Neural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity of Birmingham-
Autor(es): dc.contributorUniversity of Lagos-
Autor(es): dc.contributorBusiness Unit HydroMet-
Autor(es): dc.creatorRosa, André Henrique-
Autor(es): dc.creatorStubbings, William A.-
Autor(es): dc.creatorAkinrinade, Olumide Emmanuel-
Autor(es): dc.creatorJeunon Gontijo, Erik Sartori-
Autor(es): dc.creatorHarrad, Stuart-
Data de aceite: dc.date.accessioned2025-08-21T21:41:46Z-
Data de disponibilização: dc.date.available2025-08-21T21:41:46Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-01-14-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.envpol.2023.122794-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/299739-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/299739-
Descrição: dc.descriptionThe 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.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionInstitute of Science and Technology São Paulo State University (UNESP), Av. Três de Março, 511, Alto da Boa Vista, SP-
Descrição: dc.descriptionSchool of Geography Earth and Environmental Sciences University of Birmingham, Edgbaston-
Descrição: dc.descriptionDepartment of Chemistry University of Lagos, Lagos-
Descrição: dc.descriptionKISTERS AG Business Unit HydroMet, Schoemperlenstr.12a-
Descrição: dc.descriptionInstitute of Science and Technology São Paulo State University (UNESP), Av. Três de Março, 511, Alto da Boa Vista, SP-
Descrição: dc.descriptionFAPESP: 2019/06800–5-
Descrição: dc.descriptionFAPESP: 2022/00985–6-
Idioma: dc.languageen-
Relação: dc.relationEnvironmental Pollution-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAir pollution-
Palavras-chave: dc.subjectPersistent organic pollutants (POPs)-
Palavras-chave: dc.subjectSARS-CoV-2 virus-
Palavras-chave: dc.subjectSelf-organising maps-
Título: dc.titleNeural network for evaluation of the impact of the UK COVID-19 national lockdown on atmospheric concentrations of PAHs and PBDEs-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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