48 citations as recorded by crossref.

1. Observing carbon dioxide emissions over China's cities and industrial areas with the Orbiting Carbon Observatory-2 B. Zheng et al. 10.5194/acp-20-8501-2020
2. Estimating Global Anthropogenic CO2 Gridded Emissions Using a Data-Driven Stacked Random Forest Regression Model Y. Zhang et al. 10.3390/rs14163899
3. Accounting for meteorological biases in simulated plumes using smarter metrics P. Vanderbecken et al. 10.5194/amt-16-1745-2023
4. Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions K. Wu et al. 10.5194/amt-16-581-2023
5. A global map of emission clumps for future monitoring of fossil fuel CO<sub>2</sub> emissions from space Y. Wang et al. 10.5194/essd-11-687-2019
6. Pixel Size and Revisit Rate Requirements for Monitoring Power Plant CO2 Emissions from Space T. Hill & R. Nassar 10.3390/rs11131608
7. PMIF v1.0: assessing the potential of satellite observations to constrain CO<sub>2</sub> emissions from large cities and point sources over the globe using synthetic data Y. Wang et al. 10.5194/gmd-13-5813-2020
8. Spatialization and driving factors of carbon budget at county level in the Yangtze River Delta of China S. Wang et al. 10.1007/s11356-023-28917-8
9. Far-field biogenic and anthropogenic emissions as a dominant source of variability in local urban carbon budgets: A global high-resolution model study with implications for satellite remote sensing A. Schuh et al. 10.1016/j.rse.2021.112473
10. Enhancing scientific transparency in national CO2 emissions reports via satellite-based a posteriori estimates M. Watanabe et al. 10.1038/s41598-023-42664-3
11. Automated detection of atmospheric NO<sub>2</sub> plumes from satellite data: a tool to help infer anthropogenic combustion emissions D. Finch et al. 10.5194/amt-15-721-2022
12. Improved estimation of CO2 emissions from thermal power plants based on OCO-2 XCO2 retrieval using inline plume simulation Y. Li et al. 10.1016/j.scitotenv.2023.169586
13. Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates S. Noël et al. 10.5194/amt-17-2317-2024
14. Exploring Urban XCO2 Patterns Using PRISMA Satellite: A Case Study in Shanghai Y. Wu et al. 10.3390/atmos15030246
15. 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. 10.1186/s13021-020-00153-4
16. Determination of the emission rates of CO<sub>2</sub> point sources with airborne lidar S. Wolff et al. 10.5194/amt-14-2717-2021
17. Optimizing a dynamic fossil fuel CO<sub>2</sub> emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO<sub>2</sub>, CO, NO<sub><i>x</i></sub>, and SO<sub>2</sub> I. Super et al. 10.5194/gmd-13-2695-2020
18. The Space Carbon Observatory (SCARBO) concept: assessment of XCO2 and XCH4 retrieval performance M. Dogniaux et al. 10.5194/amt-15-4835-2022
19. Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO<sub>2</sub> monitoring in urban areas E. Arzoumanian et al. 10.5194/amt-12-2665-2019
20. Estimating power plant CO2 emission using OCO-2 XCO2 and high resolution WRF-Chem simulations T. Zheng et al. 10.1088/1748-9326/ab25ae
21. Detectability of CO<sub>2</sub> emission plumes of cities and power plants with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring (CO2M) mission G. Kuhlmann et al. 10.5194/amt-12-6695-2019
22. A local- to national-scale inverse modeling system to assess the potential of spaceborne CO<sub>2</sub> measurements for the monitoring of anthropogenic emissions D. Santaren et al. 10.5194/amt-14-403-2021
23. Urban carbon accounting: An overview L. Yin et al. 10.1016/j.uclim.2022.101195
24. Local Anomalies in the Column‐Averaged Dry Air Mole Fractions of Carbon Dioxide Across the Globe During the First Months of the Coronavirus Recession F. Chevallier et al. 10.1029/2020GL090244
25. The CO<sub>2</sub> integral emission by the megacity of St Petersburg as quantified from ground-based FTIR measurements combined with dispersion modelling D. Ionov et al. 10.5194/acp-21-10939-2021
26. Evaluating the Ability of the Pre-Launch TanSat-2 Satellite to Quantify Urban CO2 Emissions K. Wu et al. 10.3390/rs15204904
27. Large CO2 Emitters as Seen From Satellite: Comparison to a Gridded Global Emission Inventory F. Chevallier et al. 10.1029/2021GL097540
28. Complementing XCO2 imagery with ground-based CO2 and 14CO2 measurements to monitor CO2 emissions from fossil fuels on a regional to local scale E. Potier et al. 10.5194/amt-15-5261-2022
29. Spectral sizing of a coarse-spectral-resolution satellite sensor for XCO<sub>2</sub> J. Wilzewski et al. 10.5194/amt-13-731-2020
30. Spatial temporal pattern of carbon dioxide emission from vehicle N. Yaacob et al. 10.1088/1755-1315/1167/1/012009
31. Monitoring and quantifying CO2emissions of isolated power plants from space X. Lin et al. 10.5194/acp-23-6599-2023
32. Estimating carbon emissions from thermal power plants based on thermal characteristics K. Li et al. 10.1016/j.jag.2024.103768
33. Detection of fossil fuel emission trends in the presence of natural carbon cycle variability Y. Yin et al. 10.1088/1748-9326/ab2dd7
34. XCO<sub>2</sub> in an emission hot-spot region: the COCCON Paris campaign 2015 F. Vogel et al. 10.5194/acp-19-3271-2019
35. The CO2 Human Emissions (CHE) Project: First Steps Towards a European Operational Capacity to Monitor Anthropogenic CO2 Emissions G. Balsamo et al. 10.3389/frsen.2021.707247
36. Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites G. Kuhlmann et al. 10.3389/frsen.2021.689838
37. Deep learning applied to CO2 power plant emissions quantification using simulated satellite images J. Dumont Le Brazidec et al. 10.5194/gmd-17-1995-2024
38. Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
39. 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
40. Emerging reporting and verification needs under the Paris Agreement: How can the research community effectively contribute? L. Perugini et al. 10.1016/j.envsci.2021.04.012
41. UAV Databased Temperature Patterns Analysis with Carbon Emission Detection Using Deep Neural Network S. Mohanty et al. 10.1007/s41976-024-00143-x
42. Accounting for the vertical distribution of emissions in atmospheric CO<sub>2</sub> simulations D. Brunner et al. 10.5194/acp-19-4541-2019
43. The Influence of Instrumental Line Shape Degradation on Gas Retrievals and Observation of Greenhouse Gases in Maoming, China D. Liu et al. 10.3390/atmos12070863
44. Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5) I. Super et al. 10.5194/gmd-17-7263-2024
45. Evaluation of light atmospheric plume inversion methods using synthetic XCO2 satellite images to compute Paris CO2 emissions A. Danjou et al. 10.1016/j.rse.2023.113900
46. The ddeq Python library for point source quantification from remote sensing images (version 1.0) G. Kuhlmann et al. 10.5194/gmd-17-4773-2024
47. 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 10.5194/amt-17-5373-2024
48. Sensitivity to the sources of uncertainties in the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris J. Lian et al. 10.5194/acp-21-10707-2021