Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos

Detalhes bibliográficos
Ano de defesa: 2020
Autor(a) principal: Camargo, David Andrés Monroy
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Tecnológica Federal do Paraná
Londrina
Brasil
Programa de Pós-Graduação em Engenharia Ambiental
UTFPR
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/24711
Resumo: Every day, people are exposed to pollutants from vehicle emissions, especially in transport microenvironments, such as bus stops and terminals. However, most studies on public transport traffic do not assess the concentrations of pollutants in these microenvironments. The behavior of fine particulate matter (with aerodynamic diameter less than 2.5 µm, PM2,5), black carbon (BC) and particle number (PN) was evaluated at bus stops in of Londrina (PR) city center during monitoring campaigns, conducted in 2015 and 2019. The 2015 experiment was performed with equipment mounted on bicycles that traveled the city’s core quantifying the particulate concentrations at 31 bus stops. 2019 experiment collected BC and PN data at five points, three of them selected from 2015 experiment plus two new ones. In the mobile monitoring, the mean PM2.5, BC and PN concentrations (+/- standard deviation) were 11,00 ±19,30 µg m-3,7,60 ±14,90 µg m-3 and 27.552 ±22.570 # cm-3 , respectively. In the fixed campaign, the mean BC and PN concentrations were 9,17 ±27,50 µg m-3 and 34.980 ±33.508 # cm-3 , respectively. The PM2,5, BC and PN concentrations at the bus stops were on average 0,30-2,90, 1,58-19,62 and 1,50-6,69 times higher than at an urban background site. At four stops from the 2019 campaign, three zones were evaluated: deceleration zone (located 10 m before the stop), boarding/alighting area and acceleration zone (located 10 m after the stop). The data allowed to pinpoint increases between 2,39- 12,05 µg m-3 and 11.380-23.220 # cm-3 in BC and PN, respectively, at the bus stops during two situations: when passengers were boarding and when buses accelerated at departure. The mean BC concentrations in the acceleration and stop zones were 17% higher than at the deceleration zone. However, the mean PN concentrations in the acceleration zone were 11% higher compared to the stop zone. Thus, it is not advisable to place several consecutive bus stops since the stop located immediately after the first one will be mainly affected by the previous accelerating bus emissions. Two forecast models for PM2.5 and BC concentrations were developed using multiple linear regression, including traffic, weather, background concentration, street, and bus stop characteristics as predictive variables. The PM2,5 and BC models had coefficient of determination (R2 ) of 0,36 ±0,09 and 0,28 ±0,08, respectively, and identified the following variables as the best predictors: atmospheric pressure, the concentration of BC with a wavelength of 880 nm at the background site and the height of the buildings: width of the street ratio. Likewise, the BC model identified the truck volume as a predictive variable. Finally, the PM2,5 model also identified that the directions of the southern sector (S, SE and SW) could favor an increase in PM2,5 concentrations at bus stops, possibly affected by the large traffic rate on avenues in those sectors.
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spelling Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanosObservation and statistical modeling of particulate matter concentrations at urban bus stopsPoluentesAr - Poluição - MediçãoMonitorização ambientalTransporte urbanoPollutantsAir - Pollution - MeasurementEnvironmental monitoringUrban transportationCNPQ::ENGENHARIAS::ENGENHARIA SANITARIAEngenharia/Tecnologia/GestãoEvery day, people are exposed to pollutants from vehicle emissions, especially in transport microenvironments, such as bus stops and terminals. However, most studies on public transport traffic do not assess the concentrations of pollutants in these microenvironments. The behavior of fine particulate matter (with aerodynamic diameter less than 2.5 µm, PM2,5), black carbon (BC) and particle number (PN) was evaluated at bus stops in of Londrina (PR) city center during monitoring campaigns, conducted in 2015 and 2019. The 2015 experiment was performed with equipment mounted on bicycles that traveled the city’s core quantifying the particulate concentrations at 31 bus stops. 