Publications

2024, Pardo Cantos, I., Mahieu, E., Chipperfield, M.P., Servais, C., Reimann, S., Vollmer, M.K., First HFC-134a retrievals from ground-based FTIR solar absorption spectra, comparison with TOMCAT model simulations, in-situ AGAGE observations, and ACE-FTS satellite data for the Jungfraujoch station, Journal of Quantitative Spectroscopy and Radiative Transfer, 318, 108938, https://doi.org/10.1016/j.jqsrt.2024.108938
Tags: CFC, FTIR, Model, Satellite, Validation

2023, Bruno, A.G., Harrison, J. J., Chipperfield, M. P., Moore, D. P., Pope, R. J., Wilson, C., Mahieu, E. and Notholt, J., Atmospheric distribution of HCN from satellite observations and 3-D model simulations, Atmospheric Chemistry and Physics, 23(8), 4849–4861, https://doi.org/10.5194/acp-23-4849-2023
Tags: FTIR, Model, Satellite

2023, Poraicu, C., Müller, J.-F., Stavrakou, T., Fonteyn, D., Tack, F., Deutsch, F., Laffineur, Q., Van Malderen, R., and Veldeman, N., Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium, Geoscientific Model Development, 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023
Tags: NO2, Satellite, Sonde

2023, Karagkiozidis, D., Koukouli M-E, Bais A, Balis D, Tzoumaka P., Assessment of the NO2 Spatio-Temporal Variability over Thessaloniki, Greece, Using MAX-DOAS Measurements and Comparison with S5P/TROPOMI Observations, Applied Sciences, 13(4):2641, https://doi.org/10.3390/app13042641
Tags: NO2, Satellite, UVVis

2023, Tu, Q., Hase, F., Chen, Z., Schneider, M., García, O., Khosrawi, F., Chen, S., Blumenstock, T., Liu, F., Qin, K., Cohen, J., He, Q., Lin, S., Jiang, H., and Fang, D., Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique, Atmospheric Measurement Techniques, 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023
Tags: FTIR, NO2

2022, Summa, D., F. Madonna, N. Franco, B. De Rosa, and P. Di Girolamo , Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1, Atmospheric Measurement Techniques, 15, 4153–4170, https://doi.org/10.5194/amt-15-4153-2022
Tags: Lidar, Model

2022, Koukouli, M.-E., Pseftogkas A, Karagkiozidis D, Skoulidou I, Drosoglou T, Balis D, Bais A, Melas D, Hatzianastassiou N., Air Quality in Two Northern Greek Cities Revealed by Their Tropospheric NO2 Levels, Atmosphere, 13(5):840, https://doi.org/10.3390/atmos13050840
Tags: NO2, UVVis

2022, Zeng, X., Wang, W., Liu, C., Shan, C., Xie, Y., Wu, P., Zhu, Q., Zhou, M., De Mazière, M., Mahieu, E., Pardo Cantos, I., Makkor, J., and Polyakov, A., Retrieval of atmospheric CFC-11 and CFC-12 from high-resolution FTIR observations at Hefei and comparisons with other independent datasets, Atmospheric Measurement Techniques, 15, 6739–6754, https://doi.org/10.5194/amt-15-6739-2022
Tags: CFC, FTIR, Validation

2022, Pardo Cantos, I., E. Mahieu, M. P. Chipperfield, D. Smale, J. W. Hannigan, M. Friedrich, P. Fraser, P.Krummel, M. Prignon, J. Makkor, C. Servaisj and J. Robinson, Determination and analysis of time series of CFC-11 (CCl3F) from FTIR solar spectra, in situ observations, and model data in the past 20 years above Jungfraujoch (46°N), Lauder (45°S), and Cape Grim (40°S) stations, Environmental Sciences, 2, 1487-1501, https://doi.org/10.1039/D2EA00060A
Tags: CFC, FTIR, Model

2022, Lutsch, E., D. Wunch, D. B. A. Jones, C. Clerbaux, J. W. Hannigan, T.-L. He, I. Ortega, S. Roche, K. Strong, and H. M. Worden, Can the data assimilation of CO from MOPITT or IASI constrain high-latitude wildfire emissions? A Case Study of the 2017 Canadian Wildfires, Earth and Space Science, p. 44, https://doi.org/10.1002/essoar.10510875.1
Tags: CO, Fire, Model, Satellite