Applying hybrid source apportionment models on fine particulate matters in Tehran, Iran

Fine particulate matter (PM2.5) is one of the most important air pollutants in the world. The chemical composition and sources contribution of this pollutant is relatively unknown in Tehran, Iran. For this purpose, daily PM2.5 samples were collected at a main residential station (Sharif University of Technology as a main Air Quality Control Company site (AQCC)) every six days for a full year, and the samples were analyzed for ions, organic carbon (including water-soluble and insoluble portions) and elemental carbon (EC) by means of TOT, GCMS, IC, SF-ICPMS. The results show organic matter (OM) and dust oxide is the most important compounds in PM2.5. Moreover, the contribution of PM2.5 sources was determined by the chemical mass balance (CMB) and principal component analysis (PCA) model using the concentration of chemical components of the particles and the profile of possible sources in Tehran. The considered hybrid model (principal component analysis/multiple linear regression chemical mass balance; PCA/MLR+CMB), comprising two stages has been developed for improving the accuracy in identifying PM2.5 sources. The results show that the second factor of the PCA model, including 17% of PM changes is a composite source, and it is influenced by heavy metals from human resources, including industries, car brakes, car tires, car lubricating oils, and in this factor, combustion. Heavy fuels, with an average of 65.10% had the largest contribution in the emission of particulate matter associated to factor 2. The insights regarding fine PM in Tehran provided by the results of this paper could be useful in planning effective control strategies and decision making in Tehran, Iran.