76 citations as recorded by crossref.

1. Overview: Estimating and reporting uncertainties in remotely sensed atmospheric composition and temperature T. von Clarmann et al. 10.5194/amt-13-4393-2020
2. 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. 10.1039/D1EA00046B
3. A decade of GOSAT Proxy satellite CH4 observations R. Parker et al. 10.5194/essd-12-3383-2020
4. On the influence of underlying elevation data on Sentinel-5 Precursor TROPOMI satellite methane retrievals over Greenland J. Hachmeister et al. 10.5194/amt-15-4063-2022
5. 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
6. Determination of the chemical equator from GEOS-Chem model simulation: a focus on the tropical western Pacific region X. Sun et al. 10.5194/acp-23-7075-2023
7. Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks M. Reuter et al. 10.5194/amt-18-241-2025
8. 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
9. Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from TROPOMI P. Hochstaffl et al. 10.3390/rs12213486
10. Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm O. Schneising et al. 10.5194/amt-16-669-2023
11. 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
12. Severe Californian wildfires in November 2018 observed from space: the carbon monoxide perspective O. Schneising et al. 10.5194/acp-20-3317-2020
13. Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data S. Vanselow et al. 10.5194/acp-24-10441-2024
14. Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations R. Parker et al. 10.5194/bg-19-5779-2022
15. A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel‐5P TROPOMI M. Liu et al. 10.1029/2021GL094151
16. Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes H. Lindqvist et al. 10.3390/rs16162979
17. Sensors and systems for air quality assessment monitoring and management: A review D. Singh et al. 10.1016/j.jenvman.2021.112510
18. Quantifying Methane Emissions Using Satellite Data: Application of the Integrated Methane Inversion (IMI) Model to Assess Danish Emissions A. Vara-Vela et al. 10.3390/rs16234554
19. Trends in Satellite Earth Observation for Permafrost Related Analyses—A Review M. Philipp et al. 10.3390/rs13061217
20. Impact of Precursor Compounds Associated with Long-Range Transport in the East Asia Region—Variation in CO/CO2 and VOCs M. Kim et al. 10.3390/app131910783
21. XCO2 retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm S. Noël et al. 10.5194/amt-14-3837-2021
22. Random Forest Classifier for Cloud Clearing of the Operational TROPOMI XCH4 Product T. Borsdorff et al. 10.3390/rs16071208
23. Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season C. Karoff & A. Vara-Vela 10.3389/feart.2023.1119977
24. The Spatial and Temporal Distribution Patterns of XCH4 in China: New Observations from TROPOMI J. Zhang et al. 10.3390/atmos13020177
25. Avoiding methane emission rate underestimates when using the divergence method C. Roberts et al. 10.1088/1748-9326/ad0252
26. 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
27. Space-based Earth observation in support of the UNFCCC Paris Agreement M. Hegglin et al. 10.3389/fenvs.2022.941490
28. Refined line-shape parameters for CO lines broadened by air predicted from requantized classical molecular dynamics simulations F. Hendaoui et al. 10.1016/j.jqsrt.2024.108954
29. Maintenance 4.0 for HVAC Systems: Addressing Implementation Challenges and Research Gaps I. Shaban et al. 10.3390/smartcities8020066
30. Atmospheric Gravity Wave and Instability Observations From the International Space Station Using the Near InfraRed Airglow Camera (NIRAC) J. Hecht et al. 10.1029/2023JD039070
31. Do espaço ao solo V. Neves et al. 10.24927/rce2023.044
32. Potential Underestimate in Reported Bottom-up Methane Emissions from Oil and Gas Operations in the Delaware Basin S. Riddick et al. 10.3390/atmos15020202
33. Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations M. Sha et al. 10.5194/amt-14-6249-2021
34. Methane retrieved from TROPOMI: improvement of the data product and validation of the first 2 years of measurements A. Lorente et al. 10.5194/amt-14-665-2021
35. Carbon Monoxide in Optically Thick Wildfire Smoke: Evaluating TROPOMI Using CU Airborne SOF Column Observations J. Rowe et al. 10.1021/acsearthspacechem.2c00048
36. Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al. 10.1016/j.rse.2024.114039
37. Simulation and Error Analysis of Methane Detection Globally Using Spaceborne IPDA Lidar X. Zhang et al. 10.3390/rs15133239
38. Unexpected long-range transport of glyoxal and formaldehyde observed from the Copernicus Sentinel-5 Precursor satellite during the 2018 Canadian wildfires L. Alvarado et al. 10.5194/acp-20-2057-2020
