Articles | Volume 21, issue 5
Atmos. Chem. Phys., 21, 3919–3948, 2021
https://doi.org/10.5194/acp-21-3919-2021
Atmos. Chem. Phys., 21, 3919–3948, 2021
https://doi.org/10.5194/acp-21-3919-2021
Research article
17 Mar 2021
Research article | 17 Mar 2021

Meteorology-driven variability of air pollution (PM1) revealed with explainable machine learning

Roland Stirnberg et al.

Related authors

Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison
Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, and María Cruz Minguillón
Atmos. Meas. Tech., 15, 5479–5495, https://doi.org/10.5194/amt-15-5479-2022,https://doi.org/10.5194/amt-15-5479-2022, 2022
Short summary
High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds
Julia Fuchs, Hendrik Andersen, Jan Cermak, Eva Pauli, and Rob Roebeling
Atmos. Meas. Tech., 15, 4257–4270, https://doi.org/10.5194/amt-15-4257-2022,https://doi.org/10.5194/amt-15-4257-2022, 2022
Short summary
Harmonized gap-filled datasets from 20 urban flux tower sites
Mathew Lipson, Sue Grimmond, Martin Best, Winston Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-65,https://doi.org/10.5194/essd-2022-65, 2022
Revised manuscript under review for ESSD
Short summary
Cellulose in atmospheric particulate matter at rural and urban sites across France and Switzerland
Adam Brighty, Véronique Jacob, Gaëlle Uzu, Lucille Borlaza, Sébastien Conil, Christoph Hueglin, Stuart K. Grange, Olivier Favez, Cécile Trébuchon, and Jean-Luc Jaffrezo
Atmos. Chem. Phys., 22, 6021–6043, https://doi.org/10.5194/acp-22-6021-2022,https://doi.org/10.5194/acp-22-6021-2022, 2022
Short summary
Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O’Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-14,https://doi.org/10.5194/amt-2022-14, 2022
Preprint under review for AMT
Short summary

Related subject area

Subject: Aerosols | Research Activity: Field Measurements | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Impact of water uptake and mixing state on submicron particle deposition in the human respiratory tract (HRT) based on explicit hygroscopicity measurements at HRT-like conditions
Ruiqi Man, Zhijun Wu, Taomou Zong, Aristeidis Voliotis, Yanting Qiu, Johannes Größ, Dominik van Pinxteren, Limin Zeng, Hartmut Herrmann, Alfred Wiedensohler, and Min Hu
Atmos. Chem. Phys., 22, 12387–12399, https://doi.org/10.5194/acp-22-12387-2022,https://doi.org/10.5194/acp-22-12387-2022, 2022
Short summary
Parameterizations of size distribution and refractive index of biomass burning organic aerosol with black carbon content
Biao Luo, Ye Kuang, Shan Huang, Qicong Song, Weiwei Hu, Wei Li, Yuwen Peng, Duohong Chen, Dingli Yue, Bin Yuan, and Min Shao
Atmos. Chem. Phys., 22, 12401–12415, https://doi.org/10.5194/acp-22-12401-2022,https://doi.org/10.5194/acp-22-12401-2022, 2022
Short summary
Newly identified climatically and environmentally significant high-latitude dust sources
Outi Meinander, Pavla Dagsson-Waldhauserova, Pavel Amosov, Elena Aseyeva, Cliff Atkins, Alexander Baklanov, Clarissa Baldo, Sarah L. Barr, Barbara Barzycka, Liane G. Benning, Bojan Cvetkovic, Polina Enchilik, Denis Frolov, Santiago Gassó, Konrad Kandler, Nikolay Kasimov, Jan Kavan, James King, Tatyana Koroleva, Viktoria Krupskaya, Markku Kulmala, Monika Kusiak, Hanna K. Lappalainen, Michał Laska, Jerome Lasne, Marek Lewandowski, Bartłomiej Luks, James B. McQuaid, Beatrice Moroni, Benjamin Murray, Ottmar Möhler, Adam Nawrot, Slobodan Nickovic, Norman T. O’Neill, Goran Pejanovic, Olga Popovicheva, Keyvan Ranjbar, Manolis Romanias, Olga Samonova, Alberto Sanchez-Marroquin, Kerstin Schepanski, Ivan Semenkov, Anna Sharapova, Elena Shevnina, Zongbo Shi, Mikhail Sofiev, Frédéric Thevenet, Throstur Thorsteinsson, Mikhail Timofeev, Nsikanabasi Silas Umo, Andreas Uppstu, Darya Urupina, György Varga, Tomasz Werner, Olafur Arnalds, and Ana Vukovic Vimic
Atmos. Chem. Phys., 22, 11889–11930, https://doi.org/10.5194/acp-22-11889-2022,https://doi.org/10.5194/acp-22-11889-2022, 2022
Short summary
Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties
Samuel E. LeBlanc, Michal Segal-Rozenhaimer, Jens Redemann, Connor Flynn, Roy R. Johnson, Stephen E. Dunagan, Robert Dahlgren, Jhoon Kim, Myungje Choi, Arlindo da Silva, Patricia Castellanos, Qian Tan, Luke Ziemba, Kenneth Lee Thornhill, and Meloë Kacenelenbogen
Atmos. Chem. Phys., 22, 11275–11304, https://doi.org/10.5194/acp-22-11275-2022,https://doi.org/10.5194/acp-22-11275-2022, 2022
Short summary
Using aircraft measurements to characterize subgrid-scale variability of aerosol properties near the Atmospheric Radiation Measurement Southern Great Plains site
Jerome D. Fast, David M. Bell, Gourihar Kulkarni, Jiumeng Liu, Fan Mei, Georges Saliba, John E. Shilling, Kaitlyn Suski, Jason Tomlinson, Jian Wang, Rahul Zaveri, and Alla Zelenyuk
Atmos. Chem. Phys., 22, 11217–11238, https://doi.org/10.5194/acp-22-11217-2022,https://doi.org/10.5194/acp-22-11217-2022, 2022
Short summary

