94 citations as recorded by crossref.

1. Limited impact of El Niño–Southern Oscillation on variability and growth rate of atmospheric methane H. Schaefer et al. 10.5194/bg-15-6371-2018
2. Assimilation of atmospheric methane products into the MACC-II system: from SCIAMACHY to TANSO and IASI S. Massart et al. 10.5194/acp-14-6139-2014
3. Large XCH4 anomaly in summer 2013 over northeast Asia observed by GOSAT M. Ishizawa et al. 10.5194/acp-16-9149-2016
4. Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane Y. Zhang et al. 10.5194/acp-18-15959-2018
5. Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements J. Landgraf et al. 10.5194/amt-9-4955-2016
6. Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition H. Nesser et al. 10.5194/amt-14-5521-2021
7. Separation of biospheric and fossil fuel fluxes of CO2 by atmospheric inversion of CO2 and 14CO2 measurements: Observation System Simulations S. Basu et al. 10.5194/acp-16-5665-2016
8. Analyzing spatio-temporal patterns in atmospheric carbon dioxide concentration across Iran from 2003 to 2020 S. Mousavi et al. 10.1016/j.aeaoa.2022.100163
9. Global methane emission estimates for 2000–2012 from CarbonTracker Europe-CH4 v1.0 A. Tsuruta et al. 10.5194/gmd-10-1261-2017
10. On the use of satellite-derived CH4 : CO2 columns in a joint inversion of CH4 and CO2 fluxes S. Pandey et al. 10.5194/acp-15-8615-2015
11. The operational methane retrieval algorithm for TROPOMI H. Hu et al. 10.5194/amt-9-5423-2016
12. A study of synthetic 13CH4 retrievals from TROPOMI and Sentinel-5/UVNS E. Malina et al. 10.5194/amt-12-6273-2019
13. Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. 10.5194/acp-16-14371-2016
14. The unintended consequences of antiflaring policies—and measures for mitigation R. Calel & P. Mahdavi 10.1073/pnas.2006774117
15. Methane Mitigation: Methods to Reduce Emissions, on the Path to the Paris Agreement E. Nisbet et al. 10.1029/2019RG000675
16. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
17. The Global Methane Budget 2000–2017 M. Saunois et al. 10.5194/essd-12-1561-2020
18. Copernicus Climate Change Service (C3S) Global Satellite Observations of Atmospheric Carbon Dioxide and Methane M. Buchwitz et al. 10.1007/s42423-018-0004-6
19. The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017 A. Petrescu et al. 10.5194/essd-13-2307-2021
20. Quantification of methane emitted by ruminants: a review of methods L. Tedeschi et al. 10.1093/jas/skac197
21. CH4 Fluxes Derived from Assimilation of TROPOMI XCH4 in CarbonTracker Europe-CH4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes A. Tsuruta et al. 10.3390/rs15061620
22. Automatic processing of atmospheric CO2 and CH4 mole fractions at the ICOS Atmosphere Thematic Centre L. Hazan et al. 10.5194/amt-9-4719-2016
23. The amplitude of the CO2 seasonal cycle in the atmosphere of the Ural region retrieved from ground-based and satellite near-IR measurements N. Rokotyan et al. 10.1134/S102485601501011X
24. Age of air as a diagnostic for transport timescales in global models M. Krol et al. 10.5194/gmd-11-3109-2018
25. Partitioning anthropogenic and natural methane emissions in Finland during 2000–2021 by combining bottom-up and top-down estimates M. Tenkanen et al. 10.5194/acp-25-2181-2025
26. Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability A. Ostler et al. 10.5194/amt-7-4081-2014
27. Inverse modeling of GOSAT-retrieved ratios of total column CH4 and CO2 for 2009 and 2010 S. Pandey et al. 10.5194/acp-16-5043-2016
28. Relating Multi-Scale Plume Detection and Area Estimates of Methane Emissions: A Theoretical and Empirical Analysis S. Pandey et al. 10.1021/acs.est.4c07415
29. Limited evidence that tropical inundation and precipitation powered the 2020–2022 methane surge Y. Xiong et al. 10.1038/s43247-025-02438-3
30. In situ observations of the isotopic composition of methane at the Cabauw tall tower site T. Röckmann et al. 10.5194/acp-16-10469-2016
31. Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations R. Locatelli et al. 10.5194/acp-15-9765-2015
32. Inverse modelling of carbonyl sulfide: implementation, evaluation and implications for the global budget J. Ma et al. 10.5194/acp-21-3507-2021
