Artículo
Modelling particle number size distribution: a continuous approach
Martínez Hernández, Israel; Euán, Carolina; Burr, Wesley S.; Meis, Melanie
; Blangiardo, Marta; Pirani, Monica
; Blangiardo, Marta; Pirani, Monica
Fecha de publicación:
10/2024
Editorial:
Wiley Blackwell Publishing, Inc
Revista:
Journal Of The Royal Statistical Society Series C-applied Statistics
ISSN:
0035-9254
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
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.
Palabras clave:
AIR POLLUTION
,
FUNCTIONAL DATA
,
FUNCTIONAL FACTOR MODEL
,
ULTRAFINE PARTICLES
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos(CIMA)
Articulos de CENTRO DE INVESTIGACIONES DEL MAR Y LA ATMOSFERA
Articulos de CENTRO DE INVESTIGACIONES DEL MAR Y LA ATMOSFERA
Citación
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
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