189 citations as recorded by crossref.

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2. Development of a continuous UAV-mounted air sampler and application to the quantification of CO2 and CH4 emissions from a major coking plant T. Han et al. 10.5194/amt-17-677-2024
3. Urban methane emission monitoring across North America using TROPOMI data: an analytical inversion approach M. Hemati et al. 10.1038/s41598-024-58995-8
4. Revised methane emissions factors and spatially distributed annual carbon fluxes for global livestock J. Wolf et al. 10.1186/s13021-017-0084-y
5. A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0) A. Bloom et al. 10.5194/gmd-10-2141-2017
6. Deep-Learning-Based Gas Leak Source Localization From Sparse Sensor Data D. Badawi et al. 10.1109/JSEN.2022.3202134
7. Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions Z. Deng et al. 10.5194/essd-14-1639-2022
8. Methane Emissions from Superemitting Coal Mines in Australia Quantified Using TROPOMI Satellite Observations P. Sadavarte et al. 10.1021/acs.est.1c03976
9. Balancing aggregation and smoothing errors in inverse models A. Turner & D. Jacob 10.5194/acp-15-7039-2015
10. Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations R. Janardanan et al. 10.3390/rs12030375
11. 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
12. 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
13. 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
14. Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling S. Miller et al. 10.5194/bg-13-1329-2016
15. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
16. Minimum detection limits of the TROPOMI satellite sensor across North America and their implications for measuring oil and gas methane emissions L. Dubey et al. 10.1016/j.scitotenv.2023.162222
17. Airborne DOAS retrievals of methane, carbon dioxide, and water vapor concentrations at high spatial resolution: application to AVIRIS-NG A. Thorpe et al. 10.5194/amt-10-3833-2017
18. Detection of Methane Emission from a Local Source Using GOSAT Target Observations A. Kuze et al. 10.3390/rs12020267
19. Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories F. Wang et al. 10.3390/rs11212489
20. A high-resolution (0.1° × 0.1°) inventory of methane emissions from Canadian and Mexican oil and gas systems J. Sheng et al. 10.1016/j.atmosenv.2017.02.036
21. Large Methane Emission Fluxes Observed From Tropical Wetlands in Zambia J. Shaw et al. 10.1029/2021GB007261
22. Underestimates of methane from intensively raised animals could undermine goals of sustainable development M. Hayek & S. Miller 10.1088/1748-9326/ac02ef
23. Atmospheric Carbon and Transport – America (ACT‐America) Data Sets: Description, Management, and Delivery Y. Wei et al. 10.1029/2020EA001634
24. A large increase in U.S. methane emissions over the past decade inferred from satellite data and surface observations A. Turner et al. 10.1002/2016GL067987
25. Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs X. Liu et al. 10.5194/acp-17-7067-2017
26. Spatial and Temporal Variations of Atmospheric CO2 Concentration in China and Its Influencing Factors Z. Lv et al. 10.3390/atmos11030231
27. Emission Monitoring Mobile Experiment (EMME): an overview and first results of the St. Petersburg megacity campaign 2019 M. Makarova et al. 10.5194/amt-14-1047-2021
28. A 15-year record of CO emissions constrained by MOPITT CO observations Z. Jiang et al. 10.5194/acp-17-4565-2017
29. Comparing mass balance and adjoint methods for inverse modeling of nitrogen dioxide columns for global nitrogen oxide emissions M. Cooper et al. 10.1002/2016JD025985
30. Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
31. 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
32. 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
33. Inverse modeling of GOSAT-retrieved ratios of total column CH<sub>4</sub> and CO<sub>2</sub> for 2009 and 2010 S. Pandey et al. 10.5194/acp-16-5043-2016
34. A new aerial approach for quantifying and attributing methane emissions: implementation and validation J. Dooley et al. 10.5194/amt-17-5091-2024
35. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models? Z. Tan et al. 10.5194/acp-16-12649-2016