39. Towards sector-based attribution using intra-city variations in satellite-based emission ratios between CO2 and CO D. Wu et al. 10.5194/acp-22-14547-2022
40. 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al. 10.3788/AOS230429
41. Estimating ground-level CH4 concentrations inferred from Sentinel-5P J. Qin et al. 10.1080/01431161.2023.2240028
42. Towards a sector-specific CO∕CO2 emission ratio: satellite-based observations of CO release from steel production in Germany O. Schneising et al. 10.5194/acp-24-7609-2024
43. 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
44. Detection and quantification of CH4 plumes using the WFM-DOAS retrieval on AVIRIS-NG hyperspectral data J. Borchardt et al. 10.5194/amt-14-1267-2021
45. 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
46. 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
47. Widespread Frequent Methane Emissions From the Oil and Gas Industry in the Permian Basin J. Veefkind et al. 10.1029/2022JD037479
48. Integrating Satellite Observations and Hydrological Models to Unravel Large TROPOMI Methane Emissions in South Sudan Wetlands Y. Albuhaisi et al. 10.3390/rs16244744
49. Mapping burn severity and monitoring CO content in Türkiye’s 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform O. Yilmaz et al. 10.1007/s12145-023-00933-9
50. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
51. Detecting Methane Emissions from Space Over India: Analysis Using EMIT and Sentinel-5P TROPOMI Datasets A. Siddiqui et al. 10.1007/s12524-024-01925-y
52. Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference C. Roberts et al. 10.1088/1748-9326/ac7062
53. The Impact of the Control Measures during the COVID-19 Outbreak on Air Pollution in China C. Fan et al. 10.3390/rs12101613
54. A Neural Network-Based Approach for Real-Time Measurement of the Concentration of Gaseous Pollutants in Tehran Using MODIS M. Saleh et al. 10.61186/jgit.11.4.55
55. A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10 W. Keely et al. 10.5194/amt-16-5725-2023
56. Meteorological Drivers of Permian Basin Methane Anomalies Derived from TROPOMI E. Crosman 10.3390/rs13050896
57. A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm J. Laughner et al. 10.5194/amt-16-1121-2023
58. Extreme wildfires over Northern Greece during Summer 2023 – Part B. Adverse effects on regional air quality M. Koukouli et al. 10.1016/j.atmosres.2025.108034
59. The spatial distribution mechanism of PM2.5 and NO2 on the eastern coast of China Y. Chi et al. 10.1016/j.envpol.2023.123122
60. Greenhouse gas observation network design for Africa A. Nickless et al. 10.1080/16000889.2020.1824486
61. Improved Gaussian regression model for retrieving ground methane levels by considering vertical profile features H. He et al. 10.3389/feart.2024.1352498
62. 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
63. Retrieval of Atmospheric XCH4 via XGBoost Method Based on TROPOMI Satellite Data W. Zhang et al. 10.3390/atmos16030279
64. 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. 10.5194/amt-15-2199-2022
65. Remote sensing of methane leakage from natural gas and petroleum systems revisited O. Schneising et al. 10.5194/acp-20-9169-2020
66. Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India A. Vellalassery et al. 10.5194/acp-21-5393-2021
67. On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases E. Malina et al. 10.5194/amt-15-2377-2022
68. How key-enabling technologies’ regimes influence sociotechnical transitions: The impact of artificial intelligence on decarbonization in the steel industry N. John et al. 10.1016/j.jclepro.2022.133624
69. Assessing uncertainties and discrepancies in agricultural greenhouse gas emissions estimation in China: A comprehensive review H. Li et al. 10.1016/j.eiar.2024.107498
70. Atmospheric Trends of CO and CH4 from Extreme Wildfires in Portugal Using Sentinel-5P TROPOMI Level-2 Data C. Magro et al. 10.3390/fire4020025
71. Drone-Assisted Monitoring of Atmospheric Pollution—A Comprehensive Review J. Jońca et al. 10.3390/su141811516
72. A twenty year record of greenhouse gases in the Eastern Mediterranean atmosphere N. Gialesakis et al. 10.1016/j.scitotenv.2022.161003
73. A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane M. Máximo-Canadas et al. 10.1021/acsengineeringau.5c00001
74. 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
75. 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. 10.3390/atmos12111382
76. High-frequency monitoring of anomalous methane point sources with multispectral Sentinel-2 satellite observations D. Varon et al. 10.5194/amt-14-2771-2021