2019 experiment collected BC and PN data at five points, three of them selected from 2015 experiment plus two new ones. In the mobile monitoring, the mean PM2.5, BC and PN concentrations (+/- standard deviation) were 11,00 ±19,30 µg m-3,7,60 ±14,90 µg m-3 and 27.552 ±22.570 # cm-3 , respectively. In the fixed campaign, the mean BC and PN concentrations were 9,17 ±27,50 µg m-3 and 34.980 ±33.508 # cm-3 , respectively. The PM2,5, BC and PN concentrations at the bus stops were on average 0,30-2,90, 1,58-19,62 and 1,50-6,69 times higher than at an urban background site. At four stops from the 2019 campaign, three zones were evaluated: deceleration zone (located 10 m before the stop), boarding/alighting area and acceleration zone (located 10 m after the stop). The data allowed to pinpoint increases between 2,39- 12,05 µg m-3 and 11.380-23.220 # cm-3 in BC and PN, respectively, at the bus stops during two situations: when passengers were boarding and when buses accelerated at departure. The mean BC concentrations in the acceleration and stop zones were 17% higher than at the deceleration zone. However, the mean PN concentrations in the acceleration zone were 11% higher compared to the stop zone. Thus, it is not advisable to place several consecutive bus stops since the stop located immediately after the first one will be mainly affected by the previous accelerating bus emissions. Two forecast models for PM2.5 and BC concentrations were developed using multiple linear regression, including traffic, weather, background concentration, street, and bus stop characteristics as predictive variables. The PM2,5 and BC models had coefficient of determination (R2 ) of 0,36 ±0,09 and 0,28 ±0,08, respectively, and identified the following variables as the best predictors: atmospheric pressure, the concentration of BC with a wavelength of 880 nm at the background site and the height of the buildings: width of the street ratio. Likewise, the BC model identified the truck volume as a predictive variable. Finally, the PM2,5 model also identified that the directions of the southern sector (S, SE and SW) could favor an increase in PM2,5 concentrations at bus stops, possibly affected by the large traffic rate on avenues in those sectors.Conselho Nacional do Desenvolvimento Científico e Tecnológico (CNPq)Diariamente, as pessoas estão expostas a poluentes oriundos das emissões veiculares, especialmente em microambientes de transporte como paradas de ônibus e terminais. No entanto, a maior parte dos estudos desenvolvidos em meios de transporte não avaliam as concentrações dos poluentes nesses microambientes. Através de duas campanhas de monitoramento, realizadas em 2015 e 2019, foi avaliado o comportamento das concentrações de material particulado fino (com diâmetro aerodinâmico menor que 2,5 µm, MP2,5), black carbon (BC) e número de partículas (NP) em paradas de ônibus localizadas no centro de Londrina (PR). O experimento de 2015 foi realizado com equipamentos montados em bicicletas que percorreram as ruas centrais da cidade, avaliando um total de 31 paradas de ônibus. O experimento de 2019 coletou dados de BC e NP de forma estática em cinco paradas de ônibus, três escolhidas do experimento de 2015 mais duas novas. No monitoramento móvel, as concentrações médias (+/- desvio padrão) de MP2,5, BC e NP foram de 11,00 ±19,30 µg m-3 , 7,60 ±14,90 µg m-3 e 27.552 ±22.570 # cm-3 , respectivamente. No monitoramento fixo, as concentrações médias de BC e NP foram de 9,17 ±27,50 µg m-3 e 34.980 ±33.508 # cm-3 , respectivamente. As concentrações de MP2,5, BC e NP nas paradas foram em média 0,30-2,90, 1,58- 19,62 e 1,50-6,69 vezes maiores do que em um ponto de medição de fundo urbano. Em quatro paradas do monitoramento de 2019 foram avaliadas três zonas: desaceleração (localizada 10 m antes da parada), parada de ônibus e aceleração (localizada 10 m depois da parada). A análise das séries temporais permitiu associar aumentos entre 2,39-12,05 µg m-3 e 11.380-23.220 # cm-3 de BC e NP, respectivamente, nas paradas de ônibus durante duas situações: quando os passageiros estavam embarcando e quando os ônibus aceleravam após o embarque dos passageiros. As concentrações médias de BC na zona de aceleração e parada foram 17% maiores do que na zona de desaceleração, enquanto as concentrações médias de NP na zona de aceleração foram 11% maiores do que na zona da parada. Deste modo, não é aconselhável situar várias paradas de ônibus consecutivas, já que a parada