Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs.
Air pollution
Persistent organic pollutants (POPs)
SARS-CoV-2 virus
Self-organising maps
Journal
Environmental pollution (Barking, Essex : 1987)
ISSN: 1873-6424
Titre abrégé: Environ Pollut
Pays: England
ID NLM: 8804476
Informations de publication
Date de publication:
03 Nov 2023
03 Nov 2023
Historique:
received:
20
04
2023
revised:
19
10
2023
accepted:
22
10
2023
pubmed:
6
11
2023
medline:
6
11
2023
entrez:
5
11
2023
Statut:
aheadofprint
Résumé
The impact of measures to restrict population mobility during the COVID-19 pandemic on atmospheric concentrations of polycyclic aromatic hydrocarbons (PAH) and brominated flame retardants (BFRs) is poorly understood. This study analyses the effects of meteorological parameters and mobility restrictions during the COVID-19 pandemic on concentrations of PAH and BFRs at the University of Birmingham in the UK utilising a neural network (self-organising maps, SOM). Air sampling was performed using Polyurethane Foam (PUF) disk passive samplers between October 2019 and January 2021. Data on concentrations of PAH and BFRs were analysed using SOM and Spearman's rank correlation. Data on meteorological parameters (air temperature, wind, and relative humidity) and mobility restrictions during the pandemic were included in the analysis. Decabromodiphenyl ether (BDE-209) was the most abundant polybrominated diphenyl ether (PBDE) (23-91% Σ
Identifiants
pubmed: 37926413
pii: S0269-7491(23)01796-7
doi: 10.1016/j.envpol.2023.122794
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
122794Informations de copyright
Copyright © 2023 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.