33. Seasonality and interannual variability of CH4 fluxes from the eastern Amazon Basin inferred from atmospheric mole fraction profiles L. Basso et al. 10.1002/2015JD023874
34. Observation and integrated Earth-system science: A roadmap for 2016–2025 A. Simmons et al. 10.1016/j.asr.2016.03.008
35. Variability and quasi-decadal changes in the methane budget over the period 2000–2012 M. Saunois et al. 10.5194/acp-17-11135-2017
36. Trends and variability in methane concentrations over the Southeastern Arabian Peninsula D. Francis et al. 10.3389/fenvs.2023.1177877
37. Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes H. Lindqvist et al. 10.3390/rs16162979
38. A three-dimensional-model inversion of methyl chloroform to constrain the atmospheric oxidative capacity S. Naus et al. 10.5194/acp-21-4809-2021
39. The Role of Emission Sources and Atmospheric Sink in the Seasonal Cycle of CH4 and δ13-CH4: Analysis Based on the Atmospheric Chemistry Transport Model TM5 V. Kangasaho et al. 10.3390/atmos13060888
40. Using Atmospheric Inverse Modelling of Methane Budgets with Copernicus Land Water and Wetness Data to Detect Land Use-Related Emissions M. Tenkanen et al. 10.3390/rs16010124
41. What do physicians think about the white coat, about patients' view of the white coat, and how empathetic are physicians toward patients in hospital gowns? An enclothed cognition view G. Gabay et al. 10.3389/fpsyg.2024.1371105
42. Quantifying Methane Emissions Using Satellite Data: Application of the Integrated Methane Inversion (IMI) Model to Assess Danish Emissions A. Vara-Vela et al. 10.3390/rs16234554
43. The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
44. Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions A. Babenhauserheide et al. 10.5194/acp-15-9747-2015
45. Regional CO2 inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0 G. Monteil & M. Scholze 10.5194/gmd-14-3383-2021
46. Evaluating CMIP6 models for CO2 and CH4 concentrations across Africa: performance, biases, and implications for climate predictions G. Magara et al. 10.1007/s00382-025-07679-8
47. Regional Methane Emission Estimation Based on Observed Atmospheric Concentrations (2002-2012) P. PATRA et al. 10.2151/jmsj.2016-006
48. Design of a high-coverage ground-based CO2 monitoring layout using a novel information theory-based optimization model P. Bakhtiari et al. 10.1007/s10661-021-08933-2
49. On the Causes and Consequences of Recent Trends in Atmospheric Methane H. Schaefer 10.1007/s40641-019-00140-z
50. Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model I. Stanevich et al. 10.5194/gmd-13-3839-2020
51. Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observations X. Lu et al. 10.5194/acp-21-4637-2021
52. A 15-year record of CO emissions constrained by MOPITT CO observations Z. Jiang et al. 10.5194/acp-17-4565-2017
53. Combined assimilation of NOAA surface and MIPAS satellite observations to constrain the global budget of carbonyl sulfide J. Ma et al. 10.5194/acp-24-6047-2024
54. Atmospheric transport and chemistry of trace gases in LMDz5B: evaluation and implications for inverse modelling R. Locatelli et al. 10.5194/gmd-8-129-2015
55. Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties R. Parker et al. 10.5194/amt-8-4785-2015
56. Inverse modelling of CH4 emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY M. Alexe et al. 10.5194/acp-15-113-2015
57. Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. 10.1016/j.rse.2016.12.027
58. CarbonTracker-CH4: an assimilation system for estimating emissions of atmospheric methane L. Bruhwiler et al. 10.5194/acp-14-8269-2014
59. U.S. CH4 emissions from oil and gas production: Have recent large increases been detected? L. Bruhwiler et al. 10.1002/2016JD026157
60. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models? Z. Tan et al. 10.5194/acp-16-12649-2016
61. Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1 J. He et al. 10.5194/acp-20-805-2020
62. Diagnostic methods for atmospheric inversions of long-lived greenhouse gases A. Michalak et al. 10.5194/acp-17-7405-2017
63. Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al. 10.5194/amt-15-4819-2022
64. Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model L. Qin et al. 10.1016/j.atmosenv.2023.120207