localizada imediatamente depois da primeira parada, será principalmente afetada pelas emissões dos ônibus que estão acelerando. Desenvolveram-se dois modelos para previsão das concentrações de MP2.5 e BC usando regressão linear múltipla, relacionando parâmetros de trânsito, meteorológicas, de concentração de fundo urbano, características da rua e da parada de ônibus. Os modelos de MP2,5 e BC tiveram R2 de 0,36 ±0,09 e 0,28 ±0,08, respectivamente, e identificaram as seguintes variáveis como melhores preditoras: pressão atmosférica, a concentração de BC com comprimento de onda de 880 nm na estação de fundo e a relação entre a altura das edificações e largura da rua. Do mesmo modo, o modelo de BC identificou o fluxo de caminhões como variável preditora. Finalmente, o modelo de MP2,5 também identificou que a direção do setor sul (S, SE e SO) favoreceu o aumento das concentrações de MP2,5 nas paradas de ônibus, possivelmente pelo fluxo veicular nas avenidas desses setores.Universidade Tecnológica Federal do ParanáLondrinaBrasilPrograma de Pós-Graduação em Engenharia AmbientalUTFPRTargino, Admir Créso de Limahttps://orcid.org/0000-0001-6679-6150http://lattes.cnpq.br/2382340975364628Targino, Admir Créso de Limahttps://orcid.org/0000-0001-6679-6150http://lattes.cnpq.br/2382340975364628Dias, Helry Luvillany Fontenelehttps://orcid.org/0000-0002-3878-1768http://lattes.cnpq.br/5363070528503735Krecl, Patricia Kreclhttps://orcid.org/0000-0002-9354-6242http://lattes.cnpq.br/7010587657666224Camargo, David Andrés Monroy2021-04-09T18:48:38Z2021-04-09T18:48:38Z2020-09-28info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfCAMARGO, David Andrés Monroy. Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos. 2020. 132 f. Dissertação (Mestrado em Engenharia Ambiental) - Universidade Tecnológica Federal do Paraná, Londrina, 2020.http://repositorio.utfpr.edu.br/jspui/handle/1/24711porhttp://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))instname:Universidade Tecnológica Federal do Paraná (UTFPR)instacron:UTFPR2021-04-10T06:10:58Zoai:repositorio.utfpr.edu.br:1/24711Repositório InstitucionalPUBhttp://repositorio.utfpr.edu.br:8080/oai/requestriut@utfpr.edu.br || sibi@utfpr.edu.bropendoar:2021-04-10T06:10:58Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT)) - Universidade Tecnológica Federal do Paraná (UTFPR)false
dc.title.none.fl_str_mv Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
Observation and statistical modeling of particulate matter concentrations at urban bus stops
title Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
spellingShingle Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
Camargo, David Andrés Monroy
Poluentes
Ar - Poluição - Medição
Monitorização ambiental
Transporte urbano
Pollutants
Air - Pollution - Measurement
Environmental monitoring
Urban transportation
CNPQ::ENGENHARIAS::ENGENHARIA SANITARIA
Engenharia/Tecnologia/Gestão
title_short Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
title_full Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
title_fullStr Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
title_full_unstemmed Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
title_sort Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos
author Camargo, David Andrés Monroy
author_facet Camargo, David Andrés Monroy
author_role author
dc.contributor.none.fl_str_mv Targino, Admir Créso de Lima
https://orcid.org/0000-0001-6679-6150
http://lattes.cnpq.br/2382340975364628
Targino, Admir Créso de Lima
https://orcid.org/0000-0001-6679-6150
http://lattes.cnpq.br/2382340975364628
Dias, Helry Luvillany Fontenele
https://orcid.org/0000-0002-3878-1768
http://lattes.cnpq.br/5363070528503735
Krecl, Patricia Krecl
https://orcid.org/0000-0002-9354-6242
http://lattes.cnpq.br/7010587657666224
dc.contributor.author.fl_str_mv Camargo, David Andrés Monroy
dc.subject.por.fl_str_mv Poluentes
Ar - Poluição - Medição
Monitorização ambiental
Transporte urbano
Pollutants
Air - Pollution - Measurement
Environmental monitoring
Urban transportation
CNPQ::ENGENHARIAS::ENGENHARIA SANITARIA
Engenharia/Tecnologia/Gestão
topic Poluentes
Ar - Poluição - Medição
Monitorização ambiental
Transporte urbano
Pollutants
Air - Pollution - Measurement
Environmental monitoring
Urban transportation
CNPQ::ENGENHARIAS::ENGENHARIA SANITARIA
Engenharia/Tecnologia/Gestão