Cited articles

Baklanov, A., Molina, L. T., and Gauss, M.: Megacities, air quality and climate, Atmos. Environ., 126, 235–249, https://doi.org/10.1016/j.atmosenv.2015.11.059, 2016. a
Beekmann, M., Prévôt, A. S. H., Drewnick, F., Sciare, J., Pandis, S. N., Denier van der Gon, H. A. C., Crippa, M., Freutel, F., Poulain, L., Ghersi, V., Rodriguez, E., Beirle, S., Zotter, P., von der Weiden-Reinmüller, S.-L., Bressi, M., Fountoukis, C., Petetin, H., Szidat, S., Schneider, J., Rosso, A., El Haddad, I., Megaritis, A., Zhang, Q. J., Michoud, V., Slowik, J. G., Moukhtar, S., Kolmonen, P., Stohl, A., Eckhardt, S., Borbon, A., Gros, V., Marchand, N., Jaffrezo, J. L., Schwarzenboeck, A., Colomb, A., Wiedensohler, A., Borrmann, S., Lawrence, M., Baklanov, A., and Baltensperger, U.: In situ, satellite measurement and model evidence on the dominant regional contribution to fine particulate matter levels in the Paris megacity, Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, 2015. a
Bressi, M., Sciare, J., Ghersi, V., Bonnaire, N., Nicolas, J. B., Petit, J.-E., Moukhtar, S., Rosso, A., Mihalopoulos, N., and Féron, A.: A one-year comprehensive chemical characterisation of fine aerosol (PM2.5) at urban, suburban and rural background sites in the region of Paris (France), Atmos. Chem. Phys., 13, 7825–7844, https://doi.org/10.5194/acp-13-7825-2013, 2013. a, b, c, d, e, f, g, h, i, j, k, l
Bressi, M., Sciare, J., Ghersi, V., Mihalopoulos, N., Petit, J.-E., Nicolas, J. B., Moukhtar, S., Rosso, A., Féron, A., Bonnaire, N., Poulakis, E., and Theodosi, C.: Sources and geographical origins of fine aerosols in Paris (France), Atmos. Chem. Phys., 14, 8813–8839, https://doi.org/10.5194/acp-14-8813-2014, 2014. a, b
Cermak, J. and Knutti, R.: Beijing Olympics as an aerosol field experiment, Geophys. Res. Lett., 36, L10806, https://doi.org/10.1029/2009GL038572, 2009. a, b
Download
Short summary
Air pollution endangers human health and poses a problem particularly in densely populated areas. Here, an explainable machine learning approach is used to analyse periods of high particle concentrations for a suburban site southwest of Paris to better understand its atmospheric drivers. Air pollution is particularly excaberated by low temperatures and low mixed layer heights, but processes vary substantially between and within seasons.
Altmetrics
Final-revised paper
Preprint