气候变化领域集成服务门户(CCPortal): Statistical modelling of spatial and temporal variation in urban particle number size distribution at traffic and background sites

CCPortal

DOI	10.1016/j.atmosenv.2020.117925
	Statistical modelling of spatial and temporal variation in urban particle number size distribution at traffic and background sites
	Gerling L.; Wiedensohler A.; Weber S.
发表日期	2021
ISSN	1352-2310
卷号	244
英文摘要	Ultrafine particles (UFP) pose a risk to human health, but due to the multitude of sources and fast transformation in the urban atmosphere, quantifying the exposure is challenging. Furthermore, physical properties of aerosol particles depend on the particle size. Statistical models are used to quantify spatial and temporal variation of UFP, but rarely used for particle number size distribution (PNSD). The aim of the study was to establish an interpretable statistical model capturing spatial and temporal variation of urban PNSDs using generalized additive models (GAM) and multivariate adaptive regression spline models (MARS). These algorithms automatically fit interpretable, non-linear marginal function to represent relationships between explanatory and response variables. Three different approaches were evaluated to cope with the multidimensionality of the PNSD data (20–800 nm, 34 size bins): a generalized additive model for the particle number concentration (PNC) of every individual size bin (GAMbins), a generalized additive model for the parameters of the PNSD function (GAMpams) and a multivariate adaptive regression spline model for the PNC of every size bin (MARSbins). Reanalysis data of meteorological quantities, urban geometry parameters and approximated traffic counts were used as explanatory variables. Marginal functions of the final models could be attributed to major processes that contribute to spatial and temporal variation of the PNSD, i.e. emissions from vehicle traffic, transport, dilution, accumulation, deposition and new particle formation. Cross-validation coefficients of determination ranged between 0.27 and 0.48 for most size bins. Nonetheless, the modelling approaches resulted in similar root mean square errors (RMSE) and mean absolute error (MAE). Though direct spatial transferability of the models is limited, the presented approaches may be useful for estimating ambient exposure to particles. © 2020 Elsevier Ltd
关键词	Generalized additive model Multivariate adaptive regression spline Particle number size distribution Statistical model Ultrafine particles Urban air quality
语种	英语
scopus关键词	Additives; Health risks; Mean square error; Particle size; Size distribution; Generalized additive model; Multivariate adaptive regression splines; New particle formation; Particle number concentration; Particle number size distribution; Root mean square errors; Spatial and temporal variation; Spatial transferability; Urban growth; additive; aerosol composition; aerosol formation; air quality; atmospheric deposition; atmospheric pollution; particle size; spatial variation; temporal variation; traffic emission; air quality; algorithm; article; concentration (parameter); cross validation; dilution; explanatory variable; geometry; human; remission; response variable; ultrafine particulate matter
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248825
作者单位	Climatology and Environmental Meteorology, Institute of Geoecology, Technische Universität Braunschweig, Langer Kamp 19c, Braunschweig, 38106, Germany; Leibniz Institute for Tropospheric Research (TROPOS), Permoserstraße 15, Leipzig, 04318, Germany
推荐引用方式 GB/T 7714	Gerling L.,Wiedensohler A.,Weber S.. Statistical modelling of spatial and temporal variation in urban particle number size distribution at traffic and background sites[J],2021,244.
APA	Gerling L.,Wiedensohler A.,&Weber S..(2021).Statistical modelling of spatial and temporal variation in urban particle number size distribution at traffic and background sites.ATMOSPHERIC ENVIRONMENT,244.
MLA	Gerling L.,et al."Statistical modelling of spatial and temporal variation in urban particle number size distribution at traffic and background sites".ATMOSPHERIC ENVIRONMENT 244(2021).