50 citations as recorded by crossref.

1. First data set of H2O/HDO columns from the Tropospheric Monitoring Instrument (TROPOMI) A. Schneider et al. https://doi.org/10.5194/amt-13-85-2020
2. Estimation of OH in urban plumes using TROPOMI-inferred NO2 ∕ CO S. Lama et al. https://doi.org/10.5194/acp-22-16053-2022
3. Carbon monoxide total columns from SCIAMACHY 2.3  µm atmospheric reflectance measurements: towards a full-mission data product (2003–2012) T. Borsdorff et al. https://doi.org/10.5194/amt-9-227-2016
4. FTIR Measurements of Greenhouse Gases over Thessaloniki, Greece in the Framework of COCCON and Comparison with S5P/TROPOMI Observations M. Mermigkas et al. https://doi.org/10.3390/rs13173395
5. Remote Sensing of Tropospheric Ozone from Space: Progress and Challenges J. Xu et al. https://doi.org/10.34133/remotesensing.0178
6. Evaluation of the WRF-Chem performance for the air pollutants over the United Arab Emirates Y. Yarragunta et al. https://doi.org/10.5194/acp-25-1685-2025
7. Methane and nitrous oxide from ground-based FTIR at Addis Ababa: observations, error analysis, and comparison with satellite data T. Yirdaw Berhe et al. https://doi.org/10.5194/amt-13-4079-2020
8. Mapping carbon monoxide pollution from space down to city scales with daily global coverage T. Borsdorff et al. https://doi.org/10.5194/amt-11-5507-2018
9. Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data M. Petters https://doi.org/10.5194/amt-14-7909-2021
10. Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network A. Luther et al. https://doi.org/10.5194/acp-22-5859-2022
11. Continuous measurements of SiF 4 and SO 2 by thermal emission spectroscopy: Insight from a 6-month survey at the Popocatépetl volcano N. Taquet et al. https://doi.org/10.1016/j.jvolgeores.2017.05.009
12. Evaluation of MOPITT and TROPOMI carbon monoxide retrievals using AirCore in situ vertical profiles S. Martínez-Alonso et al. https://doi.org/10.5194/amt-15-4751-2022
13. Measuring Carbon Monoxide With TROPOMI: First Results and a Comparison With ECMWF‐IFS Analysis Data T. Borsdorff et al. https://doi.org/10.1002/2018GL077045
14. Carbon monoxide column retrieval for clear-sky and cloudy atmospheres: a full-mission data set from SCIAMACHY 2.3  µm reflectance measurements T. Borsdorff et al. https://doi.org/10.5194/amt-10-1769-2017
15. Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing F. Ghasempour et al. https://doi.org/10.1016/j.jclepro.2021.128599
16. Airborne lidar measurements of atmospheric CO2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign J. Mao et al. https://doi.org/10.5194/amt-17-1061-2024
17. Shipborne measurements of XCO2, XCH4, and XCO above the Pacific Ocean and comparison to CAMS atmospheric analyses and S5P/TROPOMI M. Knapp et al. https://doi.org/10.5194/essd-13-199-2021
18. CO2 and CO temporal variability over Mexico City from ground-based total column and surface measurements N. Taquet et al. https://doi.org/10.5194/acp-24-11823-2024
19. Assimilation of S5P/TROPOMI carbon monoxide data with the global CAMS near-real-time system A. Inness et al. https://doi.org/10.5194/acp-22-14355-2022
20. The direct fitting approach for total ozone column retrievals: a sensitivity study on GOME-2/MetOp-A measurements A. Wassmann et al. https://doi.org/10.5194/amt-8-4429-2015
21. High-Resolution Seismic Characterization of Gas Hydrate Reservoir Using Wave-Equation-Based Inversion J. Shao et al. https://doi.org/10.3390/en15207652
22. A full-mission data set of H2O and HDO columns from SCIAMACHY 2.3 µm reflectance measurements A. Schneider et al. https://doi.org/10.5194/amt-11-3339-2018
23. Quantifying burning efficiency in megacities using the NO2∕CO ratio from the Tropospheric Monitoring Instrument (TROPOMI) S. Lama et al. https://doi.org/10.5194/acp-20-10295-2020
24. Methane profiles from GOSAT thermal infrared spectra A. de Lange & J. Landgraf https://doi.org/10.5194/amt-11-3815-2018
25. The impact of COVID-19 lockdowns on urban photochemistry as inferred from TROPOMI S. Lama et al. https://doi.org/10.1016/j.atmosenv.2023.120042
