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Source Identification of Atlanta Aerosol by Positive Matrix Factorization

Open access
Kim, Eugene, Hopke, Philip K., Edgerton, Eric S.·2003·Journal of the Air & Waste Management Association

Abstract

Data characterizing daily integrated particulate matter (PM) samples collected at the Jefferson Street monitoring site in Atlanta, GA, were analyzed through the application of a bilinear positive matrix factorization (PMF) model. A total of 662 samples and 26 variables were used for fine particle (particles < or = 2.5 microm in aerodynamic diameter) samples (PM2.5), and 685 samples and 15 variables were used for coarse particle (particles between 2.5 and 10 microm in aerodynamic diameter) samples (PM10-2.5). Measured PM mass concentrations and compositional data were used as independent variables. To obtain the quantitative contributions for each source, the factors were normalized using PMF-apportioned mass concentrations. For fine particle data, eight sources were identified: SO4(2-) -rich secondary aerosol (56%), motor vehicle (22%), wood smoke (11%), NO(3-) -rich secondary aerosol (7%), mixed source of cement kiln and organic carbon (OC) (2%), airborne soil (1%), metal recycling facility (0.5%), and mixed source of bus station and metal processing (0.3%). The SO4(2-) -rich and NO(3-) -rich secondary aerosols were associated with NH(4+). The SO4(2-) -rich secondary aerosols also included OC. For the coarse particle data, five sources contributed to the observed mass: airborne soil (60%), NO(3-)-rich secondary aerosol (16%), SO4(2-) -rich secondary aerosol (12%), cement kiln (11%), and metal recycling facility (1%). Conditional probability functions were computed using surface wind data and identified mass contributions from each source. The results of this analysis agreed well with the locations of known local point sources.

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Metadata

Authors
Kim, E., Hopke, P. K., & Edgerton, E. S.
Venue
Journal of the Air & Waste Management Association
Published
2003-06
Volume
53
Issue
6
Pages
731-739
ISSN
  • 1047-3289 (ISSN-L)
  • 1096-2247
  • 2162-2906
OpenAlex
W2022018373
Cited by
379
References
21
FWCI
12.38
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Source Identification of Atlanta Aerosol by Positive Matrix Factorization. https://app.cochat.ai/papers/10.1080/10473289.2003.10466209
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Kim, E., Hopke, P. K., & Edgerton, E. S. (2003). Source Identification of Atlanta Aerosol by Positive Matrix Factorization. Journal of the Air & Waste Management Association. https://doi.org/10.1080/10473289.2003.10466209

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.