241 citations as recorded by crossref.

1. Satellite-Based Seasonal Fingerprinting of Methane Emissions from Canadian Dairy Farms Using Sentinel-5P P. Prajesh et al.
2. Vast and hidden urban methane emissions from the Russia–Ukraine war Z. Feng et al.
3. A global methane observation system to track climate feedbacks for verifiable climate impact J. Watts et al.
4. Leveraging TROPOMI observations and WRF-GHG modeling towards improving methane emission assessments in India T. Mathew et al.
5. 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.
6. Satellite quantification of methane emissions from South American countries: a high-resolution inversion of TROPOMI and GOSAT observations S. Hancock et al.
7. Satellite-Derived Estimates on Methane Emissions From Rice Paddies Across China X. Zhang et al.
8. Quantifying Methane Emissions Using Satellite Data: Application of the Integrated Methane Inversion (IMI) Model to Assess Danish Emissions A. Vara-Vela et al.
9. CELNet: A comprehensive efficient learning network for atmospheric plume identification from remotely sensed methane concentration images F. Chen et al.
10. Measurement of fugitive methane emissions from an abandoned coal exploration hole in Queensland, Australia using a Quantum Gas LiDAR S. Hoerning & P. Hayes
11. What is causing the methane surge? E. Nisbet & M. Manning
12. First Investigation of Long-Term Methane Emissions from Wastewater Treatment Using Satellite Remote Sensing S. Mehrdad et al.
13. Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al.
14. Benchmarking data-driven inversion methods for the estimation of local CO2 emissions from synthetic satellite images of XCO2 and NO2 D. Santaren et al.
15. Spatiotemporal variations of atmospheric XCH4 in China based on multiple spatially continuous satellite-derived products Y. Liu et al.
16. Advanced AI-driven methane emission detection, quantification, and localization in Canada: A hybrid multi-source fusion framework A. Yazdinejad et al.
17. Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers A. Ayasse et al.
18. Space Imaging Point Source Detection and Characterization F. Ribeiro et al.
19. Automated recognition of oil and gas production infrastructure using satellite imagery S. Dileep et al.
20. Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space A. Thorpe et al.
21. Calibration of Maxar Constellation Over Libya-4 Site Using MAIAC Technique M. Choi et al.
22. Enabling fast greenhouse gas emissions inference from satellites with GATES: a Graph-Neural-Network Atmospheric Transport Emulation System E. Fillola et al.
23. Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins D. Varon et al.
24. Utilizing Remote Sensing and Data Analytics Techniques to Detect Methane Emissions from the Oil and Gas Industry and Assist with Sustainability Metrics Á. Esparza et al.
25. Offshore methane detection and quantification from space using sun glint measurements with the GHGSat constellation J. MacLean et al.
26. Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution M. Omara et al.
27. Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China H. He et al.
28. Linear integrated mass enhancement: A method for estimating hotspot emission rates from space-based plume observations J. Hakkarainen et al.
29. Methane emissions from Australia estimated by inverse analysis using in-situ and Satellite (GOSAT) atmospheric observations F. Wang et al.
30. Uvsq-Sat NG, a New CubeSat Pathfinder for Monitoring Earth Outgoing Energy and Greenhouse Gases M. Meftah et al.
31. U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers J. Bruno et al.
32. Global Methane Budget 2000–2020 M. Saunois et al.
33. High-resolution assessment of coal mining methane emissions by satellite in Shanxi, China S. Peng et al.
34. The role of satellite remote sensing in mitigating and adapting to global climate change S. Zhao et al.
35. Global satellite survey reveals uncertainty in landfill methane emissions M. Dogniaux et al.
36. Evaluation of satellite-derived methane emissions from coal mines using the Gaussian plume model in a topographically complex area Y. Gao et al.
37. Relation of Sentinel-2 multispectral data with surface methane and meteorological observations in summer N. Popov et al.
38. Innovative software for analysing satellite data and methane emissions using radiative transfer model K. Aghayeva & G. Krauklit
39. The Greenhouse Gas Footprint of LNG Pathways From Major Exporters A. Albatayneh et al.
40. A Bayesian inversion of TROPOMI methane observations over South Africa: Implications for bottom-up inventories K. Maliehe et al.
