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001-es BibID:	BIBFORM126014
035-os BibID:	(WOS)000643190500015 (Scopus)85105197011
Első szerző:	Machado, Milena
Cím:	Deconstruction of annoyance due to air pollution by multiple correspondence analyses / Milena Machado, Jane Meri Santos, Severine Frere, Phillipe Chagnon, Valdério Anselmo Reisen, Pascal Bondon, Márton Ispány, Ilias Mavroidis, Neyval Costa Reis Jr
Dátum:	2021
ISSN:	0944-1344 1614-7499
Megjegyzések:	Annoyance caused by air pollution is a matter of public health as it can cause stress and ill-health and affect quality of life, among other burdens. The aim of this study is to apply the multiple correspondence analyses (MCA) technique as a differential tooling to explore relationships between variables that can influence peoples' behaviour concerning annoyance caused by air pollution. Data were collected through a survey on air pollution, environmental issues and quality of life. Face-to-face survey studies were conducted in two industrialized urban areas (Vitoria in Brazil and Dunkirk in France). These two regions were chosen as their inhabitants often report feeling annoyed by air pollution, and both regions have similar industrial characteristics. The results showed a progressive correspondence between levels of annoyance and other active variables in the "air pollution" factor group: as the levels of annoyance increased, the levels of the other qualitative variables (importance of air quality, perceived exposure to industrial risk, assessment of air quality, perceived air pollution) also increased. Respondents who reported feeling annoyed by air pollution also thought that air quality was very important and were very concerned about exposure to industrial risks. Furthermore, they often assessed air quality as horrible, and they could frequently perceive air pollution by dust, odours and decreased visibility. The results also showed a statistically significant association between occurrence of allergies and high levels of annoyance.
Tárgyszavak:	Természettudományok Környezettudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Air pollution Perceived annoyance Behaviour Health impacts Multiple correspondence analysis
Megjelenés:	Environmental Science And Pollution Research. - 28 : 35 (2021), p. 47904-47920. -
További szerzők:	Santos, Jane Meri Frère, Severine Chagnon, Phillipe Reisen, Valdério Anselmo Bondon, Pascal Ispány Márton (1966-) (informatikus, matematikus) Mavroidis, Ilias Reis, Neyval Costa
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM083792
035-os BibID:	(WoS)000510946800004 (Scopus)85075889215
Első szerző:	Machado, Milena
Cím:	Use of multivariate time series techniques to estimate the impact of particulate matter on the perceived annoyance / Milena Machado, Valdério Anselmo Reisen, Jane Meri Santos, Neyval Costa Reis, Severine Frère, Pascal Bondon, Márton Ispány, Higor Henrique Aranda Cotta
Dátum:	2020
ISSN:	1352-2310
Megjegyzések:	As well known, Particulate matter (PM) is an air pollutant that causes damage to the health of humans, other animals, 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 urban and 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 minor vehicular and industrial sources emissions. The aim of this paper is to quantify the relationship between perceived annoyance and particulate matter concentration and to estimate the relative risk (RR). The data was collected in the Metropolitan Region of Vitoria (MRV), Brazil. For this purpose, the variables of interest were modeled 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 allows to estimate RR by handling multipollutant effects. This study shows that there is a strong association between the perceived annoyance and different sizes of PM. The estimates of RR indicate that an increase in air pollutant concentrations significantly contributes in increasing the probability of being annoyed.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Annoyance principal component analysis logistic regression relative risk
Megjelenés:	Atmospheric Environment. - 222 (2020), p. 1-24. -
További szerzők:	Reisen, Valdério Anselmo Santos, Jane Meri Reis, Neyval Costa Frère, Severine Bondon, Pascal Ispány Márton (1966-) (informatikus, matematikus) Cotta, Higor Henrique Aranda
Pályázati támogatás:	EFOP-3.6.1-16-2016-00022 EFOP
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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