Articles | Volume 15, issue 19
https://doi.org/10.5194/amt-15-5619-2022
https://doi.org/10.5194/amt-15-5619-2022
Research article
 | 
10 Oct 2022
Research article |  | 10 Oct 2022

Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data

Alireza Moallemi, Rob L. Modini, Tatyana Lapyonok, Anton Lopatin, David Fuertes, Oleg Dubovik, Philippe Giaccari, and Martin Gysel-Beer

Related authors

Assessment of real-time bioaerosol particle counters using reference chamber experiments
Gian Lieberherr, Kevin Auderset, Bertrand Calpini, Bernard Clot, Benoît Crouzy, Martin Gysel-Beer, Thomas Konzelmann, José Manzano, Andrea Mihajlovic, Alireza Moallemi, David O'Connor, Branko Sikoparija, Eric Sauvageat, Fiona Tummon, and Konstantina Vasilatou
Atmos. Meas. Tech., 14, 7693–7706, https://doi.org/10.5194/amt-14-7693-2021,https://doi.org/10.5194/amt-14-7693-2021, 2021
Short summary
Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition
Sebastian Landwehr, Michele Volpi, F. Alexander Haumann, Charlotte M. Robinson, Iris Thurnherr, Valerio Ferracci, Andrea Baccarini, Jenny Thomas, Irina Gorodetskaya, Christian Tatzelt, Silvia Henning, Rob L. Modini, Heather J. Forrer, Yajuan Lin, Nicolas Cassar, Rafel Simó, Christel Hassler, Alireza Moallemi, Sarah E. Fawcett, Neil Harris, Ruth Airs, Marzieh H. Derkani, Alberto Alberello, Alessandro Toffoli, Gang Chen, Pablo Rodríguez-Ros, Marina Zamanillo, Pau Cortés-Greus, Lei Xue, Conor G. Bolas, Katherine C. Leonard, Fernando Perez-Cruz, David Walton, and Julia Schmale
Earth Syst. Dynam., 12, 1295–1369, https://doi.org/10.5194/esd-12-1295-2021,https://doi.org/10.5194/esd-12-1295-2021, 2021
Short summary
Sources and nature of ice-nucleating particles in the free troposphere at Jungfraujoch in winter 2017
Larissa Lacher, Hans-Christian Clemen, Xiaoli Shen, Stephan Mertes, Martin Gysel-Beer, Alireza Moallemi, Martin Steinbacher, Stephan Henne, Harald Saathoff, Ottmar Möhler, Kristina Höhler, Thea Schiebel, Daniel Weber, Jann Schrod, Johannes Schneider, and Zamin A. Kanji
Atmos. Chem. Phys., 21, 16925–16953, https://doi.org/10.5194/acp-21-16925-2021,https://doi.org/10.5194/acp-21-16925-2021, 2021
Short summary

Related subject area

Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Spatial analysis of PM2.5 using a concentration similarity index applied to air quality sensor networks
Rósín Byrne, John C. Wenger, and Stig Hellebust
Atmos. Meas. Tech., 17, 5129–5146, https://doi.org/10.5194/amt-17-5129-2024,https://doi.org/10.5194/amt-17-5129-2024, 2024
Short summary
A novel probabilistic source apportionment approach: Bayesian auto-correlated matrix factorization
Anton Rusanen, Anton Björklund, Manousos I. Manousakas, Jianhui Jiang, Markku T. Kulmala, Kai Puolamäki, and Kaspar R. Daellenbach
Atmos. Meas. Tech., 17, 1251–1277, https://doi.org/10.5194/amt-17-1251-2024,https://doi.org/10.5194/amt-17-1251-2024, 2024
Short summary
Towards a hygroscopic growth calibration for low-cost PM2.5 sensors
Milan Y. Patel, Pietro F. Vannucci, Jinsol Kim, William M. Berelson, and Ronald C. Cohen
Atmos. Meas. Tech., 17, 1051–1060, https://doi.org/10.5194/amt-17-1051-2024,https://doi.org/10.5194/amt-17-1051-2024, 2024
Short summary
Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry
Xinlei Ge, Yele Sun, Justin Trousdell, Mindong Chen, and Qi Zhang
Atmos. Meas. Tech., 17, 423–439, https://doi.org/10.5194/amt-17-423-2024,https://doi.org/10.5194/amt-17-423-2024, 2024
Short summary
Machine learning approaches for automatic classification of single-particle mass spectrometry data
Guanzhong Wang, Heinrich Ruser, Julian Schade, Johannes Passig, Thomas Adam, Günther Dollinger, and Ralf Zimmermann
Atmos. Meas. Tech., 17, 299–313, https://doi.org/10.5194/amt-17-299-2024,https://doi.org/10.5194/amt-17-299-2024, 2024
Short summary

Cited articles

Ahern, A. T., Erdesz, F., Wagner, N. L., Brock, C. A., Lyu, M., Slovacek, K., Moore, R. H., Wiggins, E. B., and Murphy, D. M.: Laser imaging nephelometer for aircraft deployment, Atmos. Meas. Tech., 15, 1093–1105, https://doi.org/10.5194/amt-15-1093-2022, 2022. 
Alexandrov, M. D. and Mishchenko, M. I.: Information content of bistatic lidar observations of aerosols from space, Opt. Express, 25, A134–A150, https://doi.org/10.1364/OE.25.00A134, 2017. 
Barkey, B., Paulson, S. E., and Chung, A.: Genetic algorithm inversion of dual polarization polar nephelometer data to determine aerosol refractive index, Aerosol Sci. Tech., 41, 751–760, https://doi.org/10.1080/02786820701432640, 2007. 
Bian, Y., Zhao, C., Xu, W., Zhao, G., Tao, J., and Kuang, Y.: Development and validation of a CCD-laser aerosol detective system for measuring the ambient aerosol phase function, Atmos. Meas. Tech., 10, 2313–2322, https://doi.org/10.5194/amt-10-2313-2017, 2017. 
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., and Lohmann, U.: Clouds and aerosols, in: Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 571–657, https://doi.org/10.1017/CBO9781107415324, 2013. 
Download
Short summary
Aerosol properties (size distributions, refractive indices) can be retrieved from in situ, angularly resolved light scattering measurements performed with polar nephelometers. We apply an established framework to assess the aerosol property retrieval potential for different instrument configurations, target applications, and assumed prior knowledge. We also demonstrate how a reductive greedy algorithm can be used to determine the optimal placements of the angular sensors in a polar nephelometer.