204 citations as recorded by crossref.

1. Declining methane emissions and steady, high leakage rates observed over multiple years in a western US oil/gas production basin J. Lin et al.
2. First global XCO2 observations from spaceborne lidar: methodology and initial result G. Han et al.
3. Satellite-based estimates of nitrogen oxide and methane emissions from gas flaring and oil production activities in Sakha Republic, Russia I. Ialongo et al.
4. Towards the Optimization of TanSat-2: Assessment of a Large-Swath Methane Measurement S. Zhu et al.
5. Monitoring Methane Emissions from Oil and Gas Operations W. Collins et al.
6. Occurrence and Discrepancy of Surface and Column Mole Fractions of CO2 and CH4 at a Desert Site in Dunhuang, Western China C. Wei et al.
7. 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.
8. Environmental drivers constraining the seasonal variability in satellite-observed and modelled methane at northern high latitudes E. Kivimäki et al.
9. Wetland shrinking and dust pollution in Khuzestan Iran: insights from sentinel-5 and MODIS satellites A. Yousefi-Kebriya et al.
10. Methane retrievals from airborne HySpex observations in the shortwave infrared P. Hochstaffl et al.
11. Integration of GIS in air quality monitoring: a review of low-income neighbourhoods in South Africa A. Muneri et al.
12. Impacts of climate-driven vegetation changes on air quality over East Asia: Modulation of biogenic VOC emissions and secondary pollutants S. Baek et al.
13. Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations C. Alberti et al.
14. Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al.
15. How can we trust TROPOMI based methane emissions estimation: calculating emissions over unidentified source regions B. Zheng et al.
16. The Impact of the 2020 Oil Production Fluctuations on Methane Emissions over the Gulf Cooperation Council (GCC) Countries: A Satellite Approach A. Farahat
17. Comparing satellite methane measurements to inventory estimates: A Canadian case study L. Dubey et al.
18. Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak M. Dogniaux et al.
19. The Spatial and Temporal Distribution Patterns of XCH4 in China: New Observations from TROPOMI J. Zhang et al.
20. Simultaneous Retrieval of Trace Gases, Aerosols, and Cirrus Using RemoTAP—The Global Orbit Ensemble Study for the CO2M Mission S. Lu et al.
21. Retrieval of Atmospheric XCH4 via XGBoost Method Based on TROPOMI Satellite Data W. Zhang et al.
22. Evaluating Methane Emission Estimates from Intergovernmental Panel on Climate Change Compared to Sentinel-Derived Air–Methane Data E. Wójcik-Gront & A. Wnuk
23. Trends and seasonality of 2019–2023 global methane emissions inferred from a localized ensemble transform Kalman filter (CHEEREIO v1.3.1) applied to TROPOMI satellite observations D. Pendergrass et al.
24. Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations M. Sha et al.
25. Assessing the detection potential of targeting satellites for global greenhouse gas monitoring: insights from TANGO orbit simulations H. Charuvil Asokan et al.
26. Monitoring methane emissions from oil and gas operations‡ W. Collins et al.
27. Minimizing the impacts of the ammonia economy on the nitrogen cycle and climate M. Bertagni et al.
28. Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al.
29. Quantifying CH4 emissions from coal mine aggregation areas in Shanxi, China, using TROPOMI observations and the wind-assigned anomaly method Q. Tu et al.
30. Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm O. Schneising et al.
31. Evaluation of satellite-derived methane emissions from coal mines using the Gaussian plume model in a topographically complex area Y. Gao et al.
32. Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun
33. Five years of GOSAT-2 retrievals with RemoTeC: XCO2 and XCH4 data products with quality filtering by machine learning A. Barr et al.
34. AutoMergeNet: AutoML-Based M-Source Satellite Data Fusion Evaluated With Atmospheric Case Studies J. Wąsala et al.
35. Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins L. Shen et al.
36. The Correlation Between the Changing Shadegan Wetland Extent and Dust Emission using Remote Sensing Techniques A. Yousefi Kebriya et al.
37. Quantifying urban and landfill methane emissions in the United States using TROPOMI satellite data X. Wang et al.
38. Satellite-Based Seasonal Fingerprinting of Methane Emissions from Canadian Dairy Farms Using Sentinel-5P P. Prajesh et al.
39. Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region W. Hu et al.
40. The added value of satellite observations of methane forunderstanding the contemporary methane budget P. Palmer et al.
