Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF.
ME2
Metals
Multi-time resolution
Multilinear engine
Organic sources
PMF
Positive matrix factorisation
SoFi
Source apportionment
Submicronic particulate matter
Journal
Environment international
ISSN: 1873-6750
Titre abrégé: Environ Int
Pays: Netherlands
ID NLM: 7807270
Informations de publication
Date de publication:
07 2023
07 2023
Historique:
received:
13
02
2023
revised:
09
05
2023
accepted:
29
05
2023
medline:
21
6
2023
pubmed:
8
6
2023
entrez:
7
6
2023
Statut:
ppublish
Résumé
Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM
Identifiants
pubmed: 37285710
pii: S0160-4120(23)00279-9
doi: 10.1016/j.envint.2023.108006
pii:
doi:
Substances chimiques
Air Pollutants
0
Particulate Matter
0
Aerosols
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
108006Informations de copyright
Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.