Publications

2022, Kotsakis, A., John T. Sullivan, Thomas F. Hanisco, Robert J. Swap, Vanessa Caicedo, Timothy A. Berkoff, Guillaume Gronoff et al., Sensitivity of total column NO2 at a marine site within the Chesapeake Bay during OWLETS-2, Atmospheric Environment, 277, 119063
Tags: Lidar, NO2

2022, Whiteman, D.N., Di Girolamo P., Behrendt A., Wulfmeyer V. and Franco N., Statistical Analysis of Simulated Spaceborne Thermodynamics Lidar Measurements in the Planetary Boundary Layer, Frontiers in Earth Science, 3:810032, https://doi.org/10.3389/frsen.2022.810032
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

2022, Steinbrecht, W. , Leblanc, T, Lidars in the Network for Detection of Atmospheric Composition Change (NDACC) and the Tropospheric Ozone Lidar Network (TOLNet), Handbook of Air Quality and Climate Change, pp. 1-24, Ed. Springer Nature, https://doi.org/10.1007/978-981-15-2527-8_55-1
Tags: Lidar, Ozone

2022, Chang, K., Cooper O., Gaudel A., Allaart M., Ancellet G., Clark H., Godin-Beekmann S., Leblanc T., van Malderen R., Nédélec P., Petropavlovskikh I. et al., Impact of the COVID‐19 Economic Downturn on Tropospheric Ozone Trends: An Uncertainty Weighted Data Synthesis for Quantifying Regional Anomalies Above Western North America and Europe, AGU Advances, 3 (2), pp.e2021AV000542, https://dx.doi.org/10.1029/2021av000542
Tags: COVID, Lidar, Ozone, Trends

2022, Di Paolantonio, M., Dionisi, D., and Liberti, G. L., A semi-automated procedure for the emitter–receiver geometry characterization of motor-controlled lidars, Atmospheric Measurement Techniques, 15, 1217–1231, https://doi.org/10.5194/amt-15-1217-2022
Tags: Lidar

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, 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, 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, Di Girolamo, P., F. Pini, G. Piras, The effect of COVID-19 on the distribution of PM10 pollution classes of vehicles: Comparison between 2020 and 2018, Science of the Total Environment, 811, 152036
Tags: Aerosol, Lidar