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[journal article]

dc.contributor.authorLi, Naixinde
dc.contributor.authorFriedrich, Rainerde
dc.contributor.authorSchieberle, Christiande
dc.date.accessioned2023-07-21T13:22:27Z
dc.date.available2023-07-21T13:22:27Z
dc.date.issued2022de
dc.identifier.issn2296-2565de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/87860
dc.description.abstractAir pollutants, especially PM2.5 and NO2, are associated with adverse health impacts, as shown by numerous epidemiological studies. In these studies, the observed health impacts have been correlated with ambient concentrations, mainly taken from air pollution monitoring stations. However, individuals are harmed by the pollutants in the inhaled air at the places where they stay, and thus, the concentration of pollutants in the inhaled air is obviously a better indicator for health impacts than the ambient concentration at a monitoring station. Furthermore, the current method for estimating the occurrence of chronic diseases uses annual average concentrations as indicator. However, according to current hypotheses, chronic diseases, especially chronic mortality, develop through the exposure to pollutants over many years, maybe up to a full lifetime. Thus in this study, a methodology and a computer-aided probabilistic model system are described for calculating the exposure of a person to PM2.5 and NO2 over the whole lifetime where the person is characterized by attributes such as age, gender, place of residence and work as well as socioeconomic status. The model system contains a "life course trajectory model", which estimates the course of the education and professional development for the past lifetime of a person, whose present socioeconomic status is known. Furthermore, a "time-activity model" estimates at which places (so-called micro-environments) a person with a certain socioeconomic status stayed and how long he stayed there within a certain year. The concentrations of air pollutants in indoor environments are calculated with a "mass-balance model", the outdoor concentrations with "atmospheric models". Finally, the results of these models are combined to estimate the annual average exposure for the life years of individuals and population subgroups. The exposure is then used to estimate and monetize health impacts. The exposures and health impacts for a number of population subgroups in Europe are presented. For instance, a European citizen, who was 70 years old in 2015, has been exposed to around 25 μg/m3 of PM2.5 during his lifetime above the age of 30, which is associated with a reduction of life expectancy of 13.4 days per year of exposure above 30.de
dc.languageende
dc.subject.ddcÖkologiede
dc.subject.ddcEcologyen
dc.subject.otherPM2.5; NO2; exposure to air pollution; health impacts related to air pollution; EU-SILCde
dc.titleExposure of Individuals in Europe to Air Pollution and Related Health Effectsde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalFrontiers in Public Health
dc.source.volume10de
dc.publisher.countryCHEde
dc.subject.classozÖkologie und Umweltde
dc.subject.classozEcology, Environmenten
dc.subject.thesozUmweltverschmutzungde
dc.subject.thesozenvironmental pollutionen
dc.subject.thesozLuftde
dc.subject.thesozairen
dc.subject.thesozUmweltbelastungde
dc.subject.thesozenvironmental impacten
dc.subject.thesozsoziale Faktorende
dc.subject.thesozsocial factorsen
dc.subject.thesozdemographische Faktorende
dc.subject.thesozdemographic factorsen
dc.subject.thesozgesundheitliche Folgende
dc.subject.thesozhealth consequencesen
dc.subject.thesozEUde
dc.subject.thesozEUen
dc.subject.thesozSchadstoffde
dc.subject.thesozpollutanten
dc.identifier.urnurn:nbn:de:0168-ssoar-87860-5
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
ssoar.contributor.institutionFDBde
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10045125
internal.identifier.thesoz10045124
internal.identifier.thesoz10038093
internal.identifier.thesoz10045241
internal.identifier.thesoz10040663
internal.identifier.thesoz10043855
internal.identifier.thesoz10041441
internal.identifier.thesoz10057142
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo1-21de
internal.identifier.classoz20900
internal.identifier.journal1971
internal.identifier.document32
internal.identifier.ddc577
dc.identifier.doihttps://doi.org/10.3389/fpubh.2022.871144de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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