78 citations as recorded by crossref.

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4. Estimation of Anthropogenic CH4 and CO2 Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots C. Hu et al. 10.1029/2022JD037915
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14. 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
15. 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
16. Revealing Non-CO2 GHG Emissions in China’s Transportation Networks Z. Meng et al. 10.1021/acs.estlett.2c00832
17. 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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19. 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
20. 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
21. 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
22. Towards the Optimization of TanSat-2: Assessment of a Large-Swath Methane Measurement S. Zhu et al. 10.3390/rs17030543
23. 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
24. Quantifying methane emissions from United States landfills D. Cusworth et al. 10.1126/science.adi7735
25. A decade of GOSAT Proxy satellite CH4 observations R. Parker et al. 10.5194/essd-12-3383-2020
26. 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
27. 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
28. 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
29. Where to place methane monitoring sites in China to better assist carbon management X. Zhang et al. 10.1038/s41612-023-00359-6
30. Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements K. Mottungan et al. 10.5194/amt-17-5861-2024
31. What can we learn about tropospheric OH from satellite observations of methane? E. Penn et al. 10.5194/acp-25-2947-2025
32. 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
33. 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
34. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics S. Voshtani et al. 10.3390/rs14020375
35. Global Methane Budget 2000–2020 M. Saunois et al. 10.5194/essd-17-1873-2025
36. An Unexpected Seasonal Cycle in U.S. Oil and Gas Methane Emissions L. Hu et al. 10.1021/acs.est.4c14090
37. Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al. 10.5194/acp-24-6845-2024
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. Global warming will largely increase waste treatment CH4 emissions in Chinese megacities: insight from the first city-scale CH4 concentration observation network in Hangzhou, China C. Hu et al. 10.5194/acp-23-4501-2023
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. Structural shifts in China’s oil and gas CH4 emissions with implications for mitigation efforts J. Luo et al. 10.1038/s41467-025-58237-z
42. 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
43. China's pathways to synchronize the emission reductions of air pollutants and greenhouse gases: Pros and cons R. Feng & X. Fang 10.1016/j.resconrec.2022.106392
44. 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
45. Recent Slowdown of Anthropogenic Methane Emissions in China Driven by Stabilized Coal Production G. Liu et al. 10.1021/acs.estlett.1c00463
46. Estimates of the spatially complete, observational-data-driven planetary boundary layer height over the contiguous United States Z. Ayazpour et al. 10.5194/amt-16-563-2023
47. 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
48. Geospatial Analysis of Alaskan Lakes Indicates Wetland Fraction and Surface Water Area Are Useful Predictors of Methane Ebullition M. Savignano et al. 10.1080/24694452.2023.2277817
49. Observed changes in China’s methane emissions linked to policy drivers Y. Zhang et al. 10.1073/pnas.2202742119
50. Metal–organic frameworks as catalysts and biocatalysts for methane oxidation: The current state of the art L. Andrade et al. 10.1016/j.ccr.2023.215042
51. 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
52. 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
53. 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
54. 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
55. Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space A. Thorpe et al. 10.1126/sciadv.adh2391
56. 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
57. 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
58. 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
59. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
60. 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
61. Revisiting the quantification of power plant CO2 emissions in the United States and China from satellite: A comparative study using three top-down approaches C. He et al. 10.1016/j.rse.2024.114192
62. A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel‐5P TROPOMI M. Liu et al. 10.1029/2021GL094151
63. Decreasing methane emissions from China’s coal mining with rebounded coal production J. Gao et al. 10.1088/1748-9326/ac38d8
64. 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
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. Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport E. Dowd et al. 10.5194/acp-23-7363-2023
67. Forecasting short-term methane based on corrected numerical weather prediction outputs S. Zhao et al. 10.1016/j.jclepro.2024.142500
68. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
69. A gridded inventory of Canada’s anthropogenic methane emissions T. Scarpelli et al. 10.1088/1748-9326/ac40b1
70. Simulation and Error Analysis of Methane Detection Globally Using Spaceborne IPDA Lidar X. Zhang et al. 10.3390/rs15133239
71. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
72. Monthly methane emissions in Chinese mainland provinces from 2013–2022 D. Cui et al. 10.1038/s41597-025-05107-4
73. 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
74. Methane emission and influencing factors of China's oil and natural gas sector in 2020–2060: A source level analysis S. Sun et al. 10.1016/j.scitotenv.2023.167116
75. Slowdown in China's methane emission growth M. Zhao et al. 10.1093/nsr/nwae223
76. Investigation of the renewed methane growth post-2007 with high-resolution 3-D variational inverse modeling and isotopic constraints J. Thanwerdas et al. 10.5194/acp-24-2129-2024
77. A decade of GOSAT Proxy satellite CH4 observations R. Parker et al. 10.5194/essd-12-3383-2020
78. 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