Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/356335
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampNogarotto, Danilo Covaes-
dc.contributor.authorunicampPozza, Simone Andréa-
dc.typeArtigopt_BR
dc.titleA review of multivariate analysis: is there a relationship between airborne particulate matter and meteorological variables?pt_BR
dc.contributor.authorNogarotto, Danilo Covaes-
dc.contributor.authorPozza, Simone Andrea-
dc.subjectAnálise por agrupamentopt_BR
dc.subject.otherlanguageCluster analysispt_BR
dc.description.abstractAmong statistical tools for the study of atmospheric pollutants, trajectory regression analysis (TRA), cluster analysis (CA), and principal component analysis (PCA) can be highlighted. Therefore, this article presents a systematic review of such techniques based on (i) air mass influences on particulate matter (PM) and (ii) the study of the relationship between PM and meteorological variables. This article aims to review studies that use TRA and to review studies that adopt CA and/or PCA to identify the associations and relationship between meteorological variables and atmospheric pollutants. Papers published between 2006 and 2018 and indexed by five of the main scientific databases were considered (ScienceDirect, Web of Science, PubMed, SciELO, and Scopus databases). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations supported this systematic review. From the resulting most relevant papers, eight studies analyzed the influence of air mass trajectories on PM using TRA and twenty-one studies searched for the relationship between meteorological variables and PM using CA and/or PCA. A combination of TRA and time series models was identified as the possibility of future works. Besides, studies that simultaneously combine the three techniques to identify both the influence of air masses on PM and its relationship with meteorological variables are a possibility of future papers, because it can lead to a better comprehension of such a phenomenonpt_BR
dc.relation.ispartofEnvironmental monitoring and assessmentpt_BR
dc.relation.ispartofabbreviationEnviron. monit. assess.pt_BR
dc.publisher.cityDordrechtpt_BR
dc.publisher.countryPaíses Baixospt_BR
dc.publisherSpringerpt_BR
dc.date.issued2020-
dc.date.monthofcirculationAug.pt_BR
dc.language.isoengpt_BR
dc.description.volume192pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn0167-6369pt_BR
dc.identifier.eissn1573-2959pt_BR
dc.identifier.doi10.1007/s10661-020-08538-1pt_BR
dc.identifier.urlhttps://link.springer.com/article/10.1007%2Fs10661-020-08538-1pt_BR
dc.description.sponsorshipCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESpt_BR
dc.description.sponsordocumentnumber001pt_BR
dc.date.available2021-02-23T16:59:51Z-
dc.date.accessioned2021-02-23T16:59:51Z-
dc.description.provenanceSubmitted by Susilene Barbosa da Silva (susilene@unicamp.br) on 2021-02-23T16:59:51Z No. of bitstreams: 0. Added 1 bitstream(s) on 2021-05-24T19:06:37Z : No. of bitstreams: 1 000561205000001.pdf: 1047787 bytes, checksum: 32d3b32cc9945118acd58ef2874ec428 (MD5)en
dc.description.provenanceMade available in DSpace on 2021-02-23T16:59:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2020en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/356335-
dc.contributor.departmentSem informaçãopt_BR
dc.contributor.departmentSem informaçãopt_BR
dc.contributor.unidadeFaculdade de Tecnologiapt_BR
dc.subject.keywordParticulate matterpt_BR
dc.subject.keywordAir mass trajectoriespt_BR
dc.identifier.source000561205000001pt_BR
dc.creator.orcid0000-0002-5046-807Xpt_BR
dc.creator.orcid0000-0001-7423-0982pt_BR
dc.type.formArtigopt_BR
dc.identifier.articleid573pt_BR
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