Modelling particle number size distribution: a continuous approach

被引:0
|
作者
Martinez-Hernandez, Israel [1 ]
Euan, Carolina [1 ]
Burr, Wesley S. [2 ]
Meis, Melanie [3 ]
Blangiardo, Marta [4 ]
Pirani, Monica [4 ]
机构
[1] Univ Lancaster, Sch Math Sci, Lancaster LA1 4YW, England
[2] Trent Univ, Dept Math & Stat, Peterborough, ON, Canada
[3] Univ Buenos Aires, Fac Ciencias Exactas & Nat, Dept Ciencias Atmosfera & Oceanos, CONICET, Buenos Aires, Argentina
[4] Imperial Coll London, MRC Ctr Environm & Hlth, Dept Epidemiol & Biostat, London, England
基金
英国医学研究理事会;
关键词
air pollution; functional data; functional factor model; particle number size distribution; source apportionment; ultrafine particles; POSITIVE MATRIX FACTORIZATION; PRINCIPAL COMPONENT ANALYSIS; SOURCE APPORTIONMENT; DENSITY-FUNCTIONS; AIR-POLLUTION; POLLUTANTS; LONDON;
D O I
10.1093/jrsssc/qlae053
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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.
引用
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页数:20
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