Publications
- 268 results
- Tag: HCN
- Tag: NO2
- Tag: Temperature
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2023, Mariaccia, A., Keckhut P., Hauchecorne A., Khaykin S., Ratynski M., Co‐Located Wind and Temperature Observations at Mid‐Latitudes During Mesospheric Inversion Layer Events, Geophysical Research Letters, 50 (9), pp.e2022GL102683, http://doi.org/10.1029/2022gl102683
Tags: Lidar, Temperature, Wind
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
2023, Farhani, G., Martucci, G., Roberts, T., Haefele, A., Sica, R.J., A Bayesian neural network approach for tropospheric temperature retrievals from a lidar instrument, International Journal of Remote Sensing, 44:5, 1611-1627, http://doi.org/10.1080/01431161.2023.2187723
Tags: Algorithm, Lidar, Temperature
2023, Zhou, M., Langerock, B., Wang, P., Vigouroux, C., Ni, Q., Hermans, C., Dils, B., Kumps, N., Nan, W., and De Mazière, M., Understanding the variations and sources of CO, C2H2, C2H6, H2CO, and HCN columns based on 3 years of new ground-based Fourier transform infrared measurements at Xianghe, China, Atmospheric Measurement Techniques, 16, 273–293, https://doi.org/10.5194/amt-16-273-2023
Tags: C2H2, C2H6, CO, FTIR, H2CO, HCN
2023, Chane Ming, F., Hauchecorne A., Bellisario C., Simoneau P., Keckhut P., Trémoulu S., Listowski C., Berthet G., Jégou F., Khaykin S., Tidiga M. et al., Case Study of a Mesospheric Temperature Inversion over Maïdo Observatory through a Multi-Instrumental Observation, Remote Sensing, 15, 2045, http://doi.org/10.3390/rs15082045
Tags: Lidar, Temperature
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, Ardalan, M., Keckhut P., Hauchecorne A., Wing R., Meftah M., Farhani G., Updated Climatology of Mesospheric Temperature Inversions Detected by Rayleigh Lidar above Observatoire de Haute Provence, France, Using a K-Mean Clustering Technique, Atmosphere, 13 (5), pp.814, https://doi.org/10.3390/atmos13050814
Tags: Lidar, Temperature
2022, Le Du, T., Keckhut P., Hauchecorne A., Simoneau P., Observation of Gravity Wave Vertical Propagation through a Mesospheric Inversion Layer, Atmosphere, 13 (7), pp.1003, https://doi.org/10.3390/atmos13071003
Tags: Lidar, Temperature