77 citations as recorded by crossref.

1. Anthropogenic CO2 emissions from a megacity in the Yangtze River Delta of China C. Hu et al. 10.1007/s11356-018-2325-3
2. Carbon dioxide, methane and nitrous oxide emissions from the human-impacted Seine watershed in France A. Marescaux et al. 10.1016/j.scitotenv.2018.06.151
3. Errors and uncertainties in a gridded carbon dioxide emissions inventory T. Oda et al. 10.1007/s11027-019-09877-2
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5. The influence of near-field fluxes on seasonal carbon dioxide enhancements: results from the Indianapolis Flux Experiment (INFLUX) N. Miles et al. 10.1186/s13021-020-00166-z
6. XCO2 in an emission hot-spot region: the COCCON Paris campaign 2015 F. Vogel et al. 10.5194/acp-19-3271-2019
7. Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO2 monitoring in urban areas E. Arzoumanian et al. 10.5194/amt-12-2665-2019
8. Constraining Fossil Fuel CO2 Emissions From Urban Area Using OCO‐2 Observations of Total Column CO2 X. Ye et al. 10.1029/2019JD030528
9. Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts G. Nicolini et al. 10.1016/j.scitotenv.2022.154662
10. The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities G. Broquet et al. 10.5194/amt-11-681-2018
11. The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
12. 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
13. 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. 10.5194/acp-23-6719-2023
14. The Utah urban carbon dioxide (UUCON) and Uintah Basin greenhouse gas networks: instrumentation, data, and measurement uncertainty R. Bares et al. 10.5194/essd-11-1291-2019
15. Estimating vehicle carbon dioxide emissions from Boulder, Colorado, using horizontal path-integrated column measurements E. Waxman et al. 10.5194/acp-19-4177-2019
16. 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. 10.5194/amt-17-5821-2024
17. Can We Detect Urban‐Scale CO2 Emission Changes Within Medium‐Sized Cities? D. Mallia et al. 10.1029/2023JD038686
18. Low-cost urban carbon monitoring network and implications for china: a comprehensive review H. Jiang et al. 10.1007/s11356-023-29836-4
19. 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. 10.5194/amt-14-403-2021
20. Sensitivity to the sources of uncertainties in the modeling of atmospheric CO2 concentration within and in the vicinity of Paris J. Lian et al. 10.5194/acp-21-10707-2021
21. Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria B. Matthews & H. Schume 10.1016/j.atmosenv.2022.118941
22. Anthropogenic and biogenic CO 2 fluxes in the Boston urban region M. Sargent et al. 10.1073/pnas.1803715115
23. From political pledges to quantitative mapping of climate mitigation plans: Comparison of two European cities I. Albarus et al. 10.1186/s13021-023-00236-y
24. 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. 10.1525/elementa.319
25. 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
26. 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. 10.5194/acp-23-6127-2023
27. Can we separate industrial CH4 emission sources from atmospheric observations? - A test case for carbon isotopes, PMF and enhanced APCA S. Assan et al. 10.1016/j.atmosenv.2018.05.004
28. 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. 10.1016/j.aeaoa.2021.100119
29. Assimilation of OCO-2 retrievals with WRF-Chem/DART: A case study for the Midwestern United States Q. Zhang et al. 10.1016/j.atmosenv.2020.118106
30. An emerging GHG estimation approach can help cities achieve their climate and sustainability goals K. Mueller et al. 10.1088/1748-9326/ac0f25
31. High‐Resolution Lagrangian Inverse Modeling of CO2 Emissions Over the Paris Region During the First 2020 Lockdown Period K. Nalini et al. 10.1029/2021JD036032
32. Climate mitigation policies for cities must consider air quality impacts R. Commane & L. Schiferl 10.1016/j.chempr.2022.02.006
33. Potential of European 14CO2 observation network to estimate the fossil fuel CO2 emissions via atmospheric inversions Y. Wang et al. 10.5194/acp-18-4229-2018
34. Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
35. Overview of the Meso-NH model version 5.4 and its applications C. Lac et al. 10.5194/gmd-11-1929-2018
36. 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. 10.1175/JAMC-D-17-0268.1
37. Integrated urban services: Experience from four cities on different continents A. Baklanov et al. 10.1016/j.uclim.2020.100610
38. 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. 10.3390/rs13112037
39. Variation of carbon dioxide mole fraction at a typical urban area in the Yangtze River Delta, China S. Fang et al. 10.1016/j.atmosres.2021.105884
40. 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
