<i>Rolling</i> vs. <i>seasonal</i> PMF: real-world multi-site and synthetic dataset comparison - Archive ouverte HAL
Article Dans Une Revue Atmospheric Measurement Techniques Année : 2022

Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison

Marta Via
Gang Chen
Francesco Canonaco
  • Fonction : Auteur
Kaspar Daellenbach
  • Fonction : Auteur
Benjamin Chazeau
Laboratoire Chimie de l'environnement
Hasna Chebaicheb
  • Fonction : Auteur
Jianhui Jiang
  • Fonction : Auteur
Hannes Keernik
  • Fonction : Auteur
Chunshui Lin
  • Fonction : Auteur
Nicolas Marchand
Laboratoire Chimie de l'environnement
CV
Cristina Marin
  • Fonction : Auteur
Colin O'Dowd
Jurgita Ovadnevaite
  • Fonction : Auteur
Jean-Eudes Petit
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette]
Chimie Atmosphérique Expérimentale
Michael Pikridas
Véronique Riffault
CV
Jean Sciare
  • Fonction : Auteur
Jay Slowik
  • Fonction : Auteur
Leïla Simon
  • Fonction : Auteur
Institut National de l'Environnement Industriel et des Risques
Jeni Vasilescu
  • Fonction : Auteur
Yunjiang Zhang
Institut National de l'Environnement Industriel et des Risques
Olivier Favez
Institut National de l'Environnement Industriel et des Risques
CV
André Prévôt
Andrés Alastuey
María Cruz Minguillón

Résumé

Abstract. Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected “true” values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here, especially in periods between seasons. The results of this multi-site comparison coincide with the synthetic dataset in terms of rolling–seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the results of this study provide solid evidence of the robustness of both methods and of the overall efficiency of the recently proposed rolling PMF approach.

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Sciences de l'environnement Océan, Atmosphère
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https://hal.science/hal-03800466

Soumis le : lundi 21 novembre 2022-16:21:10

Dernière modification le : lundi 2 décembre 2024-14:48:10

Archivage à long terme le : mercredi 22 février 2023-21:07:53

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hal-03800466 , version 1 (21-11-2022)

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Marta Via, Gang Chen, Francesco Canonaco, Kaspar Daellenbach, Benjamin Chazeau, et al.. Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison. Atmospheric Measurement Techniques, 2022, 15 (18), pp.5479-5495. ⟨10.5194/amt-15-5479-2022⟩. ⟨hal-03800466⟩

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