41. Monthly and annual oscillation of methane and ozone in eastern India using Sentinel-5P TROPOMI: assessment and validation A. Ghosh & S. Manna
42. Intercomparison of CH4 Products in China from GOSAT, TROPOMI, IASI, and AIRS Satellites Q. Ni et al.
43. Design and description of the MUSICA IASI full retrieval product M. Schneider et al.
44. Fiducial Reference Measurements for Greenhouse Gases (FRM4GHG): Validation of Satellite (Sentinel-5 Precursor, OCO-2, and GOSAT) Missions Using the COllaborative Carbon Column Observing Network (COCCON) M. Sha et al.
45. Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins D. Varon et al.
46. Meteorological Drivers of Permian Basin Methane Anomalies Derived from TROPOMI E. Crosman
47. Use of Differential Optical Spectroscopy for Satellite Diagnostics of Methane Content in a Scattering Atmosphere A. Bril et al.
48. An Effective Quantification of Methane Point-Source Emissions with the Multi-Level Matched Filter from Hyperspectral Imagery M. Liang et al.
49. Quantifying Methane–Climate Interactions in Eastern Saudi Arabia Using Geospatial and Machine Learning Modeling M. Rahman et al.
50. Quantification of Central and Eastern China's atmospheric CH4 enhancement changes and its contributions based on machine learning approach X. Ai et al.
51. FTIR Measurements of Greenhouse Gases over Thessaloniki, Greece in the Framework of COCCON and Comparison with S5P/TROPOMI Observations M. Mermigkas et al.
52. The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product N. Jacobs et al.
53. Estimating Methane Emissions by Integrating Satellite Regional Emissions Mapping and Point-Source Observations: Case Study in the Permian Basin M. Gao & Z. Xing
54. Simulation analysis of the effects of aerosol and surface albedo on the remote sensing detection of greenhouse gases in the short-wave infrared 1.6 μm M. Li et al.
55. Spatiotemporal Variations of Atmospheric Methane over the Korean Peninsula from Sentinel-5P/TROPOMI Observations H. Choi & U. Jeong
56. Trends in Satellite Earth Observation for Permafrost Related Analyses—A Review M. Philipp et al.
57. Theoretical Potential of TanSat-2 to Quantify China’s CH4 Emissions S. Zhu et al.
58. Long-Term Trends and Spatiotemporal Variations in Atmospheric XCH4 over China Utilizing Satellite Observations J. Xu et al.
59. Environmental impacts of methane emissions from the oil and gas industry H. Lu et al.
60. Recent advances in TROPOMI-based methane source detection: a systematic review R. Liu et al.
61. Computing focused beam transmissions of photonic crystals using angular spectrum field synthesis M. Siemons & R. Kohlhaas
62. Underestimated Dry Season Methane Emissions from Wetlands in the Pantanal M. Li et al.
63. Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission C. Chan Miller et al.
64. An integrated analysis of air pollution from US coal-fired power plants M. Filonchyk & M. Peterson
65. Satellite-Based Emission Inversion for Air Pollutants and Greenhouse Gases: A Review Z. Jiang et al.
66. Uncertainty and retrieval sensitivity in TROPOMI-based methane inversions over the North Slope of Alaska R. Ward et al.
67. Atmospheric methane retrieval and validation using FY-3F/ HIRAS-II observations W. Fang et al.
68. Spatiotemporal Variability of Global Atmospheric Methane Observed from Two Decades of Satellite Hyperspectral Infrared Sounders L. Zhou et al.
69. Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions P. Han et al.
70. A data driven assessment to link tropospheric methane concentration and surface biophysical factors using remotely sensed data S. Manna et al.
71. Space-based observation of global increase in urban methane emissions from 2019–2023 E. Whiting et al.
72. Advancements in satellite-based methane point source monitoring: A systematic review F. Mohammadimanesh et al.
73. Using satellites to uncover large methane emissions from landfills J. Maasakkers et al.
74. Quantifying Methane Emissions Using Satellite Data: Application of the Integrated Methane Inversion (IMI) Model to Assess Danish Emissions A. Vara-Vela et al.
75. Global Methane Retrieval, Monitoring, and Quantification in Hotspot Regions Based on AHSI/ZY-1 Satellite T. Lu et al.