41. From planetary scenarios to planetary sensing: Models, observations, and political legibility D. Pendergrass
42. Estimating Methane Emissions by Integrating Satellite Regional Emissions Mapping and Point-Source Observations: Case Study in the Permian Basin M. Gao & Z. Xing
43. Quantifying Methane–Climate Interactions in Eastern Saudi Arabia Using Geospatial and Machine Learning Modeling M. Rahman et al.
44. Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data S. Vanselow et al.
45. Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data H. Wang et al.
46. CH4Vision: Machine Learning Estimation of Methane Flux with GaoFen-5 Hyperspectral Imagery K. Li et al.
47. Instrument Performance Analysis for Methane Point Source Retrieval and Estimation Using Remote Sensing Technique Y. Jiang et al.
48. Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission C. Chan Miller et al.
49. Mapping multi-sectoral methane emissions across Queensland’s gas production areas J. Lane et al.
50. Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes H. Lindqvist et al.
51. Improved Quantification of Methane Point-Source Emissions from Hyperspectral Imagery Using a Spectrally Corrected Levenberg–Marquardt Matched Filter Z. He et al.
52. A review of methane emissions source types, characteristics, rates, and mitigation effectiveness across U.S. and Canadian cities C. Vollrath et al.
53. Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States D. Cusworth et al.
54. Constraining industrial ammonia emissions using hyperspectral infrared imaging L. Noppen et al.
55. Quantifying methane emissions from United States landfills D. Cusworth et al.
56. Investigation of U.S. landfill GHG reporting program methane emission models B. Stark et al.
57. Reconciling Methane Emission Measurements for Offshore Oil and Gas Platforms with Detailed Emission Inventories: Accounting for Emission Intermittency Z. Chen et al.
58. A new aerial approach for quantifying and attributing methane emissions: implementation and validation J. Dooley et al.
59. Temperature dependence of the absorption of the R(6) manifold of the 2ν3 band of methane in air in support of the MERLIN mission S. Vasilchenko et al.
60. Methane intensity and emissions across major oil and gas basins and individual jurisdictions using MethaneSAT observations J. Williams et al.
61. Considering the observation and illumination angular configuration for an improved detection and quantification of methane emissions J. Gorroño et al.
62. Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region W. Hu et al.
63. MAM-YOLOv9: A Multiattention Mechanism Network for Methane Emission Facility Detection in High-Resolution Satellite Remote Sensing Images Y. Xing et al.
64. 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.
65. Satellite Data and Machine Learning for Benchmarking Methane Concentrations in the Canadian Dairy Industry H. Bi & S. Neethirajan
66. Small emission sources in aggregate disproportionately account for a large majority of total methane emissions from the US oil and gas sector J. Williams et al.
67. Spatiotemporal variability of methane concentrations driven by ruminant livestock in Mongolia: insights from satellite observations and machine learning C. Bao et al.
68. Development of a Multi-Source Satellite Fusion Method for XCH4 Product Generation in Oil and Gas Production Areas L. Fan et al.
69. Towards Supporting Satellite Design Through the Top-Down Approach: A General Model for Assessing the Ability of Future Satellite Missions to Quantify Point Source Emissions L. Yao et al.
70. Improving WRF-Chem aerosol optical depth prediction over India using artificial neural network A. Khan et al.
71. Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al.
72. Airborne measurements of agricultural ammonia emissions: A case study over a livestock farm in Grosseto, Italy L. Noppen et al.
73. Defining Detection Limits for Continuous Monitoring Systems for Methane Emissions at Oil and Gas Facilities Q. Chen et al.
74. Characterization of methane plumes during the Aliso Canyon natural gas leak: a remote sensing perspective D. Cusworth et al.
75. Satellite monitoring of annual US landfill methane emissions and trends N. Balasus et al.
76. Understanding the potential of Sentinel-2 for monitoring methane point emissions J. Gorroño et al.
77. Monitoring Persistent Methane Emissions from the Secunda CTL Synthetic Fuel Plant Using Satellite Observations H. Virta et al.
78. Probability of Detection and Multi-Sensor Persistence of Methane Emissions from Coincident Airborne and Satellite Observations A. Ayasse et al.
79. Feasibility of Detecting Low-Level Methane Emissions from Abandoned Oil Wells Using a Multi-Band, Multi-Pass Satellite Approach B. Hoshino et al.
80. 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.
81. Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al.
82. 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.
