87 citations as recorded by crossref.

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2. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
3. High-resolution assessment of coal mining methane emissions by satellite in Shanxi, China S. Peng et al. 10.1016/j.isci.2023.108375
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10. Ensemble estimates of global wetland methane emissions over 2000–2020 Z. Zhang et al. 10.5194/bg-22-305-2025
11. Satellite-Based Monitoring of Methane Emissions from China’s Rice Hub R. Liang et al. 10.1021/acs.est.4c09822
12. Atmospheric methane isotopes identify inventory knowledge gaps in the Surat Basin, Australia, coal seam gas and agricultural regions B. Kelly et al. 10.5194/acp-22-15527-2022
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16. Decreasing methane emissions from China’s coal mining with rebounded coal production J. Gao et al. 10.1088/1748-9326/ac38d8
17. Locating and quantifying CH4 sources within a wastewater treatment plant based on mobile measurements J. Yang et al. 10.5194/acp-25-4571-2025
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19. 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
20. 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
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23. 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
24. Identifying the main drivers of the spatiotemporal variations in wetland methane emissions during 2001–2020 Y. Hu et al. 10.3389/fenvs.2023.1275742
25. 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
26. 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
27. Evaluation of the Stratospheric Contribution to the Inter‐Annual Variabilities of Tropospheric Methane Growth Rates P. Zhang et al. 10.1029/2023GL103350
28. 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
29. 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
30. Opinion: Beyond global means – novel space-based approaches to indirectly constrain the concentrations of and trends and variations in the tropospheric hydroxyl radical (OH) B. Duncan et al. 10.5194/acp-24-13001-2024
31. 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
32. 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
33. 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
34. Emissions of climate-altering species from open vegetation fires in the Mediterranean region - A review on methods and data R. Hundal et al. 10.1016/j.scitotenv.2024.177713
35. Plant mediated methane efflux from a boreal peatland complex A. Korrensalo et al. 10.1007/s11104-021-05180-9
36. Bottom‐Up Evaluation of the Methane Budget in Asia and Its Subregions A. Ito et al. 10.1029/2023GB007723
37. African rice cultivation linked to rising methane Z. Chen et al. 10.1038/s41558-023-01907-x
38. China's methane emissions derived from the inversion of GOSAT observations with a CMAQ and EnKS-based regional data assimilation system X. Kou et al. 10.1016/j.apr.2024.102333
39. 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
40. 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
41. 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
42. Evaluation of the High Altitude Lidar Observatory (HALO) methane retrievals during the summer 2019 ACT-America campaign R. Barton-Grimley et al. 10.5194/amt-15-4623-2022
43. Toward cleaner air and better health: Current state, challenges, and priorities W. Huang et al. 10.1126/science.adp7832
44. An Effective Quantification of Methane Point-Source Emissions with the Multi-Level Matched Filter from Hyperspectral Imagery M. Liang et al. 10.3390/rs17050843
45. The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps G. Hurtt et al. 10.1088/1748-9326/ac7407
46. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
47. Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region W. Hu et al. 10.1007/s40789-024-00700-1
48. Atmospheric Methane Retrieval Based on Back Propagation Neural Network and Simulated AVIRIS-NG Data Y. Huang et al. 10.1109/LGRS.2024.3379119
49. 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
50. 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
51. 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
52. Evaluation of methane emission from MSW landfills in China, India, and the U.S. from space using a two-tier approach S. Zhang et al. 10.1016/j.jenvman.2025.124705
53. Nutrient management may reduce global warming potential of rice cultivation in subtropical India K. Abbhishek et al. 10.1016/j.crsust.2022.100169
54. Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
55. 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
56. 煤炭行业甲烷排放卫星遥感研究进展与展望 秦. Qin Kai et al. 10.3788/AOS231293
57. City-scale methane emissions from the midstream oil and gas industry: A satellite survey of the Zhoushan archipelago X. Yang et al. 10.1016/j.jclepro.2024.141673
58. What can we learn about tropospheric OH from satellite observations of methane? E. Penn et al. 10.5194/acp-25-2947-2025
59. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics S. Voshtani et al. 10.3390/rs14020375
60. 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
61. A gridded inventory of Canada’s anthropogenic methane emissions T. Scarpelli et al. 10.1088/1748-9326/ac40b1
62. 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
63. A XCO Retrieval Algorithm Coupled Spatial Correlation for the Aerosol and Carbon Detection Lidar Z. Pei et al. 10.1016/j.atmosenv.2023.119933
64. 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
65. A Bayesian framework for deriving sector-based methane emissions from top-down fluxes D. Cusworth et al. 10.1038/s43247-021-00312-6
66. Integrating Satellite Observations and Hydrological Models to Unravel Large TROPOMI Methane Emissions in South Sudan Wetlands Y. Albuhaisi et al. 10.3390/rs16244744
67. Quantifying methane emission baselines with high-resolution satellite data to support China’s emission control H. Zhong et al. 10.1016/j.scib.2025.04.047
68. A review of organophosphonates, their natural and anthropogenic sources, environmental fate and impact on microbial greenhouse gases emissions – Identifying knowledge gaps A. Furtak et al. 10.1016/j.jenvman.2024.120453
69. Detecting Methane Emissions from Space Over India: Analysis Using EMIT and Sentinel-5P TROPOMI Datasets A. Siddiqui et al. 10.1007/s12524-024-01925-y
70. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
71. 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
72. Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993–2017 Z. Zhang et al. 10.1093/nsr/nwab200
73. Rapid rise in premature mortality due to anthropogenic air pollution in fast-growing tropical cities from 2005 to 2018 K. Vohra et al. 10.1126/sciadv.abm4435
74. Recent Slowdown of Anthropogenic Methane Emissions in China Driven by Stabilized Coal Production G. Liu et al. 10.1021/acs.estlett.1c00463
75. 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
76. 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
77. 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
78. 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
79. Trends in atmospheric methane concentrations since 1990 were driven and modified by anthropogenic emissions R. Skeie et al. 10.1038/s43247-023-00969-1
80. 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
81. Application of nitrogen-rich sunflower husks biochar promotes methane oxidation and increases abundance of Methylobacter in nitrogen-poor soil A. Kubaczyński et al. 10.1016/j.jenvman.2023.119324
82. Trends and variability in methane concentrations over the Southeastern Arabian Peninsula D. Francis et al. 10.3389/fenvs.2023.1177877
83. 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
84. 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
85. Jump in Tropospheric Methane Concentrations in 2020–2021 and Slowdown in 2022–2024: New Hypotheses on Causation T. Ming et al. 10.3390/atmos16040406
86. 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
87. Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area J. Sheng et al. 10.1088/1748-9326/ac24d1