111 citations as recorded by crossref.

1. Global and regional emission estimates for HCFC-22 E. Saikawa et al. 10.5194/acp-12-10033-2012
2. Large and increasing methane emissions from eastern Amazonia derived from satellite data, 2010–2018 C. Wilson et al. 10.5194/acp-21-10643-2021
3. Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results O. Schneising et al. 10.5194/acp-12-1527-2012
4. Application of direct regularization techniques and bounded–variable least squares for inverse modeling of an urban emissions inventory A. Vanoye & A. Mendoza 10.5094/APR.2014.027
5. Optimizing global CO emission estimates using a four-dimensional variational data assimilation system and surface network observations P. Hooghiemstra et al. 10.5194/acp-11-4705-2011
6. Constraints and biases in a tropospheric two-box model of OH S. Naus et al. 10.5194/acp-19-407-2019
7. How much CO was emitted by the 2010 fires around Moscow? M. Krol et al. 10.5194/acp-13-4737-2013
8. Development of a variational flux inversion system (INVICAT v1.0) using the TOMCAT chemical transport model C. Wilson et al. 10.5194/gmd-7-2485-2014
9. Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
10. Fundamentals of data assimilation applied to biogeochemistry P. Rayner et al. 10.5194/acp-19-13911-2019
11. Order of magnitude wall time improvement of variational methane inversions by physical parallelization: a demonstration using TM5-4DVAR S. Pandey et al. 10.5194/gmd-15-4555-2022
12. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models? Z. Tan et al. 10.5194/acp-16-12649-2016
13. Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions S. Naus et al. 10.5194/acp-22-14735-2022
14. Global and regional emissions estimates for N<sub>2</sub>O E. Saikawa et al. 10.5194/acp-14-4617-2014
15. Inverse modelling of European N<sub>2</sub>O emissions: assimilating observations from different networks M. Corazza et al. 10.5194/acp-11-2381-2011
16. Inverse modeling of GOSAT-retrieved ratios of total column CH<sub>4</sub> and CO<sub>2</sub> for 2009 and 2010 S. Pandey et al. 10.5194/acp-16-5043-2016
17. Estimating US fossil fuel CO 2 emissions from measurements of 14 C in atmospheric CO 2 S. Basu et al. 10.1073/pnas.1919032117
18. Combined assimilation of NOAA surface and MIPAS satellite observations to constrain the global budget of carbonyl sulfide J. Ma et al. 10.5194/acp-24-6047-2024
19. Technical note: A high-resolution inverse modelling technique for estimating surface CO<sub>2</sub> fluxes based on the NIES-TM–FLEXPART coupled transport model and its adjoint S. Maksyutov et al. 10.5194/acp-21-1245-2021
20. Validation of TES methane with HIPPO aircraft observations: implications for inverse modeling of methane sources K. Wecht et al. 10.5194/acp-12-1823-2012
21. Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport E. Dowd et al. 10.5194/acp-23-7363-2023
22. Four-dimensional variational inversion of black carbon emissions during ARCTAS-CARB with WRFDA-Chem J. Guerrette & D. Henze 10.5194/acp-17-7605-2017
23. Estimating emissions of methane consistent with atmospheric measurements of methane and δ13C of methane S. Basu et al. 10.5194/acp-22-15351-2022
24. Improving computational efficiency in large linear inverse problems: an example from carbon dioxide flux estimation V. Yadav & A. Michalak 10.5194/gmd-6-583-2013
25. Comparison of CH4 inversions based on 15 months of GOSAT and SCIAMACHY observations G. Monteil et al. 10.1002/2013JD019760
26. Evaluation Criteria on the Design for Assimilating Remote Sensing Data Using Variational Approaches S. Lu et al. 10.1175/MWR-D-16-0289.1
27. ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application P. Bosman & M. Krol 10.5194/gmd-16-47-2023
28. Decadal Changes in Atmospheric Methane Emissions in the Eastern Himalayan Region: Source Apportionment and Impact Assessment A. Saikia et al. 10.1007/s41742-022-00501-x