65. Global CH4 fluxes derived from JAXA/GOSAT lower-tropospheric partial column data and the CarbonTracker Europe-CH4 atmospheric inverse model A. Tsuruta et al. 10.5194/acp-25-7829-2025
66. Methane fluxes in the high northern latitudes for 2005–2013 estimated using a Bayesian atmospheric inversion R. Thompson et al. 10.5194/acp-17-3553-2017
67. Error Budget of the MEthane Remote LIdar missioN and Its Impact on the Uncertainties of the Global Methane Budget P. Bousquet et al. 10.1029/2018JD028907
68. Emissions of methane in Europe inferred by total column measurements D. Wunch et al. 10.5194/acp-19-3963-2019
69. Order of magnitude wall time improvement of variational methane inversions by physical parallelization: a demonstration using TM5-4DVAR S. Pandey et al. 10.5194/gmd-15-4555-2022
70. The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019 A. Petrescu et al. 10.5194/essd-15-1197-2023
71. Characterisation of methane sources in Lutjewad, The Netherlands, using quasi-continuous isotopic composition measurements M. Menoud et al. 10.1080/16000889.2020.1823733
72. XCO2 observations using satellite measurements with moderate spectral resolution: investigation using GOSAT and OCO-2 measurements L. Wu et al. 10.5194/amt-13-713-2020
73. Satellite-derived methane hotspot emission estimates using a fast data-driven method M. Buchwitz et al. 10.5194/acp-17-5751-2017
74. Utilizing Earth Observations of Soil Freeze/Thaw Data and Atmospheric Concentrations to Estimate Cold Season Methane Emissions in the Northern High Latitudes M. Tenkanen et al. 10.3390/rs13245059
75. Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements L. Wu et al. 10.5194/amt-11-3111-2018
76. Model simulations of atmospheric methane (1997–2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations P. Zimmermann et al. 10.5194/acp-20-5787-2020
77. A Review of Satellite-Based CO2 Data Reconstruction Studies: Methodologies, Challenges, and Advances K. Hu et al. 10.3390/rs16203818
78. Global and Regional CH4 Emissions for 1995–2013 Derived From Atmospheric CH4, δ13C‐CH4, and δD‐CH4 Observations and a Chemical Transport Model R. Fujita et al. 10.1029/2020JD032903
79. Methane budget estimates in Finland from the CarbonTracker Europe-CH₄ data assimilation system A. Tsuruta et al. 10.1080/16000889.2018.1565030
80. Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions A. Ražnjević et al. 10.5194/amt-15-3611-2022
81. Retrieval of atmospheric CH4 vertical information from ground-based FTS near-infrared spectra M. Zhou et al. 10.5194/amt-12-6125-2019
82. Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments Z. Qu et al. 10.5194/acp-21-14159-2021
83. The description and validation of the computationally Efficient CH4–CO–OH (ECCOHv1.01) chemistry module for 3-D model applications Y. Elshorbany et al. 10.5194/gmd-9-799-2016
84. Atmospheric methane evolution the last 40 years S. Dalsøren et al. 10.5194/acp-16-3099-2016
85. Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere A. Ostler et al. 10.5194/amt-9-4843-2016
86. AirCore-HR: a high-resolution column sampling to enhance the vertical description of CH4 and CO2 O. Membrive et al. 10.5194/amt-10-2163-2017
87. Global Atmospheric δ13CH4 and CH4 Trends for 2000–2020 from the Atmospheric Transport Model TM5 Using CH4 from Carbon Tracker Europe–CH4 Inversions V. Mannisenaho et al. 10.3390/atmos14071121
88. The global methane budget 2000–2012 M. Saunois et al. 10.5194/essd-8-697-2016
89. Interpreting contemporary trends in atmospheric methane A. Turner et al. 10.1073/pnas.1814297116
90. High-resolution US methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills H. Nesser et al. 10.5194/acp-24-5069-2024
91. A 21st-century shift from fossil-fuel to biogenic methane emissions indicated by 13 CH 4 H. Schaefer et al. 10.1126/science.aad2705
92. Global inverse modeling of CH4 sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
93. Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications B. Ringeval et al. 10.5194/bg-11-1519-2014
94. Carbon Monitoring Satellite (CarbonSat): assessment of atmospheric CO2 and CH4 retrieval errors by error parameterization M. Buchwitz et al. 10.5194/amt-6-3477-2013