Application of positive matrix factorization in characterization of PM10 and PM2.5 emission sources at urban roadside

作者：Srimuruganandam B; Nagendra S M Shiva^*

来源：Chemosphere, 2012, 88(1): 120-130.

DOI：10.1016/j.chemosphere.2012.02.083

• Particulate matter
• Source apportionment
• PMF model
• Motor vehicles
• Marine aerosols
• Secondary PM

The 24-h average coarse (PM10) and fine (PM2.5) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM10 and PM2.5 concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM10 concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM2.5 concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM10 and PM2.5 masses showed a high concentration in winter followed by monsoon and summer seasons. The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM10 and PM2.5 concentrations at the study area. Results indicated that marine aerosol (40.4% in PM10 and 21.5% in PM2.5) and secondary PM (22.9% in PM10 and 42.1% in PM2.5) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM10 and 6% in PM2.5), biomass burning (0.7% in PM10 and 14% in PM2.5), tire and brake wear (4.1% in PM10 and 5.4% in PM2.5), soil (3.4% in PM10 and 4.3% in PM2.5) and other sources (12.7% in PM10 and 6.8% in PM2.5).

• 出版日期2012-6