41. A Modeling Framework of Atmospheric CO2 in the Mediterranean Marseille Coastal City Area, France B. Nathan et al. 10.3390/atmos15101193
42. Investigations into the use of multi-species measurements for source apportionment of the Indianapolis fossil fuel CO2 signal B. Nathan et al. 10.1525/elementa.131
43. 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. 10.1525/elementa.138
44. Analysis of temporal and spatial variability of atmospheric CO2 concentration within Paris from the GreenLITE™ laser imaging experiment J. Lian et al. 10.5194/acp-19-13809-2019
45. 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. 10.5194/gmd-13-2695-2020
46. 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. 10.1016/j.jes.2021.04.016
47. 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. 10.1016/j.aeaoa.2023.100208
48. Exploration of the impact of nearby sources on urban atmospheric inversions using large eddy simulation B. Gaudet et al. 10.1525/elementa.247
49. Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study A. Karion et al. 10.5194/acp-19-2561-2019
50. Source decomposition of eddy-covariance CO2 flux measurements for evaluating a high-resolution urban CO2 emissions inventory K. Wu et al. 10.1088/1748-9326/ac7c29
51. Estimates of CO2 fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling A. Nickless et al. 10.5194/acp-18-4765-2018
52. Policy-Relevant Assessment of Urban CO2 Emissions T. Lauvaux et al. 10.1021/acs.est.0c00343
53. Detection of fossil fuel emission trends in the presence of natural carbon cycle variability Y. Yin et al. 10.1088/1748-9326/ab2dd7
54. Assessing the Effectiveness of an Urban CO2 Monitoring Network over the Paris Region through the COVID-19 Lockdown Natural Experiment J. Lian et al. 10.1021/acs.est.1c04973
55. Wintertime CO2, CH4, and CO Emissions Estimation for the Washington, DC–Baltimore Metropolitan Area Using an Inverse Modeling Technique I. Lopez-Coto et al. 10.1021/acs.est.9b06619
56. An atmospheric inversion over the city of Cape Town: sensitivity analyses A. Nickless et al. 10.5194/acp-19-7789-2019
57. 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. 10.5194/gmd-13-5813-2020
58. Development of an urban greenhouse gas modelling system to support a London monitoring network T. Hoare et al. 10.1002/wea.3795
59. Large and seasonally varying biospheric CO 2 fluxes in the Los Angeles megacity revealed by atmospheric radiocarbon J. Miller et al. 10.1073/pnas.2005253117
60. Synthesis of Urban CO2 Emission Estimates from Multiple Methods from the Indianapolis Flux Project (INFLUX) J. Turnbull et al. 10.1021/acs.est.8b05552
61. The Hestia fossil fuel CO2 emissions data product for the Los Angeles megacity (Hestia-LA) K. Gurney et al. 10.5194/essd-11-1309-2019
62. 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. 10.5194/acp-23-8823-2023
63. Quantification of fossil fuel CO2 from combined CO, δ13CO2 and Δ14CO2 observations J. Kim et al. 10.5194/acp-23-14425-2023
64. Observing Annual Trends in Vehicular CO2 Emissions J. Kim et al. 10.1021/acs.est.1c06828
65. Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model X. Zhao et al. 10.5194/acp-23-14325-2023
66. 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
67. 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
68. A High-Resolution Monitoring Approach of Urban Co2 Fluxes. Part 2 - Optimisation Framework Using Eddy Covariance Observations S. Stagakis et al. 10.2139/ssrn.4172740
69. 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. 10.1021/acs.est.3c00566
70. Diurnal, synoptic and seasonal variability of atmospheric CO2 in the Paris megacity area I. Xueref-Remy et al. 10.5194/acp-18-3335-2018
71. A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations S. Stagakis et al. 10.1016/j.scitotenv.2023.166035
72. New York City greenhouse gas emissions estimated with inverse modeling of aircraft measurements J. Pitt et al. 10.1525/elementa.2021.00082
73. 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. 10.5194/acp-21-10015-2021
74. A global map of emission clumps for future monitoring of fossil fuel CO2 emissions from space Y. Wang et al. 10.5194/essd-11-687-2019
75. What would dense atmospheric observation networks bring to the quantification of city CO2 emissions? L. Wu et al. 10.5194/acp-16-7743-2016
76. Analysis of the potential of near-ground measurements of CO2 and CH4 in London, UK, for the monitoring of city-scale emissions using an atmospheric transport model A. Boon et al. 10.5194/acp-16-6735-2016
77. The Wintertime Covariation of CO2 and Criteria Pollutants in an Urban Valley of the Western United States R. Bares et al. 10.1002/2017JD027917