86 citations as recorded by crossref.

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3. Carbon dioxide, methane and nitrous oxide emissions from the human-impacted Seine watershed in France A. Marescaux et al. https://doi.org/10.1016/j.scitotenv.2018.06.151
4. Errors and uncertainties in a gridded carbon dioxide emissions inventory T. Oda et al. https://doi.org/10.1007/s11027-019-09877-2
5. Site selection and effects of background towers on urban CO2 estimates: A case study from central downtown Zhengzhou in China G. Ren et al. https://doi.org/10.1016/j.envres.2024.120169
6. The influence of near-field fluxes on seasonal carbon dioxide enhancements: results from the Indianapolis Flux Experiment (INFLUX) N. Miles et al. https://doi.org/10.1186/s13021-020-00166-z
7. XCO2 in an emission hot-spot region: the COCCON Paris campaign 2015 F. Vogel et al. https://doi.org/10.5194/acp-19-3271-2019
8. Estimation of CO2 fluxes in the cities of Zurich and Paris using the ICON-ART CTDAS inverse modelling framework N. Ponomarev et al. https://doi.org/10.5194/acp-26-547-2026
9. Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO2 monitoring in urban areas E. Arzoumanian et al. https://doi.org/10.5194/amt-12-2665-2019
10. 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
11. Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts G. Nicolini et al. https://doi.org/10.1016/j.scitotenv.2022.154662
12. 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
13. The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. https://doi.org/10.5194/gmd-14-5331-2021
14. 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. https://doi.org/10.5194/amt-15-5261-2022
15. The carbon sink in China as seen from GOSAT with a regional inversion system based on the Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS) X. Kou et al. https://doi.org/10.5194/acp-23-6719-2023
16. The Utah urban carbon dioxide (UUCON) and Uintah Basin greenhouse gas networks: instrumentation, data, and measurement uncertainty R. Bares et al. https://doi.org/10.5194/essd-11-1291-2019
17. Estimating vehicle carbon dioxide emissions from Boulder, Colorado, using horizontal path-integrated column measurements E. Waxman et al. https://doi.org/10.5194/acp-19-4177-2019
18. Development and deployment of a mid-cost CO2 sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO2 emissions in Paris J. Lian et al. https://doi.org/10.5194/amt-17-5821-2024
19. Bayesian inversion of urban sectoral scale anthropogenic CO 2 emissions coupled with weather research and forecasting (WRF) and stochastic time-inverted lagrangian transport (STILT) models in Chengdu-Chongqing economic circle Z. Xia et al. https://doi.org/10.1080/17583004.2026.2627657
20. Monitoring CO2 in diverse European cities: highlighting needs and challenges through characterisation I. Storm et al. https://doi.org/10.5194/essd-17-6681-2025
21. Building-resolving simulations of anthropogenic and biospheric CO2 in the city of Zurich with GRAMM/GRAL D. Brunner et al. https://doi.org/10.5194/acp-25-14387-2025
22. Can We Detect Urban‐Scale CO2 Emission Changes Within Medium‐Sized Cities? D. Mallia et al. https://doi.org/10.1029/2023JD038686
23. Low-cost urban carbon monitoring network and implications for china: a comprehensive review H. Jiang et al. https://doi.org/10.1007/s11356-023-29836-4
24. 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
25. Sensitivity to the sources of uncertainties in the modeling of atmospheric CO2 concentration within and in the vicinity of Paris J. Lian et al. https://doi.org/10.5194/acp-21-10707-2021
26. Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria B. Matthews & H. Schume https://doi.org/10.1016/j.atmosenv.2022.118941
27. Anthropogenic and biogenic CO 2 fluxes in the Boston urban region M. Sargent et al. https://doi.org/10.1073/pnas.1803715115
28. From political pledges to quantitative mapping of climate mitigation plans: Comparison of two European cities I. Albarus et al. https://doi.org/10.1186/s13021-023-00236-y
29. Evaluation of the WRF-UCM mesoscale model and ECMWF global operational forecasts over the Paris region in the prospect of tracer atmospheric transport modeling J. Lian et al. https://doi.org/10.1525/elementa.319
30. 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
