<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yu Song</style></author><author><style face="normal" font="default" size="100%">Yuanhang* Zhang</style></author><author><style face="normal" font="default" size="100%">Shaodong Xie</style></author><author><style face="normal" font="default" size="100%">Limin Zeng</style></author><author><style face="normal" font="default" size="100%">Mei* Zheng</style></author><author><style face="normal" font="default" size="100%">Lynn G. Salmon</style></author><author><style face="normal" font="default" size="100%">Min Shao</style></author><author><style face="normal" font="default" size="100%">Sjaak Slanina</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Source apportionment of PM2.5 in Beijing by positive matrix factorization</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Backward trajectories</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S1352231005010174</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">1526 - 1537</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Air pollution associated with atmospheric fine particulate matter (PM2.5, i.e., particles with an aerodynamic diameter of 2.5μm or less) is a serious problem in Beijing, China. To provide a better understanding of the sources contributing to PM2.5, 24-h samples were collected at 6-day intervals in January, April, July, and October in 2000 at five locations in the Beijing metropolitan area. Both backward trajectory and elemental analyses identified two dust storm events; the distinctly low value of Ca:Si (&amp;lt;0.2) and high Al:Ca (&amp;gt;1.7) in Beijing PM2.5 appear indicative of contributions from dust storms. Positive matrix factorization (PMF) was used to apportion sources of PM2.5, and eight sources were identified: biomass burning (11%), secondary sulfates (17%), secondary nitrates (14%), coal combustion (19%), industry (6%), motor vehicles (6%), road dust (9%), and yellow dust. The lower organic carbon (OC), elemental carbon (EC), SO42−, and Ca values of yellow dust enable it to be distinguished from road dust. The PMF method resolved 82% of PM2.5 mass concentrations and showed excellent agreement with a previous calculation using organic tracers in a chemical mass balance (CMB) model. The present study is the first reported comparison between a PMF source apportionment model and a molecular marker-based CMB in Beijing.&lt;/p&gt;</style></abstract></record></records></xml>