80 citations as recorded by crossref.

1. Complementing the topsoil information of the Land Use/Land Cover Area Frame Survey (LUCAS) with modelled N2O emissions E. Lugato et al. 10.1371/journal.pone.0176111
2. Eight-Year Estimates of Methane Emissions from Oil and Gas Operations in Western Canada Are Nearly Twice Those Reported in Inventories E. Chan et al. 10.1021/acs.est.0c04117
3. Global anthropogenic CO<sub>2</sub> emissions and uncertainties as a prior for Earth system modelling and data assimilation M. Choulga et al. 10.5194/essd-13-5311-2021
4. Nitrous Oxide Formation by Corona Discharge: Isotopic Composition Measurements and Atmospheric Applications M. Smith et al. 10.1029/2020JD033927
5. Analysis of total column CO<sub>2</sub> and CH<sub>4</sub> measurements in Berlin with WRF-GHG X. Zhao et al. 10.5194/acp-19-11279-2019
6. Assessing the optimized precision of the aircraft mass balance method for measurement of urban greenhouse gas emission rates through averaging A. Heimburger et al. 10.1525/elementa.134
7. 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
8. Continuous atmospheric in-situ measurements of the CH4/CO ratio at the Mt. Cimone station (Italy, 2165 m a.s.l.) and their possible use for estimating regional CH4 emissions C. Fratticioli et al. 10.1016/j.envres.2023.116343
9. Uncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases E. Solazzo et al. 10.5194/acp-21-5655-2021
10. Evidence of a recent decline in UK emissions of hydrofluorocarbons determined by the InTEM inverse model and atmospheric measurements A. Manning et al. 10.5194/acp-21-12739-2021
11. Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling S. Henne et al. 10.5194/acp-16-3683-2016
12. Abundance and sources of atmospheric halocarbons in the Eastern Mediterranean F. Schoenenberger et al. 10.5194/acp-18-4069-2018
13. Atmospheric observations consistent with reported decline in the UK's methane emissions (2013–2020) M. Lunt et al. 10.5194/acp-21-16257-2021
14. Simulating CH<sub>4</sub> and CO<sub>2</sub> over South and East Asia using the zoomed chemistry transport model LMDz-INCA X. Lin et al. 10.5194/acp-18-9475-2018
15. Atmospheric observations show accurate reporting and little growth in India’s methane emissions A. Ganesan et al. 10.1038/s41467-017-00994-7
16. 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
17. Evaluation of the boundary layer dynamics of the TM5 model over Europe E. Koffi et al. 10.5194/gmd-9-3137-2016
18. First results of tall tower based nitrous oxide flux monitoring over an agricultural region in Central Europe L. Haszpra et al. 10.1016/j.atmosenv.2017.12.035
19. Methane fluxes in the high northern latitudes for 2005–2013 estimated using a Bayesian atmospheric inversion R. Thompson et al. 10.5194/acp-17-3553-2017
20. A decade of CH<sub>4</sub>, CO and N<sub>2</sub>O in situ measurements at Lauder, New Zealand: assessing the long-term performance of a Fourier transform infrared trace gas and isotope analyser D. Smale et al. 10.5194/amt-12-637-2019
21. 2001~2018年瓦里全球本底站氧化亚氮浓度变化特征 苗. 梁 et al. 10.1360/N072023-0042
22. A Sensitivity Study of a Bayesian Inversion Model Used to Estimate Emissions of Synthetic Greenhouse Gases at the European Scale S. Annadate et al. 10.3390/atmos15010051
23. Estimation of greenhouse gas emission factors based on observed covariance of CO2, CH4, N2O and CO mole fractions L. Haszpra et al. 10.1186/s12302-019-0277-y
24. Comparison of nitrous oxide (N<sub>2</sub>O) analyzers for high-precision measurements of atmospheric mole fractions B. Lebegue et al. 10.5194/amt-9-1221-2016
25. European anthropogenic AFOLU greenhouse gas emissions: a review and benchmark data A. Petrescu et al. 10.5194/essd-12-961-2020
