Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs
Main Author: | |
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Publication Date: | 2024 |
Other Authors: | , , , |
Format: | Article |
Language: | eng |
Source: | Repositório Institucional da UNESP |
Download full: | http://dx.doi.org/10.1016/j.envpol.2023.122794 https://hdl.handle.net/11449/299739 |
Summary: | 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% Σ7PBDEs) but was detected at lower absolute concentrations (4.2–35.0 pg m−3) than in previous investigations in Birmingham. Air samples were clustered in five groups based on SOM analysis and the effects of meteorology and pandemic-related restrictions on population mobility could be visualised. Concentrations of most PAH decreased during the early stages of the pandemic when mobility was most restricted. SOM analysis also helped to identify the important influence of wind speed on contaminant concentrations, contributing to reduce the concentration of all analysed pollutants. In contrast, concentrations of most PBDEs remained similar or increased during the first COVID-19 lockdown which was attributed to their primarily indoor sources that were either unaffected or increased during lockdown. |
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Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEsAir pollutionPersistent organic pollutants (POPs)SARS-CoV-2 virusSelf-organising mapsThe 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% Σ7PBDEs) but was detected at lower absolute concentrations (4.2–35.0 pg m−3) than in previous investigations in Birmingham. Air samples were clustered in five groups based on SOM analysis and the effects of meteorology and pandemic-related restrictions on population mobility could be visualised. Concentrations of most PAH decreased during the early stages of the pandemic when mobility was most restricted. SOM analysis also helped to identify the important influence of wind speed on contaminant concentrations, contributing to reduce the concentration of all analysed pollutants. In contrast, concentrations of most PBDEs remained similar or increased during the first COVID-19 lockdown which was attributed to their primarily indoor sources that were either unaffected or increased during lockdown.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Institute of Science and Technology São Paulo State University (UNESP), Av. Três de Março, 511, Alto da Boa Vista, SPSchool of Geography Earth and Environmental Sciences University of Birmingham, EdgbastonDepartment of Chemistry University of Lagos, LagosKISTERS AG Business Unit HydroMet, Schoemperlenstr.12aInstitute of Science and Technology São Paulo State University (UNESP), Av. Três de Março, 511, Alto da Boa Vista, SPFAPESP: 2019/06800–5FAPESP: 2022/00985–6Universidade Estadual Paulista (UNESP)University of BirminghamUniversity of LagosBusiness Unit HydroMetRosa, André Henrique [UNESP]Stubbings, William A.Akinrinade, Olumide EmmanuelJeunon Gontijo, Erik Sartori [UNESP]Harrad, Stuart2025-04-29T18:43:19Z2024-01-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.envpol.2023.122794Environmental Pollution, v. 341.1873-64240269-7491https://hdl.handle.net/11449/29973910.1016/j.envpol.2023.1227942-s2.0-85177487934Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEnvironmental Pollutioninfo:eu-repo/semantics/openAccess2025-04-30T13:24:22Zoai:repositorio.unesp.br:11449/299739Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462025-04-30T13:24:22Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs |
title |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs |
spellingShingle |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs Rosa, André Henrique [UNESP] Air pollution Persistent organic pollutants (POPs) SARS-CoV-2 virus Self-organising maps |
title_short |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs |
title_full |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs |
title_fullStr |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs |
title_full_unstemmed |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs |
title_sort |
Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs |
author |
Rosa, André Henrique [UNESP] |
author_facet |
Rosa, André Henrique [UNESP] Stubbings, William A. Akinrinade, Olumide Emmanuel Jeunon Gontijo, Erik Sartori [UNESP] Harrad, Stuart |
author_role |
author |
author2 |
Stubbings, William A. Akinrinade, Olumide Emmanuel Jeunon Gontijo, Erik Sartori [UNESP] Harrad, Stuart |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) University of Birmingham University of Lagos Business Unit HydroMet |
dc.contributor.author.fl_str_mv |
Rosa, André Henrique [UNESP] Stubbings, William A. Akinrinade, Olumide Emmanuel Jeunon Gontijo, Erik Sartori [UNESP] Harrad, Stuart |
dc.subject.por.fl_str_mv |
Air pollution Persistent organic pollutants (POPs) SARS-CoV-2 virus Self-organising maps |
topic |
Air pollution Persistent organic pollutants (POPs) SARS-CoV-2 virus Self-organising maps |
description |
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% Σ7PBDEs) but was detected at lower absolute concentrations (4.2–35.0 pg m−3) than in previous investigations in Birmingham. Air samples were clustered in five groups based on SOM analysis and the effects of meteorology and pandemic-related restrictions on population mobility could be visualised. Concentrations of most PAH decreased during the early stages of the pandemic when mobility was most restricted. SOM analysis also helped to identify the important influence of wind speed on contaminant concentrations, contributing to reduce the concentration of all analysed pollutants. In contrast, concentrations of most PBDEs remained similar or increased during the first COVID-19 lockdown which was attributed to their primarily indoor sources that were either unaffected or increased during lockdown. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-01-15 2025-04-29T18:43:19Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.envpol.2023.122794 Environmental Pollution, v. 341. 1873-6424 0269-7491 https://hdl.handle.net/11449/299739 10.1016/j.envpol.2023.122794 2-s2.0-85177487934 |
url |
http://dx.doi.org/10.1016/j.envpol.2023.122794 https://hdl.handle.net/11449/299739 |
identifier_str_mv |
Environmental Pollution, v. 341. 1873-6424 0269-7491 10.1016/j.envpol.2023.122794 2-s2.0-85177487934 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Environmental Pollution |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
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UNESP |
reponame_str |
Repositório Institucional da UNESP |
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Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
repositoriounesp@unesp.br |
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1834482833989566464 |