Can radon help to improve methane emission estimates? Results from a dual-tracer inversion
- 1Max Planck Institute for Biogeochemistry (Jena, Germany)
Abstract
A major source of uncertainty in inverse modelling of greenhouse gas emissions are deficits in atmospheric transport models, in particular in the description of vertical mixing within the planetary boundary layer (PBL). The properties of radon-222 (Rn) makes it a suitable natural tracer for vertical mixing in the PBL. When comparing the CH ₄ model-data mismatch (MDM), i.e. the differences between the observed and modelled CH ₄ concentrations, with the MDM of Rn, we found substantial correlations for several observation sites in central Europe in 2021 (the median CH ₄ -Rn MDM correlation coefficient is 0.6), indicating that a large part of the CH ₄ and Rn MDM variability can be explained by common errors in the simulated (vertical) transport. We aim to exploit this information in a joint inversion for CH ₄ and Rn by taking into account prior uncertainties and making use of the fact that the transport model error is correlated between the two gases. We use simultaneous CH ₄ and Rn observations from 17 sites across central Europe in 2021. The dual-tracer CH ₄ -Rn inversion yields lower CH ₄ fluxes in several countries covered by the observation sites compared to a single-tracer CH ₄ -only inversion without Rn information. The differences in country-total CH ₄ fluxes between the dual-tracer and single-tracer inversions are on the order of a few percent and depend on the assumed uncertainty for the Rn prior fluxes. These findings underscore the importance of accurate Rn flux maps for fully leveraging the dual-tracer approach and enhancing the reliability of CH ₄ flux estimates.
Versions
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BibTeX
@article{maier2026radon,
title = {{Can radon help to improve methane emission estimates? Results from a dual-tracer inversion}},
author = {Fabian Maier and Christian Rödenbeck and Ute Karstens and Frank-Thomas Koch and Maksym Gachkivskyi and Andrew Smerald and Christoph Gerbig},
journal = {Atmospheric Chemistry and Physics},
year = {2026},
month = oct,
doi = {10.5194/acp-26-14699-2026},
url = {https://acp.copernicus.org/articles/26/14699/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Can radon help to improve methane emission estimates? Results from a dual-tracer inversion
AU - Fabian Maier
AU - Christian Rödenbeck
AU - Ute Karstens
AU - Frank-Thomas Koch
AU - Maksym Gachkivskyi
AU - Andrew Smerald
AU - Christoph Gerbig
PY - 2026
DA - 2026/10/20
JO - Atmospheric Chemistry and Physics
DO - 10.5194/acp-26-14699-2026
UR - https://acp.copernicus.org/articles/26/14699/2026/
AB - A major source of uncertainty in inverse modelling of greenhouse gas emissions are deficits in atmospheric transport models, in particular in the description of vertical mixing within the planetary boundary layer (PBL). The properties of radon-222 (Rn) makes it a suitable natural tracer for vertical mixing in the PBL. When comparing the CH ₄ model-data mismatch (MDM), i.e. the differences between the observed and modelled CH ₄ concentrations, with the MDM of Rn, we found substantial correlations for several observation sites in central Europe in 2021 (the median CH ₄ -Rn MDM correlation coefficient is 0.6), indicating that a large part of the CH ₄ and Rn MDM variability can be explained by common errors in the simulated (vertical) transport. We aim to exploit this information in a joint inversion for CH ₄ and Rn by taking into account prior uncertainties and making use of the fact that the transport model error is correlated between the two gases. We use simultaneous CH ₄ and Rn observations from 17 sites across central Europe in 2021. The dual-tracer CH ₄ -Rn inversion yields lower CH ₄ fluxes in several countries covered by the observation sites compared to a single-tracer CH ₄ -only inversion without Rn information. The differences in country-total CH ₄ fluxes between the dual-tracer and single-tracer inversions are on the order of a few percent and depend on the assumed uncertainty for the Rn prior fluxes. These findings underscore the importance of accurate Rn flux maps for fully leveraging the dual-tracer approach and enhancing the reliability of CH ₄ flux estimates.
SN - 1680-7324
ER -