Source Identification of Traffic-Related Ultrafine Particles Data Mining Contest

被引：5

作者：

Sabaliauskas, Kelly

Evans, Greg ^{[1
]}

Jeong, Cheol-Heon ^{[1
]}

机构：

[1] Univ Toronto, Southern Ontario Ctr Atmospher Aerosol Res, 200 Coll St, Toronto, ON M5S 3E5, Canada

来源：

PROCEEDINGS OF THE INTERNATIONAL NEURAL NETWORK SOCIETY WINTER CONFERENCE (INNS-WC2012) | 2012年 / 13卷

基金：

加拿大创新基金会;

关键词：

atmospheric PM; ultrafine particles; UFP; aerosol; particle size distribution; PARTICULATE MATTER;

D O I：

10.1016/j.procs.2012.09.118

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Atmospheric particulate matter (PM) is a complex mixture of microscopic particles with different shapes, sizes and chemical compositions. The ultrafine size fraction of PM consists of particles with diameters less than 100nm. In urban areas, traffic is a dominant source of ultrafine particles (UFP). Gasoline-powered and diesel-powered engines emit UFP with different size distributions and chemical compositions. This paper describes the UFP and supporting data provided by Southern Ontario Centre for Atmospheric Aerosol Research for the purposes of identifying particle size distributions emitted from diesel-powered and gasoline-powered vehicles. (C) 2012 Published by Elsevier B. V. Selection and/or peer-review under responsibility of Program Committee of INNS-WC 2012

引用

页码：99 / 107

页数：9

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