99 citations as recorded by crossref.

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4. 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
5. Using satellites to uncover large methane emissions from landfills J. Maasakkers et al. 10.1126/sciadv.abn9683
6. Dietary fat and carbohydrate—balancing the lactation performance and methane emissions in the dairy cow industry: a meta-analysis C. Zhang et al. 10.1016/j.aninu.2024.02.004
7. A gridded inventory of Canada’s anthropogenic methane emissions T. Scarpelli et al. 10.1088/1748-9326/ac40b1
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9. 基于WRF-Chem/DART的硫酸盐化学反应速率同化研究 丛. 黄 et al. 10.1360/SSTe-2023-0057
10. An Inversion Framework for Optimizing Non‐Methane VOC Emissions Using Remote Sensing and Airborne Observations in Northeast Asia During the KORUS‐AQ Field Campaign J. Choi et al. 10.1029/2021JD035844
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12. Quantifying Time-Averaged Methane Emissions from Individual Coal Mine Vents with GHGSat-D Satellite Observations D. Varon et al. 10.1021/acs.est.0c01213
13. Burr marigold (Bidens tripartita L.) roots directly and immediately scavenge rhizosphere methane with highly exuded hydrogen peroxide via a rhizosphere Fenton reaction T. Wagatsuma et al. 10.1007/s11104-020-04766-z
14. Evaluating urban methane emissions from space using TROPOMI methane and carbon monoxide observations G. Plant et al. 10.1016/j.rse.2021.112756
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17. The 2019 methane budget and uncertainties at 1° resolution and each country through Bayesian integration Of GOSAT total column methane data and a priori inventory estimates J. Worden et al. 10.5194/acp-22-6811-2022
18. On the Causes and Consequences of Recent Trends in Atmospheric Methane H. Schaefer 10.1007/s40641-019-00140-z
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20. A global gridded (0.1° × 0.1°) inventory of methane emissions from oil, gas, and coal exploitation based on national reports to the United Nations Framework Convention on Climate Change T. Scarpelli et al. 10.5194/essd-12-563-2020
21. 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
22. 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
23. Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics X. Lu et al. 10.1073/pnas.2217900120
24. Avoiding methane emission rate underestimates when using the divergence method C. Roberts et al. 10.1088/1748-9326/ad0252
25. Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al. 10.1080/01431161.2023.2240028
26. Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
27. Methane, carbon dioxide, hydrogen sulfide, and isotopic ratios of methane observations from the Permian Basin tower network V. Monteiro et al. 10.5194/essd-14-2401-2022
28. 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
29. New evidence for CH4 enhancement in the upper troposphere associated with the Asian summer monsoon M. Tao et al. 10.1088/1748-9326/ad2738
30. Advancing Scientific Understanding of the Global Methane Budget in Support of the Paris Agreement A. Ganesan et al. 10.1029/2018GB006065
31. Estimating Drivers and Pathways for Hydroelectric Reservoir Methane Emissions Using a New Mechanistic Model K. Delwiche et al. 10.1029/2022JG006908
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33. Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations Y. Zhang et al. 10.5194/acp-21-3643-2021
34. 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
35. 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
36. Missing OH reactivity in the global marine boundary layer A. Thames et al. 10.5194/acp-20-4013-2020
37. 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
38. Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations R. Parker et al. 10.5194/bg-17-5669-2020
39. Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations Z. Qu et al. 10.1088/1748-9326/ac8754
40. Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane Y. Zhang et al. 10.5194/acp-18-15959-2018
41. Large Increase in Atmospheric Methane over West Siberian Wetlands during Summer Detected from Space Y. Someya et al. 10.2151/sola.2020-027
42. Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions X. Yu et al. 10.5194/acp-21-951-2021
43. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
44. 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane J. Maasakkers et al. 10.5194/acp-21-4339-2021
45. Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al. 10.1038/s41598-023-41914-8
46. 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
47. Methane retrieved from TROPOMI: improvement of the data product and validation of the first 2 years of measurements A. Lorente et al. 10.5194/amt-14-665-2021
48. Atmospheric methane and nitrous oxide: challenges alongthe path to Net Zero E. Nisbet et al. 10.1098/rsta.2020.0457
49. Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observations S. Baray et al. 10.5194/acp-21-18101-2021
50. Distributionally Robust Optimal Sensor Placement Method for Site-Scale Methane-Emission Monitoring Y. Zi et al. 10.1109/JSEN.2022.3214176
51. 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
52. 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
53. 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