83. 2019–2024 trends in African livestock and wetland emissions as contributors to the global methane rise N. Balasus et al.
84. Comparative Review of Global Methane Budget Estimation: Top-Down, Bottom-Up, and Integrated Approaches B. Alem et al.
85. Investigation of spectral bands and sensor parameters for methane emission detection imaging spectrometer H. Varchand et al.
86. Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al.
87. 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.
88. Monitoring and regression analysis of landfill surface temperatures using remote sensing and image processing techniques K. Sharma et al.
89. PRISMethaNet: A novel deep learning model for landfill methane detection using PRISMA satellite data M. Marjani et al.
90. Advancements in satellite-based methane point source monitoring: A systematic review F. Mohammadimanesh et al.
91. Evaluation of Uncertainties in the Anthropogenic SO2 Emissions in the USA from the OMI Point Source Catalog K. Narayan et al.
92. Deployment-invariant probability of detection characterization for aerial LiDAR methane detection M. Thorpe et al.
93. Tracking regional CH4 emissions through collocated air pollution measurement: a pilot application and robustness analysis in China Y. Li & B. Zheng
94. Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison G. McNicol et al.
95. Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera M. Knapp et al.
96. A High-Resolution Satellite Survey of Methane Emissions from 60 North American Municipal Solid Waste Landfills M. Krause et al.
97. Broadband photodetectors based on PbS quantum dots synthesized using the multiple injection growth method W. Feng et al.
98. High Spatial and Temporal Resolution Simulations of Methane Column Loadings Due to Routine Emissions and Emission Events in Oil and Gas Regions L. Huang et al.
99. Determination of Greenhouse Gas Concentrations from the 16U CubeSat Spacecraft Using Fourier Transform Infrared Spectroscopy V. Mayorova et al.
100. Comparison of observation- and inventory-based methane emissions for eight large global emitters A. Petrescu et al.
101. RETRACTED: Real-Time Coal Emissions Monitoring System Using Geospatial Satellite Images and Deep Neural Networks A. Doshi
102. A Review of City-Scale Methane Flux Inversion Based on Top-Down Methods X. Li et al.
103. Assessment of the Fugitive Emission Distributed Sampling (FEDS) system: a mobile, multi-inlet system for continuous emissions monitoring J. Shaw et al.
104. A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B Z. He et al.
105. Towards verifying and improving estimations of China's CO2 and CH4 budgets using atmospheric inversions Y. Wang et al.
106. Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery E. Sun et al.
107. Forecasting short-term methane based on corrected numerical weather prediction outputs S. Zhao et al.
108. Exploring uncertainties in the integrated mass enhancement method for remote sensing retrievals of methane emissions M. Hasan et al.
109. US oil and gas system emissions from nearly one million aerial site measurements E. Sherwin et al.
110. SSRMF: A sparse spectral reconstruction enhanced matched filter for improving point-source methane emission detection in complex terrain K. Li et al.
111. Separating and quantifying facility-level methane emissions with overlapping plumes for spaceborne methane monitoring Y. Pang et al.
112. First validation of high-resolution satellite-derived methane emissions from an active gas leak in the UK E. Dowd et al.
113. Methane emissions from the oil and gas supply chain: Characteristics and mitigation H. Lu et al.
114. Assessment of methane emissions from US onshore oil and gas production using MethaneAIR measurements K. MacKay et al.
115. Semantic segmentation of methane plumes with hyperspectral machine learning models V. Růžička et al.
116. Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al.
117. Comparative Performance of Gaussian Plume and Backward Lagrangian Stochastic Models for Near-Field Methane Emission Estimation Using a Single Controlled Release Experiment A. Upreti et al.
118. Impact of stray light on greenhouse gas concentration retrievals and emission estimates as observed with the passive airborne remote sensing imager MAMAP2D-Light O. Huhs et al.
119. 煤炭行业甲烷排放卫星遥感研究进展与展望 秦. Qin Kai et al.
120. Global Identification of Solid Waste Methane Super Emitters Using Hyperspectral Satellites X. Zhang et al.
121. 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.
122. Retrieval of Atmospheric XCH4 via XGBoost Method Based on TROPOMI Satellite Data W. Zhang et al.
123. 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.