26. Seasonal variations of atmospheric CH4 at Jingdezhen station in Central China: Understanding the regional transport and its correlation with CO2 and CO L. Xia et al. 10.1016/j.atmosres.2020.104982
27. Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
28. 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
29. Comparison of four inverse modelling systems applied to the estimation of HFC-125, HFC-134a, and SF<sub>6</sub> emissions over Europe D. Brunner et al. 10.5194/acp-17-10651-2017
30. Systems biology approaches towards predictive microbial ecology A. Otwell et al. 10.1111/1462-2920.14378
31. Diagnosing Mixing Properties in Model Simulations for CH4 in the Stratosphere Z. Wang et al. 10.1029/2020JD032524
32. EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012 G. Janssens-Maenhout et al. 10.5194/essd-11-959-2019
33. Validation of WRF-Chem Model and CAMS Performance in Estimating Near-Surface Atmospheric CO2 Mixing Ratio in the Area of Saint Petersburg (Russia) G. Nerobelov et al. 10.3390/atmos12030387
34. Technical opportunities to reduce global anthropogenic emissions of nitrous oxide W. Winiwarter et al. 10.1088/1748-9326/aa9ec9
35. 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
36. The fingerprint of the summer 2018 drought in Europe on ground-based atmospheric CO2measurements M. Ramonet et al. 10.1098/rstb.2019.0513
37. A complete rethink is needed on how greenhouse gas emissions are quantified for national reporting A. Leip et al. 10.1016/j.atmosenv.2017.12.006
38. Observational evidence of high methane emissions over a city in western India N. Chandra et al. 10.1016/j.atmosenv.2019.01.007
39. LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination O. Tichý et al. 10.5194/gmd-9-4297-2016
40. Uncertainty of hourly-average concentration values derived from non-continuous measurements L. Haszpra & E. Prácser 10.5194/amt-14-3561-2021
41. Global 3‐D Simulations of the Triple Oxygen Isotope Signature Δ17O in Atmospheric CO2 G. Koren et al. 10.1029/2019JD030387
42. Tracers for evaluating computational models of atmospheric transport and oxidation at regional to global scales P. Simmonds et al. 10.1016/j.atmosenv.2020.118074
43. 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
44. How a European network may help with estimating methane emissions on the French national scale I. Pison et al. 10.5194/acp-18-3779-2018
45. Retrieval of Metop-A/IASI N2O Profiles and Validation with NDACC FTIR Data B. Barret et al. 10.3390/atmos12020219
46. Enhancing Uncrewed Aerial Vehicle Techniques for Monitoring Greenhouse Gas Plumes at Point Sources H. Kim et al. 10.1016/j.atmosenv.2024.120924
47. Inverse modelling of European CH<sub>4</sub> emissions during 2006–2012 using different inverse models and reassessed atmospheric observations P. Bergamaschi et al. 10.5194/acp-18-901-2018
48. Reconciling a national methane emission inventory with in-situ measurements Y. Liu et al. 10.1016/j.scitotenv.2023.165896
49. Impact of model resolution and its representativeness consistency with observations on operational prediction of PM2.5 with 3D-VAR data assimilation Y. Wei et al. 10.1016/j.apr.2024.102141
50. A pragmatic protocol for characterising errors in atmospheric inversions of methane emissions over Europe B. Szénási et al. 10.1080/16000889.2021.1914989
51. Tracing the origin of odour nuisance from citizens’ notifications with the SMART modelling system S. Trini Castelli et al. 10.1016/j.atmosenv.2023.119992
52. Diagnostic methods for atmospheric inversions of long-lived greenhouse gases A. Michalak et al. 10.5194/acp-17-7405-2017
53. Evaluating methane inventories by isotopic analysis in the London region G. Zazzeri et al. 10.1038/s41598-017-04802-6
54. A use-chain model to deal with uncertainties. A focus on GHG emission inventories S. Tonin et al. 10.1080/17583004.2016.1249217
