133 citations as recorded by crossref.

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41. Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. 10.5194/acp-16-14371-2016
42. SpectroCube: a European 6U nanosatellite spectroscopy platform for astrobiology and astrochemistry A. Elsaesser et al. 10.1016/j.actaastro.2020.01.028
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45. Permafrost carbon emissions in a changing Arctic K. Miner et al. 10.1038/s43017-021-00230-3
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47. Retrieval of atmospheric CO<sub>2</sub> vertical profiles from ground-based near-infrared spectra S. Roche et al. 10.5194/amt-14-3087-2021
48. Slowdown in China's methane emission growth M. Zhao et al. 10.1093/nsr/nwae223
49. Regional‐Scale Wilting Point Estimation Using Satellite SIF, Radiative‐Transfer Inversion, and Soil‐Vegetation‐Atmosphere Transfer Simulation: A Grassland Study T. Kiyono et al. 10.1029/2022JG007074
50. Soil respiration–driven CO 2 pulses dominate Australia’s flux variability E. Metz et al. 10.1126/science.add7833
51. Methane retrievals from airborne HySpex observations in the shortwave infrared P. Hochstaffl et al. 10.5194/amt-16-4195-2023
52. Inverse modeling of 2010–2022 satellite observations shows that inundation of the wet tropics drove the 2020–2022 methane surge Z. Qu et al. 10.1073/pnas.2402730121
53. Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm S. Noël et al. 10.5194/amt-15-3401-2022
54. Comparison of Retrieved L2 Products from Four Successive Versions of L1B Spectra in the Thermal Infrared Band of TANSO-FTS over the Arctic Ocean S. Payan et al. 10.3390/rs9111167
55. 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
56. Interpreting contemporary trends in atmospheric methane A. Turner et al. 10.1073/pnas.1814297116
57. Simulation and analysis of the CO2 range-resolved differential absorption lidar system at 2 μm B. Zhang et al. 10.1038/s41598-024-68137-9
58. Study of Atmospheric Carbon Dioxide Retrieval Method Based on Normalized Sensitivity L. Zhao et al. 10.3390/rs14051106
59. MERLIN: A French-German Space Lidar Mission Dedicated to Atmospheric Methane G. Ehret et al. 10.3390/rs9101052
60. Anthropogenic CO2 emissions assessment of Nile Delta using XCO2 and SIF data from OCO-2 satellite A. Shekhar et al. 10.1088/1748-9326/ab9cfe
61. Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) <i>X</i><sub>CO<sub>2</sub></sub> measurements with TCCON D. Wunch et al. 10.5194/amt-10-2209-2017
62. XCO<sub>2</sub> retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm S. Noël et al. 10.5194/amt-14-3837-2021
63. Methane measurement method based on F-P angle-dependent correlation spectroscopy Y. Lv et al. 10.1364/OE.526026
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. Evaluating Radiometric Responsivity Degradations of TANSO-FTS/GOSAT Using Principal Component Analysis Y. Someya & Y. Yoshida 10.1175/JTECH-D-19-0224.1
66. 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
67. Variation patterns and driving factors of regional atmospheric CO2 anomalies in China Y. Fu et al. 10.1007/s11356-021-17139-5
68. 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
69. Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al. 10.5194/acp-24-6845-2024
70. 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
71. 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
72. Quantifying CO2 Emissions From Individual Power Plants From Space R. Nassar et al. 10.1002/2017GL074702
73. Methane Growth Rate Estimation and Its Causes in Western Canada Using Satellite Observations S. Islam et al. 10.1029/2020JD033948
74. Detecting high-emitting methane sources in oil/gas fields using satellite observations D. Cusworth et al. 10.5194/acp-18-16885-2018
75. Emissions from the Oil and Gas Sectors, Coal Mining and Ruminant Farming Drive Methane Growth over the Past Three Decades N. CHANDRA et al. 10.2151/jmsj.2021-015
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77. An improved band design framework for atmospheric pollutant detection and its application to the design of satellites for CO2 observation Z. Wu et al. 10.1016/j.jqsrt.2023.108712
78. Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions M. Helbig et al. 10.1016/j.agrformet.2021.108509
79. Distinguishing Anthropogenic CO2 Emissions From Different Energy Intensive Industrial Sources Using OCO‐2 Observations: A Case Study in Northern China S. Wang et al. 10.1029/2018JD029005
80. Quantification of methane emitted by ruminants: a review of methods L. Tedeschi et al. 10.1093/jas/skac197
81. 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
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83. An 11-year record of XCO<sub>2</sub> estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm T. Taylor et al. 10.5194/essd-14-325-2022
84. The Potential of Monitoring Carbon Dioxide Emission in a Geostationary View with the GIIRS Meteorological Hyperspectral Infrared Sounder Q. Zhang et al. 10.3390/rs15040886
85. Bias assessment of lower and middle tropospheric CO<sub>2</sub> concentrations of GOSAT/TANSO-FTS TIR version 1 product N. Saitoh et al. 10.5194/amt-10-3877-2017
86. Dynamic Coupling Between Atmospheric CO2 Concentration and Land Surface Temperature in Major Urban Agglomerations in China: Insights for Sustainable Urban Development Q. Sun et al. 10.3390/su16219484
87. Aerosol Property Retrieval Algorithm over Northeast Asia from TANSO-CAI Measurements Onboard GOSAT S. Lee et al. 10.3390/rs9070687
88. Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals M. Buchwitz et al. 10.5194/amt-14-2141-2021
89. XCO2 and XCH4 Reconstruction Using GOSAT Satellite Data Based on EOF-Algorithm F. Lopez et al. 10.3390/rs14112622
90. Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003–2016 M. Buchwitz et al. 10.5194/acp-18-17355-2018
91. 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
92. Spectrum calibration of the first hyperspectral infrared measurements from a geostationary platform: Method and preliminary assessment Q. Guo et al. 10.1002/qj.3981
93. Investigation of monthly and seasonal changes of methane gas with respect to climate change using satellite data S. Javadinejad et al. 10.1007/s13201-019-1067-9
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95. Methane profiles from GOSAT thermal infrared spectra A. de Lange & J. Landgraf 10.5194/amt-11-3815-2018
96. Quantifying the impact of aerosol scattering on the retrieval of methane from airborne remote sensing measurements Y. Huang et al. 10.5194/amt-13-6755-2020
97. A Bayesian framework for deriving sector-based methane emissions from top-down fluxes D. Cusworth et al. 10.1038/s43247-021-00312-6
98. Measuring Atmospheric CO2 Enhancements From the 2017 British Columbia Wildfires Using a Lidar J. Mao et al. 10.1029/2021GL093805
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100. Performance Evaluation of Spaceborne Integrated Path Differential Absorption Lidar for Carbon Dioxide Detection at 1572 nm S. Wang et al. 10.3390/rs12162570
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108. Assessing Greenhouse Gas Monitoring Capabilities Using SolAtmos End-to-End Simulator: Application to the Uvsq-Sat NG Mission C. Clavier et al. 10.3390/rs16081442
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110. 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
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122. A high-level cloud detection method utilizing the GOSAT TANSO-FTS water vapor saturated band N. Eguchi & Y. Yoshida 10.5194/amt-12-389-2019
123. Seasonal variation of the O3–CO correlation derived from remote sensing measurements over western Japan H. Ohyama et al. 10.1016/j.atmosenv.2016.10.027
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131. Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010–2017 sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) atmospheric observations X. Lu et al. 10.5194/acp-22-395-2022
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