124. Monthly methane emissions in Chinese mainland provinces from 2013–2022 D. Cui et al.
125. The Carbon Mapper emissions monitoring system R. Duren et al.
126. National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations L. Shen et al.
127. Global energy sector methane emissions estimated by using facility-level satellite observations D. Jervis et al.
128. State of the Art in Monitoring Methane Emissions from Arctic–boreal Wetlands and Lakes M. Mahdianpari et al.
129. Review and perspective of remote sensing research on global greenhouse gas monitoring and stocktaking L. Liu et al.
130. Global Methane Retrieval, Monitoring, and Quantification in Hotspot Regions Based on AHSI/ZY-1 Satellite T. Lu et al.
131. Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer B. Rouet-Leduc & C. Hulbert
132. Atmospheric remote sensing for anthropogenic methane emissions: Applications and research opportunities S. Zhang et al.
133. A methane monitoring station siting method based on WRF-STILT and genetic algorithm L. Fan et al.
134. S2MetNet: A novel dataset and deep learning benchmark for methane point source quantification using Sentinel-2 satellite imagery A. Radman et al.
135. Effect of Chicken Feather Hydrolysate on Growth and Yield of French Bean S. Devi et al.
136. Response to Gallagher (2022)—the Australian Tidal Restoration for Blue Carbon method 2022—conservative, robust, and practical C. Lovelock et al.
137. Reduction of methane emissions through improved landfill management H. Tong et al.
138. Methane and nitrous oxide emissions from municipal wastewater treatment plants in China: A plant-level and technology-specific study H. Li et al.
139. Geostationary satellite observations of extreme and transient methane emissions from oil and gas infrastructure M. Watine-Guiu et al.
140. Direct measurement of plume velocity to characterize point source emissions M. Eastwood et al.
141. The HITRAN2024 methane update T. Bertin et al.
142. Review of methane emission source tracing methods in oilfield regions Y. Liu et al.
143. Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al.
144. 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.
145. Recent advances in TROPOMI-based methane source detection: a systematic review R. Liu et al.
146. 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.
147. Intermittent Emissions from Oil and Gas Operations: Implications for Detection Effectiveness from Periodic Leak Detection Surveys A. Hodshire et al.
148. Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions Q. Zhu et al.
149. Assessment of GHG emissions from small-capacity logistics cold storage in China based on field measurements H. Niu et al.
150. Validation of Long-Term Methane (CH4) Satellite Measurements from the AIRS Spectrometer and Correction of Their Temporal Drift V. Rakitin et al.
151. Single-photon laser methane detection methodology and initial validation S. Zhu et al.
152. Satellite-Derived Estimate of City-Level Methane Emissions from Calgary, Alberta, Canada Z. Xing et al.
153. Atmospheric Methane Retrieval Based on Back Propagation Neural Network and Simulated AVIRIS-NG Data Y. Huang et al.
154. Global Estimates of Daily Gapless Atmospheric XCH4 Concentrations From Satellite and Reanalysis Data During 2003–2020 Y. Qu et al.
155. 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.
156. Theoretical Potential of TanSat-2 to Quantify China’s CH4 Emissions S. Zhu et al.
157. Joint Estimation of the Global Facility-Scale Oil–Gas Methane Emission Rate Distribution and Survey-Mode Detection Probabilities from Multiple Satellite Systems D. Jervis et al.
158. Tightening up methane plume source rate estimation in EnMAP and PRISMA images E. Ouerghi et al.
159. Development of Artificial Intelligence/Machine Learning (AI/ML) Models for Methane Emissions Forecasting in Seaweed C. Louime & T. Raza
160. Accounting for the effect of aerosols in GHGSat methane retrieval Q. Yu et al.
161. Cavity-Enhanced Doppler-Broadening Thermometry via All-Frequency Metrology Q. Huang et al.
162. Single-blind validation of space-based point-source detection and quantification of onshore methane emissions E. Sherwin et al.
163. Comparison of Landfill Methane Emission Quantification Using Multiple Observation Methods L. Gillespie et al.
164. Assessing the Detection of Methane Plumes in Offshore Areas Using High-Resolution Imaging Spectrometers J. Roger et al.
165. Air pollution accountability research: Moving from a chain to a web S. Ebelt et al.
166. An Improved CH4 Profile Retrieving Method for Ground-Based Differential Absorption Lidar L. Fan et al.
167. Current potential of CH4 emission estimates using TROPOMI in the Middle East M. Liu et al.
168. Investigating high methane emissions from urban areas detected by TROPOMI and their association with untreated wastewater B. de Foy et al.