36. Influences of Uncertainties in the STT Flux on Modeled Tropospheric Methane Z. Wang 10.1029/2023JD039107
37. Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. 10.5194/acp-16-14371-2016
38. Contribution of oil and natural gas production to renewed increase in atmospheric methane (2007–2014): top–down estimate from ethane and methane column observations P. Hausmann et al. 10.5194/acp-16-3227-2016
39. Atmospheric CO and CH<sub>4</sub> time series and seasonal variations on Reunion Island from ground-based in situ and FTIR (NDACC and TCCON) measurements M. Zhou et al. 10.5194/acp-18-13881-2018
40. Mineralization of organic matter in boreal lake sediments: rates, pathways, and nature of the fermenting substrates F. Clayer et al. 10.5194/bg-17-4571-2020
41. Constraints on methane emissions in North America from future geostationary remote-sensing measurements N. Bousserez et al. 10.5194/acp-16-6175-2016
42. Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone B. Duncan et al. 10.1029/2019RG000652
43. 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
44. Comparison of Methane Detection Using Shortwave and Longwave Infrared Hyperspectral Sensors Under Varying Environmental Conditions L. Zimmerman & J. Kerekes 10.1109/JSTARS.2023.3247246
45. 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
46. Comparative analysis of low-Earth orbit (TROPOMI) and geostationary (GeoCARB, GEO-CAPE) satellite instruments for constraining methane emissions on fine regional scales: application to the Southeast US J. Sheng et al. 10.5194/amt-11-6379-2018
47. Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources R. Bun et al. 10.1007/s11027-018-9791-2
48. What are the greenhouse gas observing system requirements for reducing fundamental biogeochemical process uncertainty? Amazon wetland CH<sub>4</sub> emissions as a case study A. Bloom et al. 10.5194/acp-16-15199-2016
49. The challenge of reconciling bottom-up agricultural methane emissions inventories with top-down measurements R. Desjardins et al. 10.1016/j.agrformet.2017.09.003
50. Methyl, Ethyl, and Propyl Nitrates: Global Distribution and Impacts on Reactive Nitrogen in Remote Marine Environments J. Fisher et al. 10.1029/2018JD029046
51. 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
52. Detecting high-emitting methane sources in oil/gas fields using satellite observations D. Cusworth et al. 10.5194/acp-18-16885-2018
53. Bias Correction of the Ratio of Total Column CH4 to CO2 Retrieved from GOSAT Spectra H. Oshio et al. 10.3390/rs12193155
54. Using Multiscale Ethane/Methane Observations to Attribute Coal Mine Vent Emissions in the San Juan Basin From 2013 to 2021 A. Meyer et al. 10.1029/2022JD037092
55. Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model I. Stanevich et al. 10.5194/gmd-13-3839-2020
56. A multiyear estimate of methane fluxes in Alaska from CARVE atmospheric observations S. Miller et al. 10.1002/2016GB005419
57. 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
58. 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
59. 2010–2016 methane trends over Canada, the United States, and Mexico observed by the GOSAT satellite: contributions from different source sectors J. Sheng et al. 10.5194/acp-18-12257-2018
60. On Methane Leaks from Pipelines in Bryan and College Station, Texas, USA K. Koch et al. 10.2174/1874282301610010056
61. The recent increase of atmospheric methane from 10 years of ground-based NDACC FTIR observations since 2005 W. Bader et al. 10.5194/acp-17-2255-2017
62. Assessment of Anthropogenic Methane Emissions over Large Regions Based on GOSAT Observations and High Resolution Transport Modeling R. Janardanan et al. 10.3390/rs9090941
63. Methane emissions are predominantly responsible for record-breaking atmospheric methane growth rates in 2020 and 2021 L. Feng et al. 10.5194/acp-23-4863-2023
64. Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales A. Turner et al. 10.5194/acp-18-8265-2018
65. 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
66. Spatial and temporal change patterns of near-surface CO2 and CH4 concentrations in different permafrost regions on the Mongolian Plateau from 2010 to 2017 S. Adiya et al. 10.1016/j.scitotenv.2021.149433
