73 citations as recorded by crossref.

1. 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
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
4. Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations Z. Qu et al. 10.1088/1748-9326/ac8754
5. Estimating emissions of methane consistent with atmospheric measurements of methane and δ13C of methane S. Basu et al. 10.5194/acp-22-15351-2022
6. Towards a whole‐system framework for wildfire monitoring using Earth observations M. Crowley et al. 10.1111/gcb.16567
7. 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
8. Estimation of CH4emission based on an advanced 4D-LETKF assimilation system J. Bisht et al. 10.5194/gmd-16-1823-2023
9. 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
10. A 130‐year global inventory of methane emissions from livestock: Trends, patterns, and drivers L. Zhang et al. 10.1111/gcb.16280
11. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
12. 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
13. Decreasing methane emissions from China’s coal mining with rebounded coal production J. Gao et al. 10.1088/1748-9326/ac38d8
14. Atmospheric observations suggest methane emissions in north-eastern China growing with natural gas use F. Wang et al. 10.1038/s41598-022-19462-4
15. 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
16. 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
17. Observed changes in China’s methane emissions linked to policy drivers Y. Zhang et al. 10.1073/pnas.2202742119
18. Global Scale Inversions from MOPITT CO and MODIS AOD B. Gaubert et al. 10.3390/rs15194813
19. 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
20. Identifying the main drivers of the spatiotemporal variations in wetland methane emissions during 2001–2020 Y. Hu et al. 10.3389/fenvs.2023.1275742
21. 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
22. 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
23. Evaluation of the Stratospheric Contribution to the Inter‐Annual Variabilities of Tropospheric Methane Growth Rates P. Zhang et al. 10.1029/2023GL103350
24. 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
25. 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
26. 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 CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations X. Lu et al. 10.5194/acp-22-395-2022
27. 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
28. 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
29. Plant mediated methane efflux from a boreal peatland complex A. Korrensalo et al. 10.1007/s11104-021-05180-9
30. Bottom‐Up Evaluation of the Methane Budget in Asia and Its Subregions A. Ito et al. 10.1029/2023GB007723
31. African rice cultivation linked to rising methane Z. Chen et al. 10.1038/s41558-023-01907-x
32. 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
33. 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
34. 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
35. 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
36. 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
37. Toward cleaner air and better health: Current state, challenges, and priorities W. Huang et al. 10.1126/science.adp7832
38. The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps G. Hurtt et al. 10.1088/1748-9326/ac7407
39. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
40. 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
41. Atmospheric Methane Retrieval Based on Back Propagation Neural Network and Simulated AVIRIS-NG Data Y. Huang et al. 10.1109/LGRS.2024.3379119
42. Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations X. Lu et al. 10.5194/acp-21-4637-2021
43. 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
44. 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
45. Nutrient management may reduce global warming potential of rice cultivation in subtropical India K. Abbhishek et al. 10.1016/j.crsust.2022.100169
46. Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
47. 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
48. 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
49. 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
50. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics S. Voshtani et al. 10.3390/rs14020375
51. 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
52. A gridded inventory of Canada’s anthropogenic methane emissions T. Scarpelli et al. 10.1088/1748-9326/ac40b1
53. 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
54. A XCO Retrieval Algorithm Coupled Spatial Correlation for the Aerosol and Carbon Detection Lidar Z. Pei et al. 10.1016/j.atmosenv.2023.119933
55. A Bayesian framework for deriving sector-based methane emissions from top-down fluxes D. Cusworth et al. 10.1038/s43247-021-00312-6
56. 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
57. 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
58. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
59. 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
60. Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993–2017 Z. Zhang et al. 10.1093/nsr/nwab200
61. 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
62. Recent Slowdown of Anthropogenic Methane Emissions in China Driven by Stabilized Coal Production G. Liu et al. 10.1021/acs.estlett.1c00463
63. 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
64. 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
65. 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
66. Trends in atmospheric methane concentrations since 1990 were driven and modified by anthropogenic emissions R. Skeie et al. 10.1038/s43247-023-00969-1
67. 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
68. 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
69. Trends and variability in methane concentrations over the Southeastern Arabian Peninsula D. Francis et al. 10.3389/fenvs.2023.1177877
70. 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
71. 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
72. A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
73. Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area J. Sheng et al. 10.1088/1748-9326/ac24d1