26. A Tikhonov regularized penalty function approach for solving polylinear programming problems J. Clempner & A. Poznyak https://doi.org/10.1016/j.cam.2017.07.032
27. Random Forest Classifier for Cloud Clearing of the Operational TROPOMI XCH4 Product T. Borsdorff et al. https://doi.org/10.3390/rs16071208
28. Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from TROPOMI P. Hochstaffl et al. https://doi.org/10.3390/rs12213486
29. 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
30. Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun https://doi.org/10.1029/2022GL101102
31. Vertical information of CO from TROPOMI total column measurements in context of the CAMS-IFS data assimilation scheme T. Borsdorff et al. https://doi.org/10.5194/amt-16-3027-2023
32. A study of synthetic 13CH4 retrievals from TROPOMI and Sentinel-5/UVNS E. Malina et al. https://doi.org/10.5194/amt-12-6273-2019
33. Carbon monoxide air pollution on sub-city scales and along arterial roads detected by the Tropospheric Monitoring Instrument T. Borsdorff et al. https://doi.org/10.5194/acp-19-3579-2019
34. Detection of carbon monoxide pollution from cities and wildfires on regional and urban scales: the benefit of CO column retrievals from SCIAMACHY 2.3 µm measurements under cloudy conditions T. Borsdorff et al. https://doi.org/10.5194/amt-11-2553-2018
35. Carbon Monoxide in Optically Thick Wildfire Smoke: Evaluating TROPOMI Using CU Airborne SOF Column Observations J. Rowe et al. https://doi.org/10.1021/acsearthspacechem.2c00048
36. Carbon monoxide total column retrievals from TROPOMI shortwave infrared measurements J. Landgraf et al. https://doi.org/10.5194/amt-9-4955-2016
37. A singular value decomposition framework for retrievals with vertical distribution information from greenhouse gas column absorption spectroscopy measurements A. Ramanathan et al. https://doi.org/10.5194/amt-11-4909-2018
38. Retrieval algorithm for the column CO2 mixing ratio from pulsed multi-wavelength lidar measurements X. Sun et al. https://doi.org/10.5194/amt-14-3909-2021
39. HDO and H2O total column retrievals from TROPOMI shortwave infrared measurements R. Scheepmaker et al. https://doi.org/10.5194/amt-9-3921-2016
40. An Inverse Problem Approach for the Retrieval of Ice Particle Mass from In Situ Measurements P. Coutris et al. https://doi.org/10.1175/JTECH-D-17-0013.1
41. 1.5 years of TROPOMI CO measurements: comparisons to MOPITT and ATom S. Martínez-Alonso et al. https://doi.org/10.5194/amt-13-4841-2020
42. Intercomparison of CO measurements from TROPOMI, ACE-FTS, and a high-Arctic ground-based Fourier transform spectrometer T. Wizenberg et al. https://doi.org/10.5194/amt-14-7707-2021
43. Monitoring CO emissions of the metropolis Mexico City using TROPOMI CO observations T. Borsdorff et al. https://doi.org/10.5194/acp-20-15761-2020
44. Retrieving H2O/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI) A. Schneider et al. https://doi.org/10.5194/amt-15-2251-2022
45. Radiative forcing due to shifting southern African fire regimes T. Eames et al. https://doi.org/10.5194/acp-25-17429-2025
46. Air quality impacts of COVID-19 lockdown measures detected from space using high spatial resolution observations of multiple trace gases from Sentinel-5P/TROPOMI P. Levelt et al. https://doi.org/10.5194/acp-22-10319-2022
47. Assessment of Tikhonov-type regularization methods for solving atmospheric inverse problems J. Xu et al. https://doi.org/10.1016/j.jqsrt.2016.08.003
48. Quantification and evaluation of atmospheric emissions from crop residue burning constrained by satellite observations in China during 2016–2020 X. Hong et al. https://doi.org/10.1016/j.scitotenv.2022.161237
49. What caused the extreme CO concentrations during the 2017 high-pollution episode in India? I. Dekker et al. https://doi.org/10.5194/acp-19-3433-2019
50. Global inverse modeling of CH4 sources and sinks: an overview of methods S. Houweling et al. https://doi.org/10.5194/acp-17-235-2017