Articles | Volume 18, issue 19
https://doi.org/10.5194/acp-18-14511-2018
https://doi.org/10.5194/acp-18-14511-2018
Research article
 | 
10 Oct 2018
Research article |  | 10 Oct 2018

A neural network aerosol-typing algorithm based on lidar data

Doina Nicolae, Jeni Vasilescu, Camelia Talianu, Ioannis Binietoglou, Victor Nicolae, Simona Andrei, and Bogdan Antonescu

Related authors

High-resolution air quality maps for Bucharest using Mixed-Effects Modeling Framework
Camelia Talianu, Jeni Vasilescu, Doina Nicolae, Alexandru Ilie, Andrei Dandocsi, Anca Nemuc, and Livio Belegante
EGUsphere, https://doi.org/10.5194/egusphere-2024-2930,https://doi.org/10.5194/egusphere-2024-2930, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023,https://doi.org/10.5194/amt-16-6025-2023, 2023
Short summary
A novel method of identifying and analysing oil smoke plumes based on MODIS and CALIPSO satellite data
Alexandru Mereuţă, Nicolae Ajtai, Andrei T. Radovici, Nikolaos Papagiannopoulos, Lucia T. Deaconu, Camelia S. Botezan, Horaţiu I. Ştefănie, Doina Nicolae, and Alexandru Ozunu
Atmos. Chem. Phys., 22, 5071–5098, https://doi.org/10.5194/acp-22-5071-2022,https://doi.org/10.5194/acp-22-5071-2022, 2022
Short summary
Biomass burning events measured by lidars in EARLINET – Part 2: Optical properties investigation
Mariana Adam, Iwona S. Stachlewska, Lucia Mona, Nikolaos Papagiannopoulos, Juan Antonio Bravo-Aranda, Michaël Sicard, Doina N. Nicolae, Livio Belegante, Lucja Janicka, Dominika Szczepanik, Maria Mylonaki, Christina-Anna Papanikolaou, Nikolaos Siomos, Kalliopi Artemis Voudouri, Luca Alados-Arboledas, Arnoud Apituley, Ina Mattis, Anatoli Chaikovsky, Constantino Muñoz-Porcar, Aleksander Pietruczuk, Daniele Bortoli, Holger Baars, Ivan Grigorov, and Zahary Peshev
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-759,https://doi.org/10.5194/acp-2021-759, 2021
Revised manuscript not accepted
Short summary
Aerosol type classification analysis using EARLINET multiwavelength and depolarization lidar observations
Maria Mylonaki, Elina Giannakaki, Alexandros Papayannis, Christina-Anna Papanikolaou, Mika Komppula, Doina Nicolae, Nikolaos Papagiannopoulos, Aldo Amodeo, Holger Baars, and Ourania Soupiona
Atmos. Chem. Phys., 21, 2211–2227, https://doi.org/10.5194/acp-21-2211-2021,https://doi.org/10.5194/acp-21-2211-2021, 2021
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Rapid oxidation of phenolic compounds by O3 and HO: effects of the air–water interface and mineral dust in tropospheric chemical processes
Yanru Huo, Mingxue Li, Xueyu Wang, Jianfei Sun, Yuxin Zhou, Yuhui Ma, and Maoxia He
Atmos. Chem. Phys., 24, 12409–12423, https://doi.org/10.5194/acp-24-12409-2024,https://doi.org/10.5194/acp-24-12409-2024, 2024
Short summary
Modeling the contribution of leads to sea spray aerosol in the high Arctic
Rémy Lapere, Louis Marelle, Pierre Rampal, Laurent Brodeau, Christian Melsheimer, Gunnar Spreen, and Jennie L. Thomas
Atmos. Chem. Phys., 24, 12107–12132, https://doi.org/10.5194/acp-24-12107-2024,https://doi.org/10.5194/acp-24-12107-2024, 2024
Short summary
Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth
Haihui Zhu, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Chi Li, Jun Meng, Christopher R. Oxford, Xuan Liu, Yanshun Li, Dandan Zhang, Inderjeet Singh, and Alexei Lyapustin
Atmos. Chem. Phys., 24, 11565–11584, https://doi.org/10.5194/acp-24-11565-2024,https://doi.org/10.5194/acp-24-11565-2024, 2024
Short summary
The co-benefits of a low-carbon future for PM2.5 and O3 air pollution in Europe
Connor J. Clayton, Daniel R. Marsh, Steven T. Turnock, Ailish M. Graham, Kirsty J. Pringle, Carly L. Reddington, Rajesh Kumar, and James B. McQuaid
Atmos. Chem. Phys., 24, 10717–10740, https://doi.org/10.5194/acp-24-10717-2024,https://doi.org/10.5194/acp-24-10717-2024, 2024
Short summary
Assessing the effectiveness of SO2, NOx, and NH3 emission reductions in mitigating winter PM2.5 in Taiwan using CMAQ
Ping-Chieh Huang, Hui-Ming Hung, Hsin-Chih Lai, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 10759–10772, https://doi.org/10.5194/acp-24-10759-2024,https://doi.org/10.5194/acp-24-10759-2024, 2024
Short summary

Cited articles

Alados-Arboledas, L., Müller, D., Guerrero-Rascado, J. L., Navas-Guzman, F., Perez-Ramirez, D., and Olmo, F. J.: Optical and microphysical properties of fresh biomass burning aerosol retrieved by Raman lidar, and star-and sun-photometry, Geophys. Res. Lett., 38, 1–5, https://doi.org/10.1029/2010GL045999, 2011. a, b
Ali, A., Amin, S. E., Ramadan, H. H., and Tolba, M. F.: Enhancement of OMI aerosol optical depth data assimilation using artificial neural network, Neural Comput. Appl., 23, 2267–2279, https://doi.org/10.1007/s00521-012-1178-9, 2012. a
Amiridis, V., Giannakaki, E., Balis, D. S., Gerasopoulos, E., Pytharoulis, I., Zanis, P., Kazadzis, S., Melas, D., and Zerefos, C.: Smoke injection heights from agricultural burning in Eastern Europe as seen by CALIPSO, Atmos. Chem. Phys., 10, 11567–11576, https://doi.org/10.5194/acp-10-11567-2010, 2010. a
Ansmann, A., Wagner, F., Müller, D., Althausen, D., Herber, A., von Hoyningen-Huene, W., and Wandinger, U.: European pollution outbreaks during ACE 2: Optical particle properties inferred from multiwavelength lidar and star-Sun photometry, J. Geophys. Res., 107, 4259, https://doi.org/10.1029/2001JD001109, 2002. a, b
Ansmann, A., Tesche, M., Groß, S., Freudenthaler, V., Seifert, P., Hiebsch, A., Schmidt, J., Wandinger, U., Mattis, I., Müller, D., and Wiegner, M.: The 16 April 2010 major volcanic ash plume over central Europe: EARLINET lidar and AERONET photometer observations at Leipzig and Munich, Germany, Geophys. Res. Lett., 37, L13810, https://doi.org/10.1029/2010GL043809, 2010. a, b, c, d, e, f, g
Download
Short summary
A new aerosol typing algorithm based on artificial neural networks (ANNs) has been developed. The algorithm is providing the most probable aerosol type based on EARLINET LIDAR profiles. The ANNs used by the algorithm were trained using synthetic data, for which a new aerosol model has been developed. Blind tests on EARLINET data samples showed the capability of the algorithm to retrieve the aerosol type from a large variety of data, with different quality and physical content.
Altmetrics
Final-revised paper
Preprint