85 citations as recorded by crossref.

1. Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates S. Noël et al. https://doi.org/10.5194/amt-17-2317-2024
2. Tropospheric aerosol profile information from high-resolution oxygen A-band measurements from space A. Geddes & H. Bösch https://doi.org/10.5194/amt-8-859-2015
3. Assimilation of atmospheric CO2 observations from space can support national CO2 emission inventories T. Kaminski et al. https://doi.org/10.1088/1748-9326/ac3cea
4. Development of a small unmanned aircraft system to derive CO2 emissions of anthropogenic point sources M. Reuter et al. https://doi.org/10.5194/amt-14-153-2021
5. The impact of spectral resolution on satellite retrieval accuracy of CO2 and CH4 A. Galli et al. https://doi.org/10.5194/amt-7-1105-2014
6. Application of a PCA‐Based Fast Radiative Transfer Model to XCO2 Retrievals in the Shortwave Infrared P. Somkuti et al. https://doi.org/10.1002/2017JD027013
7. An optimal estimation-based retrieval of upper atmospheric oxygen airglow and temperature from SCIAMACHY limb observations K. Sun et al. https://doi.org/10.5194/amt-15-3721-2022
8. Atmospheric Monitoring of Methane in Beijing Using a Mobile Observatory W. Sun et al. https://doi.org/10.3390/atmos10090554
9. A study of measurement scenarios for the future CO2M mission: avoidance of detector saturation and the impact on XCO2 retrievals M. Weimer et al. https://doi.org/10.5194/amt-18-3321-2025
10. Discovery of New Lines in the R9 Multiplet of the 2v3 Band of CH124 H. Lin et al. https://doi.org/10.1103/PhysRevLett.122.013002
11. Mapping spectroscopic uncertainties into prospective methane retrieval errors from Sentinel-5 and its precursor R. Checa-Garcia et al. https://doi.org/10.5194/amt-8-3617-2015
12. XCO2 observations using satellite measurements with moderate spectral resolution: investigation using GOSAT and OCO-2 measurements L. Wu et al. https://doi.org/10.5194/amt-13-713-2020
13. PMIF v1.0: assessing the potential of satellite observations to constrain CO2 emissions from large cities and point sources over the globe using synthetic data Y. Wang et al. https://doi.org/10.5194/gmd-13-5813-2020
14. Investigation and Experimental Validation of a CH₄ Point-Source Detection Method Based on a Fabry-Pérot Interferometer . ZHANG Qiang et al. https://doi.org/10.7498/aps.75.20260051
15. Quantifying the impact of aerosol scattering on the retrieval of methane from airborne remote sensing measurements Y. Huang et al. https://doi.org/10.5194/amt-13-6755-2020
16. Satellite-inferred European carbon sink larger than expected M. Reuter et al. https://doi.org/10.5194/acp-14-13739-2014
17. Detecting high-emitting methane sources in oil/gas fields using satellite observations D. Cusworth et al. https://doi.org/10.5194/acp-18-16885-2018
18. Sensor array for wireless remote monitoring of carbon dioxide and methane near carbon sequestration and oil recovery sites W. Honeycutt et al. https://doi.org/10.1039/D0RA08593F
19. Multi-laboratory measurements of 12CH4 2ν3-band line parameters. Part I: Line intensities with relative combined standard uncertainties at the permille level Z. Reed et al. https://doi.org/10.1016/j.jqsrt.2025.109571
20. Constraining sector-specific CO2 and CH4 emissions in the US S. Miller & A. Michalak https://doi.org/10.5194/acp-17-3963-2017
21. Molecular dynamic simulations of N2-broadened methane line shapes and comparison with experiments T. Le et al. https://doi.org/10.1063/1.4976978
22. Development of a custom OMI NO2 data product for evaluating biases in a regional chemistry transport model G. Kuhlmann et al. https://doi.org/10.5194/acp-15-5627-2015
23. Bayesian denoising of satellite images using co-registered NO2 images E. Koene et al. https://doi.org/10.5194/amt-19-3999-2026
24. Improving Error Estimates for Evaluating Satellite-Based Atmospheric CO2 Measurement Concepts through Numerical Simulations B. Silveira et al. https://doi.org/10.3390/rs16132452
25. Space- and ground-based CO2 measurements: A review T. Yue et al. https://doi.org/10.1007/s11430-015-0239-7
26. Making methane visible M. Gålfalk et al. https://doi.org/10.1038/nclimate2877
27. Methane emissions from a Californian landfill, determined from airborne remote sensing and in situ measurements S. Krautwurst et al. https://doi.org/10.5194/amt-10-3429-2017
28. Jacobian matrix for near-infrared remote sensing based on vector radiative transfer model W. Bai et al. https://doi.org/10.1007/s11430-019-9586-7
29. Constraining Fossil Fuel CO2 Emissions From Urban Area Using OCO‐2 Observations of Total Column CO2 X. Ye et al. https://doi.org/10.1029/2019JD030528
