17 citations as recorded by crossref.

1. Characterizing anthropogenic and biogenic sources of CO2 and CH4 using carbon isotopic signature δ13C in Houston, Texas, USA I. Karim & B. Rappenglück https://doi.org/10.1016/j.atmosenv.2026.122058
2. Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01 J. Thanwerdas et al. https://doi.org/10.5194/gmd-18-1505-2025
3. High-Resolution Global Methane Mapping: Advances in Satellite Remote Sensing, Machine Learning, and Policy Frameworks A. Singh & . Madhubala https://doi.org/10.3390/methane5030021
4. CH4 emissions from Northern Europe wetlands: compared data assimilation approaches G. Monteil et al. https://doi.org/10.5194/acp-25-14251-2025
5. The methane imperative D. Shindell et al. https://doi.org/10.3389/fsci.2024.1349770
6. Inverse modeling of 2010–2022 satellite observations shows that inundation of the wet tropics drove the 2020–2022 methane surge Z. Qu et al. https://doi.org/10.1073/pnas.2402730121
7. Dynamic and high methane emission flux in pond and lake aquaculture J. Zhao et al. https://doi.org/10.1016/j.jhydrol.2025.132765
8. Global Methane Budget 2000–2020 M. Saunois et al. https://doi.org/10.5194/essd-17-1873-2025
9. A global dataset of δ13C-CH4 source signatures and associated uncertainties (1998–2022), with a sensitivity analysis to support isotopic inversions E. Tapin et al. https://doi.org/10.5194/essd-18-4793-2026
10. Fractionation of Methane Isotopologues during Preparation for Analysis from Ambient Air E. Safi et al. https://doi.org/10.1021/acs.analchem.3c04891
11. Distinct dual-isotopic signatures of major methane sources in South Asia P. Yao et al. https://doi.org/10.5194/acp-26-7765-2026
12. Partitioning anthropogenic and natural methane emissions in Finland during 2000–2021 by combining bottom-up and top-down estimates M. Tenkanen et al. https://doi.org/10.5194/acp-25-2181-2025
13. Microbial driver of 2006–2023 CH 4 growth indicated by trends in atmospheric δD–CH 4 and δ 13 C–CH 4 B. Riddell-Young et al. https://doi.org/10.1073/pnas.2516543122
14. Exploring uncertainty reduction in high-resolution methane emissions in Gippsland through in-situ data: A Bayesian inverse modeling and variational assimilation method S. Aghdasi et al. https://doi.org/10.1016/j.atmosres.2025.107911
15. German methane fluxes estimated top-down using ICON–ART – Part 2: Inversion results for 2021 V. Bruch et al. https://doi.org/10.5194/acp-25-17187-2025
16. Incorporating methane isotopologues alters tropical and subtropical methane emission estimates X. Yu et al. https://doi.org/10.1038/s41467-026-72668-2
17. Harmonisation of methane isotope ratio measurements from different laboratories using atmospheric samples B. Dasgupta et al. https://doi.org/10.5194/amt-18-6591-2025