99 citations as recorded by crossref.

1. Declining methane emissions and steady, high leakage rates observed over multiple years in a western US oil/gas production basin J. Lin et al. 10.1038/s41598-021-01721-5
2. Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia I. Ialongo et al. 10.1016/j.aeaoa.2021.100114
3. Atmospheric Greenhouse Gas Distributions: Satellite-Based Measurements A. Uspensky 10.1134/S0001433823140141
4. Estimation of CH4emission based on an advanced 4D-LETKF assimilation system J. Bisht et al. 10.5194/gmd-16-1823-2023
5. Monitoring Methane Emissions from Oil and Gas Operations W. Collins et al. 10.1103/PRXEnergy.1.017001
6. Occurrence and Discrepancy of Surface and Column Mole Fractions of CO2 and CH4 at a Desert Site in Dunhuang, Western China C. Wei et al. 10.3390/atmos13040571
7. Toward a versatile spaceborne architecture for immediate monitoring of the global methane pledge Y. Wang et al. 10.5194/acp-23-5233-2023
8. CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model D. Pendergrass et al. 10.5194/gmd-16-4793-2023
9. Methane retrievals from airborne HySpex observations in the shortwave infrared P. Hochstaffl et al. 10.5194/amt-16-4195-2023
10. Satellite-Derived Estimate of City-Level Methane Emissions from Calgary, Alberta, Canada Z. Xing et al. 10.3390/rs16071149
11. Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations C. Alberti et al. 10.5194/amt-15-2199-2022
12. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
13. The Impact of the 2020 Oil Production Fluctuations on Methane Emissions over the Gulf Cooperation Council (GCC) Countries: A Satellite Approach A. Farahat 10.3390/atmos13010011
14. Comparing satellite methane measurements to inventory estimates: A Canadian case study L. Dubey et al. 10.1016/j.aeaoa.2022.100198
15. Ship- and aircraft-based XCH4 over oceans as a new tool for satellite validation A. Müller et al. 10.5194/amt-17-1297-2024
16. Permafrost carbon emissions in a changing Arctic K. Miner et al. 10.1038/s43017-021-00230-3
17. A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel‐5P TROPOMI M. Liu et al. 10.1029/2021GL094151
18. The Spatial and Temporal Distribution Patterns of XCH4 in China: New Observations from TROPOMI J. Zhang et al. 10.3390/atmos13020177
19. Simultaneous Retrieval of Trace Gases, Aerosols, and Cirrus Using RemoTAP—The Global Orbit Ensemble Study for the CO2M Mission S. Lu et al. 10.3389/frsen.2022.914378
20. Evaluation of Korean methane emission sources with satellite retrievals by spatial correlation analysis J. Moon et al. 10.1007/s10661-024-12449-w
21. Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations M. Sha et al. 10.5194/amt-14-6249-2021
22. Monitoring methane emissions from oil and gas operations‡ W. Collins et al. 10.1364/OE.464421
23. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
24. Minimizing the impacts of the ammonia economy on the nitrogen cycle and climate M. Bertagni et al. 10.1073/pnas.2311728120
25. Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al. 10.1080/01431161.2023.2240028
26. Random Forest Classifier for Cloud Clearing of the Operational TROPOMI XCH4 Product T. Borsdorff et al. 10.3390/rs16071208
27. Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm O. Schneising et al. 10.5194/amt-16-669-2023
28. Trends and variability in methane concentrations over the Southeastern Arabian Peninsula D. Francis et al. 10.3389/fenvs.2023.1177877
29. Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun 10.1029/2022GL101102
30. Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins L. Shen et al. 10.5194/acp-22-11203-2022
31. Spatiotemporal Variations of XCH4 across China during 2003–2021 Based on Observations from Multiple Satellites J. Qin et al. 10.3390/atmos13091362
32. Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images P. Joyce et al. 10.5194/amt-16-2627-2023
33. Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al. 10.5194/acp-22-5961-2022
34. Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al. 10.1016/j.rse.2024.114039
35. The added value of satellite observations of methane forunderstanding the contemporary methane budget P. Palmer et al. 10.1098/rsta.2021.0106
36. Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action Z. Chen et al. 10.5194/acp-23-5945-2023
37. Intercomparison of CH4 Products in China from GOSAT, TROPOMI, IASI, and AIRS Satellites Q. Ni et al. 10.3390/rs15184499
38. Design and description of the MUSICA IASI full retrieval product M. Schneider et al. 10.5194/essd-14-709-2022
39. Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations D. Varon et al. 10.5194/gmd-15-5787-2022
40. An optimal estimation-based retrieval of upper atmospheric oxygen airglow and temperature from SCIAMACHY limb observations K. Sun et al. 10.5194/amt-15-3721-2022
41. Meteorological Drivers of Permian Basin Methane Anomalies Derived from TROPOMI E. Crosman 10.3390/rs13050896
42. COVID-19 slowdown induced improvement in air quality in India: rapid assessment using Sentinel-5P TROPOMI data M. Behera et al. 10.1080/10106049.2021.1993351
43. Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season C. Karoff & A. Vara-Vela 10.3389/feart.2023.1119977
44. Use of Differential Optical Spectroscopy for Satellite Diagnostics of Methane Content in a Scattering Atmosphere A. Bril et al. 10.1007/s10812-023-01635-2
45. Quantification of Central and Eastern China's atmospheric CH4 enhancement changes and its contributions based on machine learning approach X. Ai et al. 10.1016/j.jes.2023.03.010
46. FTIR Measurements of Greenhouse Gases over Thessaloniki, Greece in the Framework of COCCON and Comparison with S5P/TROPOMI Observations M. Mermigkas et al. 10.3390/rs13173395
47. Latitudinal distribution and sources analysis of greenhouse gases and air pollutants observed during the 2021 Yellow Sea Air Quality campaign aboard a research vessel S. Li et al. 10.1016/j.atmosenv.2023.120201
48. The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product N. Jacobs et al. 10.5194/amt-17-1375-2024
49. Reconstructing and quantifying methane emissions from the full duration of a 38-day natural gas well blowout using space-based observations J. Maasakkers et al. 10.1016/j.rse.2021.112755
50. Trends in Satellite Earth Observation for Permafrost Related Analyses—A Review M. Philipp et al. 10.3390/rs13061217
51. On the influence of underlying elevation data on Sentinel-5 Precursor TROPOMI satellite methane retrievals over Greenland J. Hachmeister et al. 10.5194/amt-15-4063-2022
52. Long-Term Trends and Spatiotemporal Variations in Atmospheric XCH4 over China Utilizing Satellite Observations J. Xu et al. 10.3390/atmos13040525
53. Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al. 10.5194/acp-23-7503-2023
54. Evaluation of the methane full-physics retrieval applied to TROPOMI ocean sun glint measurements A. Lorente et al. 10.5194/amt-15-6585-2022
55. 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
56. Underestimated Dry Season Methane Emissions from Wetlands in the Pantanal M. Li et al. 10.1021/acs.est.3c09250
57. An integrated analysis of air pollution from US coal-fired power plants M. Filonchyk & M. Peterson 10.1016/j.gsf.2022.101498
58. Mineral Luminescence Observed From Space P. Köhler et al. 10.1029/2021GL095227
59. Spatiotemporal Variability of Global Atmospheric Methane Observed from Two Decades of Satellite Hyperspectral Infrared Sounders L. Zhou et al. 10.3390/rs15122992
60. Spatiotemporal variation in near-surface CH4 concentrations in China over the last two decades J. Xu et al. 10.1007/s11356-021-14007-0
61. Temporal variation of surface reflectance and cloud fraction used to identify background aerosol retrieval information over East Asia S. Park et al. 10.1016/j.atmosenv.2023.119916
62. Investigating high methane emissions from urban areas detected by TROPOMI and their association with untreated wastewater B. de Foy et al. 10.1088/1748-9326/acc118
63. Using satellites to uncover large methane emissions from landfills J. Maasakkers et al. 10.1126/sciadv.abn9683
64. A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases N. Balasus et al. 10.5194/amt-16-3787-2023
65. How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35) X. Yu et al. 10.5194/gmd-14-7775-2021
66. Estimating Drivers and Pathways for Hydroelectric Reservoir Methane Emissions Using a New Mechanistic Model K. Delwiche et al. 10.1029/2022JG006908
67. Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
68. Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products M. Schneider et al. 10.5194/amt-15-4339-2022
69. Accounting for surface reflectance spectral features in TROPOMI methane retrievals A. Lorente et al. 10.5194/amt-16-1597-2023
70. Role of space station instruments for improving tropical carbon flux estimates using atmospheric data P. Palmer et al. 10.1038/s41526-022-00231-6
71. Large Methane Emission Fluxes Observed From Tropical Wetlands in Zambia J. Shaw et al. 10.1029/2021GB007261
72. Methods for quantifying methane emissions using unmanned aerial vehicles: a review J. Shaw et al. 10.1098/rsta.2020.0450
73. National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations L. Shen et al. 10.1038/s41467-023-40671-6
74. Seasonal and Diurnal Variations in XCO2 Characteristics in China as Observed by OCO‐2/3 Satellites: Effects of Land Cover and Local Meteorology H. Zhao et al. 10.1029/2023JD038841
75. Before and After: A Multiscale Remote Sensing Assessment of the Sinop Dam, Mato Grosso, Brazil O. Lucanus et al. 10.3390/earth2020018
76. Air quality monitoring in Ukraine during 2022 military conflict using Sentinel-5P imagery M. Mehrabi et al. 10.1007/s11869-023-01488-w
77. Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations T. Scarpelli et al. 10.5194/acp-22-3235-2022
78. On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases E. Malina et al. 10.5194/amt-15-2377-2022
79. East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis R. Liang et al. 10.5194/acp-23-8039-2023
80. A high-resolution satellite-based map of global methane emissions reveals missing wetland, fossil fuel, and monsoon sources X. Yu et al. 10.5194/acp-23-3325-2023
81. Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data A. Vara-Vela et al. 10.5194/gmd-16-6413-2023
82. Quantifying CH4 emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method Q. Tu et al. 10.5194/acp-22-9747-2022
83. Spatial-Temporal Changes of Methane Content in the Atmosphere for Selected Countries and Regions with High Methane Emission from Rice Cultivation K. Kozicka et al. 10.3390/atmos12111382
84. 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al. 10.3788/AOS230429
85. Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al. 10.5194/acp-23-9071-2023
86. The HITRAN2020 molecular spectroscopic database I. Gordon et al. 10.1016/j.jqsrt.2021.107949
87. Methane Emissions from Superemitting Coal Mines in Australia Quantified Using TROPOMI Satellite Observations P. Sadavarte et al. 10.1021/acs.est.1c03976
88. Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations Z. Qu et al. 10.1088/1748-9326/ac8754
89. 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
90. Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions A. Mavrovic et al. 10.5194/bg-20-2941-2023
91. Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al. 10.5194/acp-22-9617-2022
92. A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm J. Laughner et al. 10.5194/amt-16-1121-2023
93. Monitoring Greenhouse Gases from Space H. Boesch et al. 10.3390/rs13142700
94. Quantification of CH<sub>4</sub> emissions from waste disposal sites near the city of Madrid using ground- and space-based observations of COCCON, TROPOMI and IASI Q. Tu et al. 10.5194/acp-22-295-2022
95. Assessing the Relative Importance of Satellite-Detected Methane Superemitters in Quantifying Total Emissions for Oil and Gas Production Areas in Algeria S. Naus et al. 10.1021/acs.est.3c04746
96. Phenology is the dominant control of methane emissions in a tropical non-forested wetland C. Helfter et al. 10.1038/s41467-021-27786-4
97. Ground-Based Atmospheric CO2, CH4, and CO Column Measurements at Golmud in the Qinghai-Tibetan Plateau and Comparisons with TROPOMI/S5P Satellite Observations M. Zhou et al. 10.1007/s00376-022-2116-0
98. Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting J. Cooper et al. 10.1039/D1EA00046B
99. Rain-fed pulses of methane from East Africa during 2018–2019 contributed to atmospheric growth rate M. Lunt et al. 10.1088/1748-9326/abd8fa