127 citations as recorded by crossref.

1. Analysis of Oil and Gas Ethane and Methane Emissions in the Southcentral and Eastern United States Using Four Seasons of Continuous Aircraft Ethane Measurements Z. Barkley et al. 10.1029/2020JD034194
2. Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
3. Inverse modeling of 2010–2022 satellite observations shows that inundation of the wet tropics drove the 2020–2022 methane surge Z. Qu et al. 10.1073/pnas.2402730121
4. Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission C. Chan Miller et al. 10.5194/amt-17-5429-2024
5. 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
6. 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
7. Using satellites to uncover large methane emissions from landfills J. Maasakkers et al. 10.1126/sciadv.abn9683
8. 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
9. A gridded inventory of Canada’s anthropogenic methane emissions T. Scarpelli et al. 10.1088/1748-9326/ac40b1
10. Slowdown in China's methane emission growth M. Zhao et al. 10.1093/nsr/nwae223
11. What can we learn about tropospheric OH from satellite observations of methane? E. Penn et al. 10.5194/acp-25-2947-2025
12. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics S. Voshtani et al. 10.3390/rs14020375
13. 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
14. Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions Q. Zhu et al. 10.1088/1748-9326/adad02
15. 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
16. 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
17. Improved biomass burning emissions from 1750 to 2010 using ice core records and inverse modeling B. Zhang et al. 10.1038/s41467-024-47864-7
18. Satellite quantification of methane emissions from South American countries: a high-resolution inversion of TROPOMI and GOSAT observations S. Hancock et al. 10.5194/acp-25-797-2025
19. Quantifying Time-Averaged Methane Emissions from Individual Coal Mine Vents with GHGSat-D Satellite Observations D. Varon et al. 10.1021/acs.est.0c01213
20. 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
21. Evaluating urban methane emissions from space using TROPOMI methane and carbon monoxide observations G. Plant et al. 10.1016/j.rse.2021.112756
22. An integrated analysis of contemporary methane emissions and concentration trends over China using in situ and satellite observations and model simulations H. Tan et al. 10.5194/acp-22-1229-2022
23. 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
24. 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
25. On the Causes and Consequences of Recent Trends in Atmospheric Methane H. Schaefer 10.1007/s40641-019-00140-z
26. Country-level methane emissions and their sectoral trends during 2009–2020 estimated by high-resolution inversion of GOSAT and surface observations R. Janardanan et al. 10.1088/1748-9326/ad2436
27. 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
28. 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
29. 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
30. 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
31. Avoiding methane emission rate underestimates when using the divergence method C. Roberts et al. 10.1088/1748-9326/ad0252
32. Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al. 10.1080/01431161.2023.2240028
33. 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
34. 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
35. Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes H. Lindqvist et al. 10.3390/rs16162979
36. 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
37. New evidence for CH4 enhancement in the upper troposphere associated with the Asian summer monsoon M. Tao et al. 10.1088/1748-9326/ad2738
38. Advancing Scientific Understanding of the Global Methane Budget in Support of the Paris Agreement A. Ganesan et al. 10.1029/2018GB006065
39. Estimating Drivers and Pathways for Hydroelectric Reservoir Methane Emissions Using a New Mechanistic Model K. Delwiche et al. 10.1029/2022JG006908
40. 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
41. Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010–2017 sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric observations X. Lu et al. 10.5194/acp-22-395-2022
42. 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
43. Satellite-Based Monitoring of Methane Emissions from China’s Rice Hub R. Liang et al. 10.1021/acs.est.4c09822
44. Temporal and spatial comparison of coal mine ventilation methane emissions and mitigation quantified using PRISMA satellite data and on-site measurements C. Karacan et al. 10.1016/j.scitotenv.2025.179268
45. 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
46. 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
47. Thermoelectric energy harvesting from geothermal micro-seepage N. Kulkarni et al. 10.1016/j.ijhydene.2024.10.400
48. Missing OH reactivity in the global marine boundary layer A. Thames et al. 10.5194/acp-20-4013-2020
49. 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
50. Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations R. Parker et al. 10.5194/bg-17-5669-2020
51. Tracking regional CH4 emissions through collocated air pollution measurement: a pilot application and robustness analysis in China Y. Li & B. Zheng 10.1038/s41612-025-01011-1
52. Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations Z. Qu et al. 10.1088/1748-9326/ac8754
53. Large Increase in Atmospheric Methane over West Siberian Wetlands during Summer Detected from Space Y. Someya et al. 10.2151/sola.2020-027
