Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization

Balakrishnaiah Gugamsetty, Han Wei, Chun Nan Liu, Amit Awasthi, Chuen-Tinn Tsai*, Gwo Dong Roam, Yue Chuen Wu, Chung Fang Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

144 Scopus citations


Ambient Particulate Matters (PM10, PM2.5 and PM0.1) were investigated at Shinjung station in New Taipei City, Taiwan. Samples were collected simultaneously using a dichotomous sampler (Andersen Model SA-241) and a MOUDI (MSP Model 110) over a 24-h period from May 2011 to November 2011 at Shinjung station. Samples were analyzed for metallic trace elements using ion coupled plasma mass spectroscopy (ICP-MS) and ionic compounds by ion chromatography (IC). The average concentrations of PM10, PM2.5 and PM0.1 were found to be 39.45 ± 11.58, 21.82 ± 7.50 and 1.42 ± 0.56 μg/m3, respectively. Based on the chemical information, positive matrix factorization (PMF) was used to identify PM sources. A total of five source types were identified, soil dust, vehicle emissions, sea salt, industrial emissions and secondary aerosols, and their contributions were estimated using PMF. The crustal enrichment factors (EF) were calculated using Al as a reference for the trace metal species to identify the sources. Conditional probability functions (CPF) were computed using wind profiles and factor contributions. The results of CPF analysis were used to identify local point sources. The results suggest a competitive relationship between anthropogenic and natural source processes over the monitoring station.

Original languageEnglish
Pages (from-to)476-491
Number of pages16
JournalAerosol and Air Quality Research
Issue number4
StatePublished - 1 Aug 2012


  • Conditional probability function analysis
  • Enrichment factor analysis
  • PM
  • PM
  • PM
  • Positive matrix factorization

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