Source apportionment of PM2.5 in Beijing by positive matrix factorization

Air pollution associated with atmospheric fine particulate matter (PM2.5, i.e., particles with an aerodynamic diameter of 2.5mm 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 (o0.2) and high Al:Ca (41.7) 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), SO4 2 , 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. r 2005 Elsevier Ltd. All rights reserved.