54. 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
55. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
56. 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
57. Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al. 10.1038/s41598-023-41914-8
58. 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
59. 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
60. Atmospheric methane and nitrous oxide: challenges alongthe path to Net Zero E. Nisbet et al. 10.1098/rsta.2020.0457
61. Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al. 10.5194/acp-24-6845-2024
62. 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
63. Distributionally Robust Optimal Sensor Placement Method for Site-Scale Methane-Emission Monitoring Y. Zi et al. 10.1109/JSEN.2022.3214176
64. 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
65. 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
66. 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
67. 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
68. Urban methane emission monitoring across North America using TROPOMI data: an analytical inversion approach M. Hemati et al. 10.1038/s41598-024-58995-8
69. Towards verifying and improving estimations of China's CO2 and CH4 budgets using atmospheric inversions Y. Wang et al. 10.1093/nsr/nwaf090
70. Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations L. Estrada et al. 10.5194/gmd-18-3311-2025
71. African rice cultivation linked to rising methane Z. Chen et al. 10.1038/s41558-023-01907-x
72. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
73. 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
74. 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
75. Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area J. Sheng et al. 10.1088/1748-9326/ac24d1
76. Observed changes in China’s methane emissions linked to policy drivers Y. Zhang et al. 10.1073/pnas.2202742119
77. Atmospheric observations suggest methane emissions in north-eastern China growing with natural gas use F. Wang et al. 10.1038/s41598-022-19462-4
78. Single photon Lidar gas imagers for practical and widespread continuous methane monitoring J. Titchener et al. 10.1016/j.apenergy.2021.118086
79. 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
80. A Minireview on the Role of Cocatalysts in Semiconductor-Based Photocatalytic CH4 Conversion Z. Ma et al. 10.1021/acs.energyfuels.2c01351
81. Global assessment of oil and gas methane ultra-emitters T. Lauvaux et al. 10.1126/science.abj4351
82. Discovery of Large Methane Emissions Using a Complementary Method Based on Multispectral and Hyperspectral Data X. Cai et al. 10.3390/atmos16050532
83. 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
84. 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
85. 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
86. 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
87. Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1 J. He et al. 10.5194/acp-20-805-2020
88. 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
89. Quantifying CH4 emissions from coal mine aggregation areas in Shanxi, China, using TROPOMI observations and the wind-assigned anomaly method Q. Tu et al. 10.5194/acp-24-4875-2024
90. A decade of GOSAT Proxy satellite CH4 observations R. Parker et al. 10.5194/essd-12-3383-2020
91. Unravelling a large methane emission discrepancy in Mexico using satellite observations L. Shen et al. 10.1016/j.rse.2021.112461
92. 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
93. Evaluation of single-footprint AIRS CH4 profile retrieval uncertainties using aircraft profile measurements S. Kulawik et al. 10.5194/amt-14-335-2021
94. 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
95. 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
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98. Explaining Global Trends in Cattle Population Changes between 1961 and 2020 Directly Affecting Methane Emissions K. Kozicka et al. 10.3390/su151310533
99. 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
100. Open-data-based city-scale gridded carbon dioxide emission inventory: supporting urban carbon monitoring in Chengdu, China R. Wang et al. 10.20517/cf.2024.19
101. Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations R. Janardanan et al. 10.3390/rs12030375
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117. Bayesian inversion of HFC-134a emissions in southern China from a new AGAGE site: Results from an observing system simulation experiment J. Li et al. 10.1016/j.atmosenv.2024.120715
118. A three-dimensional-model inversion of methyl chloroform to constrain the atmospheric oxidative capacity S. Naus et al. 10.5194/acp-21-4809-2021
119. Quantifying methane emissions from the largest oil-producing basin in the United States from space Y. Zhang et al. 10.1126/sciadv.aaz5120
120. Satellite Data and Machine Learning for Benchmarking Methane Concentrations in the Canadian Dairy Industry H. Bi & S. Neethirajan 10.3390/su162310400
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122. 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
123. Connecting the ruminant microbiome to climate change: insights from current ecological and evolutionary concepts A. Frazier et al. 10.3389/fmicb.2024.1503315
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127. Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane Y. Zhang et al. 10.5194/acp-18-15959-2018