29. Tropospheric methane in the tropics – first year from IASI hyperspectral infrared observations C. Crevoisier et al. 10.5194/acp-9-6337-2009
30. Emissions estimation from satellite retrievals: A review of current capability D. Streets et al. 10.1016/j.atmosenv.2013.05.051
31. Multi-year observations reveal a larger than expected autumn respiration signal across northeast Eurasia B. Byrne et al. 10.5194/bg-19-4779-2022
32. Constraints on methane emissions in North America from future geostationary remote-sensing measurements N. Bousserez et al. 10.5194/acp-16-6175-2016
33. The importance of transport model uncertainties for the estimation of CO<sub>2</sub> sources and sinks using satellite measurements S. Houweling et al. 10.5194/acp-10-9981-2010
34. Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere A. Ostler et al. 10.5194/amt-9-4843-2016
35. On the consistency between global and regional methane emissions inferred from SCIAMACHY, TANSO-FTS, IASI and surface measurements C. Cressot et al. 10.5194/acp-14-577-2014
36. A multi-year methane inversion using SCIAMACHY, accounting for systematic errors using TCCON measurements S. Houweling et al. 10.5194/acp-14-3991-2014
37. A remote sensing technique for global monitoring of power plant CO<sub>2</sub> emissions from space and related applications H. Bovensmann et al. 10.5194/amt-3-781-2010
38. Constraining global methane emissions and uptake by ecosystems R. Spahni et al. 10.5194/bg-8-1643-2011
39. Retrieval of methane source strengths in Europe using a simple modeling approach to assess the potential of spaceborne lidar observations C. Weaver et al. 10.5194/acp-14-2625-2014
40. Multi-species inversion of CH<sub>4</sub>, CO and H<sub>2</sub> emissions from surface measurements I. Pison et al. 10.5194/acp-9-5281-2009
41. Diagnosing Mixing Properties in Model Simulations for CH4 in the Stratosphere Z. Wang et al. 10.1029/2020JD032524
42. Top-down estimates of European CH<sub>4</sub> and N<sub>2</sub>O emissions based on four different inverse models P. Bergamaschi et al. 10.5194/acp-15-715-2015
43. A Bayesian framework for deriving sector-based methane emissions from top-down fluxes D. Cusworth et al. 10.1038/s43247-021-00312-6
44. Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements J. Landgraf et al. 10.5194/amt-9-4955-2016
45. Contributions of the troposphere and stratosphere to CH<sub>4</sub> model biases Z. Wang et al. 10.5194/acp-17-13283-2017
46. On the use of satellite-derived CH<sub>4</sub> : CO<sub>2</sub> columns in a joint inversion of CH<sub>4</sub> and CO<sub>2</sub> fluxes S. Pandey et al. 10.5194/acp-15-8615-2015
47. Global modelling of H<sub>2</sub> mixing ratios and isotopic compositions with the TM5 model G. Pieterse et al. 10.5194/acp-11-7001-2011
48. Inversion of long-lived trace gas emissions using combined Eulerian and Lagrangian chemical transport models M. Rigby et al. 10.5194/acp-11-9887-2011
49. A Method for Estimating the Background Column Concentration of CO2 Using the Lagrangian Approach Z. Pei et al. 10.1109/TGRS.2022.3176134
50. First ground-based FTIR observations of methane in the inner tropics over several years A. Petersen et al. 10.5194/acp-10-7231-2010
51. Atmospheric CH4 in the first decade of the 21st century: Inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements P. Bergamaschi et al. 10.1002/jgrd.50480
52. Evaluation of the boundary layer dynamics of the TM5 model over Europe E. Koffi et al. 10.5194/gmd-9-3137-2016
53. The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017 A. Petrescu et al. 10.5194/essd-13-2307-2021
54. Anomalous carbon uptake in Australia as seen by GOSAT R. Detmers et al. 10.1002/2015GL065161
55. What can <sup>14</sup>CO measurements tell us about OH? M. Krol et al. 10.5194/acp-8-5033-2008
56. Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling S. Henne et al. 10.5194/acp-16-3683-2016
57. Estimates of black carbon emissions in the western United States using the GEOS-Chem adjoint model Y. Mao et al. 10.5194/acp-15-7685-2015