76. Global Identification of Solid Waste Methane Super Emitters Using Hyperspectral Satellites X. Zhang et al.
77. Temperature, pressure, velocity, and water vapor mole fraction profiles in a ramjet combustor using dual frequency comb spectroscopy and a high temperature absorption database D. Yun et al.
78. Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al.
79. Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes H. Lindqvist et al.
80. Role of space station instruments for improving tropical carbon flux estimates using atmospheric data P. Palmer et al.
81. Large Methane Emission Fluxes Observed From Tropical Wetlands in Zambia J. Shaw et al.
82. Spatiotemporal variations of atmospheric XCH4 in China based on multiple spatially continuous satellite-derived products Y. Liu et al.
83. Methods for quantifying methane emissions using unmanned aerial vehicles: a review J. Shaw et al.
84. National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations L. Shen et al.
85. Seasonal and Diurnal Variations in XCO2 Characteristics in China as Observed by OCO‐2/3 Satellites: Effects of Land Cover and Local Meteorology H. Zhao et al.
86. Before and After: A Multiscale Remote Sensing Assessment of the Sinop Dam, Mato Grosso, Brazil O. Lucanus et al.
87. 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.
88. On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases E. Malina et al.
89. Development of a Multi-Source Satellite Fusion Method for XCH4 Product Generation in Oil and Gas Production Areas L. Fan et al.
90. Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al.
91. A high-resolution satellite-based map of global methane emissions reveals missing wetland, fossil fuel, and monsoon sources X. Yu et al.
92. Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data A. Vara-Vela et al.
93. Quantifying CH4 emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method Q. Tu et al.
94. Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al.
95. The HITRAN2020 molecular spectroscopic database I. Gordon et al.
96. Methane Emissions from Wetlands on the Tibetan Plateau over the Past 40 Years T. Sun et al.
97. Methane Emissions from Superemitting Coal Mines in Australia Quantified Using TROPOMI Satellite Observations P. Sadavarte et al.
98. Satellite-Derived Approaches for Coal Mine Methane Estimation: A Review A. Chauhan & S. Raval
99. Attribution of the 2020 surge in atmospheric methane by inverse analysis of GOSAT observations Z. Qu et al.
100. Assessing methane emissions and multiple benefits of mitigation through coupled crop-livestock system L. Li et al.
101. Greenhouse gas column observations from a portable spectrometer in Uganda N. Humpage et al.
102. An Intercomparison of Underground Coal Mine Methane Emission Estimation in Shanxi, China: S5P/TROPOMI vs. GF-5B/AHSI Z. Yang et al.
103. Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments Z. Qu et al.
104. 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.
105. The Greenhouse gas Emission Monitoring network to Inform Net-zero Initiatives UK (GEMINI-UK): network design, theoretical performance, and initial data A. Kurganskiy et al.
106. Quantification of CH4 emissions from waste disposal sites near the city of Madrid using ground- and space-based observations of COCCON, TROPOMI and IASI Q. Tu et al.
107. COCCON Measurements of XCO2, XCH4 and XCO over Coal Mine Aggregation Areas in Shanxi, China, and Comparison to TROPOMI and CAMS Datasets Q. Tu et al.
108. Towards verifying and improving estimations of China's CO2 and CH4 budgets using atmospheric inversions Y. Wang et al.
109. Attributing 2019–2024 methane growth using TROPOMI satellite observations M. He et al.
110. 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.
111. Spatiotemporal variability of methane concentrations driven by ruminant livestock in Mongolia: insights from satellite observations and machine learning C. Bao et al.
112. Phenology is the dominant control of methane emissions in a tropical non-forested wetland C. Helfter et al.
113. A Review of City-Scale Methane Flux Inversion Based on Top-Down Methods X. Li et al.
114. Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery E. Sun et al.
115. Satellite-driven assessment of methane trends, seasonal variability, and emission hotspots in Botswana’s Central and Ngamiland Regions B. Masocha & P. Mhangara
116. Enhanced characterization of SO2 plume height and column density using the second UV spectral band of TROPOMI L. Fabris et al.
117. Atmospheric Greenhouse Gas Distributions: Satellite-Based Measurements A. Uspensky
118. Estimation of CH4emission based on an advanced 4D-LETKF assimilation system J. Bisht et al.
119. Toward a versatile spaceborne architecture for immediate monitoring of the global methane pledge Y. Wang et al.
120. Satellite-based assessment and forecasting of greenhouse gas (GHG) concentrations in Indian megacities using advanced statistical methods A. Alagade & M. Sahu
121. Satellite-Derived Estimate of City-Level Methane Emissions from Calgary, Alberta, Canada Z. Xing et al.
122. A dataset of trace gases in the Yellow River Basin based on Sentinel-5P (2018–2024) S. CAO et al.
123. Satellite-Based Methane Emission Monitoring: A Review Across Industries S. Mehrdad & K. Du
124. Gap-filled spatiotemporal reconstruction of XCH4 data and analysis of methane emission patterns Q. Xiao et al.
125. Development of an Algorithm for the Simultaneous Retrieval of Cloud-Top Height and Cloud Optical Thickness Combining Radiative Transfer and Multisource Satellite Information From O₄ Hyperspectral Measurements W. Wang et al.
126. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al.
127. Ship- and aircraft-based XCH4 over oceans as a new tool for satellite validation A. Müller et al.
128. Demonstration of Photonic Integrated Circuit Seed Laser System: Toward Space-Based Water Vapor and Methane Differential Absorption Lidar N. Dostart et al.
129. Permafrost carbon emissions in a changing Arctic K. Miner et al.
130. A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel‐5P TROPOMI M. Liu et al.
131. Satellite remote sensing and artificial intelligence for livestock greenhouse gas benchmarking: measurement, attribution, and verification challenges P. Prajesh et al.
132. Evaluation of Korean methane emission sources with satellite retrievals by spatial correlation analysis J. Moon et al.
133. Surface reflectance biases in XCH4 retrievals from the 2.3 µm band are enhanced in the presence of aerosols P. Somkuti et al.
134. Assessing Agricultural Methane Emissions and Temperature Feedbacks in the Loiret Region, France: A High-Resolution Sentinel-5P and Machine Learning Approach N. El Beyrouthy et al.
135. 温室气体多平台遥感探测研究（特邀） 刘. Liu Dong et al.
136. A novel physics-based cloud retrieval algorithm based on neural networks (CRANN) from hyperspectral measurements in the O2-O2 band W. Wang et al.
137. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al.
138. Monitoring Persistent Methane Emissions from the Secunda CTL Synthetic Fuel Plant Using Satellite Observations H. Virta et al.
139. Random Forest Classifier for Cloud Clearing of the Operational TROPOMI XCH4 Product T. Borsdorff et al.
140. Assessing Greenhouse Gas Monitoring Capabilities Using SolAtmos End-to-End Simulator: Application to the Uvsq-Sat NG Mission C. Clavier et al.
141. Satellite monitoring of annual US landfill methane emissions and trends N. Balasus et al.
142. Trends and variability in methane concentrations over the Southeastern Arabian Peninsula D. Francis et al.
143. Temporal and Topographic Comparative Analysis of NO2 And CO Concentration Densities Using NASA SRTM, Sentinel-5P and QGIS M. Pant & A. Vidyarthi
144. A multi-year global methane data set obtained by merging observations from TROPOMI and IASI K. Shahzadi et al.
145. Seasonal and Diurnal Variations in Greenhouse Gas Methane (CH4) in a Rural Area of Rome (Italy) A. Ianniello et al.
146. Spatiotemporal Variations of XCH4 across China during 2003–2021 Based on Observations from Multiple Satellites J. Qin et al.
147. Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images P. Joyce et al.
148. Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al.
149. Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al.
150. Long-range transport of short-lived nitrogen dioxide in East Asia S. Baek et al.
151. 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.
152. 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.
153. An optimal estimation-based retrieval of upper atmospheric oxygen airglow and temperature from SCIAMACHY limb observations K. Sun et al.
154. COVID-19 slowdown induced improvement in air quality in India: rapid assessment using Sentinel-5P TROPOMI data M. Behera et al.
155. Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season C. Karoff & A. Vara-Vela
156. High-Resolution Daily XCH4 Prediction Using New Convolutional Neural Network Autoencoder Model and Remote Sensing Data M. Awad & S. Homayouni
157. Latitudinal distribution and sources analysis of greenhouse gases and air pollutants observed during the 2021 Yellow Sea Air Quality campaign aboard a research vessel S. Li et al.
158. Greenhouse gas measurement campaign of the Earth Summit Mission-2022: ground-based in situ and FTIR observations and contribution to satellite validation in the Qomolangma region M. Zhou et al.
159. Reconciling Bottom–Up and Top–Down Approaches to Quantify Sub-Regional Methane Emissions with Improved Inventory and Three-Year High-Resolution Satellite Measurements C. He et al.
160. Review of methane emission source tracing methods in oilfield regions Y. Liu et al.
161. Reconstructing and quantifying methane emissions from the full duration of a 38-day natural gas well blowout using space-based observations J. Maasakkers et al.
162. On the influence of underlying elevation data on Sentinel-5 Precursor TROPOMI satellite methane retrievals over Greenland J. Hachmeister et al.
163. Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al.
164. Evaluation of the methane full-physics retrieval applied to TROPOMI ocean sun glint measurements A. Lorente et al.
165. 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.
166. Accounting for the effect of aerosols in GHGSat methane retrieval Q. Yu et al.
167. Mineral Luminescence Observed From Space P. Köhler et al.
168. Mid-Infrared line intensity for the fundamental (1–0) vibrational band of carbon monoxide (CO) D. Bailey et al.
169. Spatiotemporal variation in near-surface CH4 concentrations in China over the last two decades J. Xu et al.
170. Temporal variation of surface reflectance and cloud fraction used to identify background aerosol retrieval information over East Asia S. Park et al.
171. Investigating high methane emissions from urban areas detected by TROPOMI and their association with untreated wastewater B. de Foy et al.
172. From planetary scenarios to planetary sensing: Models, observations, and political legibility D. Pendergrass
173. A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases N. Balasus et al.
174. Leveraging TROPOMI observations and WRF-GHG modeling towards improving methane emission assessments in India T. Mathew et al.
175. 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.
176. 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.
177. Estimating Drivers and Pathways for Hydroelectric Reservoir Methane Emissions Using a New Mechanistic Model K. Delwiche et al.
178. Quantifying CO emissions from boreal wildfires by assimilating TROPOMI and TCCON observations S. Voshtani et al.
179. Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products M. Schneider et al.
180. Spatial distribution pattern and long-term trend of atmospheric methane in the Atlantic-Mediterranean transition region based on TROPOMI and GOSAT measurements J. Adame et al.
181. Accounting for surface reflectance spectral features in TROPOMI methane retrievals A. Lorente et al.
182. SERF-XCH4: A Stacked Ensemble Framework for Spatiotemporal Continuous Methane Monitoring and Driver Analysis H. Zhao et al.
183. Observed and modeled interactions between atmospheric pollutants and urban thermal environment in an arid city: Urumqi as a case study C. Wen et al.
184. Air quality monitoring in Ukraine during 2022 military conflict using Sentinel-5P imagery M. Mehrabi et al.
185. Towards Sustainable Hydrocarbon Extraction: A Study of Atmospheric Pollutant Dynamics (CO, CH4, SO2, HCHO) via Remote Sensing and Meteorological Data V. Fernández Maldonado et al.
186. East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis R. Liang et al.
187. Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction A. Bradley et al.
188. Estimation of Carbon Dioxide and Methane Emissions and Absorption by Land and Ocean Surfaces in the 21st Century A. Olchev
189. 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.
190. 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al.
191. 基于偏振和高光谱联合的气溶胶与温室气体协同仿真 李. Li Min et al.
192. Remote Sensing for Quantifying Greenhouse Gas Emissions at Carbon Capture, Utilisation and Storage Facilities: A Review C. Karoff et al.
193. Spatio-Temporal Patterns of Methane Emissions from 2019 Onwards: A Satellite-Based Comparison of High- and Low-Emission Regions E. Wójcik-Gront et al.
194. If the Yedoma thaws, will we notice? Quantifying detection limits of top-down methane monitoring infrastructures M. Pallandt et al.
195. Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions A. Mavrovic et al.
196. OOA-LightGBM: An Optimized Machine Learning Approach for Nationwide Seamless Reconstruction of XCH4 in China Z. Luo et al.
197. Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al.
198. A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm J. Laughner et al.
199. Monitoring Greenhouse Gases from Space H. Boesch et al.
200. 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.
201. Ground-Based Atmospheric CO2, CH4, and CO Column Measurements at Golmud in the Qinghai-Tibetan Plateau and Comparisons with TROPOMI/S5P Satellite Observations M. Zhou et al.
202. Machine Learning for Methane Detection and Quantification From Space: A survey E. Tiemann et al.
203. Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting J. Cooper et al.
204. The HITRAN2024 methane update T. Bertin et al.