67. Quantification of CH<sub>4</sub> coal mining emissions in Upper Silesia by passive airborne remote sensing observations with the Methane Airborne MAPper (MAMAP) instrument during the CO<sub>2</sub> and Methane (CoMet) campaign S. Krautwurst et al. 10.5194/acp-21-17345-2021
68. Recovery of sparse urban greenhouse gas emissions B. Zanger et al. 10.5194/gmd-15-7533-2022
69. Remote sensing of methane plumes: instrument tradeoff analysis for detecting and quantifying local sources at global scale S. Jongaramrungruang et al. 10.5194/amt-14-7999-2021
70. 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
71. Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH<sub>4</sub> data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. 10.5194/acp-21-9545-2021
72. 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
73. A critical review of green growth indicators in G7 economies from 1990 to 2019 K. Herman et al. 10.1007/s11625-023-01397-y
74. Characterisation of methane variability and trends from near-infrared solar spectra over Hefei, China Y. Tian et al. 10.1016/j.atmosenv.2017.11.001
75. Retrieval of Metop-A/IASI N2O Profiles and Validation with NDACC FTIR Data B. Barret et al. 10.3390/atmos12020219
76. Conversion of surface CH4 concentrations from GOSAT satellite observations using XGBoost algorithm Y. Wan et al. 10.1016/j.atmosenv.2023.119694
77. Simultaneous shipborne measurements of CO<sub>2</sub>, CH<sub>4</sub> and CO and their application to improving greenhouse-gas flux estimates in Australia B. Bukosa et al. 10.5194/acp-19-7055-2019
78. Methane emissions from dairies in the Los Angeles Basin C. Viatte et al. 10.5194/acp-17-7509-2017
79. MethaNet – An AI-driven approach to quantifying methane point-source emission from high-resolution 2-D plume imagery S. Jongaramrungruang et al. 10.1016/j.rse.2021.112809
80. A gridded inventory of anthropogenic methane emissions from Mexico based on Mexico’s national inventory of greenhouse gases and compounds T. Scarpelli et al. 10.1088/1748-9326/abb42b
81. Tropical methane emissions explain large fraction of recent changes in global atmospheric methane growth rate L. Feng et al. 10.1038/s41467-022-28989-z
82. Investigation of spectral bands and sensor parameters for methane emission detection imaging spectrometer H. Varchand et al. 10.1016/j.jqsrt.2024.109100
83. Atmospheric observations suggest methane emissions in north-eastern China growing with natural gas use F. Wang et al. 10.1038/s41598-022-19462-4
84. Greenhouse gas column observations from a portable spectrometer in Uganda N. Humpage et al. 10.5194/amt-17-5679-2024
85. Tropospheric emissions: Monitoring of pollution (TEMPO) P. Zoogman et al. 10.1016/j.jqsrt.2016.05.008
86. Revisiting global fossil fuel and biofuel emissions of ethane Z. Tzompa‐Sosa et al. 10.1002/2016JD025767
87. Methane emissions from underground gas storage in California A. Thorpe et al. 10.1088/1748-9326/ab751d
88. Uncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases E. Solazzo et al. 10.5194/acp-21-5655-2021
89. Interpreting contemporary trends in atmospheric methane A. Turner et al. 10.1073/pnas.1814297116
90. Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane Y. Zhang et al. 10.5194/acp-18-15959-2018
91. Cattle, climate and complexity: food security, quality and sustainability of the Australian cattle industries I. Lean & P. Moate 10.1111/avj.13072
92. 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
93. A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS E. Malina et al. 10.14324/111.444/ucloe.000013
94. Hydrocarbon Tracers Suggest Methane Emissions from Fossil Sources Occur Predominately Before Gas Processing and That Petroleum Plays Are a Significant Source A. Tribby et al. 10.1021/acs.est.2c00927
95. Examining partial-column density retrieval of lower-tropospheric CO2 from GOSAT target observations over global megacities A. Kuze et al. 10.1016/j.rse.2022.112966
96. 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
97. Large XCH<sub>4</sub> anomaly in summer 2013 over northeast Asia observed by GOSAT M. Ishizawa et al. 10.5194/acp-16-9149-2016
98. Methane emissions from a waste treatment site: Numerical analysis of aircraft-based data Y. Cai et al. 10.1016/j.agrformet.2020.108102
99. Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations Z. Qu et al. 10.1088/1748-9326/ac8754
100. Assessment of the climate commitments and additional mitigation policies of the United States J. Greenblatt & M. Wei 10.1038/nclimate3125
101. High-resolution inversion of methane emissions in the Southeast US using SEAC<sup>4</sup>RS aircraft observations of atmospheric methane: anthropogenic and wetland sources J. Sheng et al. 10.5194/acp-18-6483-2018
102. Update on GOSAT TANSO-FTS performance, operations, and data products after more than 6 years in space A. Kuze et al. 10.5194/amt-9-2445-2016
103. Dairy Methane Emissions in California's San Joaquin Valley Inferred With Ground‐Based Remote Sensing Observations in the Summer and Winter S. Heerah et al. 10.1029/2021JD034785
104. 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
105. 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
106. Evaluating urban methane emissions from space using TROPOMI methane and carbon monoxide observations G. Plant et al. 10.1016/j.rse.2021.112756
107. Quantifying Time-Averaged Methane Emissions from Individual Coal Mine Vents with GHGSat-D Satellite Observations D. Varon et al. 10.1021/acs.est.0c01213
108. Assessing the Iterative Finite Difference Mass Balance and 4D‐Var Methods to Derive Ammonia Emissions Over North America Using Synthetic Observations C. Li et al. 10.1029/2018JD030183
109. 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
110. A Coupled CH4, CO and CO2 Simulation for Improved Chemical Source Modeling B. Bukosa et al. 10.3390/atmos14050764
111. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
112. 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
113. Artificial Intelligence Approach for Estimating Dairy Methane Emissions S. Jeong et al. 10.1021/acs.est.1c08802
114. Improvements of a low-cost CO2 commercial nondispersive near-infrared (NDIR) sensor for unmanned aerial vehicle (UAV) atmospheric mapping applications Y. Liu et al. 10.5194/amt-15-4431-2022
115. 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
116. Seasonal variability of stratospheric methane: implications for constraining tropospheric methane budgets using total column observations K. Saad et al. 10.5194/acp-16-14003-2016
117. Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics S. Voshtani et al. 10.3390/rs14020375
118. The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps G. Hurtt et al. 10.1088/1748-9326/ac7407
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120. Emerging reporting and verification needs under the Paris Agreement: How can the research community effectively contribute? L. Perugini et al. 10.1016/j.envsci.2021.04.012
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122. Estimating methane emissions in California's urban and rural regions using multitower observations S. Jeong et al. 10.1002/2016JD025404
123. A gridded inventory of Canada’s anthropogenic methane emissions T. Scarpelli et al. 10.1088/1748-9326/ac40b1
124. The CHRONOS mission: capability for sub-hourly synoptic observations of carbon monoxide and methane to quantify emissions and transport of air pollution D. Edwards et al. 10.5194/amt-11-1061-2018
125. Interannual variability on methane emissions in monsoon Asia derived from GOSAT and surface observations F. Wang et al. 10.1088/1748-9326/abd352
126. The added value of satellite observations of methane forunderstanding the contemporary methane budget P. Palmer et al. 10.1098/rsta.2021.0106
127. Implications of Generation Efficiencies and Supply Chain Leaks for the Life Cycle Greenhouse Gas Emissions of Natural Gas-Fired Electricity in the United States S. Tavakkoli et al. 10.1021/acs.est.1c05246
128. Emissions of methane in Europe inferred by total column measurements D. Wunch et al. 10.5194/acp-19-3963-2019
129. U.S. CH4 emissions from oil and gas production: Have recent large increases been detected? L. Bruhwiler et al. 10.1002/2016JD026157
130. Methane emission reduction in China's natural gas industry: Construction of technology inventory and selection of optimal technology programs N. Li et al. 10.1016/j.spc.2023.12.002
131. Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method Y. Wang et al. 10.5194/essd-15-3597-2023
132. Quantifying lower tropospheric methane concentrations using GOSAT near-IR and TES thermal IR measurements J. Worden et al. 10.5194/amt-8-3433-2015
133. Global inverse modeling of CH<sub>4</sub> sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
134. Estimating methane emissions from biological and fossil‐fuel sources in the San Francisco Bay Area S. Jeong et al. 10.1002/2016GL071794
135. Source Partitioning of Methane Emissions and its Seasonality in the U.S. Midwest Z. Chen et al. 10.1002/2017JG004356
136. 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
137. Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere A. Ostler et al. 10.5194/amt-9-4843-2016
138. Quantifying sources of Brazil's CH<sub>4</sub> emissions between 2010 and 2018 from satellite data R. Tunnicliffe et al. 10.5194/acp-20-13041-2020
139. Atmospheric observations consistent with reported decline in the UK's methane emissions (2013–2020) M. Lunt et al. 10.5194/acp-21-16257-2021
140. Rates and pathways of sedimentary organic matter mineralization in two basins of a boreal lake: Emphasis on methanogenesis and methanotrophy F. Clayer et al. 10.1002/lno.10323
141. Individual coal mine methane emissions constrained by eddy covariance measurements: low bias and missing sources K. Qin et al. 10.5194/acp-24-3009-2024
142. Contributions of the troposphere and stratosphere to CH<sub>4</sub> model biases Z. Wang et al. 10.5194/acp-17-13283-2017
143. 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
144. Gridded National Inventory of U.S. Methane Emissions J. Maasakkers et al. 10.1021/acs.est.6b02878
145. Constraining sector-specific CO<sub>2</sub> and CH<sub>4</sub> emissions in the US S. Miller & A. Michalak 10.5194/acp-17-3963-2017
146. Atmospheric observation-based estimation of fossil fuel CO2 emissions from regions of central and southern California X. Cui et al. 10.1016/j.scitotenv.2019.01.081
147. Methane variability associated with natural and anthropogenic sources in an Australian context M. Hatch et al. 10.1080/08120099.2018.1471004
148. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
149. A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
150. 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
151. Comparison of Satellite-Observed XCO2 from GOSAT, OCO-2, and Ground-Based TCCON A. Liang et al. 10.3390/rs9101033
152. Atmospheric CO2 column concentration over Iran: Emissions, GOSAT satellite observations, and WRF-GHG model simulations S. Karbasi et al. 10.1016/j.atmosres.2024.107818
153. Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling S. Henne et al. 10.5194/acp-16-3683-2016
154. China’s coal mine methane regulations have not curbed growing emissions S. Miller et al. 10.1038/s41467-018-07891-7
155. 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
156. Biogenic link to the recent increase in atmospheric methane over India A. Singh et al. 10.1016/j.jenvman.2021.112526
157. Fuel cycle emissions and life cycle costs of alternative fuel vehicle policy options for the City of Houston municipal fleet S. Sengupta & D. Cohan 10.1016/j.trd.2017.04.039
158. 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
159. 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
160. Top-down constraints on global N<sub>2</sub>O emissions at optimal resolution: application of a new dimension reduction technique K. Wells et al. 10.5194/acp-18-735-2018
161. Landfill gas collection efficiency: Categorization of data from existing in-situ measurements C. Giordano et al. 10.1016/j.wasman.2023.12.042
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166. Non-intrusive soil carbon content quantification methods using machine learning algorithms: A comparison of microwave and millimeter wave radar sensors D. An & Y. Chen 10.1016/j.jai.2023.09.001
167. Observations of XCO<sub>2</sub> and XCH<sub>4</sub> with ground-based high-resolution FTS at Saga, Japan, and comparisons with GOSAT products H. Ohyama et al. 10.5194/amt-8-5263-2015
168. Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. 10.1016/j.rse.2016.12.027
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170. 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
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