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Atmospheric new particle formation identifier using longitudinal global particle number size distribution data

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Title: Atmospheric new particle formation identifier using longitudinal global particle number size distribution data
Authors: Kecorius, Simonas, Madueño, Leizel, Lovric, Mario, Racic, Nikolina, Schwarz, Maximilian, Cyrys, Josef, Casquero-Vera, Juan Andrés, Alados-Arboledas, Lucas, Conil, Sébastien, Sciare, Jean, Ondracek, Jakub, Gannet Hallar, Anna, Gómez-Moreno, Francisco J., Ellul, Raymond, Kristensson, Adam, Sorribas, Mar, Kalivitis, Nikolaos, Mihalopoulos, Nikolaos, Peters, Annette, Gini, Maria, Konstantinos, Konstantinos, Vratolis, Stergios, Jeongeun, Kim, Birmili, Wolfram, Bergmans, Benjamin, Nikolova, Nina, Dinoi, Adelaide, Contini, Daniele, Marinoni, Angela, Alastuey, Andres, Petäjä, Tuukka, Rodriguez, Sergio, Picard, David, Brem, Benjamin, Priestman, Max, Green, David C., Beddows, David C. S., Harrison, Roy M., O’Dowd, Colin, Ceburnis, Darius, Hyvärinen, Antti, Henzing, Bas, Crumeyrolle, Suzanne, Putaud, Jean-Philippe, Laj, Paolo, Weinhold, Kay, Plauškaitė, Kristina, Byčenkienė, Steigvilė
Publisher Information: Springer Nature
Publication Year: 2024
Collection: University of Malta: OAR@UM / L-Università ta' Malta
Subject Terms: Particles -- Environmental aspects, Air -- Pollution, Elementary particles (Physics), Particles (Nuclear physics)
Description: Atmospheric new particle formation (NPF) is a naturally occurring phenomenon, during which high concentrations of sub-10 nm particles are created through gas to particle conversion. The NPF is observed in multiple environments around the world. Although it has observable influence onto annual total and ultrafine particle number concentrations (PNC and UFP, respectively), only limited epidemiological studies have investigated whether these particles are associated with adverse health effects. One plausible reason for this limitation may be related to the absence of NPF identifiers available in UFP and PNC data sets. Until recently, the regional NPF events were usually identified manually from particle number size distribution contour plots. Identification of NPF across multi-annual and multiple station data sets remained a tedious task. In this work, we introduce a regional NPF identifier, created using an automated, machine learning based algorithm. The regional NPF event tag was created for 65 measurement sites globally, covering the period from 1996 to 2023. The discussed data set can be used in future studies related to regional NPF. ; peer-reviewed
Document Type: article in journal/newspaper
Language: English
Relation: Kecorius, S., Madueño, L., Lovric, M., Racic, N., Schwarz, M., Cyrys, J., . & Byčenkienė, S. (2024). Atmospheric new particle formation identifier using longitudinal global particle number size distribution data. Scientific Data, 11(1), 1239.; https://www.um.edu.mt/library/oar/handle/123456789/138996
DOI: 10.1038/s41597-024-04079-1
Availability: https://www.um.edu.mt/library/oar/handle/123456789/138996
https://doi.org/10.1038/s41597-024-04079-1
Rights: info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder
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  Data: Atmospheric new particle formation (NPF) is a naturally occurring phenomenon, during which high concentrations of sub-10 nm particles are created through gas to particle conversion. The NPF is observed in multiple environments around the world. Although it has observable influence onto annual total and ultrafine particle number concentrations (PNC and UFP, respectively), only limited epidemiological studies have investigated whether these particles are associated with adverse health effects. One plausible reason for this limitation may be related to the absence of NPF identifiers available in UFP and PNC data sets. Until recently, the regional NPF events were usually identified manually from particle number size distribution contour plots. Identification of NPF across multi-annual and multiple station data sets remained a tedious task. In this work, we introduce a regional NPF identifier, created using an automated, machine learning based algorithm. The regional NPF event tag was created for 65 measurement sites globally, covering the period from 1996 to 2023. The discussed data set can be used in future studies related to regional NPF. ; peer-reviewed
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  Data: Kecorius, S., Madueño, L., Lovric, M., Racic, N., Schwarz, M., Cyrys, J., . & Byčenkienė, S. (2024). Atmospheric new particle formation identifier using longitudinal global particle number size distribution data. Scientific Data, 11(1), 1239.; https://www.um.edu.mt/library/oar/handle/123456789/138996
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  Data: info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder
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