42 citations as recorded by crossref.

1. Estimation of Anthropogenic CH4 and CO2 Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots C. Hu et al. 10.1029/2022JD037915
2. 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
3. Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area J. Sheng et al. 10.1088/1748-9326/ac24d1
4. Observed changes in China’s methane emissions linked to policy drivers Y. Zhang et al. 10.1073/pnas.2202742119
5. Development of the WRF-CO2 4D-Var assimilation system v1.0 T. Zheng et al. 10.5194/gmd-11-1725-2018
6. 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
7. 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
8. 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
9. The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
10. 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane J. Maasakkers et al. 10.5194/acp-21-4339-2021
11. 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
12. High-resolution inversion of methane emissions in the Southeast US using SEAC<sup>4</sup>RS aircraft observations of atmospheric methane: anthropogenic and wetland sources J. Sheng et al. 10.5194/acp-18-6483-2018
13. Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
14. Optimal and scalable methods to approximate the solutions of large‐scale Bayesian problems: theory and application to atmospheric inversion and data assimilation N. Bousserez & D. Henze 10.1002/qj.3209
15. 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. 10.5194/acp-23-5945-2023
16. Fundamentals of data assimilation applied to biogeochemistry P. Rayner et al. 10.5194/acp-19-13911-2019
17. Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions X. Yu et al. 10.5194/acp-21-951-2021
18. Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. 10.5194/acp-16-14371-2016
19. Remote sensing evidence of decadal changes in major tropospheric ozone precursors over East Asia A. Souri et al. 10.1002/2016JD025663
20. 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
21. Estimation of trace gas fluxes with objectively determined basis functions using reversible-jump Markov chain Monte Carlo M. Lunt et al. 10.5194/gmd-9-3213-2016
22. Constraints on methane emissions in North America from future geostationary remote-sensing measurements N. Bousserez et al. 10.5194/acp-16-6175-2016
23. Assessing the Iterative Finite Difference Mass Balance and 4D‐Var Methods to Derive Ammonia Emissions Over North America Using Synthetic Observations C. Li et al. 10.1029/2018JD030183
24. Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics X. Lu et al. 10.1073/pnas.2217900120
25. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data A. Turner et al. 10.5194/acp-15-7049-2015
26. Extreme events driving year-to-year differences in gross primary productivity across the US A. Turner et al. 10.5194/bg-18-6579-2021
27. First Top‐Down Estimates of Anthropogenic NOx Emissions Using High‐Resolution Airborne Remote Sensing Observations A. Souri et al. 10.1002/2017JD028009
28. Global distribution of methane emissions, emission trends, and OH concentrations and trends inferred from an inversion of GOSAT satellite data for 2010–2015 J. Maasakkers et al. 10.5194/acp-19-7859-2019
29. An inversion of NO<sub><i>x</i></sub> and non-methane volatile organic compound (NMVOC) emissions using satellite observations during the KORUS-AQ campaign and implications for surface ozone over East Asia A. Souri et al. 10.5194/acp-20-9837-2020
30. Improvements of Simulating Urban Atmospheric CO2 Concentration by Coupling with Emission Height and Dynamic Boundary Layer Variations in WRF-STILT Model Y. Peng et al. 10.3390/atmos14020223
31. 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
32. WOMBAT v1.0: a fully Bayesian global flux-inversion framework A. Zammit-Mangion et al. 10.5194/gmd-15-45-2022
33. National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations L. Shen et al. 10.1038/s41467-023-40671-6
34. On the representation error in data assimilation T. Janjić et al. 10.1002/qj.3130
35. Source Partitioning of Methane Emissions and its Seasonality in the U.S. Midwest Z. Chen et al. 10.1002/2017JG004356
36. Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins L. Shen et al. 10.5194/acp-22-11203-2022
37. Bayesian Optimization of the Community Land Model Simulated Biosphere–Atmosphere Exchange using CO2 Observations from a Dense Tower Network and Aircraft Campaigns over Oregon A. Schmidt et al. 10.1175/EI-D-16-0011.1
38. Revisiting global fossil fuel and biofuel emissions of ethane Z. Tzompa‐Sosa et al. 10.1002/2016JD025767
39. Inferring changes to the global carbon cycle with WOMBAT v2.0, a hierarchical flux-inversion framework M. Bertolacci et al. 10.1214/23-AOAS1790
40. Anthropogenic CO2 emissions from a megacity in the Yangtze River Delta of China C. Hu et al. 10.1007/s11356-018-2325-3
41. 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
42. Constraining NOx emissions using satellite NO2 measurements during 2013 DISCOVER-AQ Texas campaign A. Souri et al. 10.1016/j.atmosenv.2016.02.020