58. European CH4 inversions with ICON-ART coupled to the CarbonTracker Data Assimilation Shell M. Steiner et al. 10.5194/acp-24-2759-2024
59. Separation of biospheric and fossil fuel fluxes of CO<sub>2</sub> by atmospheric inversion of CO<sub>2</sub> and <sup>14</sup>CO<sub>2</sub> measurements: Observation System Simulations S. Basu et al. 10.5194/acp-16-5665-2016
60. 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
61. Global column-averaged methane mixing ratios from 2003 to 2009 as derived from SCIAMACHY: Trends and variability C. Frankenberg et al. 10.1029/2010JD014849
62. Impact of wildfires on some greenhouse gases over continental USA: A study based on satellite data B. Kim & S. Sarkar 10.1016/j.rse.2016.10.047
63. The impact of transport model differences on CO<sub>2</sub> surface flux estimates from OCO-2 retrievals of column average CO<sub>2</sub> S. Basu et al. 10.5194/acp-18-7189-2018
64. Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO<sub>2</sub> surface flux inversions A. Babenhauserheide et al. 10.5194/acp-15-9747-2015
65. Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data C. Groot Zwaaftink et al. 10.5194/gmd-11-4469-2018
66. History of chemically and radiatively important atmospheric gases from the Advanced Global Atmospheric Gases Experiment (AGAGE) R. Prinn et al. 10.5194/essd-10-985-2018
67. Estimating Nitrous Oxide (N2O) emissions from managed soils at higher spatial resolution in the Republic of Ireland C. Francisco-Cruz et al. 10.1016/j.ecolind.2023.111471
68. Impact of assimilating multi-source observations on meteorological and PM2.5 forecast over Central China J. Liu et al. 10.1016/j.atmosres.2020.104945
69. Design and evaluation of CO<sub>2</sub> observation network to optimize surface CO<sub>2</sub> fluxes in Asia using observation system simulation experiments J. Park & H. Kim 10.5194/acp-20-5175-2020
70. Accounting for NOx emissions from biomass burning and urbanization doubles existing inventories over South, Southeast and East Asia J. Liu et al. 10.1038/s43247-024-01424-5
71. The 2015–2016 carbon cycle as seen from OCO-2 and the global in situ network S. Crowell et al. 10.5194/acp-19-9797-2019
72. Regional CO<sub>2</sub> inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0 G. Monteil & M. Scholze 10.5194/gmd-14-3383-2021
73. A Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) for emission estimates: system development and application S. Feng et al. 10.5194/gmd-16-5949-2023
74. Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia H. Kim et al. 10.1007/s13143-017-0049-9
75. Improved global wetland carbon isotopic signatures support post-2006 microbial methane emission increase Y. Oh et al. 10.1038/s43247-022-00488-5
76. Utilizing Earth Observations of Soil Freeze/Thaw Data and Atmospheric Concentrations to Estimate Cold Season Methane Emissions in the Northern High Latitudes M. Tenkanen et al. 10.3390/rs13245059
77. Regional data assimilation of multi-spectral MOPITT observations of CO over North America Z. Jiang et al. 10.5194/acp-15-6801-2015
78. Technical Note: Comparison of ensemble Kalman filter and variational approaches for CO<sub>2</sub> data assimilation A. Chatterjee & A. Michalak 10.5194/acp-13-11643-2013
79. Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020) J. Liu et al. 10.5194/essd-13-299-2021
80. Top-down estimates of biomass burning emissions of black carbon in the Western United States Y. Mao et al. 10.5194/acp-14-7195-2014
81. The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
82. Barriers to predicting changes in global terrestrial methane fluxes: analyses using CLM4Me, a methane biogeochemistry model integrated in CESM W. Riley et al. 10.5194/bg-8-1925-2011
83. A three-dimensional-model inversion of methyl chloroform to constrain the atmospheric oxidative capacity S. Naus et al. 10.5194/acp-21-4809-2021