169. Gap-filled spatiotemporal reconstruction of XCH4 data and analysis of methane emission patterns Q. Xiao et al.
170. The integration of vision transformers and SAM for automated methane super-emitter detection using TROPOMI data M. Marjani et al.
171. Tiered Leak Detection and Repair Programs at Simulated Oil and Gas Production Facilities: Increasing Emission Reduction by Targeting High-Emitting Sources F. Cardoso-Saldaña
172. Monitoring oil and gas field CH4 leaks by Sentinel-5P and Sentinel-2 B. He et al.
173. Mapping U.S. Surface Methane With Artificial Neural Networks M. Bade & Y. Li
174. Relating Multi-Scale Plume Detection and Area Estimates of Methane Emissions: A Theoretical and Empirical Analysis S. Pandey et al.
175. 基于自由曲面的轻小型温室气体点源监测成像光谱仪设计 陈. Chen Huiying et al.
176. Monitoring, classification and analysis of waste disposal sites using Machine Learning K. Sharma & M. Sood
177. A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases N. Balasus et al.
178. Satellite observations indicate a declining trend of methane emissions from heavy oil production in Canada Z. Xing et al.
179. Machine Learning in Forecasting Methane Concentration from Satellite Data K. Nowak et al.
180. 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.
181. Evaluating net life-cycle greenhouse gas emissions intensities from gas and coal at varying methane leakage rates D. Gordon et al.
182. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al.
183. Using new geospatial data and 2020 fossil fuel methane emissions for the Global Fuel Exploitation Inventory (GFEI) v3 T. Scarpelli et al.
184. Surface-observation-constrained high-frequency coal mine methane emissions in Shanxi, China, reveal more emissions than inventories, consistent with satellite inversion F. Lu et al.
185. Surveying methane point-source super-emissions across oil and gas basins with MethaneSAT L. Guanter et al.
186. Satellite remote sensing and artificial intelligence for livestock greenhouse gas benchmarking: measurement, attribution, and verification challenges P. Prajesh et al.
187. 碧空一号卫星大气甲烷羽流探测及点源排放量遥感分析（特邀） 何. He Zhuo et al.
188. Bayesian inversion of HFC-134a emissions in southern China from a new AGAGE site: Results from an observing system simulation experiment J. Li et al.
189. Efficient use of a Lagrangian particle dispersion model for atmospheric inversions using satellite observations of column mixing ratios R. Thompson et al.
190. CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery A. Vaughan et al.
191. Frequency and Spatial Domain Injection Network for Methane Plumes Semantic Segmentation Y. Liu et al.
192. A framework for describing and classifying methane reporting requirements, emission sources, and monitoring methods A. Connor et al.
193. Review of Sources of Uncertainty and Techniques Used in Uncertainty Quantification and Sensitivity Analysis to Estimate Greenhouse Gas Emissions from Ruminants E. Kimei et al.
194. 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.
195. Measurement approaches for greenhouse gas emissions from rice II: advanced technology for accelerating throughput T. Vo et al.
196. Разработка статистических моделей оценки концентрации метана в приземном слое атмосферы по материалам космической съемки в зимний период Н. Попов & В. Малинников
197. La surveillance des émissions anthropiques de CO2 depuis l’espace : un enjeu géopolitique émergent G. Broquet & F. Chevallier
198. Global Estimation of Surface Methane Using Low-Earth Orbit Satellite Data and Machine Learning: Comparison of Linear and Nonlinear Models D. Lee et al.
199. Deep learning for detecting and characterizing oil and gas well pads in satellite imagery N. Ramachandran et al.
200. Simulation Analysis of Unmanned Aerial Vehicle-Based Laser Remote Sensing for Methane Point Source Traceability and Leakage Quantification S. Zhu et al.
201. Breakthroughs in CH4 capture technologies: Key to reducing fugitive methane emissions in the energy sector W. Deng et al.
202. Advancing the Arctic Methane Permafrost Challenge (AMPAC) With Future Satellite Missions A. Bartsch et al.
203. Modeling global indices for estimating non-photosynthetic vegetation cover P. Dennison et al.
204. East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis R. Liang et al.
205. Temporal Variation and Persistence of Methane Emissions from Shallow Water Oil and Gas Production in the Gulf of Mexico K. Biener et al.