31. Quantification of oil and gas methane emissions in the Delaware and Marcellus basins using a network of continuous tower-based measurements Z. Barkley et al. https://doi.org/10.5194/acp-23-6127-2023
32. Can we separate industrial CH4 emission sources from atmospheric observations? - A test case for carbon isotopes, PMF and enhanced APCA S. Assan et al. https://doi.org/10.1016/j.atmosenv.2018.05.004
33. The impact of temporal variability in prior emissions on the optimization of urban anthropogenic emissions of CO2, CH4 and CO using in-situ observations I. Super et al. https://doi.org/10.1016/j.aeaoa.2021.100119
34. Observed CO2 concentration reveals steep decrease of anthropogenic emissions in winters of 2021 and 2022 in Hangzhou and Yangtze River Delta region, China C. Hu et al. https://doi.org/10.1016/j.scitotenv.2025.178884
35. Assimilation of OCO-2 retrievals with WRF-Chem/DART: A case study for the Midwestern United States Q. Zhang et al. https://doi.org/10.1016/j.atmosenv.2020.118106
36. An emerging GHG estimation approach can help cities achieve their climate and sustainability goals K. Mueller et al. https://doi.org/10.1088/1748-9326/ac0f25
37. High‐Resolution Lagrangian Inverse Modeling of CO2 Emissions Over the Paris Region During the First 2020 Lockdown Period K. Nalini et al. https://doi.org/10.1029/2021JD036032
38. Climate mitigation policies for cities must consider air quality impacts R. Commane & L. Schiferl https://doi.org/10.1016/j.chempr.2022.02.006
39. Potential of European 14CO2 observation network to estimate the fossil fuel CO2 emissions via atmospheric inversions Y. Wang et al. https://doi.org/10.5194/acp-18-4229-2018
40. Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. https://doi.org/10.3390/rs16183394
41. Overview of the Meso-NH model version 5.4 and its applications C. Lac et al. https://doi.org/10.5194/gmd-11-1929-2018
42. Observations of Thermally Driven Circulations in the Pyrenees: Comparison of Detection Methods and Impact on Atmospheric Composition Measured at a Mountaintop M. Hulin et al. https://doi.org/10.1175/JAMC-D-17-0268.1
43. Integrated urban services: Experience from four cities on different continents A. Baklanov et al. https://doi.org/10.1016/j.uclim.2020.100610
44. Sub-Daily Natural CO2 Flux Simulation Based on Satellite Data: Diurnal and Seasonal Pattern Comparisons to Anthropogenic CO2 Emissions in the Greater Tokyo Area Q. Wang et al. https://doi.org/10.3390/rs13112037
45. Variation of carbon dioxide mole fraction at a typical urban area in the Yangtze River Delta, China S. Fang et al. https://doi.org/10.1016/j.atmosres.2021.105884
46. 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. https://doi.org/10.3390/atmos14020223
47. Atmospheric network requirements to detect policy-driven urban CO2 emission changes I. Albarus et al. https://doi.org/10.1088/1748-9326/ae7b5f
48. A Modeling Framework of Atmospheric CO2 in the Mediterranean Marseille Coastal City Area, France B. Nathan et al. https://doi.org/10.3390/atmos15101193
49. Investigations into the use of multi-species measurements for source apportionment of the Indianapolis fossil fuel CO2 signal B. Nathan et al. https://doi.org/10.1525/elementa.131
50. Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties K. Wu et al. https://doi.org/10.1525/elementa.138
51. Analysis of temporal and spatial variability of atmospheric CO2 concentration within Paris from the GreenLITE™ laser imaging experiment J. Lian et al. https://doi.org/10.5194/acp-19-13809-2019
52. Optimizing a dynamic fossil fuel CO2 emission model with CTDAS (CarbonTracker Data Assimilation Shell, v1.0) for an urban area using atmospheric observations of CO2, CO, NOx, and SO2 I. Super et al. https://doi.org/10.5194/gmd-13-2695-2020
53. Government environmental control measures on CO2 emission during the 2014 Youth Olympic Games in Nanjing: Perspectives from a top-down approach C. Hu et al. https://doi.org/10.1016/j.jes.2021.04.016
54. Analysis of atmospheric CO2 variability in the Marseille city area and the north-west Mediterranean basin at different time scales I. Xueref-Remy et al. https://doi.org/10.1016/j.aeaoa.2023.100208
55. Constraining urban fossil fuel CO2 emissions in Seoul using combined ground and satellite observations with Bayesian inverse modelling S. Sim & S. Jeong https://doi.org/10.5194/acp-25-18509-2025
56. Exploration of the impact of nearby sources on urban atmospheric inversions using large eddy simulation B. Gaudet et al. https://doi.org/10.1525/elementa.247
57. Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study A. Karion et al. https://doi.org/10.5194/acp-19-2561-2019
58. Source decomposition of eddy-covariance CO2 flux measurements for evaluating a high-resolution urban CO2 emissions inventory K. Wu et al. https://doi.org/10.1088/1748-9326/ac7c29
59. Estimates of CO2 fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling A. Nickless et al. https://doi.org/10.5194/acp-18-4765-2018
60. Policy-Relevant Assessment of Urban CO2 Emissions T. Lauvaux et al. https://doi.org/10.1021/acs.est.0c00343
61. Detection of fossil fuel emission trends in the presence of natural carbon cycle variability Y. Yin et al. https://doi.org/10.1088/1748-9326/ab2dd7
62. Two years of total column measurements of CO2, CH4 and CO in Paris, France J. Doc et al. https://doi.org/10.5194/acp-26-8937-2026
63. Assessing the Effectiveness of an Urban CO2 Monitoring Network over the Paris Region through the COVID-19 Lockdown Natural Experiment J. Lian et al. https://doi.org/10.1021/acs.est.1c04973
64. Wintertime CO2, CH4, and CO Emissions Estimation for the Washington, DC–Baltimore Metropolitan Area Using an Inverse Modeling Technique I. Lopez-Coto et al. https://doi.org/10.1021/acs.est.9b06619
65. Constraining anthropogenic CO2 emissions using dense observations from OCO-3: Disentangling observed imprints over Xiamen-Zhangzhou-Quanzhou metropolitan area and challenges X. Ye et al. https://doi.org/10.1016/j.uclim.2025.102591
66. An atmospheric inversion over the city of Cape Town: sensitivity analyses A. Nickless et al. https://doi.org/10.5194/acp-19-7789-2019
67. 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
68. Development of an urban greenhouse gas modelling system to support a London monitoring network T. Hoare et al. https://doi.org/10.1002/wea.3795
69. Large and seasonally varying biospheric CO 2 fluxes in the Los Angeles megacity revealed by atmospheric radiocarbon J. Miller et al. https://doi.org/10.1073/pnas.2005253117
70. Synthesis of Urban CO2 Emission Estimates from Multiple Methods from the Indianapolis Flux Project (INFLUX) J. Turnbull et al. https://doi.org/10.1021/acs.est.8b05552
71. The Hestia fossil fuel CO2 emissions data product for the Los Angeles megacity (Hestia-LA) K. Gurney et al. https://doi.org/10.5194/essd-11-1309-2019
72. Can we use atmospheric CO2 measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris J. Lian et al. https://doi.org/10.5194/acp-23-8823-2023
73. Quantification of fossil fuel CO2 from combined CO, δ13CO2 and Δ14CO2 observations J. Kim et al. https://doi.org/10.5194/acp-23-14425-2023
74. Observing Annual Trends in Vehicular CO2 Emissions J. Kim et al. https://doi.org/10.1021/acs.est.1c06828
75. Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model X. Zhao et al. https://doi.org/10.5194/acp-23-14325-2023
76. Effects of Environmental Factors on the Performance of Ground-Based Low-Cost CO2 Sensors X. Ren et al. https://doi.org/10.3390/s25196114
77. 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. https://doi.org/10.5194/gmd-17-7263-2024
78. 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. https://doi.org/10.1016/j.rse.2021.112473
79. A Gradient-Descent Optimization of CO2–CO–NOx Emissions over the Paris Megacity─The Case of the First SARS-CoV-2 Lockdown C. Abdallah et al. https://doi.org/10.1021/acs.est.3c00566
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81. Diurnal, synoptic and seasonal variability of atmospheric CO2 in the Paris megacity area I. Xueref-Remy et al. https://doi.org/10.5194/acp-18-3335-2018
82. A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations S. Stagakis et al. https://doi.org/10.1016/j.scitotenv.2023.166035
83. Harmonised boundary layer wind profile dataset from six ground-based Doppler wind lidars in a transect across Paris, France W. Morrison et al. https://doi.org/10.5194/essd-17-6507-2025
84. New York City greenhouse gas emissions estimated with inverse modeling of aircraft measurements J. Pitt et al. https://doi.org/10.1525/elementa.2021.00082
85. Anthropogenic and natural controls on atmospheric δ13C-CO2 variations in the Yangtze River delta: insights from a carbon isotope modeling framework C. Hu et al. https://doi.org/10.5194/acp-21-10015-2021
86. 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