Balakrishnaiah Gugamsetty1, Han Wei1, Chun-Nan Liu1, Amit Awasthi1, Shih-Chieh Hsu2, Chuen-Jinn Tsai 1, Gwo-Dong Roam3, Yue-Chuen Wu3, Chung-Fang Chen3

  • 1 Institute of Environmental Engineering, National Chiao Tung University, Hsinchu 300, Taiwan
  • 2 Research Center for Environmental Changes, Academia Sinica, Taipei 115, Taiwan
  • 3 Environmental Analysis Laboratory, Environmental Protection Administration, Jhongli 320, Taiwan

Received: April 12, 2012
Revised: May 3, 2012
Accepted: May 3, 2012
Download Citation: ||https://doi.org/10.4209/aaqr.2012.04.0084  

  • Download: PDF


Cite this article:
Gugamsetty, B., Wei, H., Liu, C.N., Awasthi, A., Hsu, S.C., Tsai, C.J., Roam, G.D., Wu, Y.C. and Chen, C.F. (2012). Source Characterization and Apportionment of PM10, PM2.5 and PM0.1 by Using Positive Matrix Factorization. Aerosol Air Qual. Res. 12: 476-491. https://doi.org/10.4209/aaqr.2012.04.0084


 

ABSTRACT


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.


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


Share this article with your colleagues 

 

Subscribe to our Newsletter 

Aerosol and Air Quality Research has published over 2,000 peer-reviewed articles. Enter your email address to receive latest updates and research articles to your inbox every second week.

7.3
2022CiteScore
 
 
77st percentile
Powered by
Scopus
 
   SCImago Journal & Country Rank

2022 Impact Factor: 4.0
5-Year Impact Factor: 3.4

Aerosol and Air Quality Research partners with Publons

CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit
CLOCKSS system has permission to ingest, preserve, and serve this Archival Unit

Aerosol and Air Quality Research (AAQR) is an independently-run non-profit journal that promotes submissions of high-quality research and strives to be one of the leading aerosol and air quality open-access journals in the world. We use cookies on this website to personalize content to improve your user experience and analyze our traffic. By using this site you agree to its use of cookies.