily R. Stuchiner, and Wendy H. Yang

Status: open (until 01 May 2026)

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Ayesha Riaz, Kang Sun, Brian D. Baker, Brian Buma, Karen E. Cady-Pereira, Christopher Chan Miller, William C. Eddy III, Betsy M. Farris, Thomas U. Kampe, Eric A. Kort, Nathan P. Leisso, Robert Spurr, Emily R. Stuchiner, and Wendy H. Yang
Ayesha Riaz, Kang Sun, Brian D. Baker, Brian Buma, Karen E. Cady-Pereira, Christopher Chan Miller, William C. Eddy III, Betsy M. Farris, Thomas U. Kampe, Eric A. Kort, Nathan P. Leisso, Robert Spurr, Emily R. Stuchiner, and Wendy H. Yang
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Latest update: 26 Mar 2026
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Short summary
N2O is a powerful greenhouse gas mainly released from agricultural soils, but its emissions are difficult to track as they vary strongly in space and time. We tested whether combining two kind of infrared measurements in one instrument could improve ability of airborne and satellite instruments to observe these emissions. We found that this combined approach improves sensitivity to near-surface emissions with low measurement error and could guide the design of future N2O dedicated missions.
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