Modelling particle number size distribution: a continuous approach
提出一种新的函数因子模型，用于从粒子数粒径分布数据中解析颗粒物来源，并在伦敦7年小时数据中识别出6个来源，方法快速准确且可重复。
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.