Modelling particle number size distribution: a continuous approach
File(s)
Published version
Author(s)
Type
Journal Article
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.
Date Issued
2025-01-01
Date Acceptance
2024-09-16
Citation
Journal of the Royal Statistical Society Series C: Applied Statistics, 2025, 74 (1), pp.229-248
ISSN
0035-9254
Publisher
Royal Statistical Society
Start Page
229
End Page
248
Journal / Book Title
Journal of the Royal Statistical Society Series C: Applied Statistics
Volume
74
Issue
1
Copyright Statement
© The Royal Statistical Society 2024. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium,provided the original work is properly cited.
License URL
Identifier
http://dx.doi.org/10.1093/jrsssc/qlae053
Subjects
air pollution
functional data
functional factor model
particle number size distribution
source apportionment
ultrafine particles
Publication Status
Published
Article Number
qlae053
Date Publish Online
2024-10-14