Articles | Volume 15, issue 14
https://doi.org/10.5194/amt-15-4195-2022
https://doi.org/10.5194/amt-15-4195-2022
Research article
 | 
20 Jul 2022
Research article |  | 20 Jul 2022

Automated identification of local contamination in remote atmospheric composition time series

Ivo Beck, Hélène Angot, Andrea Baccarini, Lubna Dada, Lauriane Quéléver, Tuija Jokinen, Tiia Laurila, Markus Lampimäki, Nicolas Bukowiecki, Matthew Boyer, Xianda Gong, Martin Gysel-Beer, Tuukka Petäjä, Jian Wang, and Julia Schmale

Related authors

On spatial scales of local aerosol production in boreal ecosystems
Ekaterina Ezhova, Üllar Rannik, Santeri Tuovinen, Olga Garmash, Otso Peräkylä, Piaopiao Ke, Topi Laanti, Janne Lampilahti, Markus Lampimäki, Anna Lintunen, Veli-Matti Kerminen, Janne Rinne, Timo Vesala, and Markku Kulmala
Atmos. Chem. Phys., 26, 13463–13483, https://doi.org/10.5194/acp-26-13463-2026,https://doi.org/10.5194/acp-26-13463-2026, 2026
Short summary
Understanding new particle formation based on continuous nanoparticle ranking in boreal forest and urban megacity
Tinghan Zhang, Wei Du, Xinran Zhang, Janne Lampilahti, Chengfeng Liu, Zehao Zou, Men Xia, Qi Yuan, Qiaozhi Zha, Jing Cai, Yiyang Wang, Tom Kokkonen, Katrianne Lehtipalo, Tuukka Petäjä, Veli-Matti Kerminen, Chao Yan, Jingkun Jiang, Yongchun Liu, and Markku Kulmala
EGUsphere, https://doi.org/10.5194/egusphere-2026-5379,https://doi.org/10.5194/egusphere-2026-5379, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Cloud processing signatures in boreal forest aerosol revealed by long-term in-situ observations
Liine Heikkinen, Rahul Ranjan, Sini Talvinen, Niels Behr, Sara M. Blichner, Maura Dewey, Lauri R. Ahonen, Mikael Ehn, Annica M. L. Ekman, Radovan Krejci, Tuukka Petäjä, Peter Tunved, and Ilona Riipinen
EGUsphere, https://doi.org/10.5194/egusphere-2026-5082,https://doi.org/10.5194/egusphere-2026-5082, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Unraveling the chemical structures and sources of biomass-derived organic aerosols through a year-long offline analysis in Hyytiälä, Finland
Qianzhe Sun, Ruichen Zhou, Sho Ohata, Chiaki Shirota, Tuukka Petäjä, Ilona Jaakkola, Lauri Ahonen, Markku Kulmala, and Michihiro Mochida
Atmos. Chem. Phys., 26, 12813–12836, https://doi.org/10.5194/acp-26-12813-2026,https://doi.org/10.5194/acp-26-12813-2026, 2026
Short summary
GloPINE dataset: model-ready measurements of INP concentrations using PINE instruments
Ross J. Herbert, Larissa Lacher, Alexander Böhmländer, Mark D. Tarn, Antoine Canzi, Aidan Pantoya, Evelyn Freney, Kristina Höhler, Pia Bogert, Céline Planche, Ping Tian, Michael Adams, Sarah Barr, David Brus, Nicole Büttner, Martin Daily, Konstantinos Doulgeris, Konstantinos Eleftheriadis, Grant Forster, Romy Fösig, Dimitrios G. Georgakopoulos, Maria I. Gini, A. Gannet Hallar, Radovan Krejci, Elke Ludewig, Mauro Mazzola, Ian B. McCubbin, Athanasios Nenes, Tuukka Petäjä, Joseph Robinson, Franziska Vogel, Paul Zieger, Stephen Arnold, Kenneth S. Carslaw, Naruki Hiranuma, Ottmar Möhler, and Benjamin J. Murray
Earth Syst. Sci. Data, 18, 6465–6483, https://doi.org/10.5194/essd-18-6465-2026,https://doi.org/10.5194/essd-18-6465-2026, 2026
Short summary

Cited articles

Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung: Polar Research and Supply Vessel POLARSTERN Operated by the Alfred-Wegener-Institute, Journal of large-scale research facilities, 3, 119, https://doi.org/10.17815/jlsrf-3-163, 2017. 
Alroe, J., Cravigan, L. T., Miljevic, B., Johnson, G. R., Selleck, P., Humphries, R. S., Keywood, M. D., Chambers, S. D., Williams, A. G., and Ristovski, Z. D.: Marine productivity and synoptic meteorology drive summer-time variability in Southern Ocean aerosols, Atmos. Chem. Phys., 20, 8047–8062, https://doi.org/10.5194/acp-20-8047-2020, 2020. 
Angot, H., Beck, I., Jokinen, T., Laurila, T., Quéléver, L., and Schmale, J.: Carbon dioxide dry air mole fractions measured in the Swiss container during MOSAiC 2019/2020, PANGAEA [data set], https://doi.pangaea.de/10.1594/PANGAEA.944248, in review, 2022a. 
Download
Short summary
We present the pollution detection algorithm (PDA), a new method to identify local primary pollution in remote atmospheric aerosol and trace gas time series. The PDA identifies periods of contaminated data and relies only on the target dataset itself; i.e., it is independent of ancillary data such as meteorological variables. The parameters of all pollution identification steps are adjustable so that the PDA can be tuned to different locations and situations. It is available as open-access code.
Share