55. Country-scale greenhouse gas budgets using shipborne measurements: a case study for the UK and Ireland C. Helfter et al. 10.5194/acp-19-3043-2019
56. A gap in nitrous oxide emission reporting complicates long-term climate mitigation S. Del Grosso et al. 10.1073/pnas.2200354119
57. U.S. CH4 emissions from oil and gas production: Have recent large increases been detected? L. Bruhwiler et al. 10.1002/2016JD026157
58. Exploring Gaps between Bottom-Up and Top-Down Emission Estimates Based on Uncertainties in Multiple Emission Inventories: A Case Study on CH4 Emissions in China P. Cheewaphongphan et al. 10.3390/su11072054
59. Assessing London CO<sub>2</sub>, CH<sub>4</sub> and CO emissions using aircraft measurements and dispersion modelling J. Pitt et al. 10.5194/acp-19-8931-2019
60. Lagrangian Particle Dispersion Models in the Grey Zone of Turbulence: Adaptations to FLEXPART-COSMO for Simulations at 1 km Grid Resolution I. Katharopoulos et al. 10.1007/s10546-022-00728-3
61. India leads in emission intensity per GDP: Insights from the gridded emission inventory for residential, road transport, and energy sectors V. Velamuri et al. 10.1016/j.jes.2024.10.015
62. Urban sources of methane characterised by long-term eddy covariance observations in central Europe M. Stichaner et al. 10.1016/j.atmosenv.2024.120743
63. Methane budget estimates in Finland from the CarbonTracker Europe-CH₄ data assimilation system A. Tsuruta et al. 10.1080/16000889.2018.1565030
64. Contributions of the troposphere and stratosphere to CH<sub>4</sub> model biases Z. Wang et al. 10.5194/acp-17-13283-2017
65. 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
66. Estimating the size of a methane emission point source at different scales: from local to landscape S. Riddick et al. 10.5194/acp-17-7839-2017
67. 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
68. Building on Paris: integrating nitrous oxide mitigation into future climate policy D. Kanter et al. 10.1016/j.cosust.2020.04.005
69. 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
70. Temporal characteristics and vertical profiles of atmospheric CH4 at the northern foot of the Qinling Mountains in China W. Liu et al. 10.1016/j.atmosenv.2024.120786
71. Short-term methane emissions from 2 dairy farms in California estimated by different measurement techniques and US Environmental Protection Agency inventory methodology: A case study C. Arndt et al. 10.3168/jds.2017-13881
72. Marine Nitrous Oxide Emissions From Three Eastern Boundary Upwelling Systems Inferred From Atmospheric Observations A. Ganesan et al. 10.1029/2020GL087822
73. Changing views of nitrous oxide emissions from agricultural soil: key controlling processes and assessment at different spatial scales K. Smith 10.1111/ejss.12409
74. The Monitoring Nitrous Oxide Sources (MIN2OS) satellite project P. Ricaud et al. 10.1016/j.rse.2021.112688
75. Characteristics of atmospheric nitrous oxide observed at Mt. Waliguan GAW global station in the inland Eurasia during eighteen years M. Liang et al. 10.1007/s11430-023-1197-7
76. Methodological progress in the measurement of agricultural greenhouse gases N. Mumu et al. 10.1080/17583004.2024.2366527
77. Quantification of methane emissions from cattle farms, using the tracer gas dispersion method N. Vechi et al. 10.1016/j.agee.2022.107885
78. Greenhouse gas observation network design for Africa A. Nickless et al. 10.1080/16000889.2020.1824486
79. Food systems are responsible for a third of global anthropogenic GHG emissions M. Crippa et al. 10.1038/s43016-021-00225-9
80. FLEXINVERT: an atmospheric Bayesian inversion framework for determining surface fluxes of trace species using an optimized grid R. Thompson & A. Stohl 10.5194/gmd-7-2223-2014