84. Inverse modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals P. Bergamaschi et al. 10.1029/2009JD012287
85. Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition H. Nesser et al. 10.5194/amt-14-5521-2021
86. High-resolution inverse modelling of European CH4 emissions using the novel FLEXPART-COSMO TM5 4DVAR inverse modelling system P. Bergamaschi et al. 10.5194/acp-22-13243-2022
87. Global methane emission estimates for 2000–2012 from CarbonTracker Europe-CH<sub>4</sub> v1.0 A. Tsuruta et al. 10.5194/gmd-10-1261-2017
88. Network design for quantifying urban CO<sub>2</sub> emissions: assessing trade-offs between precision and network density A. Turner et al. 10.5194/acp-16-13465-2016
89. Interpreting contemporary trends in atmospheric methane A. Turner et al. 10.1073/pnas.1814297116
90. The global methane budget 2000–2012 M. Saunois et al. 10.5194/essd-8-697-2016
91. Three years of greenhouse gas column-averaged dry air mole fractions retrieved from satellite – Part 2: Methane O. Schneising et al. 10.5194/acp-9-443-2009
92. Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling R. Locatelli et al. 10.5194/acp-13-9917-2013
93. Global inverse modeling of CH<sub>4</sub> sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
94. Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories F. Wang et al. 10.3390/rs11212489
95. Mapping spectroscopic uncertainties into prospective methane retrieval errors from Sentinel-5 and its precursor R. Checa-Garcia et al. 10.5194/amt-8-3617-2015
96. Inverse modelling of CH<sub>4</sub> emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY M. Alexe et al. 10.5194/acp-15-113-2015
97. Quantifying methane and nitrous oxide emissions from the UK and Ireland using a national-scale monitoring network A. Ganesan et al. 10.5194/acp-15-6393-2015
98. Atmospheric constraints on 2004 emissions of methane and nitrous oxide in North America from atmospheric measurements and a receptor-oriented modeling framework E. Kort et al. 10.1080/19438151003767483
99. Evaluation of CH4MOD<sub>wetland</sub> and Terrestrial Ecosystem Model (TEM) used to estimate global CH<sub>4</sub> emissions from natural wetlands T. Li et al. 10.5194/gmd-13-3769-2020
100. Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite S. Miller et al. 10.5194/gmd-13-1771-2020
101. The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019 A. Petrescu et al. 10.5194/essd-15-1197-2023
102. Inverse modeling of European CH<sub>4</sub> emissions: sensitivity to the observational network M. Villani et al. 10.5194/acp-10-1249-2010
103. Computationally efficient methods for large-scale atmospheric inverse modeling T. Cho et al. 10.5194/gmd-15-5547-2022
104. Methane and nitrous oxide from ground-based FTIR at Addis Ababa: observations, error analysis, and comparison with satellite data T. Yirdaw Berhe et al. 10.5194/amt-13-4079-2020
105. Methane retrievals from Greenhouse Gases Observing Satellite (GOSAT) shortwave infrared measurements: Performance comparison of proxy and physics retrieval algorithms D. Schepers et al. 10.1029/2012JD017549
106. Atmospheric measurements of Δ17O in CO2 in Göttingen, Germany reveal a seasonal cycle driven by biospheric uptake M. Hofmann et al. 10.1016/j.gca.2016.11.019
107. Estimation of CH4emission based on an advanced 4D-LETKF assimilation system J. Bisht et al. 10.5194/gmd-16-1823-2023
108. Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations R. Janardanan et al. 10.3390/rs12030375
109. Investigating regional source and sink patterns of Alpine CO2 and CH4 concentrations based on a back trajectory receptor model E. Giemsa et al. 10.1186/s12302-019-0233-x
110. Four‐dimensional variational data assimilation for inverse modeling of atmospheric methane emissions: Analysis of SCIAMACHY observations J. Meirink et al. 10.1029/2007JD009740
111. Global CO<sub>2</sub> fluxes estimated from GOSAT retrievals of total column CO<sub>2</sub> S. Basu et al. 10.5194/acp-13-8695-2013