Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 26, issue 14
Articles | Volume 26, issue 14
https://doi.org/10.5194/acp-26-10477-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-10477-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 14
Research article
 | 
27 Jul 2026
Research article |  | 27 Jul 2026

Exploring atmospheric CH4 monitoring network expansion in Italy using inverse modelling

Joël Thanwerdas, Paolo Cristofanelli, Angela Fiore, Rianne Dröge, Sophie Van Mil, Yohanna Villalobos, Zhendong Wu, and Dominik Brunner

Supplement

https://doi.org/10.5194/acp-26-10477-2026-supplement

Data sets

Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate Hans Hersbach et al. https://doi.org/10.24381/cds.143582cf

ERA5 hourly data on single levels from 1940 to present Hans Hersbach et al. https://doi.org/10.24381/cds.adbb2d47

European anthropogenic emissions of CO2, CH4 and N2O 2010-2021 for AVENGERS Sophie van Mil et al. https://doi.org/10.18160/TGMJ-4YGJ

Investigation of the post-2007 methane renewed growth with high-resolution 3-D variational inverse modelling and isotopic constraints - Input data Joël Thanwerdas https://doi.org/10.5281/zenodo.10390430

Model code and software

ICON release 2024.01 ICON partnership (DWD; MPI-M; DKRZ; KIT; C2SM) https://doi.org/10.35089/WDCC/IconRelease01

The Community Inversion Framework: codes and documentation (v1.2) Antoine Berchet et al. https://doi.org/10.5281/zenodo.12742377

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Short summary
We assess how expanding Italy’s sparse ICOS (Integrated Carbon Observation System) methane network could improve methane emission estimates. Using transport modelling, data assimilation methods and synthetic observations, we test eight candidate sites. Chieti, in Central Italy and Mount Venda, in Northern Italy, provide the strongest added constraints, respectively. The framework developed here can be applied to other countries to optimize their atmospheric measurement networks and to improve constraints on greenhouse gas emissions.
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