description Every day, people are exposed to pollutants from vehicle emissions, especially in transport microenvironments, such as bus stops and terminals. However, most studies on public transport traffic do not assess the concentrations of pollutants in these microenvironments. The behavior of fine particulate matter (with aerodynamic diameter less than 2.5 µm, PM2,5), black carbon (BC) and particle number (PN) was evaluated at bus stops in of Londrina (PR) city center during monitoring campaigns, conducted in 2015 and 2019. The 2015 experiment was performed with equipment mounted on bicycles that traveled the city’s core quantifying the particulate concentrations at 31 bus stops. 2019 experiment collected BC and PN data at five points, three of them selected from 2015 experiment plus two new ones. In the mobile monitoring, the mean PM2.5, BC and PN concentrations (+/- standard deviation) were 11,00 ±19,30 µg m-3,7,60 ±14,90 µg m-3 and 27.552 ±22.570 # cm-3 , respectively. In the fixed campaign, the mean BC and PN concentrations were 9,17 ±27,50 µg m-3 and 34.980 ±33.508 # cm-3 , respectively. The PM2,5, BC and PN concentrations at the bus stops were on average 0,30-2,90, 1,58-19,62 and 1,50-6,69 times higher than at an urban background site. At four stops from the 2019 campaign, three zones were evaluated: deceleration zone (located 10 m before the stop), boarding/alighting area and acceleration zone (located 10 m after the stop). The data allowed to pinpoint increases between 2,39- 12,05 µg m-3 and 11.380-23.220 # cm-3 in BC and PN, respectively, at the bus stops during two situations: when passengers were boarding and when buses accelerated at departure. The mean BC concentrations in the acceleration and stop zones were 17% higher than at the deceleration zone. However, the mean PN concentrations in the acceleration zone were 11% higher compared to the stop zone. Thus, it is not advisable to place several consecutive bus stops since the stop located immediately after the first one will be mainly affected by the previous accelerating bus emissions. Two forecast models for PM2.5 and BC concentrations were developed using multiple linear regression, including traffic, weather, background concentration, street, and bus stop characteristics as predictive variables. The PM2,5 and BC models had coefficient of determination (R2 ) of 0,36 ±0,09 and 0,28 ±0,08, respectively, and identified the following variables as the best predictors: atmospheric pressure, the concentration of BC with a wavelength of 880 nm at the background site and the height of the buildings: width of the street ratio. Likewise, the BC model identified the truck volume as a predictive variable. Finally, the PM2,5 model also identified that the directions of the southern sector (S, SE and SW) could favor an increase in PM2,5 concentrations at bus stops, possibly affected by the large traffic rate on avenues in those sectors.
publishDate 2020
dc.date.none.fl_str_mv 2020-09-28
2021-04-09T18:48:38Z
2021-04-09T18:48:38Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv CAMARGO, David Andrés Monroy. Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos. 2020. 132 f. Dissertação (Mestrado em Engenharia Ambiental) - Universidade Tecnológica Federal do Paraná, Londrina, 2020.
http://repositorio.utfpr.edu.br/jspui/handle/1/24711
identifier_str_mv CAMARGO, David Andrés Monroy. Observação e modelagem estatística das concentrações de material particulado em paradas de ônibus urbanos. 2020. 132 f. Dissertação (Mestrado em Engenharia Ambiental) - Universidade Tecnológica Federal do Paraná, Londrina, 2020.
url http://repositorio.utfpr.edu.br/jspui/handle/1/24711
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Tecnológica Federal do Paraná
Londrina
Brasil
Programa de Pós-Graduação em Engenharia Ambiental
UTFPR
publisher.none.fl_str_mv Universidade Tecnológica Federal do Paraná
Londrina
Brasil
Programa de Pós-Graduação em Engenharia Ambiental
UTFPR
dc.source.none.fl_str_mv reponame:Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
instname:Universidade Tecnológica Federal do Paraná (UTFPR)
instacron:UTFPR
instname_str Universidade Tecnológica Federal do Paraná (UTFPR)
instacron_str UTFPR
institution UTFPR
reponame_str Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
collection Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
repository.name.fl_str_mv Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT)) - Universidade Tecnológica Federal do Paraná (UTFPR)
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