54. Accelerating methane growth rate from 2010 to 2017: leading contributions from the tropics and East Asia Y. Yin et al. 10.5194/acp-21-12631-2021
55. African rice cultivation linked to rising methane Z. Chen et al. 10.1038/s41558-023-01907-x
56. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
57. 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
58. The Development of a Low-Cost Method for Monitoring Methane Leakage from the Subsurface of Natural Gas Fields M. Farhan et al. 10.3390/methane1010003
59. Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area J. Sheng et al. 10.1088/1748-9326/ac24d1
60. Observed changes in China’s methane emissions linked to policy drivers Y. Zhang et al. 10.1073/pnas.2202742119
61. Atmospheric observations suggest methane emissions in north-eastern China growing with natural gas use F. Wang et al. 10.1038/s41598-022-19462-4
62. Single photon Lidar gas imagers for practical and widespread continuous methane monitoring J. Titchener et al. 10.1016/j.apenergy.2021.118086
63. 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
64. A Minireview on the Role of Cocatalysts in Semiconductor-Based Photocatalytic CH4 Conversion Z. Ma et al. 10.1021/acs.energyfuels.2c01351
65. Global assessment of oil and gas methane ultra-emitters T. Lauvaux et al. 10.1126/science.abj4351
66. 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
67. 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
68. A focused review on membrane contactors for the recovery of dissolved methane from anaerobic membrane bioreactor (AnMBR) effluents P. Velasco et al. 10.1016/j.chemosphere.2021.130448
69. 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
70. Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1 J. He et al. 10.5194/acp-20-805-2020
71. 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
72. A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
73. Unravelling a large methane emission discrepancy in Mexico using satellite observations L. Shen et al. 10.1016/j.rse.2021.112461
74. Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
75. Evaluation of single-footprint AIRS CH<sub>4</sub> profile retrieval uncertainties using aircraft profile measurements S. Kulawik et al. 10.5194/amt-14-335-2021
76. 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
77. 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
78. A Coupled CH4, CO and CO2 Simulation for Improved Chemical Source Modeling B. Bukosa et al. 10.3390/atmos14050764
79. A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel‐5P TROPOMI M. Liu et al. 10.1029/2021GL094151
80. Explaining Global Trends in Cattle Population Changes between 1961 and 2020 Directly Affecting Methane Emissions K. Kozicka et al. 10.3390/su151310533
81. New contributions of measurements in Europe to the global inventory of the stable isotopic composition of methane M. Menoud et al. 10.5194/essd-14-4365-2022
82. Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations R. Janardanan et al. 10.3390/rs12030375
83. Influences of hydroxyl radicals (OH) on top-down estimates of the global and regional methane budgets Y. Zhao et al. 10.5194/acp-20-9525-2020
84. Middle East oil and gas methane emissions signature captured at a remote site using light hydrocarbon tracers E. Germain-Piaulenne et al. 10.1016/j.aeaoa.2024.100253
85. 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
86. WRF-GC (v1.0): online coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.2.1) for regional atmospheric chemistry modeling – Part 1: Description of the one-way model H. Lin et al. 10.5194/gmd-13-3241-2020
87. Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003–2018) for carbon and climate applications M. Reuter et al. 10.5194/amt-13-789-2020
88. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
89. The added value of satellite observations of methane forunderstanding the contemporary methane budget P. Palmer et al. 10.1098/rsta.2021.0106
90. The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps G. Hurtt et al. 10.1088/1748-9326/ac7407
91. Historical trend of China's CH4 concentrations and emissions during 2003–2020 based on satellite observations, and their implications D. Chen et al. 10.1016/j.apr.2022.101615
92. Study on the assimilation of the sulphate reaction rates based on WRF-Chem/DART C. Huang et al. 10.1007/s11430-023-1153-9
93. A three-dimensional-model inversion of methyl chloroform to constrain the atmospheric oxidative capacity S. Naus et al. 10.5194/acp-21-4809-2021
94. Quantifying methane emissions from the largest oil-producing basin in the United States from space Y. Zhang et al. 10.1126/sciadv.aaz5120
95. An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data M. Lunt et al. 10.5194/acp-19-14721-2019
96. The rumen microbiome: balancing food security and environmental impacts I. Mizrahi et al. 10.1038/s41579-021-00543-6
97. Assessment of methane emissions from oil, gas and coal sectors across inventories and atmospheric inversions K. Tibrewal et al. 10.1038/s43247-023-01190-w
98. Emissions of methane in Europe inferred by total column measurements D. Wunch et al. 10.5194/acp-19-3963-2019
99. Bottom-Up Estimates of Coal Mine Methane Emissions in China: A Gridded Inventory, Emission Factors, and Trends J. Sheng et al. 10.1021/acs.estlett.9b00294