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Use of data imputation tools to reconstruct incomplete air quality datasets: A case-study in Temuco, Chile

Authordc.contributor.authorQuinteros, María Elisa 
Authordc.contributor.authorLu, Siyao 
Authordc.contributor.authorBlazquez, Carola 
Authordc.contributor.authorCárdenas-R, Juan Pablo 
Authordc.contributor.authorOssa, Ximena 
Authordc.contributor.authorDelgado-Saborit, Juana María 
Authordc.contributor.authorHarrison, Roy M. 
Authordc.contributor.authorRuiz Rudolph, Pablo 
Admission datedc.date.accessioned2019-10-11T17:27:24Z
Available datedc.date.available2019-10-11T17:27:24Z
Publication datedc.date.issued2019
Cita de ítemdc.identifier.citationAtmospheric Environment, Volumen 200,
Identifierdc.identifier.issn18732844
Identifierdc.identifier.issn13522310
Identifierdc.identifier.other10.1016/j.atmosenv.2018.11.053
Identifierdc.identifier.urihttp://repositorio.uchile.cl/handle/2250/171184
Abstractdc.description.abstract© 2018 Elsevier LtdMissing data from air quality datasets is a common problem, but is much more severe in small cities or localities. This poses a great challenge for environmental epidemiology as high exposures to pollutants worldwide occur in these settings and gaps in datasets hinder health studies that could later inform local and international policies. Here, we propose the use of imputation methods as a tool to reconstruct air quality datasets and have applied this approach to an air quality dataset in Temuco, a mid-size city in Chile as a case-study. We attempted to reconstruct the database comparing five approaches: mean imputation, conditional mean imputation, K-Nearest Neighbor imputation, multiple imputation and Bayesian Principal Component Analysis imputation. As a base for the imputation methods, linear regression models were fitted for PM2.5 against other air quality and meteorological variables. Methods were challenged against validation sets where data was removed artif
Lenguagedc.language.isoen
Publisherdc.publisherElsevier Ltd
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
Sourcedc.sourceAtmospheric Environment
Keywordsdc.subjectAir pollution
Keywordsdc.subjectEnvironmental epidemiology
Keywordsdc.subjectMissing data
Keywordsdc.subjectMultiple imputation
Keywordsdc.subjectSingle imputation
Keywordsdc.subjectWood-burning
Títulodc.titleUse of data imputation tools to reconstruct incomplete air quality datasets: A case-study in Temuco, Chile
Document typedc.typeArtículo de revista
Catalogueruchile.catalogadorSCOPUS
Indexationuchile.indexArtículo de publicación SCOPUS
uchile.cosechauchile.cosechaSI


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Attribution-NonCommercial-NoDerivs 3.0 Chile
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile