European aerosol phenomenology − 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets - Archive ouverte HAL
Article Dans Une Revue Environment International Année : 2022

European aerosol phenomenology − 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

Gang Chen (1) , Francesco Canonaco (1, 2) , Anna Tobler (1, 2) , Wenche Aas (3) , Andres Alastuey (4) , James Allan (5) , Samira Atabakhsh (6) , Minna Aurela (7) , Urs Baltensperger (1) , Aikaterini Bougiatioti (8) , Joel de Brito (9) , Darius Ceburnis (10) , Benjamin Chazeau (1, 11) , Hasna Chebaicheb (12, 9) , Kaspar Daellenbach (1) , Mikael Ehn (13) , Imad El Haddad (1) , Konstantinos Eleftheriadis (14) , Olivier Favez (12) , Harald Flentje (15) , Anna Font (16) , Kirsten Fossum (17) , Evelyn Freney (18) , Maria Gini (14) , David Green (16) , Liine Heikkinen (13) , Hartmut Herrmann (6) , Athina-Cerise Kalogridis (14) , Hannes Keernik (19) , Radek Lhotka (20) , Chunshui Lin (17) , Chris Lunder (3) , Marek Maasikmets (21) , Manousos Manousakas (1) , Nicolas Marchand (11) , Cristina Marin (22, 23) , Luminita Marmureanu (22) , Nikolaos Mihalopoulos (8) , Griša Močnik (24, 25) , Jaroslaw Nęcki (26) , Colin O'Dowd (17) , Jurgita Ovadnevaite (17) , Thomas Peter (27) , Jean-Eudes Petit (28) , Michael Pikridas (29) , Stephen Matthew Platt (3) , Petra Pokorná (20) , Laurent Poulain (6) , Max Priestman (16) , Véronique Riffault (9) , Matteo Rinaldi (30) , Kazimierz Różański (31) , Jaroslav Schwarz (20) , Jean Sciare (29) , Leïla Simon (28, 12) , Alicja Skiba (28) , Jay Slowik (1) , Yulia Sosedova (2) , Iasonas Stavroulas (32, 29) , Katarzyna Styszko (26) , Erik Teinemaa (33) , Hilkka Timonen (7) , Anja Tremper (16) , Jeni Vasilescu (22) , Marta Via (34) , Petr Vodička (19) , Alfred Wiedensohler (6) , Olga Zografou (14) , María Cruz Minguillón (34) , André S.H. Prévôt (1)
1 PSI - Paul Scherrer Institute
2 Datalystica
3 NILU - Norwegian Institute for Air Research
4 CID-CSIC - Centre d'Investigació i Desenvolupament [Barcelona]
5 University of Manchester [Manchester]
6 TROPOS - Leibniz Institute for Tropospheric Research
7 FMI - Finnish Meteorological Institute
8 NOA - National Observatory of Athens
9 CERI EE - IMT Nord Europe - Centre for Energy and Environment
10 Martin Ryan Institute
11 LCE - Laboratoire Chimie de l'environnement
12 INERIS - Institut National de l'Environnement Industriel et des Risques
13 INAR - Institute for Atmospheric and Earth System Research
14 NCSR - National Center for Scientific Research "Demokritos"
15 MOHp - Meteorologisches Observatorium Hohenpeißenberg
16 Imperial College London
17 NUI Galway - National University of Ireland [Galway]
18 LaMP - Laboratoire de Météorologie Physique
19 TalTech - Tallinn University of Technology
20 CAS - Czech Academy of Sciences [Prague]
21 Estonian Environmental Research Center, Tallinn, Estonia
22 INOE - National Institute of Research and Development for Optoelectronics
23 UPB - University Politehnica of Bucharest [Romania]
24 IJS - Jozef Stefan Institute [Ljubljana]
25 University of Nova Gorica
26 AGH UST - AGH University of Science and Technology [Krakow, PL]
27 D-USYS - Department of Environmental Systems Science [ETH Zürich]
28 LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette]
29 CARE-C - Climate and Atmosphere Research Centre [Nicosia]
30 ISAC - Istituto di Scienze dell'Atmosfera e del Clima [Bologna]
31 FPACS - Faculty of Physics and Applied Computer Science [Kraków]
32 AMU - Aix Marseille Université
33 EKUK - Estonian Environmental Research Centre
34 CSIC - Consejo Superior de Investigaciones Científicas [Spain]
Joel de Brito
Anna Font
Evelyn Freney
Nicolas Marchand
Colin O'Dowd
Yulia Sosedova
  • Fonction : Auteur
André S.H. Prévôt
  • Fonction : Auteur correspondant

Résumé

Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models.
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hal-03738357 , version 1 (26-07-2022)

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Gang Chen, Francesco Canonaco, Anna Tobler, Wenche Aas, Andres Alastuey, et al.. European aerosol phenomenology − 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets. Environment International, 2022, 166, pp.107325. ⟨10.1016/j.envint.2022.107325⟩. ⟨hal-03738357⟩
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