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dc.contributor.author
Martínez Hernández, Israel  
dc.contributor.author
Euán, Carolina  
dc.contributor.author
Burr, Wesley S.  
dc.contributor.author
Meis, Melanie  
dc.contributor.author
Blangiardo, Marta  
dc.contributor.author
Pirani, Monica  
dc.date.available
2025-05-12T11:30:21Z  
dc.date.issued
2024-10  
dc.identifier.citation
Martínez Hernández, Israel; Euán, Carolina; Burr, Wesley S.; Meis, Melanie; Blangiardo, Marta; et al.; Modelling particle number size distribution: a continuous approach; Wiley Blackwell Publishing, Inc; Journal Of The Royal Statistical Society Series C-applied Statistics; 74; 1; 10-2024; 229-248  
dc.identifier.issn
0035-9254  
dc.identifier.uri
http://hdl.handle.net/11336/261015  
dc.description.abstract
Particulate matter (PM) is well known to be detrimental to health, and it is crucial to apportion PM into the underlying sources to target policies. Particle number size distribution (PNSD) is the most accessible data to identify these sources, which provides information on the PM sizes. Here, we propose a new functional factor model for PNSD, which allows to disentangle PM into sources and contributions while considering the complex dependencies of the data across different sizes and periods. Through a simulation study, we show that this method is able to identify sources correctly, and we use it to analyse hourly PNSD data collected in London for 7 years, finding 6 well-defined sources. Our proposed methodology is fast, accurate, and reproducible.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Wiley Blackwell Publishing, Inc  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
AIR POLLUTION  
dc.subject
FUNCTIONAL DATA  
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FUNCTIONAL FACTOR MODEL  
dc.subject
ULTRAFINE PARTICLES  
dc.subject.classification
Estadística y Probabilidad  
dc.subject.classification
Matemáticas  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Modelling particle number size distribution: a continuous approach  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2025-05-09T15:55:31Z  
dc.journal.volume
74  
dc.journal.number
1  
dc.journal.pagination
229-248  
dc.journal.pais
Reino Unido  
dc.journal.ciudad
Londres  
dc.description.fil
Fil: Martínez Hernández, Israel. Lancaster University; Reino Unido  
dc.description.fil
Fil: Euán, Carolina. Lancaster University; Reino Unido  
dc.description.fil
Fil: Burr, Wesley S.. Trent University (trent University);  
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Fil: Meis, Melanie. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina  
dc.description.fil
Fil: Blangiardo, Marta. Imperial College London; Reino Unido  
dc.description.fil
Fil: Pirani, Monica. Imperial College London; Reino Unido  
dc.journal.title
Journal Of The Royal Statistical Society Series C-applied Statistics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/jrsssc/advance-article/doi/10.1093/jrsssc/qlae053/7820614  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1093/jrsssc/qlae053