30. How Much CO2 Is Taken Up by the European Terrestrial Biosphere? M. Reuter et al. https://doi.org/10.1175/BAMS-D-15-00310.1
31. Impact of Meteorological Uncertainties in the Methane Retrieval Ground Segment of the MERLIN Lidar Mission V. Cassé et al. https://doi.org/10.3390/atmos13030431
32. A Review of Greenhouse Gas Emissions from Agricultural Soil S. Basheer et al. https://doi.org/10.3390/su16114789
33. A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering—Part 2: Application to XCO2 Retrievals from OCO-2 M. Reuter et al. https://doi.org/10.3390/rs9111102
34. The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities G. Broquet et al. https://doi.org/10.5194/amt-11-681-2018
35. The potential of a constellation of low earth orbit satellite imagers to monitor worldwide fossil fuel CO2 emissions from large cities and point sources F. Lespinas et al. https://doi.org/10.1186/s13021-020-00153-4
36. Precise methane absorption measurements in the 1.64 μm spectral region for the MERLIN mission T. Delahaye et al. https://doi.org/10.1002/2016JD025024
37. Benchmarking data-driven inversion methods for the estimation of local CO2 emissions from synthetic satellite images of XCO2 and NO2 D. Santaren et al. https://doi.org/10.5194/amt-18-211-2025
38. Carbon Monitoring Satellite (CarbonSat): assessment of atmospheric CO2 and CH4 retrieval errors by error parameterization M. Buchwitz et al. https://doi.org/10.5194/amt-6-3477-2013
39. NanoCarb hyperspectral sensor: on performance optimization and analysis for greenhouse gas monitoring from a constellation of small satellites S. Gousset et al. https://doi.org/10.1007/s12567-019-00273-9
40. SCIATRAN software package (V4.6): update and further development of aerosol, clouds, surface reflectance databases and models L. Mei et al. https://doi.org/10.5194/gmd-16-1511-2023
41. Uncertainty information in climate data records from Earth observation C. Merchant et al. https://doi.org/10.5194/essd-9-511-2017
42. Reevaluating the Use of O2 a1Δg Band in Spaceborne Remote Sensing of Greenhouse Gases K. Sun et al. https://doi.org/10.1029/2018GL077823
43. The potential of CO2 satellite monitoring for climate governance: A review G. Pan et al. https://doi.org/10.1016/j.jenvman.2020.111423
44. Research agenda for the Russian Far East and utilization of multi-platform comprehensive environmental observations T. Petäjä et al. https://doi.org/10.1080/17538947.2020.1826589
45. Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation D. Belikov et al. https://doi.org/10.5194/gmd-9-749-2016
46. A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering—Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup M. Reuter et al. https://doi.org/10.3390/rs9111159
47. Towards spaceborne monitoring of localized CO2 emissions: an instrument concept and first performance assessment J. Strandgren et al. https://doi.org/10.5194/amt-13-2887-2020
48. Distinguishing Anthropogenic CO2 Emissions From Different Energy Intensive Industrial Sources Using OCO‐2 Observations: A Case Study in Northern China S. Wang et al. https://doi.org/10.1029/2018JD029005
49. Can a regional-scale reduction of atmospheric CO2 during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO2 retrievals M. Buchwitz et al. https://doi.org/10.5194/amt-14-2141-2021
50. Measurements of H2O broadening coefficients of infrared methane lines T. Delahaye et al. https://doi.org/10.1016/j.jqsrt.2015.12.015
51. Satellite-derived methane hotspot emission estimates using a fast data-driven method M. Buchwitz et al. https://doi.org/10.5194/acp-17-5751-2017
52. Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm J. Heymann et al. https://doi.org/10.5194/amt-8-2961-2015
53. Comparison of Profile Models for Water Vapor Absorption Lines T. Petrova et al. https://doi.org/10.1134/S1024856021040096
54. Airborne remote sensing and in situ measurements of atmospheric CO2 to quantify point source emissions T. Krings et al. https://doi.org/10.5194/amt-11-721-2018
55. A global map of emission clumps for future monitoring of fossil fuel CO2 emissions from space Y. Wang et al. https://doi.org/10.5194/essd-11-687-2019
56. Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites G. Kuhlmann et al. https://doi.org/10.3389/frsen.2021.689838
57. Assessing the Impact of Atmospheric CO2 and NO2 Measurements From Space on Estimating City-Scale Fossil Fuel CO2 Emissions in a Data Assimilation System T. Kaminski et al. https://doi.org/10.3389/frsen.2022.887456
58. Mapping the CO2 total column retrieval performance from shortwave infrared measurements: synthetic impacts of the spectral resolution, signal-to-noise ratio, and spectral band selection M. Dogniaux & C. Crevoisier https://doi.org/10.5194/amt-17-5373-2024
59. A new snow bidirectional reflectance distribution function model in spectral regions from UV to SWIR: Model development and application to ground-based, aircraft and satellite observations L. Mei et al. https://doi.org/10.1016/j.isprsjprs.2022.04.010
60. Geostationary Emission Explorer for Europe (G3E): mission concept and initial performance assessment A. Butz et al. https://doi.org/10.5194/amt-8-4719-2015
61. The Space Carbon Observatory (SCARBO) concept: assessment of XCO2 and XCH4 retrieval performance M. Dogniaux et al. https://doi.org/10.5194/amt-15-4835-2022
62. Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. https://doi.org/10.5194/acp-16-14371-2016
63. Reduced Methane Emissions from Santa Barbara Marine Seeps T. Krings et al. https://doi.org/10.3390/rs9111162
64. A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images B. Fuentes Andrade et al. https://doi.org/10.5194/amt-17-1145-2024
65. A Review of Satellite-Based CO2 Data Reconstruction Studies: Methodologies, Challenges, and Advances K. Hu et al. https://doi.org/10.3390/rs16203818
66. Retrieval of aerosol parameters from the oxygen A band in the presence of chlorophyll fluorescence A. Sanders & J. de Haan https://doi.org/10.5194/amt-6-2725-2013
67. Greenhouse gas emissions from soils—A review C. Oertel et al. https://doi.org/10.1016/j.chemer.2016.04.002
68. Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks M. Reuter et al. https://doi.org/10.5194/amt-18-241-2025
69. Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. https://doi.org/10.1016/j.rse.2016.12.027
70. China’s sizeable and uncertain carbon sink: a perspective from GOSAT L. Zhang et al. https://doi.org/10.1007/s11434-014-0260-3
71. Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems M. Scholze et al. https://doi.org/10.5194/bg-14-3401-2017
72. Quantifying CO2 emissions of a city with the Copernicus Anthropogenic CO2 Monitoring satellite mission G. Kuhlmann et al. https://doi.org/10.5194/amt-13-6733-2020
73. Accurate measurements of line strengths and air-broadening coefficients in methane around 1.66 µm using cavity ring down spectroscopy M. Kiseleva et al. https://doi.org/10.1016/j.jqsrt.2018.10.040
74. Introduction of Water‐Vapor Broadening Parameters and Their Temperature‐Dependent Exponents Into the HITRAN Database: Part I—CO2, N2O, CO, CH4, O2, NH3, and H2S Y. Tan et al. https://doi.org/10.1029/2019JD030929
75. A local- to national-scale inverse modeling system to assess the potential of spaceborne CO2 measurements for the monitoring of anthropogenic emissions D. Santaren et al. https://doi.org/10.5194/amt-14-403-2021
76. Airborne visualization and quantification of discrete methane sources in the environment D. Tratt et al. https://doi.org/10.1016/j.rse.2014.08.011
77. Precise predictions of H 2 O line shapes over a wide pressure range using simulations corrected by a single measurement N. Ngo et al. https://doi.org/10.1016/j.jqsrt.2017.12.014
78. Challenges in Methane Column Retrievals from AVIRIS-NG Imagery over Spectrally Cluttered Surfaces: A Sensitivity Analysis M. Zhang et al. https://doi.org/10.3390/rs9080835
79. Real-time monitoring of carbon concentration using laser-induced breakdown spectroscopy and machine learning Z. Zhou et al. https://doi.org/10.1364/OE.443732
80. Spatiotemporal evaluation of atmospheric CO2 fluctuations in Shaanxi Province (2013–2022) utilizing multi-source satellite remote sensing data Y. Li et al. https://doi.org/10.1186/s13021-025-00294-4
81. Tracking city CO2 emissions from space using a high-resolution inverse modelling approach: a case study for Berlin, Germany D. Pillai et al. https://doi.org/10.5194/acp-16-9591-2016
82. Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission G. Kuhlmann et al. https://doi.org/10.5194/amt-12-6695-2019
83. Simulated retrievals for the remote sensing of CO2, CH4, CO, and H2O from geostationary orbit X. Xi et al. https://doi.org/10.5194/amt-8-4817-2015
84. On the impact of granularity of space-based urban CO2 emissions in urban atmospheric inversions: A case study for Indianapolis, IN T. Oda et al. https://doi.org/10.1525/elementa.146
85. Insights into geological processes with CO2 remote sensing – A review of technology and applications M. Queißer et al. https://doi.org/10.1016/j.earscirev.2018.11.016