Source identifications of airborne fine particles using positive matrix factorization and U.S. Environmental Protection Agency positive matrix factorization

Kim, E; Hopke, PK

HERO ID

98181

Reference Type

Journal Article

Year

2007

Language

English

PMID

17687996

HERO ID 98181
In Press No
Year 2007
Title Source identifications of airborne fine particles using positive matrix factorization and U.S. Environmental Protection Agency positive matrix factorization
Authors Kim, E; Hopke, PK
Journal Journal of the Air and Waste Management Association
Volume 57
Issue 7
Page Numbers 811-819
Abstract The widely used source apportionment model, positive matrix factorization (PMF2), has been applied to various air pollution data. Recently, U.S. Environmental Protection Agency (EPA) developed EPA positive matrix factorization (PMF), a version of PMF that will be freely distributed by EPA. The objectives of this study were to conduct source apportionment studies for particulate matter less than 2.5 mu m in aerodynamic diameter (PM2.5) speciation data using PMF2 and EPA PMF (version 1.1) and to compare identified sources between the two models. In the present study, ambient PM2.5 compositional datasets of 24-hr integrated samples collected at EPA Speciation Trends Network monitoring sites in Chicago, IL, and Portland, OR, were analyzed. Both PMF2 and EPA PMF extracted eight sources for the Chicago data and 10 sources for the Portland data. The model-resolved source profiles were similar between two models for both datasets. However, in several sources, the average contributions did not agree well and the time series contributions were not highly correlated. The differences between PMF2 and EPA PMF solutions were caused by the different least-square algorithm and the different nonnegativity constraints. Most of the average source contributions resolved by both models were within 5-95% uncertainty provided by EPA PMF, indicating that the sources resolved by both models were reproducible.
Doi 10.3155/1047-3289.57.7.811
Pmid 17687996
Wosid WOS:000247766200005
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English
Is Qa No