206. The greenhouse gas observation mission with Global Observing SATellite for Greenhouse gases and Water cycle (GOSAT-GW): objectives, conceptual framework and scientific contributions H. Tanimoto et al.
207. A Framework for Optimizing Continuous Methane Monitoring System Configuration for Minimal Blind Time: Application and Insights from over 100 Operational Oil and Gas Facilities N. Metzger et al.
208. Methane Column Estimation Using PRISMA Hyperspectral Data and Comparison With Other Earth Observation Products D. Settembre et al.
209. Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications S. Ustin & E. Middleton
210. Satellite Insights into methane Super-Emitters: Regional emissions and yearly growth on Turkmenistan’s west coast Z. He et al.
211. Evaluation of emissions and spatial distribution of methane from offshore oil and gas platforms in the Liaodong Bay of China based on shipboard measurement Y. Yu et al.
212. Characterization and Quantification of Methane Emission Plumes and Super-Emitter Detection Across North-Central Brazil Using Hyperspectral Satellite Data G. Cotlier et al.
213. Attributing GHG emissions to individual facilities using multi-temporal hyperspectral images: Methodology and applications Y. Zhang et al.
214. A review of satellite remote sensing for pollution control and carbon reduction in China S. Zhao et al.
215. Methane Emissions from Underground Coal Mines M. Guzman et al.
216. Towards the Optimization of TanSat-2: Assessment of a Large-Swath Methane Measurement S. Zhu et al.
217. A helicopter-based mass balance approach for quantifying methane emissions from industrial activities, applied for coal mine ventilation shafts in Poland E. Förster et al.
218. Practical paths towards quantifying and mitigating agricultural methane emissions E. Nisbet et al.
219. Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al.
220. An Improved Workflow in Mass Balance Approach for Estimating Regional Methane Emission Rate Using Satellite Measurements J. Bian et al.
221. Multisatellite Data Depicts a Record-Breaking Methane Leak from a Well Blowout L. Guanter et al.
222. Machine Learning for Methane Detection and Quantification From Space: A survey E. Tiemann et al.
223. Spatio-temporal dynamics of methane concentration and its association to climatic and vegetation parameters: a case study of the Northern Cape Province, South Africa N. Mashiyi et al.
224. Impact of transport model resolution and a priori assumptions on inverse modeling of Swiss F-gas emissions I. Katharopoulos et al.
225. Analysis of Flaring Activity at Liquefied Natural Gas (LNG) Export Facilities Worldwide L. Minet et al.
226. Physics-informed spatiotemporal analysis of methane concentrations in an oil sands region Y. Xu et al.
227. Detecting Methane Emissions from Space Over India: Analysis Using EMIT and Sentinel-5P TROPOMI Datasets A. Siddiqui et al.
228. Global near-surface methane distribution and emission hotspots from TROPOMI: A geospatial machine-learning approach D. Lee et al.
229. Assessing the detection potential of targeting satellites for global greenhouse gas monitoring: insights from TANGO orbit simulations H. Charuvil Asokan et al.
230. Locating and quantifying CH4 sources within a wastewater treatment plant based on mobile measurements J. Yang et al.
231. Satellite-Based Methane Emission Monitoring: A Review Across Industries S. Mehrdad & K. Du
232. Quantifying CH4 point source emissions with airborne remote sensing: first results from AVIRIS-4 S. Meier et al.
233. 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al.
234. Advances in Satellite-Based Monitoring of Urban Emission Sources and Air Quality: A Review S. Naderi et al.
235. A Remote Sensing Technique for CO2 Column Density G. Hai et al.
236. Single-blind test of nine methane-sensing satellite systems from three continents E. Sherwin et al.
237. North–south inhomogeneous variations of methane emissions observed by TROPOMI over China S. Yu et al.
238. Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al.
239. Constructing a measurement-based spatially explicit inventory of US oil and gas methane emissions (2021) M. Omara et al.
240. Limited evidence that tropical inundation and precipitation powered the 2020–2022 methane surge Y. Xiong et al.
241. New insights into the distribution of methane from sediment and surface waters in urban tropical bay (Jakarta-Indonesia) I. Kampono et al.