Use of multivariate time series techniques ...
Document type :
Article dans une revue scientifique: Article original
Title :
Use of multivariate time series techniques to estimate the impact of particulate matter on the perceived annoyance
Author(s) :
Machado, Milena [Auteur]
Federal Institute of Education, Science and Technology of Espírito Santo [IFES]
Reisen, Valdério [Auteur]
Santos, Jane Meri [Auteur]
Universidade Federal do Espirito Santo [UFES]
Reis Júnior, Neyval Costa [Auteur]
Universidade Federal do Espirito Santo [UFES]
Frere, Severine [Auteur]
Université du Littoral Côte d'Opale [ULCO]
Territoires, Villes, Environnement & Société - ULR 4477 [TVES]
Bondon, Pascal [Auteur]
Laboratoire des signaux et systèmes [L2S]
Ispány, Márton [Auteur]
University of Debrecen
Cotta, Higor [Auteur]
Federal Institute of Education, Science and Technology of Espírito Santo [IFES]
Reisen, Valdério [Auteur]
Santos, Jane Meri [Auteur]
Universidade Federal do Espirito Santo [UFES]
Reis Júnior, Neyval Costa [Auteur]
Universidade Federal do Espirito Santo [UFES]
Frere, Severine [Auteur]

Université du Littoral Côte d'Opale [ULCO]
Territoires, Villes, Environnement & Société - ULR 4477 [TVES]
Bondon, Pascal [Auteur]
Laboratoire des signaux et systèmes [L2S]
Ispány, Márton [Auteur]
University of Debrecen
Cotta, Higor [Auteur]
Journal title :
Atmospheric Environment
Pages :
117080
Publisher :
Elsevier
Publication date :
2020-02-01
ISSN :
1352-2310
English keyword(s) :
Annoyance
Principal component analysis
Logistic regression
Relative risk
Principal component analysis
Logistic regression
Relative risk
HAL domain(s) :
Statistiques [stat]/Théorie [stat.TH]
English abstract : [en]
As well known, Particulate matter (PM) is an air pollutant that causes damage to the health of humans, otheranimals, plants, affects the climate and is a potential cause of annoyance through deposition on various surfaces.The ...
Show more >As well known, Particulate matter (PM) is an air pollutant that causes damage to the health of humans, otheranimals, plants, affects the climate and is a potential cause of annoyance through deposition on various surfaces.The perceived annoyance caused by particulate matter is related mainly to the increase of settled dust in urbanand residential environments. PM can originate from many sources, i.e., paved and unpaved roads, buildings,agricultural operations and wind erosion represent the largest contributions beyond the relatively minorvehicular and industrial sources emissions. The aim of this paper is to quantify the relationship betweenperceived annoyance and particulate matter concentration and to estimate the relative risk (RR). The data wascollected in the Metropolitan Region of Vitoria (MRV), Brazil. For this purpose, the variables of interest weremodelled using vector time series model (VAR), principal component analysis (PCA), and logistic regression(LOG). The combination of these techniques resulted in a hybrid model denoted as LOG-PCA-VAR which allowsto estimate RR by handling multipollutant effects. This study shows that there is a strong association between theperceived annoyance and different sizes of PM. The estimates of RR indicate that an increase in air pollutantconcentrations significantly contributes in increasing the probability of being annoyedShow less >
Show more >As well known, Particulate matter (PM) is an air pollutant that causes damage to the health of humans, otheranimals, plants, affects the climate and is a potential cause of annoyance through deposition on various surfaces.The perceived annoyance caused by particulate matter is related mainly to the increase of settled dust in urbanand residential environments. PM can originate from many sources, i.e., paved and unpaved roads, buildings,agricultural operations and wind erosion represent the largest contributions beyond the relatively minorvehicular and industrial sources emissions. The aim of this paper is to quantify the relationship betweenperceived annoyance and particulate matter concentration and to estimate the relative risk (RR). The data wascollected in the Metropolitan Region of Vitoria (MRV), Brazil. For this purpose, the variables of interest weremodelled using vector time series model (VAR), principal component analysis (PCA), and logistic regression(LOG). The combination of these techniques resulted in a hybrid model denoted as LOG-PCA-VAR which allowsto estimate RR by handling multipollutant effects. This study shows that there is a strong association between theperceived annoyance and different sizes of PM. The estimates of RR indicate that an increase in air pollutantconcentrations significantly contributes in increasing the probability of being annoyedShow less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
ANR Project :
Source :
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