4.5 Article

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

Journal

AEROSOL AND AIR QUALITY RESEARCH
Volume 12, Issue 4, Pages 476-491

Publisher

TAIWAN ASSOC AEROSOL RES-TAAR
DOI: 10.4209/aaqr.2012.04.0084

Keywords

Positive matrix factorization; Enrichment factor analysis; Conditional probability function analysis; PM10; PM2.5; PM0.1

Funding

  1. Taiwan EPA project [EPA-100-1602-02-01]
  2. Taiwan NSC project [NSC 98-2221-E-009-020-MY3]

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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 mu g/m(3), respectively. Based on the chemical information, positive matrix factorization (PMF) was used to identify PM sources. A total of five source types were identified, including 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.

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